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Volume 32 Issue 4
Sep.  2019
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Genetic Analysis of Larix kaempferi Growth Traits in Full-diallel Crosses

  • Corresponding author: SUN Xiao-mei, xmsun@caf.ac.cn
  • Received Date: 2018-05-27
    Accepted Date: 2019-05-15
  • Objective The analysis of combining ability was conducted through full-diallel mating design to study the relative contribution of special combining ability (SCA) to economically important traits, aiming to provide important genetic parameter information for the development of Japanese larch (Larix kaempferi) breeding strategies and the management of breeding populations. Method The progeny trail mainly consists of two full-diallels (6×6 and 4×4, respectively) derived from 13 parent trees used as female and 23 used as male. The phenotypic data for growth traits measured at age 16 and age 26 were adjusted using first order autoregression model, and then were used in individual mixed models to conduct combining ability and reciprocal effect analysis. The importance of dominance related to additive effect was investigated and its application in Japanese larch breeding was discussed. Result The self-crossed offspring showed no significant self-depression in the survival, and even outperformed the corresponding non-selfed individuals in some parents in terms of growth. The reciprocal effects of the growth traits were not notable, indicating that the mating direction needs not to be considered in future's breeding. At age 16, the additive and dominance effect of DBH and volume were significant, and the dominant effect was greater than the additive effect. At this age, the genetic gains were 3.21% and 8.04% when selected for the top 10 families based on combining breeding value and SCA, which increased by 16.30% and 12.92% compared with selection on breeding value solely (2.76% and 7.12%, respectively). The additive effects of DBH and volume were significant at age 26 while the dominant effects were disappeared. The narrow-sense heritability, broad sense heredity and broad family heritability of the average family were 0.070-0.074, 0.164-0.173, and 0.546-0.572 for DBH and volume at age 16, and the narrow-sense heredity increased to 0.13 and 0.10 for this two traits, respectively. Conclusion The SCA effects are significant for DBH and volume at age 16. More genetic gain can be captured by the utilization of SCA through producing improved seeds from mating those parent pairs with high GCA and high SCA effects. Further, genetic gain can be maximized through vegetative propagation of the trees developed from those seeds.
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Genetic Analysis of Larix kaempferi Growth Traits in Full-diallel Crosses

    Corresponding author: SUN Xiao-mei, xmsun@caf.ac.cn
  • Research Institute of Forestry, Chinese Academy of Forestry, Key Laboratory of Tree Breeding and Cultivation, National Forestry and Grassland Administration, Beijing 100091, China

Abstract:  Objective The analysis of combining ability was conducted through full-diallel mating design to study the relative contribution of special combining ability (SCA) to economically important traits, aiming to provide important genetic parameter information for the development of Japanese larch (Larix kaempferi) breeding strategies and the management of breeding populations. Method The progeny trail mainly consists of two full-diallels (6×6 and 4×4, respectively) derived from 13 parent trees used as female and 23 used as male. The phenotypic data for growth traits measured at age 16 and age 26 were adjusted using first order autoregression model, and then were used in individual mixed models to conduct combining ability and reciprocal effect analysis. The importance of dominance related to additive effect was investigated and its application in Japanese larch breeding was discussed. Result The self-crossed offspring showed no significant self-depression in the survival, and even outperformed the corresponding non-selfed individuals in some parents in terms of growth. The reciprocal effects of the growth traits were not notable, indicating that the mating direction needs not to be considered in future's breeding. At age 16, the additive and dominance effect of DBH and volume were significant, and the dominant effect was greater than the additive effect. At this age, the genetic gains were 3.21% and 8.04% when selected for the top 10 families based on combining breeding value and SCA, which increased by 16.30% and 12.92% compared with selection on breeding value solely (2.76% and 7.12%, respectively). The additive effects of DBH and volume were significant at age 26 while the dominant effects were disappeared. The narrow-sense heritability, broad sense heredity and broad family heritability of the average family were 0.070-0.074, 0.164-0.173, and 0.546-0.572 for DBH and volume at age 16, and the narrow-sense heredity increased to 0.13 and 0.10 for this two traits, respectively. Conclusion The SCA effects are significant for DBH and volume at age 16. More genetic gain can be captured by the utilization of SCA through producing improved seeds from mating those parent pairs with high GCA and high SCA effects. Further, genetic gain can be maximized through vegetative propagation of the trees developed from those seeds.

  • 在一个林木育种计划中,及时精确地估算主要经济性状的遗传参数对育种策略的制定和实施起着至关重要的作用[1]。遗传参数中遗传效应方差通常分为加性和非加性两部分,非加性遗传效应又可进一步分为显性和上位效应[2]。加性遗传效应(或一般配合力,GCA)被认为是性状在代际遗传中可以固定的遗传效应,是育种值大小的二分之一,在林木育种中占有相对重要的位置。因此,亲本选择、育种群体构建及相应的育种评价主要是基于加性遗传模型。显性效应(特殊配合力SCA的4倍)是等位基因间的相互作用,被认为是能遗传而不能被固定的遗传效应,是产生杂种优势的主要部分。早期遗传分析中忽视了非加性遗传效应尤其是显性效应的重要性,将其归入环境效应中,从而导致方差组分和育种值估计的偏差[3-5]

    双列交配设计可同时估计加性和显性效应方差,提供丰富的遗传信息,同时还可为高世代育种提供大量谱系清楚的供选子代,因此,国内外很多针叶树均开展了基于双列交配设计的配合力研究[6-8]。早期研究中,将GCA作为最重要的遗传参数用于育种策略的制定,而对SCA的关注较少。Carson利用辐射松(Pinus radiata)半双列杂交子代多点试验结果,报道了SCA相对于GCA的重要性在不同环境下变化较大,比值最高可达98%[9]。Wu等[7]在对辐射松不连续半双列交配设计的10个地点测定林的联合分析时发现,SCA方差近等于GCA方差。近期对火炬松(P.taeda)双列交配设计的多点子代测定研究中也证实树高受到更显著的显性效应控制[10]。因此,在特定的改良计划中,除了对GCA的利用,对SCA的研究也是必不可少的。

    日本落叶松(Larix kaempferi (Lamb.) Carr.)具有早期速生、成林快、易于栽培、适应性广等特点,在我国的温带(吉林、辽宁、山东、河南等)及中北亚热带(湖北、湖南、四川、甘肃等)高山区得到迅速推广应用[11-12]。1965年在辽宁大孤家林场营建我国最早的日本落叶松种子园,随后陆续开展人工杂交和子代测定工作。已有研究多集中在对自由授粉家系的生长、形质及材性等遗传变异方面[12-15],但对全同胞子代表现的研究比较缺乏。本研究以来自13个母本和23个父本包括6×6和4×4两组全双列交配及部分随机交配的子代测定林为对象,对16年生和26年生的生长数据进行区组效应和空间环境效应校正后,研究自交子代的生长表现、正反交效应和GCA与SCA的相对重要性,为合理制定和调整日本落叶松遗传改良策略提供依据。

1.   材料与方法
  • 育种种子园于1965年建于辽宁省清原县大孤家林场(42.72° N,124.88° E),建园无性系由选自辽宁地区30~40年生早期引种的日本落叶松人工林优树嫁接而成,包含12个小区,株行距为4 m×4 m。1986—1987年在种子园开展控制授粉进行人工制种,共获得来自13个母本和23个父本的杂交组合66个,其中,包括6×6和4×4两组全双列交配组合(组1和组2),以及19个随机交配组合,交配设计见表 1。1988年在圃地育苗,1990年以2年生苗在该林场内造林。试验林采用随机完全区组设计,5次重复,10株双列小区,株行距为2 m×2 m。土壤为山地棕壤,海拔约460 m。

    母本
    Maternal
    parents
    父本Paternal parents
    RC13 RC19 RC4 RC5 RC503 RC82 RF27 Y11 Y16 R1 Y33 Y5 Y13 RC2 RC34 RC35 RC40 RC402 RC404 RC41 RC61 RC8 RC81
    RC13 × × × × × ×
    RC19 × × × × ×
    RC4 × × × ×
    RC5 × × × × × × × ×
    RC503 × × × × × ×
    RC82 × × × × × × × × ×
    RF27 × ×
    Y11 × × ×
    Y16 × × ×
    R1 × × ×
    Y55 ×
    Y10 × × × × × × ×
    RC25 × ×
    注:×-交配;⊗-自交。
    Notes: × and ⊗ indicate crossing and selfing, respectively.

    Table 1.  Mating design table

  • 分别在林龄16年和26年对测定林进行每木生长调查。树高(H/m)采用激光测高仪(Vertex Ⅲ,Haglof Company Group,Sweden)测定,胸径(DBH/cm)采用测径尺测定,并计算材积(V/dm3):

  • 在估计遗传参数之前,通过混合效应模型(2)矫正表型性状中的环境变异。

    式(2)中: y是表型观测值向量,β是固定效应向量(均值),r是随机的区组效应向量服从r~N(0, $I\hat \sigma _r^2$),I是单位矩阵,$\hat \sigma _r^2$是区组效应方差,XZ分别是固定和随机效应的关联矩阵,e是随机残差向量,服从r~N(0, R),R是残差的方差-协方差结构(3)。

    $\hat \sigma _\xi ^2$是空间残差方差,$\hat \sigma _\eta ^2$是独立残差方差,∑r(ρr)是具有维度r×r的行模型的相关矩阵,ρr是行方向上的自相关参数;∑c(ρc)是具有维度c×c的列模型的相关矩阵,ρc是列方向上的自相关参数,而且有:

    利用R软件(版本3.1.2)ASReml-R包(版本3.0)[16-17]拟合模型。最终通过从表型数据中减去随机的区组和空间位置效应,获得矫正表型数据用于后续分析。

  • 采用单株线性随机效应模型(4)和限制性最大似然估计方法(REML)估计随机效应的方差分量。

    式(4)中:y是矫正后的表型值向量,asrpe分别是随机的加性、特殊配合力、正反交、小区、残差效应向量,Z1~Z4分别是对应效应的关联矩阵。

    利用似然比检验(LRT)各方差组分的统计显著性。利用泰勒级数展开法(Taylor series expansion)计算遗传参数的标准误[16]

    遗传和表型变异系数(CVGCVP)分别按照公式(5)和(6)计算。

    式(5)~(6)中:${\hat \sigma }$a、${\hat \sigma }$p、${\bar X}$分别为加性方差平方根、总方差平方根、总体均值。

    狭义和广义单株遗传力(${\hat h}$i2和${\hat H}$i2)以及广义家系遗传力(f2)参照Weng等[18]中的公式进行计算:

    式(7)~(9)中:$ \sigma _d^2 = 4 \times \sigma _s^2, \sigma _a^2, \sigma _d^2, \sigma _s^2, \sigma _r^2, \sigma _p^2$和$\hat { \sigma } _ { e } ^ { 2 }$分别是加性方差、显性方差、特殊配合力方差、正反交效应方差、小区方差和残差方差的估计值。nrnbni分别是正反交、区组和调和小区株树。

    根据亲本育种值排名选择前10个家系,并采用基于BLUP估计的育种值和遗传值(育种值+特殊配合力)计算遗传增益[19-20]

2.   结果与分析
  • 测定林在16年生和26年生时的保存率分别为44.7%和39.8%,组1、组2与随机交配组合个体存活表现较为一致。对两组全双列交配中自交与对应亲本的异交组合保存率均值进行t检验,未发现显著性差异(表 2)。同样地,组1中自交子代与对应亲本的异交子代的各生长性状也未有明显差异,组2中自交子代的生长表现则均优于对应亲本的异交子代,而且26年生时达到极显著水平(表 2)。

    性状
    Traits
    组1 Group 1 组2 Group 2
    tt-value pp-value tt-value pp-value
    Sur16 0.69 0.52 0.87 0.41
    H16 -0.27 0.80 -1.83 0.16
    DBH16 0.68 0.53 -1.94 0.12
    V16 0.50 0.64 -2.11 0.12
    Sur26 0.93 0.40 0.61 0.56
    H26 -0.04 0.97 -3.20 0.01
    DBH26 0.92 0.41 -4.72 < 0.01
    V26 1.01 0.36 -4.86 < 0.01
    注:Sur-存活率;H-树高;DBH-胸径;V-材积指数。下同。
    Notes: Sur, H, DBH and V present survival, height, diameter at breast height and volume index, respectively. The following 16 and 26 indicate the tree ages. The same bellow.

    Table 2.  Statistics of two-tailed t-test for means comparison between selfing and non-selfing progeny from the same parents for survival and growth traits

    16年生和26年生各生长性状的表型统计值及变异系数列于表 3。整体上,26年生树高、胸径和材积的表型变异系数分别为6.22%、11.33%和25.92%,胸径的变异系数高于树高,同性状26年生时的变异系数大于16年生,树高的加性遗传变异系数极低(0.01%)。组1、组2与整体的变异趋势基本一致,只是组2各性状的加性遗传变异系数均 < 0.01%。

    性状Traits 均值
    Mean
    标准差
    SD
    极小值
    Min
    极大值
    Max
    加性遗传变异
    系数CVG/%
    表型变异系
    数CVP/%
    组1
    Group 1
    Sur16/% 45.04 15.68 9.09 75.00 NA NA
    H16/m 17.52 0.49 16.68 18.32 0.97 5.80
    DBH16/cm 15.47 0.68 14.07 16.30 2.56 9.67
    V16/dm3 43.01 4.68 34.16 51.44 6.56 24.04
    Sur26/% 38.81 14.60 9.09 75.00 NA NA
    H26/m 22.33 0.87 20.43 23.37 0.52 6.53
    DBH26/cm 20.02 1.25 17.59 22.04 4.28 11.85
    V26/dm3 93.41 14.81 64.06 117.74 9.00 28.37
    组2
    Group 2
    Sur16/% 44.98 9.51 25.00 62.00 NA NA
    H16/m 17.79 0.43 16.93 19.02 < 0.01 5.43
    DBH16/cm 15.46 0.80 12.82 16.93 < 0.01 9.56
    V16/dm3 43.96 5.30 28.17 54.61 < 0.01 21.44
    Sur26/% 40.36 10.18 16.67 58.00 NA NA
    H26/m 22.95 0.77 20.19 24.87 < 0.01 7.29
    DBH26/cm 20.32 1.30 14.93 23.00 < 0.01 11.85
    V26/dm3 98.60 12.93 52.67 126.28 0.01 27.57
    全部Total Sur16/% 44.72 11.04 9.09 75.00 NA NA
    H16/m 17.73 0.48 16.68 19.02 < 0.01 5.70
    DBH16/cm 15.58 0.86 12.82 18.29 3.38 9.49
    V16/dm3 44.40 5.71 28.17 62.27 7.88 23.34
    Sur26/% 39.82 10.59 9.09 75.00 NA NA
    H26/m 22.88 0.94 20.19 25.87 < 0.01 6.22
    DBH26/cm 20.43 1.39 14.93 24.85 4.97 11.33
    V26/dm3 99.62 15.98 52.67 161.16 9.49 25.92
    注:NA-缺失。
    Notes: NA presents not available.

    Table 3.  Descriptive statistics for survival and growth traits

  • 各性状的方差分量和遗传力估计值见表 4。似然比检验(LRT)结果显示:胸径和材积的加性效应作用极显著,而显性效应则随着年龄而变化,16年生时的显性效应极显著,且大于加性效应($ \sigma _d^2/ \sigma _a^2$=1.33~1.34),至26年生时显性效应消失(方差分量均 < 0.001);相对于胸径和材积,树高的各方差分量较小,16年生时加性效应显著,而26年生时显性效应显著,且大于加性效应($ \sigma _d^2/ \sigma _a^2$=6.36)。组1中的结果与整体基本一致,只是16年生时的显性效应低于加性效应($\hat \sigma _d^2/\hat \sigma _a^2$=0.59~0.85)。树高的各方差分量均 < 0.001,加性和显性效应可忽略不计。组2材料各性状未发现显著的加性和显性,说明其变异主要来源于环境因素,遗传变异极小,也不再进行后续的分析。各性状的正反交效应不显著,暗示交配方向对子代的生长没有影响。在整体材料中,小区对所有性状均有显著作用,表明家系在不同重复间有显著的差异。16年生时,胸径和材积的单株狭义遗传力较低,分别为0.070和0.074,树高遗传力更低为0.028;至26年生时,胸径和材积的单株狭义遗传力分别增加至0.130和0.101,树高则降至0.006。而组1中的胸径和材积受中度遗传控制,16年生时单株狭义遗传力分别为0.127和0.114,26年生时分别增加至0.192和0.134。受SCA的影响,整体材料在26年生时胸径和材积的单株广义遗传力高于单株狭义遗传力,分别0.164和0.173;家系水平上广义遗传力较高,分别为0.572和0.546。26年生时因SCA的作用减弱,胸径和材积的广义遗传力分别降至0.130和0.101;家系遗传力略有下降,分别为0.561和0.501。组1几乎贡献了整体材料的全部遗传变异,因此其遗传力和整体有相同的变化趋势,仅在数值上较高。

    组别
    Group
    性状
    Traits
    加性方差
    ${\hat \sigma }$a(SE)2
    显性方差
    ${\hat \sigma }$d(SE)2
    正反交效
    应方差
    ${\hat \sigma }$r(SE)2
    小区方差
    ${\hat \sigma }$p(SE)2
    残差方差
    ${\hat \sigma }$e(SE)2
    显性/加
    性方差
    ${\hat \sigma }$d2/a2
    单株狭义
    遗传力
    ${\hat \sigma }$i(SE)2
    单株广义
    遗传力
    ${\hat \sigma }$i(SE)2
    家系广义
    遗传力
    ${\hat \sigma }$f(SE)2
    组1
    Group 1
    H16 < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    0.382
    (0.066)**
    0.638
    (0.046)
    NA < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    DBH16 0.277
    (0.299)**
    0.164
    (0.329)**
    0.03
    (0.057)
    0.119
    (0.083)**
    1.856
    (0.165)
    0.59 0.127
    (0.083)
    0.202
    (0.078)
    0.642
    (0.357)
    V16 12.233
    (15.224)**
    10.34
    (19.26)**
    0.614
    (2.851)
    12.571
    (4.75)**
    85.48
    (7.811)
    0.85 0.114
    (0.084)
    0.21
    (0.078)
    0.593
    (0.337)
    H26 < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    0.143
    (0.087)**
    1.885
    (0.146)
    NA < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    DBH26 1.031
    (0.886)**
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    0.478
    (0.229)**
    4.367
    (0.444)
    < 0.01 0.192
    (0.099)
    0.192
    (0.109)
    0.621
    (0.349)
    V26 89.286
    (84.68)**
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    47.629
    (28.112)*
    574.56
    (52.833)
    < 0.01 0.134
    (0.075)
    0.134
    (0.094)
    0.539
    (0.315)
    组2
    Group 2
    H16 < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    0.144
    (0.098)**
    0.789
    (0.133)
    NA < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    DBH16 < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    2.187
    (0.306)
    NA < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    V16 < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    88.85
    (12.442)
    NA < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    H26 < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    0.016
    (0.364)
    2.784
    (0.594)
    NA < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    DBH26 < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    5.794
    (0.905)
    NA < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    V26 < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    739.077
    (115.425)
    < 0.01 < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    全部
    Combined
    H16 0.029
    (0.063)*
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    0.356
    (0.049)**
    0.661
    (0.041)
    < 0.01 0.028
    (0.034)
    0.028
    (0.036)
    0.128
    (0.091)
    DBH16 0.157
    (0.173)**
    0.21
    (0.288)**
    0.013
    (0.043)
    0.084
    (0.061)*
    2.013
    (0.124)
    1.34 0.07
    (0.046)
    0.164
    (0.04)
    0.572
    (0.229)
    V16 7.951
    (8.926)**
    10.578
    (15.038)**
    < 0.001
    (< 0.001)
    9.343
    (3.29)**
    90.961
    (5.751)
    1.33 0.074
    (0.05)
    0.173
    (0.043)
    0.546
    (0.218)
    H26 0.014
    (0.103)
    0.087
    (0.28)*
    < 0.001
    (< 0.001)
    0.159
    (0.076)*
    1.937
    (0.122)
    6.36 0.006
    (0.028)
    0.047
    (0.025)
    0.182
    (0.113)
    DBH26 0.735
    (0.479)**
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    0.166
    (0.162)*
    5.098
    (0.346)
    < 0.01 0.13
    (0.051)
    0.13
    (0.065)
    0.561
    (0.324)
    V26 70.653
    (52.565)**
    < 0.001
    (< 0.001)
    < 0.001
    (< 0.001)
    12.532
    (19.864)*
    654.455
    (43.092)
    < 0.01 0.101
    (0.045)
    0.101
    (0.055)
    0.501
    (0.31)
    注:*和**分别表示在0.05和0.01水平显著;NA-缺失;SE-标准误。
    Note: * and ** present significance at 0.05 and 0.01 level, respectively; NA presents not available; SE indicates standard error.

    Table 4.  Estimates of variance components, heritability, and standard errors (in parentheses) for growth traits

  • 根据亲本育种值选择排名前10的组合,然后分别根据育种值和遗传效应值(育种值+SCA效应值)估算遗传增益,结果见表 5。仅根据育种值进行选择,16年生时胸径和材积的遗传增益分别为2.76%和7.12%;当联合育种值和SCA效应值进行选择时,遗传增益分别为3.21%和8.04%,比单纯育种值选择遗传增益分别提高16.30%和12.92%。26年生时SCA消失,根据育种值和遗传值进行选择的效果一致,胸径和材积的遗传增益分别为6.31%和11.00%(表 5)。

    性状
    Traits
    均值
    Mean
    育种值
    Breeding value
    遗传值
    Genetic value
    育种值遗传增益/%
    Genetic gains with breeding value
    遗传值遗传增益/%
    Genetic gains with genetic value
    H16/m 17.73 0.12 0.12 0.68 0.68
    DBH16/cm 15.58 0.43 0.50 2.76 3.21
    V16/dm3 44.40 3.16 3.57 7.12 8.04
    H26/m 22.88 0.05 0.08 0.22 0.35
    DBH26/cm 20.43 1.29 1.29 6.31 6.31
    V26/dm3 99.62 10.96 10.96 11.00 11.00

    Table 5.  Estimates of genetic gains from selection based on breeding values and genetic values

3.   讨论
  • 林木改良过程中,了解主要经济性状的遗传变异与各组分的相对重要性及遗传力大小对选择和育种策略的制定具有重要意义[21]。一般认为加性方差较非加性方差更重要[20, 22-24],是轮回选择和种子园良种生产中的主要利用对象。但在对火炬松和辐射松的双列交配研究中发现,有些生长性状受到更为重要的显性效应控制[7, 10]。本研究结果也表明,16年生时,显性方差显著作用于胸径和材积,并且相对于加性方差起到更为重要的作用($\hat \sigma _d^2/\hat \sigma _a^2$d2/a2=1.33~1.34)。可能影响显性与加性方差的比值重要性的因素还有:一是不平衡的交配设计可能会造成抽样误差的增大;二是亲本及组合数量过少也会造成估算结果误差的增加[25];三是显性方差中可能混有上位效应方差,这有待进一步的无性系测定来验证。此外,群体内的近交也会导致显性方差的增加[7, 10, 26-27],这对天然分布范围小的日本落叶松尤为突出,当通过不同种子批次引种至国内时,对这些种子来源不清的人工林选优会进一步缩小其遗传多样性。辐射松从北美引种到新西兰、澳大利亚也是存在类似的情况[7]。显性效应对胸径和材积的作用随年龄的升高而消失,在火炬松和辐射松中均观测到类似现象[3, 28]。可能的原因是随着年龄的增加,小区内竞争效应加剧,造成显性效应相对重要性的下降[7]。研究遗传参数随年龄的动态变化需要对试验林进行持续的观测,本研究只选取了2个年龄的数据进行分析,后续研究还需要增加观测时间点才能对日本落叶松显性效应的重要性有更可靠和全面的认识及利用。

    林木遗传改良的主要目的是最大化地获取目标性状的遗传增益。相对于单纯育种值的选择策略,当存在显著的非加性效应时兼顾育种值和SCA的选择策略可显著提高性状的遗传增益。本研究结果表明,对16年生日本落叶松育种值和SCA同时选择时,胸径和材积的遗传增益可分别提高16.30%和12.92%。对辐射松的研究表明,通过GCA和SCA的同时选择可提高25%的遗传增益[7]。火炬松的研究也发现, 通过对SCA的利用可提高10%~40%的遗传增益[8]。因此,尽管非加性效应不能遗传,但可以结合无性繁殖技术对非加性遗传效应加以利用。我国自20世纪90年代建立了日本落叶松无性快繁技术体系,为非加性遗传效应的利用提供了技术支撑。

    遗传力反映性状受遗传效应控制的强弱。该子代群体在16年生时,胸径和材积的单株狭义遗传力较低,分别为0.070和0.074,26年生时分别增加至0.101和0.130,普遍低于日本落叶松自由授粉子代群体的估算值[12-13, 29-30]。这可能是由于自由授粉父本贡献不均且含有自交和全同胞子代,违背随机交配和完全半同胞的假设,按照加性方差是家系方差的4倍计算高估了遗传力值。利用系谱重建技术恢复自由授粉子代父本信息后,则降低了遗传力估计值,更接近实际情况[30-32]。本研究中,双列交配及整体材料的树高存在极低的单株狭义遗传力(< 0.03),在对自由授粉家系系谱重建后的67个家系的配合力分析中也发现了类似的结果[30],表明亲本的树高遗传价值间相差很小。可能的原因有:亲本为辽宁地区早期引种的人工林优树,均为所在林分中具有高度优势的个体;控制授粉涉及的亲本数目少、花期一致,4×4的全双列交配中树高和胸径几乎没有遗传变异。另外,相较于木材的理化性质,生长性状更易受环境条件的影响[7, 18],采用空间模型进行数据处理能够在一定程度上提高对实验设计误差的解释[33-34]。子代测定是一个长期的过程,测定林的保存率随年龄增加逐渐降低,林分密度能显著影响个体表型,对遗传力估计值有很大影响。因此,遗传力估计主要取决于3点:性状自身的变异特性、测定林试验设计及测定林的后期管理。针对后2点,建议采用不完全随机区组设计、减少小区内单株个数及增加重复数,在遗传分析时考虑空间效应;加强林地抚育管理。

    在多数林木改良过程中发现,自交能够增加致死隐性基因的频率,导致生殖和生长出现衰退的现象[35-38]。因此,在针叶树繁育中极少利用自交[39]。本研究却发现不同的结果:日本落叶松自交不仅能够产生具有生活力的种子,而且多数亲本的自交后代在存活率和生长表现方面均未表现出显著的自交衰退,甚至部分自交家系的生长要优于相应的异交后代。这些结果表明,本研究所涉及的育种群体中致死隐性基因的频率可能较低,但需要后续利用分子标记技术加以确认,产生的主要原因可能是该群体处在遗传改良初期。随着育种世代的向前推进,由于高强度的选择,自交(近交)衰退会逐步显现,成为相对棘手的问题[40]。后续研究一方面需要对自交后代进行连续自交并观测自交衰退现象,一方面通过分子生物学手段探讨背后的遗传学原因。

4.   结论
  • 本研究利用全双列交配设计子代测定林数据开展了配合力分析,重点评估了显性效应(特殊配合力)对生长性状的贡献。显性效应对胸径和材积作用显著,兼顾育种值和特殊配合力的选择策略较单纯育种值的选择平均可分别提高16.30%和12.92%的遗传增益。因此在利用一般配合力进行亲本选择的基础上,选择特殊配合力高的交配组合,并从子代中选择优良单株进行无性扩繁,可获得最大化的遗传增益。自交子代在保存率和生长方面均未表现出明显的自交衰退现象,生长性状的正反交效应不明显,暗示在今后的育种中无需考虑交配方向。

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