直接遗传效应(direct genetic effects,DGE):个体的表现型直接受基因型影响。
间接遗传效应(indirect genetic effects,IGE):个体的表现除了受本身基因的影响,还间接受到相邻个体(社会伙伴)的基因影响。它属于一种环境影响。间接遗传效应的存在改变了基因型-表型的关系,在非直观的条件下改变进化的进程。
使用CIMMYT小麦项目组提供的数据。数据有2个block,98个个体。该数据用于计算邻接材料对焦点材料的效应。
表型数据:
block focal neighbour trait
3878 b2 id_4568 id_1995 506
2038 b2 id_9637 id_9637 390
3994 b2 id_1720 id_4571 251
1642 b2 id_755 id_1771 438
1505 b2 id_6115 id_4568 486
1813 b2 id_1536 id_784 421
1459 b2 id_6115 id_5764 632
3345 b2 id_7489 id_4669 212
1680 b2 id_755 id_4960 569
1293 b2 id_4669 id_3613 652
2063 b2 id_845 id_845 629
2051 b2 id_4960 id_4960 490
1412 b2 id_5229 id_5746 891
1760 b2 id_1995 id_9779 182
3526 b2 id_8509 id_6115 455
2014 b2 id_6180 id_6180 702
1138 b2 id_5963 id_2734 351
3282 b2 id_1436 id_5963 500
2026 b2 id_5042 id_5042 332
1492 b2 id_6115 id_1802 587基因型数据:
id_5440 id_4568 id_5890 id_1309 id_4640 id_4007
id_5440 1.956696361 -0.061769158 -0.01634397 -0.06447941 -0.04040527 -0.004130619
id_4568 -0.061769158 2.002057918 0.02756001 -0.06931443 0.01471098 0.008653623
id_5890 -0.016343974 0.027560012 1.94589038 0.10144781 0.02089325 0.006026260
id_1309 -0.064479410 -0.069314435 0.10144781 1.95258925 -0.01528626 0.016297550
id_4640 -0.040405271 0.014710976 0.02089325 -0.01528626 1.92236611 -0.016776517
id_4007 -0.004130619 0.008653623 0.00602626 0.01629755 -0.01677652 1.953613106(1)直接遗传效应
表现型只由focal决定。
library(sommer)
data(DT_ige)
DT <- DT_ige
## Direct genetic effects model
modDGE <- mmer(trait ~ block, # 固定效应为block
random = ~ focal, # 随机效应为focal
rcov = ~ units,
data = DT, verbose=FALSE)
summary(modDGE)$varcomp
VarComp VarCompSE Zratio Constraint
focal.trait-trait 19894.45 3118.3474 6.379806 Positive
units.trait-trait 10134.22 477.9483 21.203584 Positive(2)间接遗传效应
表现型由focal和neighbour共同决定。这里使用DGE的方式计算focal和neighbour的方差组分。
data(DT_ige)
DT <- DT_ige
## Indirect genetic effects model
modDGE <- mmer(trait ~ block,
random = ~ focal + neighbour,
rcov = ~ units,
data = DT, verbose=FALSE)
summary(modDGE)$varcomp
VarComp VarCompSE Zratio Constraint
focal.trait-trait 20550.511 3148.6833 6.526700 Positive
neighbour.trait-trait 2926.704 607.4191 4.818261 Positive
units.trait-trait 7301.084 363.8236 20.067649 Positive此外,还可以用IGE的方式计算间接遗传效应。gvs()用来计算基因型的协方差矩阵。
data(DT_ige)
DT <- DT_ige
### Indirect genetic effects model
modIGE <- mmer(trait ~ block,
random = ~ gvs(focal, neighbour),
rcov = ~ units,
data = DT, verbose=FALSE)
summary(modIGE)$varcomp
VarComp VarCompSE Zratio Constraint
focal:focal.trait-trait 21014.516 3212.3586 6.541772 Positive
focal:neighbour.trait-trait -7469.401 1246.1105 -5.994173 Unconstr
neighbour:neighbour.trait-trait 2964.707 576.9991 5.138149 Positive
units.trait-trait 7297.715 357.8869 20.391120 Positive另外,可以通过gvs()的Gu参数提供方差协方差矩阵列表,这里Af=An都是个体的加性效应矩阵。
data(DT_ige)
DT <- DT_ige
Af <- A_ige
An <- A_ige
### Indirect genetic effects model
modIGE <- mmer(trait ~ block,
random = ~ gvs(focal, neighbour, Gu=list(Af,An)),
rcov = ~ units,
data = DT, verbose=FALSE)
summary(modIGE)$varcomp
VarComp VarCompSE Zratio Constraint
focal:focal.trait-trait 27806.797 4162.7014 6.679988 Positive
focal:neighbour.trait-trait -9901.351 1532.8048 -6.459630 Unconstr
neighbour:neighbour.trait-trait 3638.534 611.4065 5.951089 Positive
units.trait-trait 7409.998 359.9827 20.584320 Positive