Analysis of Genetic Effects of Nuclear-Cytoplasmic Interaction on Quantitative Traits:Genetic Model for Diploid Plants

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction （NCI） as well as their genotype by environment （GE） interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction （AUP） method. Data on four quantitative traits （boll number, lint percentage, fiber length, and micronaire） in Upland cotton （Gossypium hirsutum L.） were analyzed as a worked example to show the effectiveness of the model.

QTL Analysis for Seven Quality Traits of RIL Population in Japonica Rice Based on Three Genetic Statistical Models

QTL mapping for seven quality traits was conducted by using 254 recombinant inbred lines （RIL） derived from a japonica-japonica rice cross of Xiushui 79/C Bao. The seven traits investigated were grain length （GL）, grain length to width ratio （LWR）, chalk grain rate （CGR）, chalkiness degree （CD）, gelatinization temperature （GT）, amylose content （AC） and gel consistency （GC） of head rice. Three mapping methods employed were composite interval mapping in QTLMapper 2.0 software based on mixed linear model （MCIM）, inclusive composite interval mapping in QTL IciMapping 3.0 software based on stepwise regression linear model （ICIM） and multiple interval mapping with regression forward selection in Windows QTL Cartographer 2.5 based on multiple regression analysis （MIMR）. Results showed that five QTLs with additive effect （A-QTLs） were detected by all the three methods simultaneously, two by two methods simultaneously, and 23 by only one method. Five A-QTLs were detected by MCIM, nine by ICIM and 28 by MIMR. The contribution rates of single A-QTL ranged from 0.89% to 38.07%. All the QTLs with epistatic effect （E-QTLs） detected by MIMR were not detected by the other two methods. Fourteen pairs of E-QTLs were detected by both MCIM and ICIM, and 142 pairs of E-QTLs were detected by only one method. Twenty-five pairs of E-QTLs were detected by MCIM, 141 pairs by ICIM and four pairs by MIMR. The contribution rates of single pair of E-QTL were from 2.60% to 23.78%. In the Xiu-Bao RIL population, epistatic effect played a major role in the variation of GL and CD, and additive effect was the dominant in the variation of LWR, while both epistatic effect and additive effect had equal importance in the variation of CGR, AC, GT and GC. QTLs detected by two or more methods simultaneously were highly reliable, and could be applied to improve the quality traits in japonica hybrid rice.

Efficient protocols and methods for high-throughput utilization of the Collaborative Cross mouse model for dissecting the genetic basis of complex traits

The Collaborative Cross(CC)mouse model is a next‐generation mouse genetic reference population(GRP)designated for a high‐resolution quantitative trait loci(QTL)mapping of complex traits during health and disease.The CC lines were generated from reciprocal crosses of eight divergent mouse founder strains composed of five classical and three wild‐derived strains.Complex traits are defined to be controlled by variations within multiple genes and the gene/environment interactions.In this article,we introduce and present variety of protocols and results of studying the host response to infectious and chronic diseases,including type 2 diabetes and metabolic diseases,body composition,immune response,colorectal cancer,susceptibility to Aspergillus fumigatus,Klebsiella pneumoniae,Pseudomonas aeruginosa,sepsis,and mixed infections of Porphyromonas gingivalis and Fusobacterium nucleatum,which were conducted at our laboratory using the CC mouse population.These traits are observed at multiple levels of the body systems,including metabolism,body weight,immune profile,susceptibility or resistance to the development and progress of infectious or chronic diseases.Herein,we present full protocols and step‐by‐step methods,implemented in our laboratory for the phenotypic and genotypic characterization of the different CC lines,mapping the gene underlying the host response to these infections and chronic diseases.The CC mouse model is a unique and powerful GRP for dissecting the host genetic architectures underlying complex traits,including chronic and infectious diseases.

Genetic relationship of rapeseed yield-related traits revealed by elite lines under multiple environments

To provide a theoretical basis for further improvement of Brassica napus yield, additive dominance with additive - by - additive epistatic effects （ ADAA） genetic model and a 6 X 8 partial dial- lel cross design were used to analyze the genetic effects and correlations of five yield related traits of 14 excellent Brassica napus parental lines and their 46 and F2 populations. The results showed that silique density （SD） , siliques per plant （SPP） , seeds per silique （SPS） and thousand - seed weight （TSW） exhibited not only additive and dominant effects, but also significant epistatic effects. The dominant effects of all five yield - related traits were obviously greater than their additive effects and epistatic effects. Yield per plant （YPP） showed significant genetic correlation with SD, SPP and SPS, and the main component of the genetic correlation was the dominance correlation. SPP and SPS both showed a significant negative correlation with TSW. The SD of rapeseed was genetically correlated with all three components of yield to a certain extent, and there were different components of genetic effects positively correlated with the three yield components, indicating that SD is a potential trait to reconcile the conflict between TSW and SPP as well as SPS.

Genetic parameters for somatic cell score and production traits in the fi rst three lactations of Chinese Holstein cows

The objectives of this study were to estimate genetic parameters of lactation average somatic cell scores （LSCS） and examine genetic associations between LSCS and production traits in the first three lactations of Chinese Holstein cows using single-parity multi-trait animal model and multi-trait repeatability animal model. There were totally 273605 lactation records of Chinese Holstein cows with first calving from 2001 to 2012. Heritability estimates for LSCS ranged from 0.144 to 0.187. Genetic correlations between LSCS and 305 days milk, protein percentage and fat percentage were -0.079, -0.082 and -0.135, respectively. Phenotypic correlation between LSCS and 305 days milk yield was negative （-0.103 to -0.190）. Genetic correlation between 305 days milk and fat percentage or protein percentage was highly negative. Genetic correlation between milk fat percentage and milk protein percentage was highly favorable. Heritabilities of production traits decreased with increase of parity, whereas heritability of LSCS increased with increase of parity.

有棱丝瓜早熟相关性状主基因+多基因遗传模型分析

【目的】通过主基因+多基因遗传模型分析有棱丝瓜早熟性相关性状的遗传规律,为早熟丝瓜品种选育提供理论参考。【方法】以高代自交系有棱丝瓜LC034(♀)和LC052(♂)为亲本构建6世代群体,采用主基因+多基因遗传分离法分析有棱丝瓜的4个早熟相关性状(第一雌花节位、始花期、第一坐果节位和始收期)遗传规律。【结果】LC034的4个早熟相关性状均极显著低于LC052(P<0.01)。F_(1)、BC_(1)P_(1)、BC_(1)P_(2)和F_(2)代群体的4个早熟相关性状变异系数为8.70%~25.46%、14.77%~37.67%、19.93%~38.97%和22.37%~46.81%,且4个早熟相关性状在F_(2)代群体的分离频率分布均包含多种正态分布的混合分布。MX2-ADI-ADI为第一雌花节位和第一坐果节位的最优遗传模型,受2对加性—显性—上位性主基因+加性—显性—上位性多基因控制;第一雌花节位在BC_(1)P_(1)、BC_(1)P_(2)和F_(2)代群体的主基因遗传率(h^(2)_(mg))分别为4.63%、84.69%和79.99%,多基因遗传率(h^(2)_(pg))为74.60%、0和0;第一坐果节位在BC_(1)P_(1)、BC_(1)P_(2)和F_(2)代群体的h^(2)_(mg)分别为2.38%、82.86%和76.45%,h^(2)_(pg)为57.04%、0和0。2MG-ADI为始花期的最优遗传模型,受2对加性—显性—上位性主基因控制,在BC_(1)P_(1)、BC_(1)P_(2)和F_(2)代群体的h^(2)_(mg)分别为72.02%、79.05%和86.53%。2MG-AD为有棱丝瓜始收期最优遗传模型,属于2对主基因控制的加性—显性遗传模型,在BC_(1)P_(1)、BC_(1)P_(2)和F_(2)代群体的h^(2)_(mg)分别为62.33%、84.79%和85.07%。【结论】有棱丝瓜的第一雌花节位、始花期、第一坐果节位和始收期均表现为数量性状的特点,受多基因的控制,其中第一雌花节位和第一坐果节位受2对主加性—显性—上位性主基因+加性—显性—上位性多基因控制,始花期受2对加性—显性—上位性主基因控制,始收期受2对加性—显性主基因控制。

运用重复力模型估计天目多胎羊繁殖性状的遗传参数

本研究旨在通过探究绵羊新品种——天目多胎羊胎产羔数与胎平均初生重、胎产羔重、胎产活羔数的遗传关系,进一步了解其繁殖性能,为新品种培育提供理论依据。以浙江赛诺生态农业有限公司养殖的天目多胎羊为研究对象,收集胎产羔数、胎平均初生重、胎产羔重、胎产活羔数繁殖性状数据各5543条,运用SAS 9.2软件GLM程序对影响天目多胎羊繁殖性状的固定效应进行分析;运用DMU软件中AI-REML算法结合单/多性状重复力模型对4个繁殖性状进行遗传参数估计。结果表明,胎产羔数、胎平均初生重、胎产羔重和胎产活羔数的遗传力分别为0.007、0.014、0.006、0.012,均表现为低遗传力;繁殖性状间的遗传相关系数范围为-0.962~0.745,其中胎产羔数和胎产活羔数与胎平均初生重均呈较强负相关(-0.962和-0.605),其余性状间均呈现正相关。可见,上述天目多胎羊繁殖性状均为低遗传力性状,提高产羔数引起的低初生重可通过饲养管理进行弥补,这有益于新品种的选育。

澳洲白羊生长和繁殖性状的遗传评估

该研究旨在评估澳洲白羊的生长和繁殖性状的遗传特性,为科学选育、良种扩繁和提高优良特性提供理论基础。在对生长性状(初生重、 90天体重、 180天体重、 240天体重、 0~90 d日增重、 90~240 d日增重)和繁殖性状(头胎产羔数、经产羔羊数、头胎窝均重、经产窝均重、头胎窝总重、经产窝总重)进行遗传评估时,使用R包AEFchida建立动物线性混合模型,进行方差组分、遗传参数、遗传相关性和育种值的估计;对于初生重,根据不同母体效应,运用R(v4-1-1)包AEFchida,比较了6种随机效应不同的动物线性混合模型。结果表明,考虑个体加性效应、母体环境效应和母体遗传效应的模型BW1为最优模型,计算初生重遗传力为(0.33±0.04)。繁殖性状在0.03~0.12为低遗传力,其中活羔数(头胎、经产)的遗传力在0.03~0.04,而生长性状在0.33~0.77之间为高遗传力,其中日增重(0~90日、 90~240日)的遗传力在0.46~0.67。产羔数与生长性状相关性较低(0~0.25),初生重与生长性状相关性适中(0.14~0.64),且表型相关性和遗传相关性基本一致。生长性状的育种均值随着年份的增加,整体呈上升趋势;繁殖性状的育种均值则变化幅度较小,选育效果不明显。可见,澳洲白羊繁殖性状和生长性状遗传特性相差较大,应采用不同的选育方式来进一步优化澳洲白羊的生产性能和遗传特性。

Mapping novel genetic loci associated with female liver weight variations using Collaborative Cross mice

Background: Liver weight is a complex trait, controlled by polygenic factors and differs within populations. Dissecting the genetic architecture underlying these variations will facilitate the search for key role candidate genes involved directly in the hepatomegaly process and indirectly involved in related diseases etiology.Methods: Liver weight of 506 mice generated from 39 different Collaborative Cross(CC) lines with both sexes at age 20 weeks old was determined using an electronic balance. Genomic DNA of the CC lines was genotyped with high-density single nucleotide polymorphic markers.Results: Statistical analysis revealed a significant(P < 0.05) variation of liver weight between the CC lines, with broad sense heritability(H^2) of 0.32 and genetic coefficient of variation(CV_G) of 0.28. Subsequently, quantitative trait locus(QTL) mapping was performed, and results showed a significant QTL only for females on chromosome 8 at genomic interval 88.61-93.38 Mb(4.77 Mb). Three suggestive QTL were mapped at chromosomes 4, 12 and 13. The four QTL were designated as LWL1-LWL4 referring to liver weight loci 1-4 on chromosomes 8, 4, 12 and 13,respectively.Conclusion: To our knowledge, this report presents, for the first time, the utilization of the CC for mapping QTL associated with baseline liver weight in mice. Our findings demonstrate that liver weight is a complex trait controlled by multiple genetic factors that differ significantly between sexes.

甜荞产量性状综合评价及AMMI分析

为了评价全国区域试验甜荞品种(系)在山西不同生态区的性状表现、品种稳定性及适应性,本研究以2019—2020年全国甜荞区试的6个参试品种(系)为试验材料,在山西省榆次(E1)、忻州(E2)、大同(E3)3个生态区种植,对参试品种的产量、每公顷株数、株高、主茎分枝、主茎节数、单株粒数、单株粒重、千粒重、生育期等9个主要性状进行考察;采用加性主效应乘积交互作用(AMMI)模型分析和双标图对3个试点进行产量稳定性、适应性及试点鉴别力分析,并对产量相关性状进行变异性分析和遗传相关分析。结果表明,在6个参试品种(系)中,丰产性、稳定性和适应性较好的品种为白荞3号和平荞2号。3个区试点均适宜甜荞品种鉴选,但相比榆次和大同,忻州试点的鉴别力最大。不同试验年份3个试点甜荞品种的产量及相关性状变异较大,6个品种(系)9个性状的变异范围在8.71%~35.80%,平均变异系数达19.34%。其中,变异系数较大的为主茎分枝,然后依次是每公顷株数、单株粒数和单株粒重,株高和生育期变异系数较小。对产量相关性状的遗传相关性分析也表明,株高与主茎分枝、单株粒数与单株粒重、单株粒数与产量以及单株粒重与产量均呈正向遗传的相关关系,而单株粒数与千粒重呈负向遗传的相关关系。遗传力分析结果表明,株高、主茎节数的遗传力较大。因此,甜荞生产中要协调好产量各性状之间的关系,在资源创新和新品系筛选方面应注重秆高、单株粒数多、单株粒重大的品系鉴选,加强相关基因的挖掘。本研究结果为山西甜荞品种的鉴定和选育提供了理论依据。

菲律宾蛤仔早期生长性状的遗传参数评估及生长模型构建

为探究菲律宾蛤仔(Ruditapes philippinarum)早期生长性状的遗传规律,本文选取莱州海域性腺成熟的菲律宾蛤仔作为亲本,采用人工授精的方法建立了40个全同胞家系。家系培育期间,采集7~116日龄中6个不同时期的幼虫和稚贝,评估了这6个时间点壳长和壳高的遗传参数,并构建了壳长和壳高的生长模型。研究表明,壳长的狭义遗传力范围为0.684~0.775,壳高的狭义遗传力范围为0.702~0.801,这体现出蛤仔具有较高的狭义遗传力。各日龄阶段壳长和壳高的遗传相关系数均大于0.90,属于高度遗传相关。幼虫期和稚贝期的表型相关系数差异较大,分别为0.677和0.952。不同日龄蛤仔的壳长和壳高之间的遗传相关和表型相关均为极显著正相关,其中第75日龄的稚贝遗传相关系数和表型相关系数最大,分别为0.997和0.977。此外,根据壳长和壳高的拟合程度建立了4个生长模型,4个生长模型的拟合度均大于0.90,其中von Bertanffy模型的拟合度最高,壳长和壳高的拟合度分别达到0.942和0.941。综上所述,菲律宾蛤仔的壳长和壳高这两生长性状均具有较大的遗传改良潜力,对这两个生长性状的直接选择可以获得较好的选育效果。

陆海渐渗系F_(2)群体纤维品质性状数量遗传分析

本试验以陆海染色体片段渐渗系C14为父本、冀棉262为母本构建F_(2)分离群体,并对群体的纤维品质性状进行数量遗传分析,利用主基因-多基因遗传分析模型对F_(2)世代上半部平均长度、断裂比强度、马克隆值、整齐度指数和伸长率进行遗传分析,以确定各性状的最适遗传模型并掌握其遗传规律,为田间选育遗传稳定的棉花纤维品质性状提供参考。结果表明,5个纤维品质性状中,上半部平均长度、马克隆值、整齐度指数和伸长率符合遗传模型,受主基因控制,而断裂比强度不存在主基因,受微效多基因控制。上半部平均长度符合B-1模型,受2对主基因控制,为加性-显性-上位性混合遗传模型,主基因遗传率为62.56%;马克隆值和伸长率均符合A-1模型,为受1对主基因控制的加性-显性混合遗传模型,主基因遗传率分别为9.96%和27.17%;整齐度指数符合B-6模型,为受2对主基因控制的加性-显性等效混合遗传模型,主基因遗传率为43.64%。上半部平均长度主基因遗传率最高,说明该性状在后代遗传中受环境影响较小,遗传较稳定,可以在低世代直接进行选择;而马克隆值主基因遗传率低于10%,说明该性状在后代中遗传不稳定,受环境影响较大,需要在高世代进行选择。

拟南芥株高性状全基因组上位互作网络构建

【目的】以拟南芥株高性状及上位性网络模型为研究基础,通过构建不同层次的互作调控网络,探究、揭示植物生长发育过程中多基因在复杂网络中相互作用的过程或规律。【方法】以拟南芥的84个重组自交系为实验材料,共获得417 495个单核苷酸位点(SNPs)及8个时间点的株高生长数据,基于功能作图方法对测序得到的不同基因型与株高性状进行关联分析后,通过结合系统生物学中模块化的概念及统计学中降维的思想,在常微分方程组的基础上构建稀疏、有向、可量化的模块以及基因之间的上位性互作网络,同时使用拟南芥在线数据库对不同功能模块中的候选基因进行富集分析与功能注释。【结果】研究结果表明,在宏观遗传调控网络中,大部分功能模块在拟南芥发育过程中起正向调控的作用,并且随时间的变化会改变互作的策略。在微观调控网络中,与拟南芥的结构发育密切相关的基因AT4G29140在网络中对其他位点都是上调作用,同时只受到与衰老有关基因的下调作用。而与维持细胞的稳态有关的基因AT4G36910不主动发挥调控作用,其功能表达非常依赖于其他基因的控制。基因AT4G22680可能通过调节RP1的表达发挥其调控的功能。【结论】本研究从关联分析与复杂网络的角度上,探究了影响拟南芥生长的上位性机制,为植物遗传结构的解析提供了新的方法和思路。

小麦主要农艺性状的基因效应分析

选用4个亲本(驻麦328、中麦578、驻麦305、周麦36)组配的2个组合(驻麦328×中麦578、驻麦305×周麦36号)群体为材料,用尺度测验法分析了6个性状(株高、穗长、单株分蘖数、单株穗数、千粒重、单株产量)的遗传模型并估算了各类基因效应值,比较分析了6个性状各类基因效应的异同及其相对重要性。结果表明:组合Ⅰ(驻麦328×中麦578),6个性状中仅有千粒重符合加性—显性模型;组合Ⅱ(驻麦305×周麦36),6个性状中株高和穗长符合加性—显性模型,其他性状均符合加性—显性—上位性模型。加性效应对驻麦328和驻麦305各性状的遗传有重要作用,部分性状存在显著的显性效应,不同类型上位性效应对各性状有不同程度的影响。

小麦蛋白质含量和沉淀值的遗传研究

应用胚乳性状的遗传模型,以6×6双列设计研究了小麦蛋白质含量及沉淀值的遗传。结果表明:小麦F_2代籽粒的蛋白质含量的遗传符合加性-显性模型;沉淀值的遗传符合加性-显性-上位性模型。控制蛋白质含量和沉淀值的基因作用方式为超显性,显性作用大于加性作用。F_2群体中显性等位基因的频率与隐性等位基因的频率不等。本文还比较了二倍体模型与三倍体模型的异同,讨论了小麦蛋白质含量及沉淀值的改良与选择问题。

大麦蛋白质含量的遗传研究

由六个亲本组成的双列杂交试验,采用三倍体遗传模型分析蛋白质含量的遗传,经二年试验,结果表明:1.大麦蛋白质的 Wr/Vr 分析指出,F_2世代籽粒蛋白质含量符合加性-显性模型,不存在上位性效应。蛋白质含量高为隐性,Hiproly 具有最多的隐性基因;蛋白质含量低为显性,Ris(?)1508具有最多的显性基因。2.控制蛋白质含量的基因作用方式为超显性,且显性作用大于加性作用。但如用二倍体遗传模型分析则为部分显性,((?)/(?))^(1/2)=0.7503,因此,二种遗传模型的分析结果有较大的差异。3.根据大麦蛋白质含量的这种遗传特点,在以高蛋白质含量为育种目标时,可在杂种较高世代选择。反之,则可在较低世代选择。

胚乳性状的遗传模型及其分析方法

提出分析谷类作物胚乳数量性状世代平均数的遗传模型.该模型把控制胚乳性状的总遗传效应G分解为胚乳直接效应G.、细胞质效应C和母体植株效应G_(mo)而G_o又可分解为直接加性(A)和直接显性(D)遗传分量,G_m则可分解为母体加性(A_m)和母体显性(D_m)遗传分量.用MINQUE(0/l)法可以无偏地估算该模型中的直接遗传方差分量σ_A^2和σ_D^2细胞质遗传方差σ_c^2及母体植株的遗传方差分量σ_(Am)~2和σ_(Dm)~2,也可估算胚乳基因与母体植株基因的遗传协方差分量σ_(A.Am)和σ_(D.Dm).成对性状的遗传协方差分量同样可用MINQUE(0/1)法估算.该模型中的随机遗传效应则可用MINQUE(0/1)法作调整无偏预测.由于遗传变异是从若干组合的不同世代间估计,因而有关胚乳数量性状的测定可以整个世代的籽粒为样本.

多环境下水稻品质性状的遗传分析

稻米品质性状的遗传分析表明 :三套遗传控制体系对各品质性状具有不同的遗传效应。胚乳核基因主要以加性方式作用于直链淀粉含量、碱消值和粒长 ,以显性方式作用于胶稠度和蛋白质含量 ,粒重的直接加性效应和直接显性效应几乎同等重要 ;而母体植株核基因主要以显性方式作用于直链淀粉含量、胶稠度、碱消值、粒长、粒宽和粒重 ,长宽比的母体加性效应与母体显性效应差异不大。基因型×环境互作对稻米品质性状的影响一般为母体效应×环境互作和细胞质×环境互作 ,但胶稠度、蛋白质含量和粒重三性状还存在直接加性×环境的互作。不同品质性状的遗传率大小、来源均有一定差异 ,直链淀粉含量、碱消值和粒重以直接遗传率为主 ,而胶稠度、蛋白质含量和长宽比以及粒重的互作遗传率主要表现为母体互作遗传率 ,胶稠度主要表现为直接互作遗传率。稻米品质性状的杂种优势包括胚乳直接杂种优势 (简称胚乳杂种优势 )和母体杂种优势。直链淀粉含量、胶稠度、碱消值和粒重既具有胚乳杂种优势 ,又具有母体杂种优势 ;蛋白质含量仅存在胚乳杂种优势 ,而粒长、粒重和长宽比只有母体杂种优势。此外 ,环境对直链淀粉含量、胶稠度和长宽比的杂种优势有较大的影响。

不结球白菜抽薹开花性状的主基因+多基因遗传分析

为了研究不结球白菜抽薹开花性状的遗传规律,并对其耐抽薹品种进行鉴定筛选,以不结球白菜易抽薹纯系M10-1和耐抽薹纯系M10-2杂交获得的6世代(P1、P2、F1、B1、B2和F2)群体为材料,利用植物数量性状主基因+多基因多世代联合分析的方法对不结球白菜抽薹性状(现蕾期)和开花性状(开花期)进行遗传分析。结果表明,控制抽薹性状的为2对加性-显性-上位性主基因+加性-显性多基因,并存在明显的加性、显性和上位性效应。其中,2对主基因的加性效应值均为正,显性效应值hb大于ha,且以第2对主基因的正向显性效应为主;抽薹性状存在较大的主基因加性×加性和显性×显性互作效应,以呈负向的多基因的加性效应为主。B1、B2和F2的主基因遗传率分别为83.83%、87.82%和88.31%,多基因遗传率均为0,主基因+多基因遗传率平均为86.65%,环境变异占表型变异平均为13.35%,说明抽薹性状主要受主基因控制,在育种上可以应用抽薹性状(现蕾期)作为不结球白菜耐抽薹性的鉴定标准,并可在早期世代对其耐抽薹性进行选择,且要注意一定的环境因素。开花性状与抽薹性状遗传相似,均受到2对主基因控制,但主基因+多基因遗传率平均为9.57%,而环境变异平均为90.43%,对开花的影响显著,说明开花性状与环境的互作效应非常明显,不适宜作为耐抽薹性的鉴定指标。利用本研究获得的抽薹性状作为不结球白菜耐抽薹性的鉴定指标,并应用于育种实践,对选育不结球白菜耐抽薹新品种,提高产量具有重要意义。

玉米籽粒性状的遗传模型研究

用１０个遗传上和籽粒形态性状上具有差异的玉米自交系，依多种可能的交配方法获得亲本Ｐ１、Ｐ２、Ｆ１（Ｐ１× Ｐ２）、Ｆ２、Ｂ１（Ｆ１×Ｐ１）、Ｂ２（Ｆ１× Ｐ２）及其相应反交ＲＦ１、ＲＦ２、ＲＢ１、ＲＢ２共１０个种子世代。种植２年。依广义遗传模型建立包括种子胚乳加性、胚乳显性、母体加性、母体显性和细胞质效应的遗传模型，运用种子数量性状的精细鉴别法［１］和混合模型分析法［２，３］，对粒长、粒宽、粒长宽比、粒厚及百粒重作了性状表达遗传机制的鉴别与探讨。单个组合的遗传模型精细测验表明，５个籽粒性状的遗传主要受母体显性和胚乳基因型（包括加性和灵性）的控制，一个组合的粒宽、粒厚和百粒重上还检测到细胞质效应。对２５对 Ｆ１正反交组合世代均值依ＭＩＮＱＵＥ法分析的结果表明，５个籽粒性状的遗传方差中，母体遗传方差占６０％以上，胚乳基因型方差低于４０％，粒长和百粒重还有细胞质效应，约占１０％～３０％。可见，籽粒性状的遗传特点是受多套遗传系统控制，其中以母体基因型的作用最大。