1 Load datasets

rm(list = ls())
library(RColorBrewer)
library(lmodel2)
library(viridisLite)
library(seriation)
library(reshape2)

pathtofigures <- "./"
dataGR <- read.table(file=paste(pathtofigures, "AveragelogGRperstrain241het16hom20181128.csv", sep="/"), header=TRUE, sep=",")
dataGR$GR <- exp(dataGR$logGR)


dataWL <- read.table(file=paste(pathtofigures, "AveragelogWLperstrain198het16hom20180717.csv", sep="/"), header=TRUE, sep=";")
dataWL$weightloss <- exp(dataWL$logweightloss)-1

head(dataWL)
##   Acceptor Donor geno_DonorSG logweightloss     ID DonorSG AcceptorName
## 1       11     7       11_7_1     0.1750899  Het46       1         FSE7
## 2       11    30      11_30_0     0.2043858 Het205       0         FSE7
## 3       11     9       11_9_0     0.2307522  Het54       0         FSE7
## 4       11    32      11_32_0     0.2866868 Het234       0         FSE7
## 5       11    11         11_0     0.1324016  Hom11       0         FSE7
## 6       11    25      11_25_1     0.1792176 Het172       1         FSE7
##   DonorName      AcceptorPop             DonorPop  geno geneticdistance
## 1     95156 Helsinki_Finland Yekaterinburg_Russia  11_7       0.3761182
## 2      HR32 Helsinki_Finland     Smolyan_Bulgaria 11_30       0.4094155
## 3     95191 Helsinki_Finland Yekaterinburg_Russia  11_9       0.4146880
## 4     Sa948 Helsinki_Finland        Sätuna_Sweden 11_32       0.3880394
## 5      FSE7 Helsinki_Finland     Helsinki_Finland    11       0.0000000
## 6     93134 Helsinki_Finland      Aalborg_Denmark 11_25       0.4086827
##   Acceptormito geographicdistance initweight weightloss plate_rep_time
## 1            5               2078     1.1409  0.1913534         X2_2_i
## 2            5               1858     1.0707  0.2267713         X3_2_i
## 3            5               2078     1.1425  0.2595471         X1_1_i
## 4            5                778     1.1308  0.3320070         X2_2_i
## 5            5                  0     0.8004  0.1415667         X3_2_i
## 6            5                934     1.2094  0.1962811         X1_1_i
##   plate rep         Type  ID_plate geographicdistancestd
## 1    X2   2 Heterokaryon  Het46_X2             0.6313005
## 2    X3   2 Heterokaryon Het205_X3             0.4212340
## 3    X1   1 Heterokaryon  Het54_X1             0.6313005
## 4    X2   2 Heterokaryon Het234_X2            -0.6100014
## 5    X3   2   Homokaryon  Hom11_X3            -1.3528728
## 6    X1   1 Heterokaryon Het172_X1            -0.4610452
##   geneticdistancestd geneticdistancestdSq geneticdistancefac initweightstd
## 1         0.06125775          0.003752512               0.37     0.7106281
## 2         0.37385710          0.139769132               0.40     0.1910697
## 3         0.42335619          0.179230466               0.41     0.7224698
## 4         0.17317604          0.029989939               0.38     0.6358768
## 5        -3.46978937         12.039438250               0.00    -1.8094522
## 6         0.36697757          0.134672534               0.40     1.2176046
##   initweightstdSq AcceptorMM Midparent Mito AccDonCov HetDonorbyHom
## 1      0.50499224         11         7    5         7             7
## 2      0.03650762         11        30    5        30            30
## 3      0.52196268         11         9    5         9             9
## 4      0.40433928         11        32    5        32            32
## 5      3.27411733         11        11    5        11            11
## 6      1.48256088         11        25    5        25            25
##   HetAccbyHom DonorhomWL  AcchomWL midhompar midhomparcent
## 1          11         NA 0.1324016        NA            NA
## 2          11 0.07476087 0.1324016 0.1035812   -0.06348117
## 3          11 0.13500723 0.1324016 0.1337044   -0.03335799
## 4          11 0.23740947 0.1324016 0.1849055    0.01784313
## 5          11 0.13240160 0.1324016 0.1324016   -0.03466080
## 6          11         NA 0.1324016        NA            NA
##   midparentheterosis   hetvigor besthompar Acceptor15 DonorhomWL.1
## 1                 NA         NA         NA         11           NA
## 2         0.10080454 0.10080454  0.1324016         11   0.07476087
## 3         0.09704782 0.09704782  0.1350072         11   0.13500723
## 4         0.10178127 0.10178127  0.2374095         11   0.23740947
## 5         0.00000000 0.00000000  0.1324016         11   0.13240160
## 6                 NA         NA         NA         11           NA
##   AcchomWL.1    logWLcent besthomparcent strain18
## 1  0.1324016 -0.037622462             NA        3
## 2  0.1324016 -0.008326635    -0.08182514        1
## 3  0.1324016  0.018039832    -0.07921951        1
## 4  0.1324016  0.073974403     0.02318273        1
## 5  0.1324016 -0.080310802    -0.08182514        1
## 6  0.1324016 -0.033494787             NA        3
data <- rbind(dataGR[, c("geno", "Type", "DonorSG", "Acceptor", "Donor")], dataWL[, c("geno", "Type", "DonorSG", "Acceptor", "Donor")])
data$Trait <- c(rep("GR", nrow(dataGR)), rep("WL", nrow(dataWL)))
data$geno_trait <- paste(data$geno, data$Trait, sep="_")
data <- data[!duplicated(data$geno_trait)&data$Type=="Heterokaryon",]
data$geno <- factor(data$geno)
data$Acceptor <- factor(data$Acceptor, levels=sort(unique(data$Donor)))


table(data$geno, data$Trait)
##        
##         GR WL
##   11_15  1  1
##   11_18  1  1
##   11_19  1  1
##   11_2   1  1
##   11_20  1  0
##   11_21  1  1
##   11_22  1  1
##   11_23  1  1
##   11_24  1  1
##   11_25  1  1
##   11_26  1  1
##   11_30  1  1
##   11_31  1  1
##   11_32  1  1
##   11_34  1  1
##   11_5   1  1
##   11_6   1  1
##   11_7   1  1
##   11_9   1  1
##   14_30  1  0
##   14_5   1  1
##   18_11  1  1
##   18_19  1  1
##   18_2   1  1
##   18_20  1  1
##   18_24  1  1
##   18_25  1  1
##   18_26  1  1
##   18_30  1  1
##   18_31  1  1
##   18_32  1  1
##   18_33  1  1
##   18_5   1  1
##   18_9   1  1
##   19_1   1  1
##   19_11  1  1
##   19_15  1  1
##   19_18  1  1
##   19_2   1  1
##   19_20  1  1
##   19_24  1  1
##   19_26  1  1
##   19_27  1  1
##   19_30  1  1
##   19_31  1  1
##   19_32  1  1
##   19_5   1  1
##   19_9   1  1
##   2_11   1  1
##   2_14   1  1
##   2_15   1  1
##   2_18   1  1
##   2_19   1  1
##   2_20   1  0
##   2_24   1  1
##   2_26   1  1
##   2_27   1  1
##   2_3    1  1
##   2_30   1  1
##   2_31   1  1
##   2_32   1  1
##   2_33   1  1
##   2_34   1  1
##   2_5    1  1
##   2_9    1  1
##   20_11  1  1
##   20_12  1  0
##   20_14  1  1
##   20_15  1  1
##   20_18  1  0
##   20_19  1  0
##   20_2   1  0
##   20_24  1  0
##   20_26  1  0
##   20_27  1  1
##   20_3   1  1
##   20_30  1  0
##   20_31  1  0
##   20_32  1  1
##   20_5   1  0
##   20_7   1  0
##   20_9   1  0
##   23_11  1  1
##   24_1   1  0
##   24_10  1  1
##   24_11  1  1
##   24_13  1  1
##   24_14  1  1
##   24_18  1  1
##   24_19  1  1
##   24_2   1  0
##   24_20  1  1
##   24_22  1  0
##   24_25  1  0
##   24_26  1  0
##   24_27  1  0
##   24_3   1  0
##   24_30  1  1
##   24_31  1  0
##   24_32  1  0
##   24_33  1  0
##   24_34  1  1
##   24_35  1  0
##   24_4   1  0
##   24_5   1  0
##   24_7   1  1
##   24_9   1  1
##   26_1   1  1
##   26_11  1  1
##   26_18  1  1
##   26_19  1  1
##   26_2   1  1
##   26_20  1  1
##   26_24  1  1
##   26_27  1  1
##   26_30  1  1
##   26_31  1  1
##   26_32  1  1
##   26_35  1  1
##   26_5   1  1
##   26_7   1  1
##   26_9   1  1
##   27_18  1  1
##   27_19  1  1
##   27_2   1  1
##   27_20  1  0
##   27_24  1  1
##   27_26  1  1
##   27_30  1  1
##   27_31  1  1
##   27_32  1  1
##   27_5   1  1
##   30_11  1  1
##   30_12  1  1
##   30_13  1  1
##   30_14  1  1
##   30_15  1  1
##   30_18  1  1
##   30_19  1  1
##   30_2   1  1
##   30_20  1  1
##   30_21  1  1
##   30_22  1  1
##   30_23  1  1
##   30_24  1  1
##   30_26  1  1
##   30_27  1  1
##   30_31  1  1
##   30_32  1  1
##   30_33  1  1
##   30_4   1  1
##   30_5   1  1
##   30_6   1  1
##   30_9   1  1
##   31_11  1  1
##   31_13  1  1
##   31_18  1  1
##   31_19  1  1
##   31_2   1  1
##   31_20  1  1
##   31_21  1  1
##   31_24  1  1
##   31_26  1  1
##   31_27  1  1
##   31_30  1  1
##   31_32  1  1
##   31_33  1  1
##   31_34  1  1
##   31_5   1  1
##   31_7   1  1
##   31_9   1  1
##   32_1   1  1
##   32_10  1  1
##   32_11  1  1
##   32_13  1  1
##   32_14  1  1
##   32_15  1  1
##   32_18  1  1
##   32_19  1  1
##   32_2   1  1
##   32_20  1  0
##   32_23  1  1
##   32_24  1  1
##   32_26  1  1
##   32_27  1  1
##   32_3   1  1
##   32_30  1  1
##   32_31  1  1
##   32_33  1  1
##   32_35  1  1
##   32_4   1  1
##   32_5   1  1
##   32_6   1  1
##   32_9   1  1
##   5_1    1  1
##   5_11   1  1
##   5_12   1  1
##   5_13   1  1
##   5_14   1  1
##   5_15   1  1
##   5_19   1  1
##   5_2    1  1
##   5_20   1  1
##   5_22   1  1
##   5_24   1  1
##   5_26   1  1
##   5_27   1  1
##   5_3    1  1
##   5_30   1  1
##   5_31   1  1
##   5_32   1  1
##   5_33   1  1
##   5_4    1  1
##   5_9    1  1
##   9_11   1  1
##   9_18   1  1
##   9_19   1  1
##   9_2    1  1
##   9_20   1  1
##   9_26   1  1
##   9_27   1  1
##   9_30   1  1
##   9_31   1  1
##   9_32   1  1
##   9_5    1  1
##   32_21  0  1
##   5_23   0  1
table(data$Acceptor, data$Trait)
##     
##      GR WL
##   1   0  0
##   2  17 16
##   3   0  0
##   4   0  0
##   5  20 21
##   6   0  0
##   7   0  0
##   9  11 11
##   10  0  0
##   11 19 18
##   12  0  0
##   13  0  0
##   14  2  1
##   15  0  0
##   18 13 13
##   19 14 14
##   20 17  6
##   21  0  0
##   22  0  0
##   23  1  1
##   24 24 11
##   25  0  0
##   26 15 15
##   27 10  9
##   30 22 22
##   31 17 17
##   32 23 23
##   33  0  0
##   34  0  0
##   35  0  0
table(data$Donor, data$Trait)
##     
##      GR WL
##   1   5  4
##   2  12 10
##   3   5  4
##   4   4  3
##   5  13 11
##   6   3  3
##   7   5  4
##   9  11 10
##   10  2  2
##   11 12 12
##   12  3  2
##   13  5  5
##   14  6  6
##   15  7  7
##   18 11 10
##   19 12 11
##   20 12  8
##   21  3  4
##   22  4  3
##   23  3  4
##   24 11 10
##   25  3  2
##   26 12 10
##   27 10  9
##   30 13 11
##   31 12 10
##   32 12 11
##   33  7  6
##   34  4  4
##   35  3  2
table(data$Acceptor[!duplicated(data$geno)])
## 
##  1  2  3  4  5  6  7  9 10 11 12 13 14 15 18 19 20 21 22 23 24 25 26 27 30 
##  0 17  0  0 21  0  0 11  0 19  0  0  2  0 13 14 17  0  0  1 24  0 15 10 22 
## 31 32 33 34 35 
## 17 24  0  0  0
table(data$Donor[!duplicated(data$geno)])
## 
##  1  2  3  4  5  6  7  9 10 11 12 13 14 15 18 19 20 21 22 23 24 25 26 27 30 
##  5 12  5  4 13  3  5 11  2 12  3  5  6  7 11 12 12  4  4  4 11  3 12 10 13 
## 31 32 33 34 35 
## 12 12  7  4  3
data <- merge(x=dataGR, y=dataWL, by="geno_DonorSG")

head(data)
##   geno_DonorSG Acceptor.x Donor.x    logGR logintGR         unit    intGR
## 1         11_0         11      11 1.942217 2.761546    11_X6_1_1 12.75000
## 2      11_15_0         11      15 1.621652 2.725354 11_15_X4_1_3 13.91667
## 3      11_18_0         11      18 1.936294 2.830828 11_18_X1_1_4 18.75000
## 4      11_19_0         11      19 1.941956 2.930961 11_19_X1_2_1 19.83333
## 5       11_2_0         11       2 1.765159 2.663283  11_2_X1_1_1 11.66667
## 6      11_21_1         11      21 1.647588 2.443278 11_21_X1_2_2 15.41667
##   slopeGR   ID.x DonorSG.x AcceptorName.x DonorName.x    AcceptorPop.x
## 1    6.25  Hom11         0           FSE7        FSE7 Helsinki_Finland
## 2    4.25  Het96         0           FSE7      RB9411 Helsinki_Finland
## 3    7.25 Het103         0           FSE7 Sa1595(Ref) Helsinki_Finland
## 4    7.50 Het117         0           FSE7       87074 Helsinki_Finland
## 5    6.00   Het9         0           FSE7       87179 Helsinki_Finland
## 6    5.75 Het144         1           FSE7       90137 Helsinki_Finland
##         DonorPop.x geno.x geneticdistance.x Acceptormito.x
## 1 Helsinki_Finland     11         0.0000000              5
## 2   Ramsåsa_Sweden  11_15         0.3798179              5
## 3    Sätuna_Sweden  11_18         0.4538297              5
## 4    Vicenza_Italy  11_19         0.4065469              5
## 5      Oslo_Norway   11_2         0.3914800              5
## 6 Kaunas_Lithuania  11_21         0.3873960              5
##   Geographicdistance assay plate.x rep.x HoStockplatesAcc HoStockplatesDon
## 1                  0     6       1     1            11_X3            11_X3
## 2                827     4       1     3                1                1
## 3                778     1       1     4                1                1
## 4               1823     1       2     1                1                1
## 5                812     1       1     1                1                1
## 6                590     1       2     2                1                1
##   HetSynthesis HetStockplates HetPrecultures    Date       Type.x
## 1           NA             NA           11_4 Mar2016   Homokaryon
## 2            1              3              4       3 Heterokaryon
## 3            1              1              1       4 Heterokaryon
## 4            1              1              1       4 Heterokaryon
## 5            1              1              1       4 Heterokaryon
## 6            1              1              1       4 Heterokaryon
##   geographicdistancestd.x geneticdistancestd.x geneticdistancestdSq.x
## 1              -1.3016693           -2.9616024             8.77108856
## 2              -0.5120013            0.1742739             0.03037141
## 3              -0.5587894            0.7853352             0.61675145
## 4               0.4390378            0.3949555             0.15598982
## 5              -0.5263242            0.2705593             0.07320231
## 6              -0.7383028            0.2368410             0.05609364
##   geneticdistancestdCub geneticdistancegrp geneticdistancefac.x
## 1         -25.976476623               0.00                 0.00
## 2           0.005292945               0.37                 0.37
## 3           0.484356650               0.45                 0.45
## 4           0.061609031               0.40                 0.40
## 5           0.019805564               0.39                 0.39
## 6           0.013285270               0.38                 0.38
##   geno_synthesis geno_synthesis_HetStockplates
## 1          11_NA                      11_NA_NA
## 2        11_15_1                     11_15_1_3
## 3        11_18_1                     11_18_1_1
## 4        11_19_1                     11_19_1_1
## 5         11_2_1                      11_2_1_1
## 6        11_21_1                     11_21_1_1
##   geno_synthesis_HetStockplates_HetPreculture
## 1                               11_NA_NA_11_4
## 2                                 11_15_1_3_4
## 3                                 11_18_1_1_1
## 4                                 11_19_1_1_1
## 5                                  11_2_1_1_1
## 6                                 11_21_1_1_1
##   geno_synthesis_HetStockplates_HetPreculture_assay
## 1                                   11_NA_NA_11_4_6
## 2                                     11_15_1_3_4_4
## 3                                     11_18_1_1_1_1
## 4                                     11_19_1_1_1_1
## 5                                      11_2_1_1_1_1
## 6                                     11_21_1_1_1_1
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate
## 1                                       11_NA_NA_11_4_6_1
## 2                                         11_15_1_3_4_4_1
## 3                                         11_18_1_1_1_1_1
## 4                                         11_19_1_1_1_1_2
## 5                                          11_2_1_1_1_1_1
## 6                                         11_21_1_1_1_1_2
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate_rep
## 1                                         11_NA_NA_11_4_6_1_1
## 2                                           11_15_1_3_4_4_1_3
## 3                                           11_18_1_1_1_1_1_4
## 4                                           11_19_1_1_1_1_2_1
## 5                                            11_2_1_1_1_1_1_1
## 6                                           11_21_1_1_1_1_2_2
##   Acceptor_HoStockplatesAcc Donor_HoStockplatesDon AcceptorMM.x
## 1                  11_11_X3               11_11_X3           11
## 2                      11_1                   15_1           11
## 3                      11_1                   18_1           11
## 4                      11_1                   19_1           11
## 5                      11_1                    2_1           11
## 6                      11_1                   21_1           11
##   Midparent.x AccDonCov.x HetDonorbyHom.x HetAccbyHom.x Mito.x
## 1          11          11              11            11      5
## 2          15          15              15            11      5
## 3          18          18              18            11      5
## 4          19          19              19            11      5
## 5           2           2               2            11      5
## 6          21          21              21            11      5
##   Acceptor15.x DonorhomGR AcchomGR midhompar.x midhomparcent.x   logGRcent
## 1           11  1.9422174 1.942217    1.942217      0.29473623  0.14798276
## 2           11  1.3637976 1.942217    1.653007      0.00552631 -0.17258289
## 3           11  0.7038478 1.942217    1.323033     -0.32444859  0.14205902
## 4           11  1.6269875 1.942217    1.784602      0.13712130  0.14772128
## 5           11  1.3268665 1.942217    1.634542     -0.01293924 -0.02907527
## 6           11         NA 1.942217          NA              NA -0.14664696
##   midparentheterosis.x  hetvigor.x besthompar.x besthomparcent.x
## 1           0.00000000  0.00000000     1.942217       0.07045624
## 2          -0.03135574 -0.03135574     1.942217       0.07045624
## 3           0.61326107  0.61326107     1.942217       0.07045624
## 4           0.15735345  0.15735345     1.942217       0.07045624
## 5           0.13061743  0.13061743     1.942217       0.07045624
## 6                   NA          NA           NA               NA
##   strain18.x       GR Acceptor.y Donor.y logweightloss   ID.y DonorSG.y
## 1          1 6.974198         11      11     0.1324016  Hom11         0
## 2          1 5.061444         11      15     0.1178965  Het96         0
## 3          2 6.933007         11      18     0.2118536 Het103         0
## 4          1 6.972375         11      19     0.1823559 Het117         0
## 5          1 5.842503         11       2     0.2292160   Het9         0
## 6          3 5.194434         11      21     0.2371694 Het144         1
##   AcceptorName.y DonorName.y    AcceptorPop.y       DonorPop.y geno.y
## 1           FSE7        FSE7 Helsinki_Finland Helsinki_Finland     11
## 2           FSE7      RB9411 Helsinki_Finland   Ramsåsa_Sweden  11_15
## 3           FSE7 Sa1595(Ref) Helsinki_Finland    Sätuna_Sweden  11_18
## 4           FSE7       87074 Helsinki_Finland    Vicenza_Italy  11_19
## 5           FSE7       87179 Helsinki_Finland      Oslo_Norway   11_2
## 6           FSE7       90137 Helsinki_Finland Kaunas_Lithuania  11_21
##   geneticdistance.y Acceptormito.y geographicdistance initweight
## 1         0.0000000              5                  0     0.8004
## 2         0.3798179              5                827     1.1448
## 3         0.4538297              5                778     1.0529
## 4         0.4065469              5               1823     1.2000
## 5         0.3914800              5                812     1.1969
## 6         0.3873960              5                590     1.0883
##   weightloss plate_rep_time plate.y rep.y       Type.y  ID_plate
## 1  0.1415667         X3_2_i      X3     2   Homokaryon  Hom11_X3
## 2  0.1251276         X1_1_i      X1     1 Heterokaryon  Het96_X1
## 3  0.2359669         X3_2_i      X3     2 Heterokaryon Het103_X3
## 4  0.2000412         X3_2_i      X3     2 Heterokaryon Het117_X3
## 5  0.2576137         X1_1_i      X1     1 Heterokaryon   Het9_X1
## 6  0.2676558         X2_2_i      X2     2 Heterokaryon Het144_X2
##   geographicdistancestd.y geneticdistancestd.y geneticdistancestdSq.y
## 1              -1.3528728          -3.46978937           12.039438250
## 2              -0.5632139           0.09599101            0.009214274
## 3              -0.6100014           0.79082403            0.625402648
## 4               0.3878143           0.34692624            0.120357815
## 5              -0.5775366           0.20547629            0.042220506
## 6              -0.7895127           0.16713547            0.027934265
##   geneticdistancefac.y initweightstd initweightstdSq AcceptorMM.y
## 1                 0.00   -1.80945222     3.274117329           11
## 2                 0.37    0.73949242     0.546849035           11
## 3                 0.45    0.05932978     0.003520023           11
## 4                 0.40    1.14803407     1.317982217           11
## 5                 0.39    1.12509060     1.265828868           11
## 6                 0.38    0.32132932     0.103252530           11
##   Midparent.y Mito.y AccDonCov.y HetDonorbyHom.y HetAccbyHom.y DonorhomWL
## 1          11      5          11              11            11 0.13240160
## 2          15      5          15              15            11 0.07285694
## 3          18      5          18              18            11 0.02297559
## 4          19      5          19              19            11 0.26477279
## 5           2      5           2               2            11 0.10118138
## 6          21      5          21              21            11         NA
##    AcchomWL midhompar.y midhomparcent.y midparentheterosis.y  hetvigor.y
## 1 0.1324016   0.1324016     -0.03466080           0.00000000  0.00000000
## 2 0.1324016   0.1026293     -0.06443313           0.01526719  0.01526719
## 3 0.1324016   0.0776886     -0.08937381           0.13416502  0.13416502
## 4 0.1324016   0.1985872      0.03152479          -0.01623128 -0.01623128
## 5 0.1324016   0.1167915     -0.05027091           0.11242452  0.11242452
## 6 0.1324016          NA              NA                   NA          NA
##   besthompar.y Acceptor15.y DonorhomWL.1 AcchomWL.1    logWLcent
## 1    0.1324016           11   0.13240160  0.1324016 -0.080310802
## 2    0.1324016           11   0.07285694  0.1324016 -0.094815941
## 3    0.1324016           11   0.02297559  0.1324016 -0.000858789
## 4    0.2647728           11   0.26477279  0.1324016 -0.030356487
## 5    0.1324016           11   0.10118138  0.1324016  0.016503612
## 6           NA           11           NA  0.1324016  0.024456950
##   besthomparcent.y strain18.y
## 1      -0.08182514          1
## 2      -0.08182514          1
## 3      -0.08182514          2
## 4       0.05054605          1
## 5      -0.08182514          1
## 6               NA          3

2 Summary and distribution of the two traits

2.1 Summary statistics

## For MGR
## Heterokaryon with synthesised with the same homokaryon (once as a slow grower, once as a normal grower)
SG0_1 <- levels(dataGR$genoHeterokaryon)[table(dataGR$genoHeterokaryon)>1]
tapply(dataGR$GR[dataGR$genoHeterokaryon%in%SG0_1], list(dataGR$DonorSG[dataGR$genoHeterokaryon%in%SG0_1],dataGR$genoHeterokaryon[dataGR$genoHeterokaryon%in%SG0_1]), mean)
## <0 x 0 matrix>
## Get rid of the replicate where the donor homokaryon is senescent
dataGR <- dataGR[!dataGR$geno_DonorSG%in%paste0(SG0_1, "_1"),]
length(dataGR$GR[dataGR$Type=="Heterokaryon"])
## [1] 230
length(dataGR$GR[dataGR$Type=="Heterokaryon"&dataGR$DonorSG==0])
## [1] 169
length(dataGR$GR[dataGR$Type=="Heterokaryon"&dataGR$DonorSG==1])
## [1] 61
## For WWL
## Heterokaryon with synthesised with the same homokaryon (once as a slow grower, once as a normal grower)
SG0_1 <- levels(dataWL$geno)[table(dataWL$geno)>1]
tapply(dataWL$logweightloss[dataWL$geno%in%SG0_1], list(dataWL$DonorSG[dataWL$geno%in%SG0_1],dataWL$geno[dataWL$geno%in%SG0_1]), mean)
##   11 11_15 11_18 11_19 11_2 11_21 11_22 11_23 11_24 11_25 11_26 11_30
## 0 NA    NA    NA    NA   NA    NA    NA    NA    NA    NA    NA    NA
## 1 NA    NA    NA    NA   NA    NA    NA    NA    NA    NA    NA    NA
##   11_31 11_32 11_34 11_5 11_6 11_7 11_9 13 14 14_5 15 18 18_11 18_19 18_2
## 0    NA    NA    NA   NA   NA   NA   NA NA NA   NA NA NA    NA    NA   NA
## 1    NA    NA    NA   NA   NA   NA   NA NA NA   NA NA NA    NA    NA   NA
##   18_20 18_24 18_25 18_26 18_30 18_31 18_32 18_33 18_5 18_9 19 19_1 19_11
## 0    NA    NA    NA    NA    NA    NA    NA    NA   NA   NA NA   NA    NA
## 1    NA    NA    NA    NA    NA    NA    NA    NA   NA   NA NA   NA    NA
##   19_15 19_18 19_2 19_20 19_24 19_26 19_27 19_30 19_31 19_32 19_5 19_9  2
## 0    NA    NA   NA    NA    NA    NA    NA    NA    NA    NA   NA   NA NA
## 1    NA    NA   NA    NA    NA    NA    NA    NA    NA    NA   NA   NA NA
##   2_11 2_14 2_15 2_18 2_19 2_24 2_26 2_27 2_3 2_30 2_31 2_32 2_33 2_34 2_5
## 0   NA   NA   NA   NA   NA   NA   NA   NA  NA   NA   NA   NA   NA   NA  NA
## 1   NA   NA   NA   NA   NA   NA   NA   NA  NA   NA   NA   NA   NA   NA  NA
##   2_9 20 20_11 20_14 20_15 20_27 20_3 20_32 23_11 24 24_10 24_11 24_13
## 0  NA NA    NA    NA    NA    NA   NA    NA    NA NA    NA    NA    NA
## 1  NA NA    NA    NA    NA    NA   NA    NA    NA NA    NA    NA    NA
##   24_14 24_18 24_19 24_20 24_30 24_34 24_7 24_9 26 26_1 26_11 26_18 26_19
## 0    NA    NA    NA    NA    NA    NA   NA   NA NA   NA    NA    NA    NA
## 1    NA    NA    NA    NA    NA    NA   NA   NA NA   NA    NA    NA    NA
##   26_2 26_20 26_24 26_27 26_30 26_31 26_32 26_35 26_5 26_7 26_9 27 27_18
## 0   NA    NA    NA    NA    NA    NA    NA    NA   NA   NA   NA NA    NA
## 1   NA    NA    NA    NA    NA    NA    NA    NA   NA   NA   NA NA    NA
##   27_19 27_2 27_24 27_26 27_30 27_31 27_32 27_5 30 30_11 30_12 30_13 30_14
## 0    NA   NA    NA    NA    NA    NA    NA   NA NA    NA    NA    NA    NA
## 1    NA   NA    NA    NA    NA    NA    NA   NA NA    NA    NA    NA    NA
##   30_15 30_18 30_19 30_2 30_20 30_21 30_22 30_23 30_24 30_26 30_27 30_31
## 0    NA    NA    NA   NA    NA    NA    NA    NA    NA    NA    NA    NA
## 1    NA    NA    NA   NA    NA    NA    NA    NA    NA    NA    NA    NA
##   30_32 30_33 30_4 30_5 30_6 30_9 31 31_11 31_13 31_18 31_19 31_2 31_20
## 0    NA    NA   NA   NA   NA   NA NA    NA    NA    NA    NA   NA    NA
## 1    NA    NA   NA   NA   NA   NA NA    NA    NA    NA    NA   NA    NA
##   31_21 31_24 31_26 31_27 31_30 31_32 31_33 31_34 31_5 31_7 31_9 32 32_1
## 0    NA    NA    NA    NA    NA    NA    NA    NA   NA   NA   NA NA   NA
## 1    NA    NA    NA    NA    NA    NA    NA    NA   NA   NA   NA NA   NA
##   32_10 32_11 32_13 32_14 32_15 32_18 32_19 32_2 32_21 32_23 32_24 32_26
## 0    NA    NA    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
## 1    NA    NA    NA    NA    NA    NA    NA   NA    NA    NA    NA    NA
##   32_27 32_3 32_30 32_31 32_33 32_35 32_4 32_5 32_6 32_9  5 5_1 5_11 5_12
## 0    NA   NA    NA    NA    NA    NA   NA   NA   NA   NA NA  NA   NA   NA
## 1    NA   NA    NA    NA    NA    NA   NA   NA   NA   NA NA  NA   NA   NA
##   5_13 5_14 5_15 5_19 5_2 5_20 5_22 5_23       5_24 5_26 5_27 5_3 5_30
## 0   NA   NA   NA   NA  NA   NA   NA   NA 0.23026306   NA   NA  NA   NA
## 1   NA   NA   NA   NA  NA   NA   NA   NA 0.03741417   NA   NA  NA   NA
##   5_31 5_32 5_33 5_4 5_9  9 9_11 9_18 9_19 9_2 9_20 9_26 9_27 9_30 9_31
## 0   NA   NA   NA  NA  NA NA   NA   NA   NA  NA   NA   NA   NA   NA   NA
## 1   NA   NA   NA  NA  NA NA   NA   NA   NA  NA   NA   NA   NA   NA   NA
##   9_32 9_5
## 0   NA  NA
## 1   NA  NA
## Get rid of the replicate where the donor homokaryon is senescent
dataWL <- dataWL[!dataWL$geno_DonorSG%in%paste0(SG0_1, "_1"),]
head(dataWL)
##   Acceptor Donor geno_DonorSG logweightloss     ID DonorSG AcceptorName
## 1       11     7       11_7_1     0.1750899  Het46       1         FSE7
## 2       11    30      11_30_0     0.2043858 Het205       0         FSE7
## 3       11     9       11_9_0     0.2307522  Het54       0         FSE7
## 4       11    32      11_32_0     0.2866868 Het234       0         FSE7
## 5       11    11         11_0     0.1324016  Hom11       0         FSE7
## 6       11    25      11_25_1     0.1792176 Het172       1         FSE7
##   DonorName      AcceptorPop             DonorPop  geno geneticdistance
## 1     95156 Helsinki_Finland Yekaterinburg_Russia  11_7       0.3761182
## 2      HR32 Helsinki_Finland     Smolyan_Bulgaria 11_30       0.4094155
## 3     95191 Helsinki_Finland Yekaterinburg_Russia  11_9       0.4146880
## 4     Sa948 Helsinki_Finland        Sätuna_Sweden 11_32       0.3880394
## 5      FSE7 Helsinki_Finland     Helsinki_Finland    11       0.0000000
## 6     93134 Helsinki_Finland      Aalborg_Denmark 11_25       0.4086827
##   Acceptormito geographicdistance initweight weightloss plate_rep_time
## 1            5               2078     1.1409  0.1913534         X2_2_i
## 2            5               1858     1.0707  0.2267713         X3_2_i
## 3            5               2078     1.1425  0.2595471         X1_1_i
## 4            5                778     1.1308  0.3320070         X2_2_i
## 5            5                  0     0.8004  0.1415667         X3_2_i
## 6            5                934     1.2094  0.1962811         X1_1_i
##   plate rep         Type  ID_plate geographicdistancestd
## 1    X2   2 Heterokaryon  Het46_X2             0.6313005
## 2    X3   2 Heterokaryon Het205_X3             0.4212340
## 3    X1   1 Heterokaryon  Het54_X1             0.6313005
## 4    X2   2 Heterokaryon Het234_X2            -0.6100014
## 5    X3   2   Homokaryon  Hom11_X3            -1.3528728
## 6    X1   1 Heterokaryon Het172_X1            -0.4610452
##   geneticdistancestd geneticdistancestdSq geneticdistancefac initweightstd
## 1         0.06125775          0.003752512               0.37     0.7106281
## 2         0.37385710          0.139769132               0.40     0.1910697
## 3         0.42335619          0.179230466               0.41     0.7224698
## 4         0.17317604          0.029989939               0.38     0.6358768
## 5        -3.46978937         12.039438250               0.00    -1.8094522
## 6         0.36697757          0.134672534               0.40     1.2176046
##   initweightstdSq AcceptorMM Midparent Mito AccDonCov HetDonorbyHom
## 1      0.50499224         11         7    5         7             7
## 2      0.03650762         11        30    5        30            30
## 3      0.52196268         11         9    5         9             9
## 4      0.40433928         11        32    5        32            32
## 5      3.27411733         11        11    5        11            11
## 6      1.48256088         11        25    5        25            25
##   HetAccbyHom DonorhomWL  AcchomWL midhompar midhomparcent
## 1          11         NA 0.1324016        NA            NA
## 2          11 0.07476087 0.1324016 0.1035812   -0.06348117
## 3          11 0.13500723 0.1324016 0.1337044   -0.03335799
## 4          11 0.23740947 0.1324016 0.1849055    0.01784313
## 5          11 0.13240160 0.1324016 0.1324016   -0.03466080
## 6          11         NA 0.1324016        NA            NA
##   midparentheterosis   hetvigor besthompar Acceptor15 DonorhomWL.1
## 1                 NA         NA         NA         11           NA
## 2         0.10080454 0.10080454  0.1324016         11   0.07476087
## 3         0.09704782 0.09704782  0.1350072         11   0.13500723
## 4         0.10178127 0.10178127  0.2374095         11   0.23740947
## 5         0.00000000 0.00000000  0.1324016         11   0.13240160
## 6                 NA         NA         NA         11           NA
##   AcchomWL.1    logWLcent besthomparcent strain18
## 1  0.1324016 -0.037622462             NA        3
## 2  0.1324016 -0.008326635    -0.08182514        1
## 3  0.1324016  0.018039832    -0.07921951        1
## 4  0.1324016  0.073974403     0.02318273        1
## 5  0.1324016 -0.080310802    -0.08182514        1
## 6  0.1324016 -0.033494787             NA        3
length(dataWL$logweightloss[dataWL$Type=="Heterokaryon"])
## [1] 198
length(dataWL$logweightloss[dataWL$Type=="Heterokaryon"&dataWL$DonorSG==0])
## [1] 146
length(dataWL$logweightloss[dataWL$Type=="Heterokaryon"&dataWL$DonorSG==1])
## [1] 52
tapply(dataGR$GR, dataGR$Type, mean)
## Heterokaryon   Homokaryon 
##     6.259496     5.347162
tapply(dataGR$GR, dataGR$Type, sd)
## Heterokaryon   Homokaryon 
##     1.256798     2.013554
tapply(dataGR$GR, dataGR$Type, var)
## Heterokaryon   Homokaryon 
##     1.579542     4.054400
tapply(dataWL$weightloss, dataWL$Type, mean)
## Heterokaryon   Homokaryon 
##    0.2464382    0.1704119
tapply(dataWL$weightloss, dataWL$Type, sd)
## Heterokaryon   Homokaryon 
##   0.07576439   0.10237175
tapply(dataWL$weightloss, dataWL$Type, var)
## Heterokaryon   Homokaryon 
##  0.005740243  0.010479974

2.2 Fig3: Plot distributions

# Function to make color transparent
makeTransparent = function(color, alpha = 0.5) {
    if (alpha < 0 | alpha > 1) 
        stop("alpha must be between 0 and 1")
    newcol <- col2rgb(col = color, alpha = FALSE)
    return(rgb(red = newcol[1], green = newcol[2], blue = newcol[3], alpha = 255 * 
        alpha, maxColorValue = 255))
}

colpal <- brewer.pal(3, "Set2")
bordercol <- makeTransparent(colpal[2], 0)


wcorr <- 7
hcorr <- 4

pdf(file="Figure3.pdf", width = wcorr, height = hcorr)


head(dataGR)
##   Acceptor Donor geno_DonorSG    logGR logintGR         unit    intGR
## 1       11    26      11_26_0 1.922916 2.802864 11_26_X1_2_2 17.91667
## 2       11    20      11_20_0 1.958506 2.839034 11_20_X6_1_3 16.83333
## 3       11    23      11_23_1 2.058940 3.065760 11_23_X1_2_3 21.83333
## 4       11    11         11_0 1.942217 2.761546    11_X6_1_1 12.75000
## 5       11     2       11_2_0 1.765159 2.663283  11_2_X1_1_1 11.66667
## 6       11     9       11_9_0 1.887094 2.740700  11_9_X4_2_4 11.83333
##   slopeGR     ID DonorSG AcceptorName DonorName      AcceptorPop
## 1    6.25 Het178       0         FSE7    Fas161 Helsinki_Finland
## 2    7.00 Het132       0         FSE7     87075 Helsinki_Finland
## 3    7.50 Het155       1         FSE7     91132 Helsinki_Finland
## 4    6.25  Hom11       0         FSE7      FSE7 Helsinki_Finland
## 5    6.00   Het9       0         FSE7     87179 Helsinki_Finland
## 6    5.50  Het54       0         FSE7     95191 Helsinki_Finland
##               DonorPop  geno geneticdistance Acceptormito
## 1       Munich_Germany 11_26       0.3902914            5
## 2        Vicenza_Italy 11_20       0.4085754            3
## 3      Saarema_Estonia 11_23       0.3996568            5
## 4     Helsinki_Finland    11       0.0000000            5
## 5          Oslo_Norway  11_2       0.3914800            5
## 6 Yekaterinburg_Russia  11_9       0.4146880            5
##   Geographicdistance assay plate rep HoStockplatesAcc HoStockplatesDon
## 1               1589     1     2   2                1                1
## 2               1823     6     1   3                3                2
## 3                292     1     2   3                1                1
## 4                  0     6     1   1            11_X3            11_X3
## 5                812     1     1   1                1                1
## 6               2078     4     2   4                1                1
##   HetSynthesis HetStockplates HetPrecultures    Date         Type
## 1            1              1              1       4 Heterokaryon
## 2            2              4              6       9 Heterokaryon
## 3            1              1              1       4 Heterokaryon
## 4           NA             NA           11_4 Mar2016   Homokaryon
## 5            1              1              1       4 Heterokaryon
## 6            1              3              4       3 Heterokaryon
##   geographicdistancestd geneticdistancestd geneticdistancestdSq
## 1             0.2156009          0.2607463           0.06798862
## 2             0.4390378          0.4117039           0.16950014
## 3            -1.0228506          0.3380697           0.11429109
## 4            -1.3016693         -2.9616024           8.77108856
## 5            -0.5263242          0.2705593           0.07320231
## 6             0.6825268          0.4621707           0.21360178
##   geneticdistancestdCub geneticdistancegrp geneticdistancefac
## 1            0.01772778               0.39               0.39
## 2            0.06978387               0.40               0.40
## 3            0.03863835               0.39               0.39
## 4          -25.97647662               0.00               0.00
## 5            0.01980556               0.39               0.39
## 6            0.09872049               0.41               0.41
##   geno_synthesis geno_synthesis_HetStockplates
## 1        11_26_1                     11_26_1_1
## 2        11_20_2                     11_20_2_4
## 3        11_23_1                     11_23_1_1
## 4          11_NA                      11_NA_NA
## 5         11_2_1                      11_2_1_1
## 6         11_9_1                      11_9_1_3
##   geno_synthesis_HetStockplates_HetPreculture
## 1                                 11_26_1_1_1
## 2                                 11_20_2_4_6
## 3                                 11_23_1_1_1
## 4                               11_NA_NA_11_4
## 5                                  11_2_1_1_1
## 6                                  11_9_1_3_4
##   geno_synthesis_HetStockplates_HetPreculture_assay
## 1                                     11_26_1_1_1_1
## 2                                     11_20_2_4_6_6
## 3                                     11_23_1_1_1_1
## 4                                   11_NA_NA_11_4_6
## 5                                      11_2_1_1_1_1
## 6                                      11_9_1_3_4_4
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate
## 1                                         11_26_1_1_1_1_2
## 2                                         11_20_2_4_6_6_1
## 3                                         11_23_1_1_1_1_2
## 4                                       11_NA_NA_11_4_6_1
## 5                                          11_2_1_1_1_1_1
## 6                                          11_9_1_3_4_4_2
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate_rep
## 1                                           11_26_1_1_1_1_2_2
## 2                                           11_20_2_4_6_6_1_3
## 3                                           11_23_1_1_1_1_2_3
## 4                                         11_NA_NA_11_4_6_1_1
## 5                                            11_2_1_1_1_1_1_1
## 6                                            11_9_1_3_4_4_2_4
##   Acceptor_HoStockplatesAcc Donor_HoStockplatesDon AcceptorMM Midparent
## 1                      11_1                   26_1         11        26
## 2                      11_3                   20_2         11        20
## 3                      11_1                   23_1         11        23
## 4                  11_11_X3               11_11_X3         11        11
## 5                      11_1                    2_1         11         2
## 6                      11_1                    9_1         11         9
##   AccDonCov HetDonorbyHom HetAccbyHom Mito Acceptor15 DonorhomGR AcchomGR
## 1        26            26          11    5         11   1.930952 1.942217
## 2        20            20          11    3         11   1.654298 1.942217
## 3        23            23          11    5         11         NA 1.942217
## 4        11            11          11    5         11   1.942217 1.942217
## 5         2             2          11    5         11   1.326866 1.942217
## 6         9             9          11    5         11   1.137679 1.942217
##   midhompar midhomparcent   logGRcent midparentheterosis    hetvigor
## 1  1.936585    0.28910352  0.12868091        -0.01366915 -0.01366915
## 2  1.798258    0.15077637  0.16427157         0.16024867  0.16024867
## 3        NA            NA  0.26470569                 NA          NA
## 4  1.942217    0.29473623  0.14798276         0.00000000  0.00000000
## 5  1.634542   -0.01293924 -0.02907527         0.13061743  0.13061743
## 6  1.539948   -0.10753281  0.09285899         0.34714527  0.34714527
##   besthompar besthomparcent strain18       GR
## 1   1.942217     0.07045624        1 6.840874
## 2   1.942217     0.07045624        1 7.088730
## 3         NA             NA        3 7.837660
## 4   1.942217     0.07045624        1 6.974198
## 5   1.942217     0.07045624        1 5.842503
## 6   1.942217     0.07045624        1 6.600158
rang <- range(dataGR$GR)

brks <- seq(0, 10, by = 0.5)

par(mar=c(5, 5, 2, 1), mfrow=c(1, 1), xpd=TRUE)

histFull <- hist(dataGR$GR[dataGR$Type=="Heterokaryon"], breaks = brks, plot = FALSE)
histFull$counts <- histFull$counts/sum(histFull$counts)

plot(histFull, col = colpal[1], xlab = "Mycelium growth rate (mm/day)", ylab = "Frequency distribution", axes = TRUE, main = "", border = NA, freq=TRUE, xlim=c(0, 10), ylim=c(0, 0.25), las=1)
histAns <- hist(dataGR$GR[dataGR$Type=="Homokaryon"], breaks = brks, plot = FALSE)
histAns$counts <- histAns$counts/sum(histAns$counts)
lines(histAns, col=colpal[2], border=bordercol)

lines(histFull, col = NA, border = "white")

legend(-0.25, 0.275, c("homokaryons (n=16)", "heterokaryons (n=225)"), fill=colpal[2:1], border="white", bty="n")


dev.off()
## quartz_off_screen 
##                 2

2.3 FigS6: Plot distributions

colpal <- brewer.pal(3, "Set2")
bordercol <- makeTransparent(colpal[2], 0)


wcorr <- 7
hcorr <- 4

pdf(file="FigureS6_Distributions.pdf", width = wcorr, height = hcorr)


## Graph for MGR

head(dataGR)
##   Acceptor Donor geno_DonorSG    logGR logintGR         unit    intGR
## 1       11    26      11_26_0 1.922916 2.802864 11_26_X1_2_2 17.91667
## 2       11    20      11_20_0 1.958506 2.839034 11_20_X6_1_3 16.83333
## 3       11    23      11_23_1 2.058940 3.065760 11_23_X1_2_3 21.83333
## 4       11    11         11_0 1.942217 2.761546    11_X6_1_1 12.75000
## 5       11     2       11_2_0 1.765159 2.663283  11_2_X1_1_1 11.66667
## 6       11     9       11_9_0 1.887094 2.740700  11_9_X4_2_4 11.83333
##   slopeGR     ID DonorSG AcceptorName DonorName      AcceptorPop
## 1    6.25 Het178       0         FSE7    Fas161 Helsinki_Finland
## 2    7.00 Het132       0         FSE7     87075 Helsinki_Finland
## 3    7.50 Het155       1         FSE7     91132 Helsinki_Finland
## 4    6.25  Hom11       0         FSE7      FSE7 Helsinki_Finland
## 5    6.00   Het9       0         FSE7     87179 Helsinki_Finland
## 6    5.50  Het54       0         FSE7     95191 Helsinki_Finland
##               DonorPop  geno geneticdistance Acceptormito
## 1       Munich_Germany 11_26       0.3902914            5
## 2        Vicenza_Italy 11_20       0.4085754            3
## 3      Saarema_Estonia 11_23       0.3996568            5
## 4     Helsinki_Finland    11       0.0000000            5
## 5          Oslo_Norway  11_2       0.3914800            5
## 6 Yekaterinburg_Russia  11_9       0.4146880            5
##   Geographicdistance assay plate rep HoStockplatesAcc HoStockplatesDon
## 1               1589     1     2   2                1                1
## 2               1823     6     1   3                3                2
## 3                292     1     2   3                1                1
## 4                  0     6     1   1            11_X3            11_X3
## 5                812     1     1   1                1                1
## 6               2078     4     2   4                1                1
##   HetSynthesis HetStockplates HetPrecultures    Date         Type
## 1            1              1              1       4 Heterokaryon
## 2            2              4              6       9 Heterokaryon
## 3            1              1              1       4 Heterokaryon
## 4           NA             NA           11_4 Mar2016   Homokaryon
## 5            1              1              1       4 Heterokaryon
## 6            1              3              4       3 Heterokaryon
##   geographicdistancestd geneticdistancestd geneticdistancestdSq
## 1             0.2156009          0.2607463           0.06798862
## 2             0.4390378          0.4117039           0.16950014
## 3            -1.0228506          0.3380697           0.11429109
## 4            -1.3016693         -2.9616024           8.77108856
## 5            -0.5263242          0.2705593           0.07320231
## 6             0.6825268          0.4621707           0.21360178
##   geneticdistancestdCub geneticdistancegrp geneticdistancefac
## 1            0.01772778               0.39               0.39
## 2            0.06978387               0.40               0.40
## 3            0.03863835               0.39               0.39
## 4          -25.97647662               0.00               0.00
## 5            0.01980556               0.39               0.39
## 6            0.09872049               0.41               0.41
##   geno_synthesis geno_synthesis_HetStockplates
## 1        11_26_1                     11_26_1_1
## 2        11_20_2                     11_20_2_4
## 3        11_23_1                     11_23_1_1
## 4          11_NA                      11_NA_NA
## 5         11_2_1                      11_2_1_1
## 6         11_9_1                      11_9_1_3
##   geno_synthesis_HetStockplates_HetPreculture
## 1                                 11_26_1_1_1
## 2                                 11_20_2_4_6
## 3                                 11_23_1_1_1
## 4                               11_NA_NA_11_4
## 5                                  11_2_1_1_1
## 6                                  11_9_1_3_4
##   geno_synthesis_HetStockplates_HetPreculture_assay
## 1                                     11_26_1_1_1_1
## 2                                     11_20_2_4_6_6
## 3                                     11_23_1_1_1_1
## 4                                   11_NA_NA_11_4_6
## 5                                      11_2_1_1_1_1
## 6                                      11_9_1_3_4_4
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate
## 1                                         11_26_1_1_1_1_2
## 2                                         11_20_2_4_6_6_1
## 3                                         11_23_1_1_1_1_2
## 4                                       11_NA_NA_11_4_6_1
## 5                                          11_2_1_1_1_1_1
## 6                                          11_9_1_3_4_4_2
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate_rep
## 1                                           11_26_1_1_1_1_2_2
## 2                                           11_20_2_4_6_6_1_3
## 3                                           11_23_1_1_1_1_2_3
## 4                                         11_NA_NA_11_4_6_1_1
## 5                                            11_2_1_1_1_1_1_1
## 6                                            11_9_1_3_4_4_2_4
##   Acceptor_HoStockplatesAcc Donor_HoStockplatesDon AcceptorMM Midparent
## 1                      11_1                   26_1         11        26
## 2                      11_3                   20_2         11        20
## 3                      11_1                   23_1         11        23
## 4                  11_11_X3               11_11_X3         11        11
## 5                      11_1                    2_1         11         2
## 6                      11_1                    9_1         11         9
##   AccDonCov HetDonorbyHom HetAccbyHom Mito Acceptor15 DonorhomGR AcchomGR
## 1        26            26          11    5         11   1.930952 1.942217
## 2        20            20          11    3         11   1.654298 1.942217
## 3        23            23          11    5         11         NA 1.942217
## 4        11            11          11    5         11   1.942217 1.942217
## 5         2             2          11    5         11   1.326866 1.942217
## 6         9             9          11    5         11   1.137679 1.942217
##   midhompar midhomparcent   logGRcent midparentheterosis    hetvigor
## 1  1.936585    0.28910352  0.12868091        -0.01366915 -0.01366915
## 2  1.798258    0.15077637  0.16427157         0.16024867  0.16024867
## 3        NA            NA  0.26470569                 NA          NA
## 4  1.942217    0.29473623  0.14798276         0.00000000  0.00000000
## 5  1.634542   -0.01293924 -0.02907527         0.13061743  0.13061743
## 6  1.539948   -0.10753281  0.09285899         0.34714527  0.34714527
##   besthompar besthomparcent strain18       GR
## 1   1.942217     0.07045624        1 6.840874
## 2   1.942217     0.07045624        1 7.088730
## 3         NA             NA        3 7.837660
## 4   1.942217     0.07045624        1 6.974198
## 5   1.942217     0.07045624        1 5.842503
## 6   1.942217     0.07045624        1 6.600158
rang <- range(dataGR$GR)


brks <- seq(0, 10, by = 0.5)

par(mar=c(5, 5, 2, 1), mfrow=c(1, 2), xpd=TRUE)

histFull <- hist(dataGR$GR[dataGR$Type=="Heterokaryon"], breaks = brks, plot = FALSE)
histFullSG <- hist(dataGR$GR[dataGR$Type=="Heterokaryon"&dataGR$DonorSG==1], breaks = brks, plot = FALSE)
histFullSG$counts <- histFullSG$counts/sum(histFull$counts)
histFull$counts <- histFull$counts/sum(histFull$counts)


plot(histFull, col = colpal[1], xlab = "Mycelium growth rate (mm/day)", ylab = "Frequency distribution", axes = TRUE, main = "", border = NA, freq=TRUE, xlim=c(0, 10), ylim=c(0, 0.35), las=1)

histAns <- hist(dataGR$GR[dataGR$Type=="Homokaryon"], breaks = brks, plot = FALSE)
histAns$counts <- histAns$counts/sum(histAns$counts)
lines(histAns, col=colpal[2], border=bordercol)
lines(histFull, col = NA, border = "white")

lines(histFullSG, col = NA, border = colpal[3])

legend(-0.1, 0.35, c("homokaryons (n=16)", "all heterokaryons (n=225)", "senescent heterokaryons (n=56)"), fill=c(colpal[2:1], NA), border=c("white","white",colpal[3]), bty="n", cex=0.75, x.intersp=0.5)

mtext("A", side=3, at=-2, line=0, cex=1.5)
mtext("B", side=3, at=14.25, line=0, cex=1.5)

## Graph for WWL

rang <- range(dataWL$weightloss)

brks <- seq(-0.1, 0.45, by = 0.025)

histFull <- hist(dataWL$weightloss[dataWL$Type=="Heterokaryon"], breaks = brks, plot = FALSE)

histFullSG <- hist(dataWL$weightloss[dataWL$Type=="Heterokaryon"&dataWL$DonorSG==1], breaks = brks, plot = FALSE)
histFullSG$counts <- histFullSG$counts/sum(histFull$counts)

histFull$counts <- histFull$counts/sum(histFull$counts)


plot(histFull, col = colpal[1], xlab = "Wood weight loss (mg)", ylab = NA, axes = TRUE, main = "", border = NA, freq=TRUE, xlim=c(-0.1, 0.5), ylim=c(0, 0.35), las=1)

histAns <- hist(dataWL$weightloss[dataGR$Type=="Homokaryon"], breaks = brks, plot = FALSE)
histAns$counts <- histAns$counts/sum(histAns$counts)
lines(histAns, col=colpal[2], border=bordercol)
lines(histFull, col = NA, border = "white")
lines(histFullSG, col = NA, border = colpal[3])

legend(-0.1, 0.35, c("homokaryons (n=16)", "all heterokaryons (n=198)", "senescent heterokaryons (n=52)"),
       fill=c(colpal[2:1], NA), border=c("white", "white", colpal[3]), bty="n", cex=0.75, x.intersp=0.5)



dev.off()
## quartz_off_screen 
##                 2

3 Figure 4: MGR csnucl and csmit

pathtofigures <- "."
dataGR2 <- read.table(file=paste(pathtofigures, "AveragelogGRperstrain241het16hom20181128.csv", sep="/"), header=TRUE, sep=",")
head(dataGR2)
##   Acceptor Donor geno_DonorSG    logGR logintGR         unit    intGR
## 1       11    26      11_26_0 1.922916 2.802864 11_26_X1_2_2 17.91667
## 2       11    20      11_20_0 1.958506 2.839034 11_20_X6_1_3 16.83333
## 3       11    23      11_23_1 2.058940 3.065760 11_23_X1_2_3 21.83333
## 4       11    11         11_0 1.942217 2.761546    11_X6_1_1 12.75000
## 5       11     2       11_2_0 1.765159 2.663283  11_2_X1_1_1 11.66667
## 6       11     9       11_9_0 1.887094 2.740700  11_9_X4_2_4 11.83333
##   slopeGR     ID DonorSG AcceptorName DonorName      AcceptorPop
## 1    6.25 Het178       0         FSE7    Fas161 Helsinki_Finland
## 2    7.00 Het132       0         FSE7     87075 Helsinki_Finland
## 3    7.50 Het155       1         FSE7     91132 Helsinki_Finland
## 4    6.25  Hom11       0         FSE7      FSE7 Helsinki_Finland
## 5    6.00   Het9       0         FSE7     87179 Helsinki_Finland
## 6    5.50  Het54       0         FSE7     95191 Helsinki_Finland
##               DonorPop  geno geneticdistance Acceptormito
## 1       Munich_Germany 11_26       0.3902914            5
## 2        Vicenza_Italy 11_20       0.4085754            3
## 3      Saarema_Estonia 11_23       0.3996568            5
## 4     Helsinki_Finland    11       0.0000000            5
## 5          Oslo_Norway  11_2       0.3914800            5
## 6 Yekaterinburg_Russia  11_9       0.4146880            5
##   Geographicdistance assay plate rep HoStockplatesAcc HoStockplatesDon
## 1               1589     1     2   2                1                1
## 2               1823     6     1   3                3                2
## 3                292     1     2   3                1                1
## 4                  0     6     1   1            11_X3            11_X3
## 5                812     1     1   1                1                1
## 6               2078     4     2   4                1                1
##   HetSynthesis HetStockplates HetPrecultures    Date         Type
## 1            1              1              1       4 Heterokaryon
## 2            2              4              6       9 Heterokaryon
## 3            1              1              1       4 Heterokaryon
## 4           NA             NA           11_4 Mar2016   Homokaryon
## 5            1              1              1       4 Heterokaryon
## 6            1              3              4       3 Heterokaryon
##   geographicdistancestd geneticdistancestd geneticdistancestdSq
## 1             0.2156009          0.2607463           0.06798862
## 2             0.4390378          0.4117039           0.16950014
## 3            -1.0228506          0.3380697           0.11429109
## 4            -1.3016693         -2.9616024           8.77108856
## 5            -0.5263242          0.2705593           0.07320231
## 6             0.6825268          0.4621707           0.21360178
##   geneticdistancestdCub geneticdistancegrp geneticdistancefac
## 1            0.01772778               0.39               0.39
## 2            0.06978387               0.40               0.40
## 3            0.03863835               0.39               0.39
## 4          -25.97647662               0.00               0.00
## 5            0.01980556               0.39               0.39
## 6            0.09872049               0.41               0.41
##   geno_synthesis geno_synthesis_HetStockplates
## 1        11_26_1                     11_26_1_1
## 2        11_20_2                     11_20_2_4
## 3        11_23_1                     11_23_1_1
## 4          11_NA                      11_NA_NA
## 5         11_2_1                      11_2_1_1
## 6         11_9_1                      11_9_1_3
##   geno_synthesis_HetStockplates_HetPreculture
## 1                                 11_26_1_1_1
## 2                                 11_20_2_4_6
## 3                                 11_23_1_1_1
## 4                               11_NA_NA_11_4
## 5                                  11_2_1_1_1
## 6                                  11_9_1_3_4
##   geno_synthesis_HetStockplates_HetPreculture_assay
## 1                                     11_26_1_1_1_1
## 2                                     11_20_2_4_6_6
## 3                                     11_23_1_1_1_1
## 4                                   11_NA_NA_11_4_6
## 5                                      11_2_1_1_1_1
## 6                                      11_9_1_3_4_4
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate
## 1                                         11_26_1_1_1_1_2
## 2                                         11_20_2_4_6_6_1
## 3                                         11_23_1_1_1_1_2
## 4                                       11_NA_NA_11_4_6_1
## 5                                          11_2_1_1_1_1_1
## 6                                          11_9_1_3_4_4_2
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate_rep
## 1                                           11_26_1_1_1_1_2_2
## 2                                           11_20_2_4_6_6_1_3
## 3                                           11_23_1_1_1_1_2_3
## 4                                         11_NA_NA_11_4_6_1_1
## 5                                            11_2_1_1_1_1_1_1
## 6                                            11_9_1_3_4_4_2_4
##   Acceptor_HoStockplatesAcc Donor_HoStockplatesDon AcceptorMM Midparent
## 1                      11_1                   26_1         11        26
## 2                      11_3                   20_2         11        20
## 3                      11_1                   23_1         11        23
## 4                  11_11_X3               11_11_X3         11        11
## 5                      11_1                    2_1         11         2
## 6                      11_1                    9_1         11         9
##   AccDonCov HetDonorbyHom HetAccbyHom Mito Acceptor15 DonorhomGR AcchomGR
## 1        26            26          11    5         11   1.930952 1.942217
## 2        20            20          11    3         11   1.654298 1.942217
## 3        23            23          11    5         11         NA 1.942217
## 4        11            11          11    5         11   1.942217 1.942217
## 5         2             2          11    5         11   1.326866 1.942217
## 6         9             9          11    5         11   1.137679 1.942217
##   midhompar midhomparcent   logGRcent midparentheterosis    hetvigor
## 1  1.936585    0.28910352  0.12868091        -0.01366915 -0.01366915
## 2  1.798258    0.15077637  0.16427157         0.16024867  0.16024867
## 3        NA            NA  0.26470569                 NA          NA
## 4  1.942217    0.29473623  0.14798276         0.00000000  0.00000000
## 5  1.634542   -0.01293924 -0.02907527         0.13061743  0.13061743
## 6  1.539948   -0.10753281  0.09285899         0.34714527  0.34714527
##   besthompar besthomparcent strain18
## 1   1.942217     0.07045624        1
## 2   1.942217     0.07045624        1
## 3         NA             NA        3
## 4   1.942217     0.07045624        1
## 5   1.942217     0.07045624        1
## 6   1.942217     0.07045624        1
## For MGR
## Heterokaryon with synthesised with the same homokaryon (once as a slow grower, once as a normal grower)
SG0_1 <- levels(dataGR2$genoHeterokaryon)[table(dataGR2$genoHeterokaryon)>1]

## Get rid of the replicate where the donor homokaryon is senescent
dataGR2 <- dataGR2[!dataGR2$geno_DonorSG%in%paste0(SG0_1, "_1"),]
length(dataGR2$logGR[dataGR2$Type=="Heterokaryon"])
## [1] 230
length(dataGR2$logGR[dataGR2$Type=="Heterokaryon"&dataGR2$DonorSG==0])
## [1] 169
length(dataGR2$logGR[dataGR2$Type=="Heterokaryon"&dataGR2$DonorSG==1])
## [1] 61
tapply(dataGR2$ID, dataGR2$Type, length)
## Heterokaryon   Homokaryon 
##          230           16
dataGR2$logGRcentered <- NA
dataGR2$DonorhomlogGRcentered <- NA
dataGR2$AcchomGRlogGRcentered <- NA
dataGR2$logGRcentered[dataGR2$Type=="Heterokaryon"] <- dataGR2$logGR[dataGR2$Type=="Heterokaryon"] -mean(dataGR2$logGR[dataGR2$Type=="Heterokaryon"])
dataGR2$DonorhomlogGRcentered[dataGR2$Type=="Heterokaryon"] <- log(dataGR2$DonorhomGR[dataGR2$Type=="Heterokaryon"]) - mean(log(dataGR2$DonorhomGR[dataGR2$Type=="Heterokaryon"]), na.rm=TRUE)
dataGR2$AcchomlogGRcentered[dataGR2$Type=="Heterokaryon"] <- log(dataGR2$AcchomGR[dataGR2$Type=="Heterokaryon"]) - mean(log(dataGR2$AcchomGR[dataGR2$Type=="Heterokaryon"]), na.rm=TRUE)

## Sample size for figure
sum(!is.na(dataGR2$logGRcentered[dataGR2$Type=="Heterokaryon"])&!is.na(dataGR2$AcchomlogGRcentered[dataGR2$Type=="Heterokaryon"]))
## [1] 229
sum(!is.na(dataGR2$logGRcentered[dataGR2$Type=="Heterokaryon"])&!is.na(dataGR2$DonorhomlogGRcentered[dataGR2$Type=="Heterokaryon"]))
## [1] 176
color <- rgb(red = 1, green = 1, blue = 1, alpha = 255 * 0.25, maxColorValue = 255)
pdf(file=paste(pathtofigures, "Figure4.pdf", sep="/"), height=6, width=10)
## Effect of midparent
#rang <- range(c(dataGR2$logGRcentered[dataGR2$Type=="Heterokaryon"], dataGR2$DonorhomlogGRcentered[dataGR2$Type=="Heterokaryon"], dataGR2$AcchomGRlogGRcentered[dataGR2$Type=="Heterokaryon"]), na.rm=TRUE)
rang <- c(-1, 0.5)
cexlab <- 1.5
par(mar=c(6.1, 6.1, 4.1, 2.1), mfrow=c(1, 2), xpd=FALSE)
plot(dataGR2$logGRcentered[dataGR2$Type=="Heterokaryon"] ~ dataGR2$DonorhomlogGRcentered[dataGR2$Type=="Heterokaryon"], las=1, pch=16, axes=FALSE, xlim=rang, ylim=rang, xlab=NA, ylab=NA, col=color)
axis(1, at=seq(-1, 0.5, by=0.5))
axis(2, at=seq(-1, 0.5, by=0.5), las=1)
mtext("log(donor homokaryon MGR)", side = 1, line=3, cex=cexlab)
mtext("log(heterokaryon MGR)", side = 2, line=4, cex=cexlab)
abline(a=0, b=0.1693730, lty=1, lwd=2)
abline(a=0, b=0.06291601, lty=2, lwd=2)
abline(a=0, b=0.3310000, lty=2, lwd=2)

#legend(-1, 1, legend=c("Non slow grower donor parent", "Slow grower donor parent"), pch=16, col=1:2, bty="n")

mtext("A", side=3, line = 1, at=-1.2, cex=1.5)

## Effect of acceptor homokaryon parent
par(mar=c(6.1, 3.1, 4.1, 3.1))
plot(dataGR2$logGRcentered[dataGR2$Type=="Heterokaryon"] ~ dataGR2$AcchomlogGRcentered[dataGR2$Type=="Heterokaryon"], las=1, pch=16, axes=FALSE, xlim=rang, ylim=rang, xlab=NA, ylab=NA, col=color)
axis(1, at=seq(-1, 0.5, by=0.5))
axis(2, at=seq(-1, 0.5, by=0.5), las=1)
mtext("log(acceptor homokaryon MGR)", side = 1, line=3, cex=cexlab)

abline(a=0, b=0.1693730, lty=1, lwd=2)
abline(a=0, b=0.06291601, lty=2, lwd=2)
abline(a=0, b=0.3310000, lty=2, lwd=2)
mtext("B", side=3, line = 1, at=-1.2, cex=1.5)

#legend(-1, 1, legend=c("Non slow grower donor parent", "Slow grower donor parent"), pch=16, col=1:2, bty="n")



dev.off()
## quartz_off_screen 
##                 2

4 Figure S9: WWL csnucl and csmit

pathtofigures <- "."
dataWL2 <- read.table(file=paste(pathtofigures, "AveragelogWLperstrain198het16hom20180717.csv", sep="/"), header=TRUE, sep=";")

head(dataWL2)
##   Acceptor Donor geno_DonorSG logweightloss     ID DonorSG AcceptorName
## 1       11     7       11_7_1     0.1750899  Het46       1         FSE7
## 2       11    30      11_30_0     0.2043858 Het205       0         FSE7
## 3       11     9       11_9_0     0.2307522  Het54       0         FSE7
## 4       11    32      11_32_0     0.2866868 Het234       0         FSE7
## 5       11    11         11_0     0.1324016  Hom11       0         FSE7
## 6       11    25      11_25_1     0.1792176 Het172       1         FSE7
##   DonorName      AcceptorPop             DonorPop  geno geneticdistance
## 1     95156 Helsinki_Finland Yekaterinburg_Russia  11_7       0.3761182
## 2      HR32 Helsinki_Finland     Smolyan_Bulgaria 11_30       0.4094155
## 3     95191 Helsinki_Finland Yekaterinburg_Russia  11_9       0.4146880
## 4     Sa948 Helsinki_Finland        Sätuna_Sweden 11_32       0.3880394
## 5      FSE7 Helsinki_Finland     Helsinki_Finland    11       0.0000000
## 6     93134 Helsinki_Finland      Aalborg_Denmark 11_25       0.4086827
##   Acceptormito geographicdistance initweight weightloss plate_rep_time
## 1            5               2078     1.1409     0.2369         X2_2_i
## 2            5               1858     1.0707     0.3283         X3_2_i
## 3            5               2078     1.1425     0.2520         X1_1_i
## 4            5                778     1.1308     0.3086         X2_2_i
## 5            5                  0     0.8004     0.1398         X3_2_i
## 6            5                934     1.2094     0.2908         X1_1_i
##   plate rep         Type  ID_plate geographicdistancestd
## 1    X2   2 Heterokaryon  Het46_X2             0.6313005
## 2    X3   2 Heterokaryon Het205_X3             0.4212340
## 3    X1   1 Heterokaryon  Het54_X1             0.6313005
## 4    X2   2 Heterokaryon Het234_X2            -0.6100014
## 5    X3   2   Homokaryon  Hom11_X3            -1.3528728
## 6    X1   1 Heterokaryon Het172_X1            -0.4610452
##   geneticdistancestd geneticdistancestdSq geneticdistancefac initweightstd
## 1         0.06125775          0.003752512               0.37     0.7106281
## 2         0.37385710          0.139769132               0.40     0.1910697
## 3         0.42335619          0.179230466               0.41     0.7224698
## 4         0.17317604          0.029989939               0.38     0.6358768
## 5        -3.46978937         12.039438250               0.00    -1.8094522
## 6         0.36697757          0.134672534               0.40     1.2176046
##   initweightstdSq AcceptorMM Midparent Mito AccDonCov HetDonorbyHom
## 1      0.50499224         11         7    5         7             7
## 2      0.03650762         11        30    5        30            30
## 3      0.52196268         11         9    5         9             9
## 4      0.40433928         11        32    5        32            32
## 5      3.27411733         11        11    5        11            11
## 6      1.48256088         11        25    5        25            25
##   HetAccbyHom DonorhomWL  AcchomWL midhompar midhomparcent
## 1          11         NA 0.1324016        NA            NA
## 2          11 0.07476087 0.1324016 0.1035812   -0.06348117
## 3          11 0.13500723 0.1324016 0.1337044   -0.03335799
## 4          11 0.23740947 0.1324016 0.1849055    0.01784313
## 5          11 0.13240160 0.1324016 0.1324016   -0.03466080
## 6          11         NA 0.1324016        NA            NA
##   midparentheterosis   hetvigor besthompar Acceptor15 DonorhomWL.1
## 1                 NA         NA         NA         11           NA
## 2         0.10080454 0.10080454  0.1324016         11   0.07476087
## 3         0.09704782 0.09704782  0.1350072         11   0.13500723
## 4         0.10178127 0.10178127  0.2374095         11   0.23740947
## 5         0.00000000 0.00000000  0.1324016         11   0.13240160
## 6                 NA         NA         NA         11           NA
##   AcchomWL.1    logWLcent besthomparcent strain18
## 1  0.1324016 -0.037622462             NA        3
## 2  0.1324016 -0.008326635    -0.08182514        1
## 3  0.1324016  0.018039832    -0.07921951        1
## 4  0.1324016  0.073974403     0.02318273        1
## 5  0.1324016 -0.080310802    -0.08182514        1
## 6  0.1324016 -0.033494787             NA        3
## For MGR
## Heterokaryon with synthesised with the same homokaryon (once as a slow grower, once as a normal grower)
SG0_1 <- levels(dataWL2$geno)[table(dataWL2$geno)>1]

## Get rid of the replicate where the donor homokaryon is senescent
dataWL2 <- dataWL2[!dataWL2$geno_DonorSG%in%paste0(SG0_1, "_1"),]
head(dataWL2)
##   Acceptor Donor geno_DonorSG logweightloss     ID DonorSG AcceptorName
## 1       11     7       11_7_1     0.1750899  Het46       1         FSE7
## 2       11    30      11_30_0     0.2043858 Het205       0         FSE7
## 3       11     9       11_9_0     0.2307522  Het54       0         FSE7
## 4       11    32      11_32_0     0.2866868 Het234       0         FSE7
## 5       11    11         11_0     0.1324016  Hom11       0         FSE7
## 6       11    25      11_25_1     0.1792176 Het172       1         FSE7
##   DonorName      AcceptorPop             DonorPop  geno geneticdistance
## 1     95156 Helsinki_Finland Yekaterinburg_Russia  11_7       0.3761182
## 2      HR32 Helsinki_Finland     Smolyan_Bulgaria 11_30       0.4094155
## 3     95191 Helsinki_Finland Yekaterinburg_Russia  11_9       0.4146880
## 4     Sa948 Helsinki_Finland        Sätuna_Sweden 11_32       0.3880394
## 5      FSE7 Helsinki_Finland     Helsinki_Finland    11       0.0000000
## 6     93134 Helsinki_Finland      Aalborg_Denmark 11_25       0.4086827
##   Acceptormito geographicdistance initweight weightloss plate_rep_time
## 1            5               2078     1.1409     0.2369         X2_2_i
## 2            5               1858     1.0707     0.3283         X3_2_i
## 3            5               2078     1.1425     0.2520         X1_1_i
## 4            5                778     1.1308     0.3086         X2_2_i
## 5            5                  0     0.8004     0.1398         X3_2_i
## 6            5                934     1.2094     0.2908         X1_1_i
##   plate rep         Type  ID_plate geographicdistancestd
## 1    X2   2 Heterokaryon  Het46_X2             0.6313005
## 2    X3   2 Heterokaryon Het205_X3             0.4212340
## 3    X1   1 Heterokaryon  Het54_X1             0.6313005
## 4    X2   2 Heterokaryon Het234_X2            -0.6100014
## 5    X3   2   Homokaryon  Hom11_X3            -1.3528728
## 6    X1   1 Heterokaryon Het172_X1            -0.4610452
##   geneticdistancestd geneticdistancestdSq geneticdistancefac initweightstd
## 1         0.06125775          0.003752512               0.37     0.7106281
## 2         0.37385710          0.139769132               0.40     0.1910697
## 3         0.42335619          0.179230466               0.41     0.7224698
## 4         0.17317604          0.029989939               0.38     0.6358768
## 5        -3.46978937         12.039438250               0.00    -1.8094522
## 6         0.36697757          0.134672534               0.40     1.2176046
##   initweightstdSq AcceptorMM Midparent Mito AccDonCov HetDonorbyHom
## 1      0.50499224         11         7    5         7             7
## 2      0.03650762         11        30    5        30            30
## 3      0.52196268         11         9    5         9             9
## 4      0.40433928         11        32    5        32            32
## 5      3.27411733         11        11    5        11            11
## 6      1.48256088         11        25    5        25            25
##   HetAccbyHom DonorhomWL  AcchomWL midhompar midhomparcent
## 1          11         NA 0.1324016        NA            NA
## 2          11 0.07476087 0.1324016 0.1035812   -0.06348117
## 3          11 0.13500723 0.1324016 0.1337044   -0.03335799
## 4          11 0.23740947 0.1324016 0.1849055    0.01784313
## 5          11 0.13240160 0.1324016 0.1324016   -0.03466080
## 6          11         NA 0.1324016        NA            NA
##   midparentheterosis   hetvigor besthompar Acceptor15 DonorhomWL.1
## 1                 NA         NA         NA         11           NA
## 2         0.10080454 0.10080454  0.1324016         11   0.07476087
## 3         0.09704782 0.09704782  0.1350072         11   0.13500723
## 4         0.10178127 0.10178127  0.2374095         11   0.23740947
## 5         0.00000000 0.00000000  0.1324016         11   0.13240160
## 6                 NA         NA         NA         11           NA
##   AcchomWL.1    logWLcent besthomparcent strain18
## 1  0.1324016 -0.037622462             NA        3
## 2  0.1324016 -0.008326635    -0.08182514        1
## 3  0.1324016  0.018039832    -0.07921951        1
## 4  0.1324016  0.073974403     0.02318273        1
## 5  0.1324016 -0.080310802    -0.08182514        1
## 6  0.1324016 -0.033494787             NA        3
length(dataWL2$logweightloss[dataWL2$Type=="Heterokaryon"])
## [1] 198
length(dataWL2$logweightloss[dataWL2$Type=="Heterokaryon"&dataWL2$DonorSG==0])
## [1] 146
length(dataWL2$logweightloss[dataWL2$Type=="Heterokaryon"&dataWL2$DonorSG==1])
## [1] 52
dataWL2$logGRcentered <- NA
dataWL2$DonorhomlogGRcentered <- NA
dataWL2$AcchomGRlogGRcentered <- NA

dataWL2$logweightlosscentered[dataWL2$Type=="Heterokaryon"] <- dataWL2$logweightloss[dataWL2$Type=="Heterokaryon"] -mean(dataWL2$logweightloss[dataWL2$Type=="Heterokaryon"])
dataWL2$DonorhomlogWLcentered[dataWL2$Type=="Heterokaryon"] <- log(dataWL2$DonorhomWL[dataWL2$Type=="Heterokaryon"]) - mean(log(dataWL2$DonorhomWL[dataWL2$Type=="Heterokaryon"]), na.rm=TRUE)
dataWL2$AcchomlogWLcentered[dataWL2$Type=="Heterokaryon"] <- log(dataWL2$AcchomWL[dataWL2$Type=="Heterokaryon"]) - mean(log(dataWL2$AcchomWL[dataWL2$Type=="Heterokaryon"]), na.rm=TRUE)

## Sample size for figure
sum(!is.na(dataWL2$logweightlosscentered[dataWL2$Type=="Heterokaryon"])&!is.na(dataWL2$AcchomlogWLcentered[dataWL2$Type=="Heterokaryon"]))
## [1] 197
sum(!is.na(dataWL2$logweightlosscentered[dataWL2$Type=="Heterokaryon"])&!is.na(dataWL2$DonorhomlogWLcentered[dataWL2$Type=="Heterokaryon"]))
## [1] 151
pdf(file=paste(pathtofigures, "FigureS9.pdf", sep="/"), height=6, width=10)
## Effect of midparent
#rang <- range(c(dataWL2$logweightlosscentered[dataWL2$Type=="Heterokaryon"], dataWL2$AcchomlogWLcentered[dataWL2$Type=="Heterokaryon"], dataWL2$DonorhomlogWLcentered[dataWL2$Type=="Heterokaryon"]), na.rm=TRUE)

rang <- c(-2, 1)
cexlab <- 1.5
par(mar=c(6.1, 6.1, 4.1, 2.1), mfrow=c(1, 2), xpd=FALSE)
plot(dataWL2$logweightlosscentered[dataWL2$Type=="Heterokaryon"] ~ dataWL2$DonorhomlogWLcentered[dataWL2$Type=="Heterokaryon"], las=1, pch=16, axes=FALSE, xlim=rang, ylim=c(-0.25, 0.25), xlab=NA, ylab=NA)
axis(1, at=seq(-2, 1, by=1))
axis(2, at=seq(-0.25, 0.25, by=0.125), las=1)
mtext("log(donor homokaryon WWL)", side = 1, line=3, cex=cexlab)
mtext("log(heterokaryon WWL)", side = 2, line=4, cex=cexlab)
abline(a=0, b=0, lty=1, lwd=2)

mtext("A", side=3, line = 1, at=-2.5, cex=1.5)

## Effect of acceptor homokaryon parent
par(mar=c(6.1, 3.1, 4.1, 3.1))
plot(dataWL2$logweightlosscentered[dataWL2$Type=="Heterokaryon"] ~ dataWL2$AcchomlogWLcentered[dataWL2$Type=="Heterokaryon"], las=1, pch=16, axes=FALSE, xlim=rang, ylim=c(-0.25, 0.25), xlab=NA, ylab=NA)
axis(1, at=seq(-2, 1, by=1))
axis(2, at=seq(-0.25, 0.25, by=0.125), las=1)
mtext("log(acceptor homokaryon WWL)", side = 1, line=3, cex=cexlab)

abline(a=0, b=0, lty=1, lwd=2)


mtext("B", side=3, line = 1, at=-2.5, cex=1.5)



dev.off()
## quartz_off_screen 
##                 2

5 Figure 5: MGR heterosis~Genetic distance

pathtofigures <- "./"
dataGR2 <- read.table(file=paste(pathtofigures, "AveragelogGRperstrain241het16hom20181128.csv", sep="/"), header=TRUE, sep=",")
head(dataGR2)
##   Acceptor Donor geno_DonorSG    logGR logintGR         unit    intGR
## 1       11    26      11_26_0 1.922916 2.802864 11_26_X1_2_2 17.91667
## 2       11    20      11_20_0 1.958506 2.839034 11_20_X6_1_3 16.83333
## 3       11    23      11_23_1 2.058940 3.065760 11_23_X1_2_3 21.83333
## 4       11    11         11_0 1.942217 2.761546    11_X6_1_1 12.75000
## 5       11     2       11_2_0 1.765159 2.663283  11_2_X1_1_1 11.66667
## 6       11     9       11_9_0 1.887094 2.740700  11_9_X4_2_4 11.83333
##   slopeGR     ID DonorSG AcceptorName DonorName      AcceptorPop
## 1    6.25 Het178       0         FSE7    Fas161 Helsinki_Finland
## 2    7.00 Het132       0         FSE7     87075 Helsinki_Finland
## 3    7.50 Het155       1         FSE7     91132 Helsinki_Finland
## 4    6.25  Hom11       0         FSE7      FSE7 Helsinki_Finland
## 5    6.00   Het9       0         FSE7     87179 Helsinki_Finland
## 6    5.50  Het54       0         FSE7     95191 Helsinki_Finland
##               DonorPop  geno geneticdistance Acceptormito
## 1       Munich_Germany 11_26       0.3902914            5
## 2        Vicenza_Italy 11_20       0.4085754            3
## 3      Saarema_Estonia 11_23       0.3996568            5
## 4     Helsinki_Finland    11       0.0000000            5
## 5          Oslo_Norway  11_2       0.3914800            5
## 6 Yekaterinburg_Russia  11_9       0.4146880            5
##   Geographicdistance assay plate rep HoStockplatesAcc HoStockplatesDon
## 1               1589     1     2   2                1                1
## 2               1823     6     1   3                3                2
## 3                292     1     2   3                1                1
## 4                  0     6     1   1            11_X3            11_X3
## 5                812     1     1   1                1                1
## 6               2078     4     2   4                1                1
##   HetSynthesis HetStockplates HetPrecultures    Date         Type
## 1            1              1              1       4 Heterokaryon
## 2            2              4              6       9 Heterokaryon
## 3            1              1              1       4 Heterokaryon
## 4           NA             NA           11_4 Mar2016   Homokaryon
## 5            1              1              1       4 Heterokaryon
## 6            1              3              4       3 Heterokaryon
##   geographicdistancestd geneticdistancestd geneticdistancestdSq
## 1             0.2156009          0.2607463           0.06798862
## 2             0.4390378          0.4117039           0.16950014
## 3            -1.0228506          0.3380697           0.11429109
## 4            -1.3016693         -2.9616024           8.77108856
## 5            -0.5263242          0.2705593           0.07320231
## 6             0.6825268          0.4621707           0.21360178
##   geneticdistancestdCub geneticdistancegrp geneticdistancefac
## 1            0.01772778               0.39               0.39
## 2            0.06978387               0.40               0.40
## 3            0.03863835               0.39               0.39
## 4          -25.97647662               0.00               0.00
## 5            0.01980556               0.39               0.39
## 6            0.09872049               0.41               0.41
##   geno_synthesis geno_synthesis_HetStockplates
## 1        11_26_1                     11_26_1_1
## 2        11_20_2                     11_20_2_4
## 3        11_23_1                     11_23_1_1
## 4          11_NA                      11_NA_NA
## 5         11_2_1                      11_2_1_1
## 6         11_9_1                      11_9_1_3
##   geno_synthesis_HetStockplates_HetPreculture
## 1                                 11_26_1_1_1
## 2                                 11_20_2_4_6
## 3                                 11_23_1_1_1
## 4                               11_NA_NA_11_4
## 5                                  11_2_1_1_1
## 6                                  11_9_1_3_4
##   geno_synthesis_HetStockplates_HetPreculture_assay
## 1                                     11_26_1_1_1_1
## 2                                     11_20_2_4_6_6
## 3                                     11_23_1_1_1_1
## 4                                   11_NA_NA_11_4_6
## 5                                      11_2_1_1_1_1
## 6                                      11_9_1_3_4_4
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate
## 1                                         11_26_1_1_1_1_2
## 2                                         11_20_2_4_6_6_1
## 3                                         11_23_1_1_1_1_2
## 4                                       11_NA_NA_11_4_6_1
## 5                                          11_2_1_1_1_1_1
## 6                                          11_9_1_3_4_4_2
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate_rep
## 1                                           11_26_1_1_1_1_2_2
## 2                                           11_20_2_4_6_6_1_3
## 3                                           11_23_1_1_1_1_2_3
## 4                                         11_NA_NA_11_4_6_1_1
## 5                                            11_2_1_1_1_1_1_1
## 6                                            11_9_1_3_4_4_2_4
##   Acceptor_HoStockplatesAcc Donor_HoStockplatesDon AcceptorMM Midparent
## 1                      11_1                   26_1         11        26
## 2                      11_3                   20_2         11        20
## 3                      11_1                   23_1         11        23
## 4                  11_11_X3               11_11_X3         11        11
## 5                      11_1                    2_1         11         2
## 6                      11_1                    9_1         11         9
##   AccDonCov HetDonorbyHom HetAccbyHom Mito Acceptor15 DonorhomGR AcchomGR
## 1        26            26          11    5         11   1.930952 1.942217
## 2        20            20          11    3         11   1.654298 1.942217
## 3        23            23          11    5         11         NA 1.942217
## 4        11            11          11    5         11   1.942217 1.942217
## 5         2             2          11    5         11   1.326866 1.942217
## 6         9             9          11    5         11   1.137679 1.942217
##   midhompar midhomparcent   logGRcent midparentheterosis    hetvigor
## 1  1.936585    0.28910352  0.12868091        -0.01366915 -0.01366915
## 2  1.798258    0.15077637  0.16427157         0.16024867  0.16024867
## 3        NA            NA  0.26470569                 NA          NA
## 4  1.942217    0.29473623  0.14798276         0.00000000  0.00000000
## 5  1.634542   -0.01293924 -0.02907527         0.13061743  0.13061743
## 6  1.539948   -0.10753281  0.09285899         0.34714527  0.34714527
##   besthompar besthomparcent strain18
## 1   1.942217     0.07045624        1
## 2   1.942217     0.07045624        1
## 3         NA             NA        3
## 4   1.942217     0.07045624        1
## 5   1.942217     0.07045624        1
## 6   1.942217     0.07045624        1
# Function to make color transparent
makeTransparent = function(color, alpha = 0.5) {
    if (alpha < 0 | alpha > 1) 
        stop("alpha must be between 0 and 1")
    newcol <- col2rgb(col = color, alpha = FALSE)
    return(rgb(red = newcol[1], green = newcol[2], blue = newcol[3], alpha = 255 * 
        alpha, maxColorValue = 255))
}
cbbPalette <- c("#000000", "#009E73", "#e79f00", "#9ad0f3", "#0072B2", "#D55E00", 
    "#CC79A7", "#F0E442")
cbbPalette[1] <- makeTransparent(cbbPalette[1], 0.2)

cbbPalette[2] <- makeTransparent(cbbPalette[2], 0.5)
cbbPalette[3] <- makeTransparent(cbbPalette[3], 0.5)

plot(1:8, 1:8, col=cbbPalette, pch=16)

plot(1:3, 1:3, pch=c(15, 16, 17))

## Color
#legcol <- cbbPalette[c(1, 1, 1)]
legcol <- cbbPalette[c(2, 1, 3)]
## GR
dataGR2$strain18col <- factor(dataGR2$strain18)
#levels(dataGR2$strain18col) <- cbbPalette[c(1, 1, 1)]
levels(dataGR2$strain18col) <- cbbPalette[c(2, 3, 1)]
dataGR2$strain18col <- as.character(dataGR2$strain18col)

## Symbol
symb <- c("16", "15", "17")
##GR
legsymb <- as.numeric(symb)[c(1,3,2)]
dataGR2$strain18pch <- factor(dataGR2$strain18)
levels(dataGR2$strain18pch) <- symb
dataGR2$strain18pch <- as.numeric(as.character(dataGR2$strain18pch))

## Size symbol
symbsize <- c(1.5, 1.5, 1)
cexsymb <- as.numeric(symbsize)[c(1, 3, 2)]
##GR
dataGR2$strain18pchsize <- factor(dataGR2$strain18)
levels(dataGR2$strain18pchsize) <- symbsize
dataGR2$strain18pchsize <- as.numeric(as.character(dataGR2$strain18pchsize))

  
jpeg(file=paste(pathtofigures, "Figure5.jpeg", sep="/"))

par(mar=c(6, 6, 3, 2), oma=c(1,1,2,0), mfcol=c(1, 1), xpd=FALSE)

#rang <- range(dataGR2$logGRcent)
rang <- c(-1, 1)
rangx <- c(0.3, 0.5)
cexlab <- 1.5
par(mar=c(5, 5, 2, 3), xpd=FALSE)
#par(oma=c(1, 2, 1, 1), xpd=FALSE)
plot(dataGR2$hetvigor[dataGR2$Type=="Heterokaryon"] ~ dataGR2$geneticdistance[dataGR2$Type=="Heterokaryon"], las=1, pch=dataGR2$strain18pch[dataGR2$Type=="Heterokaryon"], axes=FALSE, xlim=rangx, ylim=rang, xlab=NA, ylab=NA, col=dataGR2$strain18col[dataGR2$Type=="Heterokaryon"], cex=dataGR2$strain18pchsize[dataGR2$Type=="Heterokaryon"])
axis(1)
axis(2, at=c(-1, -0.5, 0, 0.5, 1), las=1)
mtext("Genetic distance between homokaryon parents", side = 1, line=3, cex=cexlab)
mtext("MGR heterokaryon vigor index", side = 2, line=3.5, cex=cexlab, at=0)
abline(h=mean(na.omit(dataGR2$hetvigor[dataGR2$Type=="Heterokaryon"])), lty=1)

par( xpd=TRUE)
legend(0.3, 1.25, c("Heterokaryons with non-senescent donor strain", "Heterokaryons with senescent donor strain", "Heterokaryons with strain 18 as a donor or acceptor"), col=legcol, pch=legsymb, bty="n", pt.cex=1.5)


dev.off()
## quartz_off_screen 
##                 2
length(na.omit(dataGR2$hetvigor[dataGR2$Type=="Heterokaryon"]))
## [1] 175

6 Figure S10: WWL heterosis~Genetic distance

pathtofigures <- "."
dataWL2 <- read.table(file=paste(pathtofigures, "AveragelogWLperstrain198het16hom20180717.csv", sep="/"), header=TRUE, sep=";")

## WWL
dataWL2$strain18col <- factor(dataWL2$strain18)
levels(dataWL2$strain18col) <- cbbPalette[c(2, 3, 1)]
dataWL2$strain18col <- as.character(dataWL2$strain18col)
##WWL
dataWL2$strain18pch <- factor(dataWL2$strain18)
levels(dataWL2$strain18pch) <- symb
dataWL2$strain18pch <- as.numeric(as.character(dataWL2$strain18pch))
##WWL
dataWL2$strain18pchsize <- factor(dataWL2$strain18)
levels(dataWL2$strain18pchsize) <- symbsize
dataWL2$strain18pchsize <- as.numeric(as.character(dataWL2$strain18pchsize))

#rang <- range(na.omit(dataWL2$hetvigor))
rang <- c(-0.25, 0.25)
rangx <- c(0.3, 0.5)
cexlab <- 1.5


jpeg(file=paste(pathtofigures, "FigureS10.jpeg", sep="/"))

par(mar=c(5.1, 6, 3, 5), oma=c(1,1,2,0), mfcol=c(1, 1), xpd=FALSE)

plot(dataWL2$hetvigor[dataWL2$Type=="Heterokaryon"] ~ dataWL2$geneticdistance[dataWL2$Type=="Heterokaryon"], las=1, pch=dataWL2$strain18pch[dataWL2$Type=="Heterokaryon"], axes=FALSE, xlim=rangx, ylim=rang, xlab=NA, ylab=NA, col=dataWL2$strain18col[dataWL2$Type=="Heterokaryon"], cex=dataWL2$strain18pchsize[dataWL2$Type=="Heterokaryon"])
axis(1)
axis(2, at=c(-0.25, 0, 0.25), las=1)
mtext("Genetic distance between homokaryon parents", side = 1, line=3.5, cex=cexlab, at=0.4)
mtext("WWL heterokaryon vigor index", side = 2, line=3.5, cex=cexlab, at=0)
abline(h=mean(na.omit(dataWL2$hetvigor[dataWL2$Type=="Heterokaryon"])), lty=1)

par( xpd=TRUE)
legend(0.3, 0.35, c("Heterokaryons with non-senescent donor strain", "Heterokaryons with senescent donor strain", "Heterokaryons with strain 18 as a donor or acceptor"), col=legcol, pch=legsymb, bty="n", pt.cex=1.5)

dev.off()
## quartz_off_screen 
##                 2
length(na.omit(dataWL2$hetvigor[dataWL2$Type=="Heterokaryon"]))
## [1] 151

7 FigS3 and S4: Genetic distance matrix

pathtogeneticdistfiles <- "../GeneticDistance/"
## Donor genetic distance
donnucldist <- read.table(paste(pathtogeneticdistfiles, "GeneticDistances_30_isolates.csv", sep="/"), header=T , sep=";")
## Change names
names(donnucldist) <- gsub("X", "", names(donnucldist))


#pdf("FigureS1.pdf")
#A.mark <-  donnuclsim
A.mark <- as.matrix(donnucldist)
neworder <- as.factor(c(25, 1, 2, 3, 4, 14, 34, 13, 15, 33, 18, 32, 31, 10, 11, 27, 5, 6, 7, 9, 21, 23, 22, 24, 26, 12, 35, 30, 19, 20))
A.mark <- A.mark[neworder, neworder]
rownames(A.mark) <- neworder
pimage(x=A.mark, order = NULL, axes="both", main = "", key = TRUE, key.lab="Genetic distance", xlab = "Homokaryon isolate identity", ylab = "Homokaryon isolate indentity")

#dev.copy(width = 750, height = 750, png,file=paste(getwd(),"DistanceMatrix.png",sep="/")); dev.off()
#dev.copy2pdf(width = 10, height = 10, file=paste(getwd(),"DistanceMatrix.pdf",sep="/")); dev.off()

A.mark.reorder <- seriate(A.mark)

#png(file="FigureS1 NuclearDistanceMatrix.png", width = 150, height = 150, res=300)
par(mar=c(3, 3, 2, 3))
pimage(A.mark, A.mark.reorder, prop = FALSE, axes="both", main = "Nuclear genetic distance matrix", key = TRUE, key.lab="Nuclear genetic distance", xlab = "Nuclear haplotype", ylab = "Nuclear haplotype")

wcorr <- 700
hcorr <- 500
dev.copy(width = wcorr, height = hcorr, png, file=paste(getwd(),"FigureS3.png",sep="/")); dev.off()
## quartz_off_screen 
##                 3
## quartz_off_screen 
##                 2
#dev.off()


## Mitochondrial distance matrix
accmitdist <- read.table(paste(pathtogeneticdistfiles, "AcceptorMitDist20170228.csv", sep="/") , header=T , sep=";")
## Change names
names(accmitdist) <- gsub("X", "", names(accmitdist))

hist(accmitdist[upper.tri(accmitdist)])

A.markmit <- as.matrix(accmitdist)
rownames(A.markmit) <- colnames(A.markmit)
pimage(x=A.markmit, order = NULL, axes="both", main = "", key = TRUE, key.lab="Genetic distance", xlab = "Mitochondrial haplotype", ylab = "Mitochondrial haplotype")

A.markmit.reorder <- seriate(A.markmit)

#png(file="FigureS2 MitochondrialDistanceMatrix.png", width = 150, height = 150, res=300)
par(mar=c(3, 3, 2, 3))
pimage(A.markmit, A.markmit.reorder, prop = FALSE, axes="both", main = "Mitochondiral genetic distance matrix", key = TRUE, key.lab="Mitochondiral genetic distance", xlab = "Mitochondrial haplotype", ylab = "Mitochondrial haplotype")

wcorr <- 700
hcorr <- 500
dev.copy(width = wcorr, height = hcorr, png,file=paste(getwd(),"FigureS4.png",sep="/")); dev.off()
## quartz_off_screen 
##                 3
## quartz_off_screen 
##                 2

8 FigS5: Correlation between nuclear and mitochondrial genetic distance

pathtogeneticdistfiles <- "../GeneticDistance/"
## Mitochondrial genetic distance
mitdist <- read.table(paste(pathtogeneticdistfiles, "MitGeneticDistance_30_isolates.csv", sep="/"), header=T , sep=";")
colnames(mitdist) <- gsub("X", "", colnames(mitdist))
colnames(mitdist)[ncol(mitdist)] <- "Sa1595(Ref)"
rownames(mitdist) <- colnames(mitdist)
## Nuclear genetic distance
nucldist <- read.table(paste(pathtogeneticdistfiles, "NuclGeneticDistance_30_isolates.csv", sep="/"), header=T , sep=";")
colnames(nucldist) <- gsub("X", "", colnames(nucldist))
colnames(nucldist)[colnames(nucldist)=="Sa1595.Ref."] <- "Sa1595(Ref)"
rownames(nucldist) <- colnames(nucldist)

data.frame(names(nucldist)[order(names(nucldist))], names(mitdist)[order(names(mitdist))])
##    names.nucldist..order.names.nucldist...
## 1                                    87074
## 2                                    87075
## 3                                    87124
## 4                                    87179
## 5                                    87183
## 6                                    87215
## 7                                    90137
## 8                                    90166
## 9                                    91132
## 10                                   93028
## 11                                   93134
## 12                                   95123
## 13                                   95126
## 14                                   95156
## 15                                   95191
## 16                                  Br2444
## 17                                  Br5182
## 18                                  Fas161
## 19                                    FSE3
## 20                                    FSE7
## 21                                    HR32
## 22                                    OH22
## 23                                   OH235
## 24                                   Rb313
## 25                                   RB482
## 26                                   RB489
## 27                                   RB896
## 28                                  RB9411
## 29                             Sa1595(Ref)
## 30                                   Sa948
##    names.mitdist..order.names.mitdist...
## 1                                  87074
## 2                                  87075
## 3                                  87124
## 4                                  87179
## 5                                  87183
## 6                                  87215
## 7                                  90137
## 8                                  90166
## 9                                  91132
## 10                                 93028
## 11                                 93134
## 12                                 95123
## 13                                 95126
## 14                                 95156
## 15                                 95191
## 16                                Br2444
## 17                                Br5182
## 18                                Fas161
## 19                                  FSE3
## 20                                  FSE7
## 21                                  HR32
## 22                                  OH22
## 23                                 OH235
## 24                                 Rb313
## 25                                 RB482
## 26                                 RB489
## 27                                 RB896
## 28                                RB9411
## 29                           Sa1595(Ref)
## 30                                 Sa948
## Sort matrices
nucldist <- nucldist[, order(colnames(nucldist))]
nucldist <- nucldist[order(rownames(nucldist)), ]

mitdist <- mitdist[, order(colnames(mitdist))]
mitdist <- mitdist[order(rownames(mitdist)), ]

### Correlation for homokaryons
##################

homnucldist <- as.matrix(nucldist[colnames(nucldist)%in%dataGR$AcceptorName[dataGR$Type=="Homokaryon"], colnames(nucldist)%in%dataGR$AcceptorName[dataGR$Type=="Homokaryon"]])
homnucldist <- as.vector(homnucldist[upper.tri(homnucldist)])

hommitdist <- as.matrix(mitdist[colnames(mitdist)%in%dataGR$AcceptorName[dataGR$Type=="Homokaryon"], colnames(mitdist)%in%dataGR$AcceptorName[dataGR$Type=="Homokaryon"]])
hommitdist <- as.vector(hommitdist[upper.tri(hommitdist)])

library(ade4)

set.seed(123)
r1 <- mantel.rtest(as.dist(nucldist[colnames(nucldist)%in%dataGR$AcceptorName[dataGR$Type=="Homokaryon"], colnames(nucldist)%in%dataGR$AcceptorName[dataGR$Type=="Homokaryon"]]), as.dist(mitdist[colnames(mitdist)%in%dataGR$AcceptorName[dataGR$Type=="Homokaryon"], colnames(mitdist)%in%dataGR$AcceptorName[dataGR$Type=="Homokaryon"]]), nrep=100)
## Warning in is.euclid(m2): Zero distance(s)
r1
## Monte-Carlo test
## Call: mantelnoneuclid(m1 = m1, m2 = m2, nrepet = nrepet)
## 
## Observation: 0.4332972 
## 
## Based on 100 replicates
## Simulated p-value: 0.00990099 
## Alternative hypothesis: greater 
## 
##      Std.Obs  Expectation     Variance 
##  3.926326825 -0.005720802  0.012502354
jpeg(file="FigureS5.jpeg")
## Correlation between nuclear and mitochodnrial genetic distance
par(mfrow=c(1,1))
plot(homnucldist, hommitdist, col=rgb(red=0.5, green=0.5, blue=0.5, alpha=0.5), pch=16, las=1, bty="n", xlab="Nuclear genetic distance", ylab="Mitochondrial genetic distance", xlim=c(0.15, 0.50))
mtext(side=3, paste0("R=", round(r1$obs, 2)), at=0.2, line=-1)
mtext(side=3, paste0("P=", round(r1$pvalue, 2)), at=0.2, line=-2, font=3)
dev.off()
## quartz_off_screen 
##                 2
## Melt mitochondiral distance
mitdistframe <- melt(as.matrix(mitdist))
colnames(mitdistframe) <- c("AcceptorName", "DonorName", "mitdist")
mitdistframe$AccDon <- paste(mitdistframe$AcceptorName, mitdistframe$DonorName, sep="_")

## Melt nuclear distance
nucldistframe <- melt(as.matrix(nucldist))
colnames(nucldistframe) <- c("AcceptorName", "DonorName", "nucldist")
nucldistframe$AccDon <- paste(nucldistframe$AcceptorName, nucldistframe$DonorName, sep="_")

dataGR$AccDon <- paste(dataGR$AcceptorName, dataGR$DonorName, sep="_")
dataWL$AccDon <- paste(dataWL$AcceptorName, dataWL$DonorName, sep="_")

dataGR2 <- merge(x=dataGR, y=mitdistframe[, 3:4], by="AccDon")
dataGR2 <- merge(x=dataGR2, y=nucldistframe[, 3:4], by="AccDon")

dataWL2 <- merge(x=dataWL, y=mitdistframe[, 3:4], by="AccDon")
dataWL2 <- merge(x=dataWL2, y=nucldistframe[, 3:4], by="AccDon")

head(dataWL2)
##        AccDon Acceptor Donor geno_DonorSG logweightloss     ID DonorSG
## 1 87074_87074       19    19         19_0     0.2647728  Hom19       0
## 2 87074_87075       19    20      19_20_0     0.1766203 Het135       0
## 3 87074_87124       19     1       19_1_1     0.2268697   Het2       1
## 4 87074_87179       19     2       19_2_0     0.2094721  Het11       0
## 5 87074_93028       19    24      19_24_0     0.1885601 Het163       0
## 6 87074_95123       19     5       19_5_0     0.2525622  Het35       0
##   AcceptorName DonorName   AcceptorPop             DonorPop  geno
## 1        87074     87074 Vicenza_Italy        Vicenza_Italy    19
## 2        87074     87075 Vicenza_Italy        Vicenza_Italy 19_20
## 3        87074     87124 Vicenza_Italy          Oslo_Norway  19_1
## 4        87074     87179 Vicenza_Italy          Oslo_Norway  19_2
## 5        87074     93028 Vicenza_Italy     Happerg_ Germany 19_24
## 6        87074     95123 Vicenza_Italy Yekaterinburg_Russia  19_5
##   geneticdistance Acceptormito geographicdistance initweight weightloss
## 1       0.0000000            1                  0     1.2067  0.3031349
## 2       0.3579682            3                 10     0.7174  0.1931780
## 3       0.4082805            1               1559     1.0389  0.2546663
## 4       0.3742951            1               1559     1.0101  0.2330270
## 5       0.3724721            1                237     1.1249  0.2075097
## 6       0.3919447            1               3525     1.1744  0.2873195
##   plate_rep_time plate rep         Type  ID_plate geographicdistancestd
## 1         X3_1_i    X3   1   Homokaryon  Hom19_X3            -1.3528728
## 2         X3_2_i    X3   2 Heterokaryon Het135_X3            -1.3433244
## 3         X3_1_i    X3   1 Heterokaryon   Het2_X3             0.1357346
## 4         X3_2_i    X3   2 Heterokaryon  Het11_X3             0.1357346
## 5         X3_2_i    X3   2 Heterokaryon Het163_X3            -1.1265740
## 6         X3_2_i    X3   2 Heterokaryon  Het35_X3             2.0129649
##   geneticdistancestd geneticdistancestdSq geneticdistancefac initweightstd
## 1        -3.46978937         12.039438250               0.00    1.19762155
## 2        -0.10913658          0.011910794               0.35   -2.42374491
## 3         0.36320221          0.131915847               0.40   -0.04428585
## 4         0.04414281          0.001948588               0.37   -0.25743802
## 5         0.02702787          0.000730506               0.37    0.59221019
## 6         0.20983892          0.044032373               0.39    0.95856548
##   initweightstdSq AcceptorMM Midparent Mito AccDonCov HetDonorbyHom
## 1     1.434297375         19        19    1        19            19
## 2     5.874539412         19        20    3        20            20
## 3     0.001961237         19         1    1         1             1
## 4     0.066274334         19         2    1         2             2
## 5     0.350712912         19        24    1        24            24
## 6     0.918847771         19         5    1         5             5
##   HetAccbyHom DonorhomWL  AcchomWL midhompar midhomparcent
## 1          19  0.2647728 0.2647728 0.2647728    0.09771038
## 2          19  0.2422296 0.2647728 0.2535012    0.08643878
## 3          19         NA 0.2647728        NA            NA
## 4          19  0.1011814 0.2647728 0.1829771    0.01591468
## 5          19  0.2106861 0.2647728 0.2377295    0.07066704
## 6          19  0.2614209 0.2647728 0.2630969    0.09603444
##   midparentheterosis    hetvigor besthompar Acceptor15 DonorhomWL.1
## 1         0.00000000  0.00000000  0.2647728         19    0.2647728
## 2        -0.07688086 -0.07688086  0.2647728         19    0.2422296
## 3                 NA          NA         NA         19           NA
## 4         0.02649505  0.02649505  0.2647728         19    0.1011814
## 5        -0.04916932 -0.04916932  0.2647728         19    0.2106861
## 6        -0.01053470 -0.01053470  0.2647728         19    0.2614209
##   AcchomWL.1    logWLcent besthomparcent strain18   mitdist  nucldist
## 1  0.2647728  0.052060386     0.05054605        1 0.0000000 0.0000000
## 2  0.2647728 -0.036092074     0.05054605        1 0.0000000 0.3579682
## 3  0.2647728  0.014157267             NA        3 0.2275862 0.4082805
## 4  0.2647728 -0.003240268     0.05054605        1 0.1931034 0.3742951
## 5  0.2647728 -0.024152278     0.05054605        1 0.0000000 0.3724721
## 6  0.2647728  0.039849749     0.05054605        1 0.2620690 0.3919447
head(dataGR2)
##        AccDon Acceptor Donor geno_DonorSG     logGR logintGR         unit
## 1 87074_87074       19    19         19_0 1.6269875 2.719588    19_X1_2_1
## 2 87074_87075       19    20      19_20_1 0.7751937 1.781454 19_20_X1_3_3
## 3 87074_87075       19    20      19_20_0 1.9259957 2.803219 19_20_X4_2_1
## 4 87074_87124       19     1       19_1_1 0.9938704 2.017857  19_1_X1_2_1
## 5 87074_87179       19     2       19_2_0 1.7479567 2.564858  19_2_X1_2_3
## 6 87074_93028       19    24      19_24_0 1.8169945 2.473449 19_24_X3_3_2
##       intGR slopeGR     ID DonorSG AcceptorName DonorName   AcceptorPop
## 1 15.000000    5.00  Hom19       0        87074     87074 Vicenza_Italy
## 2  6.000000    2.50 Het134       1        87074     87075 Vicenza_Italy
## 3 17.083333    6.75 Het135       0        87074     87075 Vicenza_Italy
## 4  6.416667    2.75   Het2       1        87074     87124 Vicenza_Italy
## 5 10.333333    6.00  Het11       0        87074     87179 Vicenza_Italy
## 6 11.333333    6.50 Het163       0        87074     93028 Vicenza_Italy
##           DonorPop  geno geneticdistance Acceptormito Geographicdistance
## 1    Vicenza_Italy    19       0.0000000            1                  0
## 2    Vicenza_Italy 19_20       0.3579682            1                 10
## 3    Vicenza_Italy 19_20       0.3579682            3                 10
## 4      Oslo_Norway  19_1       0.4082805            1               1559
## 5      Oslo_Norway  19_2       0.3742951            1               1559
## 6 Happerg_ Germany 19_24       0.3724721            1                237
##   assay plate rep HoStockplatesAcc HoStockplatesDon HetSynthesis
## 1     1     2   1            19_X1            19_X1           NA
## 2     1     3   3                1                1            1
## 3     4     2   1                2                2            2
## 4     1     2   1                1                1            1
## 5     1     2   3                1                1            1
## 6     3     3   2                2                2            2
##   HetStockplates HetPrecultures     Date         Type
## 1             NA           19_1 June2015   Homokaryon
## 2              1              1        4 Heterokaryon
## 3              4              4        3 Heterokaryon
## 4              1              1        4 Heterokaryon
## 5              1              1        4 Heterokaryon
## 6              2              3        5 Heterokaryon
##   geographicdistancestd geneticdistancestd geneticdistancestdSq
## 1            -1.3016693       -2.961602364         8.771089e+00
## 2            -1.2921207       -0.006122689         3.748732e-05
## 3            -1.2921207       -0.006122689         3.748732e-05
## 4             0.1869552        0.409269142         1.675012e-01
## 5             0.1869552        0.128676756         1.655771e-02
## 6            -1.0753678        0.113625258         1.291070e-02
##   geneticdistancestdCub geneticdistancegrp geneticdistancefac
## 1         -2.597648e+01               0.00               0.00
## 2         -2.295232e-07               0.35               0.35
## 3         -2.295232e-07               0.35               0.35
## 4          6.855309e-02               0.40               0.40
## 5          2.130592e-03               0.37               0.37
## 6          1.466982e-03               0.37               0.37
##   geno_synthesis geno_synthesis_HetStockplates
## 1          19_NA                      19_NA_NA
## 2        19_20_1                     19_20_1_1
## 3        19_20_2                     19_20_2_4
## 4         19_1_1                      19_1_1_1
## 5         19_2_1                      19_2_1_1
## 6        19_24_2                     19_24_2_2
##   geno_synthesis_HetStockplates_HetPreculture
## 1                               19_NA_NA_19_1
## 2                                 19_20_1_1_1
## 3                                 19_20_2_4_4
## 4                                  19_1_1_1_1
## 5                                  19_2_1_1_1
## 6                                 19_24_2_2_3
##   geno_synthesis_HetStockplates_HetPreculture_assay
## 1                                   19_NA_NA_19_1_1
## 2                                     19_20_1_1_1_1
## 3                                     19_20_2_4_4_4
## 4                                      19_1_1_1_1_1
## 5                                      19_2_1_1_1_1
## 6                                     19_24_2_2_3_3
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate
## 1                                       19_NA_NA_19_1_1_2
## 2                                         19_20_1_1_1_1_3
## 3                                         19_20_2_4_4_4_2
## 4                                          19_1_1_1_1_1_2
## 5                                          19_2_1_1_1_1_2
## 6                                         19_24_2_2_3_3_3
##   geno_synthesis_HetStockplates_HetPreculture_assay_plate_rep
## 1                                         19_NA_NA_19_1_1_2_1
## 2                                           19_20_1_1_1_1_3_3
## 3                                           19_20_2_4_4_4_2_1
## 4                                            19_1_1_1_1_1_2_1
## 5                                            19_2_1_1_1_1_2_3
## 6                                           19_24_2_2_3_3_3_2
##   Acceptor_HoStockplatesAcc Donor_HoStockplatesDon AcceptorMM Midparent
## 1                  19_19_X1               19_19_X1         19        19
## 2                      19_1                   20_1         19        20
## 3                      19_2                   20_2         19        20
## 4                      19_1                    1_1         19         1
## 5                      19_1                    2_1         19         2
## 6                      19_2                   24_2         19        24
##   AccDonCov HetDonorbyHom HetAccbyHom Mito Acceptor15 DonorhomGR AcchomGR
## 1        19            19          19    1         19   1.626988 1.626988
## 2        20            20          19    1         19   1.654298 1.626988
## 3        20            20          19    3         19   1.654298 1.626988
## 4         1             1          19    1         19         NA 1.626988
## 5         2             2          19    1         19   1.326866 1.626988
## 6        24            24          19    1         19   1.794049 1.626988
##   midhompar midhomparcent   logGRcent midparentheterosis   hetvigor
## 1  1.626988  -0.020493628 -0.16724709          0.0000000  0.0000000
## 2  1.640643  -0.006838559 -1.01904090         -0.8654489 -0.8654489
## 3  1.640643  -0.006838559  0.13176109          0.2853531  0.2853531
## 4        NA            NA -0.80036419                 NA         NA
## 5  1.476927  -0.170554168 -0.04627797          0.2710297  0.2710297
## 6  1.710518   0.063036893  0.02275983          0.1064764  0.1064764
##   besthompar besthomparcent strain18       GR   mitdist  nucldist
## 1   1.626988    -0.24477362        1 5.088523 0.0000000 0.0000000
## 2   1.654298    -0.21746348        3 2.171013 0.0000000 0.3579682
## 3   1.654298    -0.21746348        1 6.861978 0.0000000 0.3579682
## 4         NA             NA        3 2.701671 0.2275862 0.4082805
## 5   1.626988    -0.24477362        1 5.742856 0.1931034 0.3742951
## 6   1.794049    -0.07771257        1 6.153337 0.0000000 0.3724721
sum(dataWL2$Type=="Heterokaryon")
## [1] 198
sum(dataGR2$Type=="Heterokaryon")
## [1] 230
cor.test(dataWL2$nucldist[dataWL2$Type=="Heterokaryon"], dataWL2$mitdist[dataWL2$Type=="Heterokaryon"])
## 
##  Pearson's product-moment correlation
## 
## data:  dataWL2$nucldist[dataWL2$Type == "Heterokaryon"] and dataWL2$mitdist[dataWL2$Type == "Heterokaryon"]
## t = 4.5338, df = 196, p-value = 1.007e-05
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.1762179 0.4290963
## sample estimates:
##      cor 
## 0.308089
cor.test(dataGR2$nucldist[dataGR2$Type=="Heterokaryon"], dataGR2$mitdist[dataGR2$Type=="Heterokaryon"])
## 
##  Pearson's product-moment correlation
## 
## data:  dataGR2$nucldist[dataGR2$Type == "Heterokaryon"] and dataGR2$mitdist[dataGR2$Type == "Heterokaryon"]
## t = 6.3619, df = 228, p-value = 1.079e-09
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.2726044 0.4928743
## sample estimates:
##      cor 
## 0.388271
plot(dataGR2$nucldist[dataGR2$Type=="Heterokaryon"], jitter(dataGR2$mitdist[dataGR2$Type=="Heterokaryon"]), pch=16, col=rgb(red=0.5, green=0.5, blue=0.5, alpha=0.5))

plot(dataWL2$nucldist[dataWL2$Type=="Heterokaryon"], dataWL2$mitdist[dataWL2$Type=="Heterokaryon"])

data.frame(colnames(nucldist), colnames(mitdist))
##    colnames.nucldist. colnames.mitdist.
## 1               87074             87074
## 2               87075             87075
## 3               87124             87124
## 4               87179             87179
## 5               87183             87183
## 6               87215             87215
## 7               90137             90137
## 8               90166             90166
## 9               91132             91132
## 10              93028             93028
## 11              93134             93134
## 12              95123             95123
## 13              95126             95126
## 14              95156             95156
## 15              95191             95191
## 16             Br2444            Br2444
## 17             Br5182            Br5182
## 18             Fas161            Fas161
## 19               FSE3              FSE3
## 20               FSE7              FSE7
## 21               HR32              HR32
## 22               OH22              OH22
## 23              OH235             OH235
## 24              Rb313             Rb313
## 25              RB482             RB482
## 26              RB489             RB489
## 27              RB896             RB896
## 28             RB9411            RB9411
## 29        Sa1595(Ref)       Sa1595(Ref)
## 30              Sa948             Sa948
data.frame(rownames(nucldist), rownames(mitdist))
##    rownames.nucldist. rownames.mitdist.
## 1               87074             87074
## 2               87075             87075
## 3               87124             87124
## 4               87179             87179
## 5               87183             87183
## 6               87215             87215
## 7               90137             90137
## 8               90166             90166
## 9               91132             91132
## 10              93028             93028
## 11              93134             93134
## 12              95123             95123
## 13              95126             95126
## 14              95156             95156
## 15              95191             95191
## 16             Br2444            Br2444
## 17             Br5182            Br5182
## 18             Fas161            Fas161
## 19               FSE3              FSE3
## 20               FSE7              FSE7
## 21               HR32              HR32
## 22               OH22              OH22
## 23              OH235             OH235
## 24              Rb313             Rb313
## 25              RB482             RB482
## 26              RB489             RB489
## 27              RB896             RB896
## 28             RB9411            RB9411
## 29        Sa1595(Ref)       Sa1595(Ref)
## 30              Sa948             Sa948
cnucldistvec <- nucldist[upper.tri(nucldist)]
mitdistvec <-mitdist[upper.tri(mitdist)]

cor.test(cnucldistvec, mitdistvec)
## 
##  Pearson's product-moment correlation
## 
## data:  cnucldistvec and mitdistvec
## t = 8.4842, df = 433, p-value = 3.475e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.2939652 0.4554051
## sample estimates:
##       cor 
## 0.3775505
cor.test(cnucldistvec[cnucldistvec>0.35], mitdistvec[cnucldistvec>0.35])
## 
##  Pearson's product-moment correlation
## 
## data:  cnucldistvec[cnucldistvec > 0.35] and mitdistvec[cnucldistvec > 0.35]
## t = 6.3509, df = 426, p-value = 5.497e-10
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.2050228 0.3783346
## sample estimates:
##       cor 
## 0.2940944
library(reshape)
## 
## Attaching package: 'reshape'
## The following objects are masked from 'package:reshape2':
## 
##     colsplit, melt, recast
nucldist2 <- melt(nucldist)
## Using  as id variables
names(nucldist2) <- c("strain1", "nucldist")
nucldist2$strain2 <- rep(names(nucldist), length(nucldist))
head(nucldist2)
##   strain1  nucldist strain2
## 1   87074 0.0000000   87074
## 2   87074 0.3579682   87075
## 3   87074 0.4082805   87124
## 4   87074 0.3742951   87179
## 5   87074 0.3682094   87183
## 6   87074 0.3907651   87215
nucldist2$strain1_strain2 <- paste(nucldist2$strain1, nucldist2$strain2, sep="_")
nucldist2[nucldist2$nucldist>0.29&nucldist2$nucldist<0.31,]
##     strain1  nucldist strain2 strain1_strain2
## 808   RB896 0.2998365  RB9411    RB896_RB9411
## 837  RB9411 0.2998365   RB896    RB9411_RB896
mitdist2 <- melt(mitdist)
## Using  as id variables
names(mitdist2) <- c("strain1", "mitdist")
mitdist2$strain2 <- rep(names(mitdist), length(mitdist))
head(mitdist2)
##   strain1   mitdist strain2
## 1   87074 0.0000000   87074
## 2   87074 0.0000000   87075
## 3   87074 0.2275862   87124
## 4   87074 0.1931034   87179
## 5   87074 0.2758621   87183
## 6   87074 0.1724138   87215
mitdist2$strain1_strain2 <- paste(mitdist2$strain1, mitdist2$strain2, sep="_")

9 FigS7: Correlation between fitness traits

homcor <- lmodel2(weightloss ~ GR, data=data[data$Type.x=="Homokaryon",], nperm=99)
## RMA was not requested: it will not be computed.
hetcor <- lmodel2(weightloss ~ GR, data=data[data$Type.x=="Heterokaryon",], nperm=99)
## RMA was not requested: it will not be computed.
homcor$rsquare
## [1] 0.1608898
homcor$P.param
## [1] 0.1236098
homcorReg <- unlist(homcor$regression.results[homcor$regression.results$Method=="MA",][2:3])
homcorCI <- unlist(homcor$confidence.intervals[homcor$confidence.intervals$Method=="MA",][2:5])

hetcorReg <- unlist(hetcor$regression.results[hetcor$regression.results$Method=="MA",][2:3])
hetcorCI <- unlist(hetcor$confidence.intervals[hetcor$confidence.intervals$Method=="MA",][2:5])

rangy <-c(-0.1, 0.5)
rangx <-c(0, 10)

wcorr <- 7
hcorr <- 4

pdf(file="FigureS6.pdf", width = wcorr, height = hcorr)

par(mar=c(5, 5, 2, 1), mfrow=c(1, 2), xpd=FALSE)

plot(data$GR[data$Type.x=="Homokaryon"], data$weightloss[data$Type.x=="Homokaryon"], bty="n", pch=16, las=1, xlab="Growth rate (mm/day)", ylab="Wood weight loss (mg)", xlim=rangx, ylim=rangy)
Lines <- bquote(paste("R"^"2","=",.(round(homcor$rsquare, 2)), sep=""))
mtext(Lines, side=3, at=2)
mtext(paste0("P-value=", round(homcor$P.param, 2)), side=3, at=3, line=-1)
abline(a=homcorReg[1], b=homcorReg[2])
mtext("A", side=3, at=-3, line=0, cex=1.5)

plot(data$GR[data$Type.x=="Heterokaryon"], data$weightloss[data$Type.x=="Heterokaryon"], bty="n", pch=16, las=1, xlab="Growth rate (mm/day)", ylab=NA, xlim=rangx, ylim=rangy)
Lines <- bquote(paste("R"^"2","=",.(round(hetcor$rsquare, 2)), sep=""))
mtext(Lines, side=3, at=2)
mtext(paste0("P-value=", round(hetcor$P.param, 3)), side=3, at=3.1, line=-1)
abline(a=hetcorReg[1], b=hetcorReg[2])
mtext("B", side=3, at=-3, line=0, cex=1.5)

dev.off()
## quartz_off_screen 
##                 2