利用分子标记和数量性状基因型值构建作物核心种质库的研究

提出了一种基于分子标记数据及数量性状基因型值构建作物种质资源核心种质库的方法.采用包括基因型与环境互作的遗传模型及相应的混合线性模型统计分析方法,无偏预测各材料的基因型值,分别用基因型值和分子标记数据计算个体间的相似系数,加权得到最终的相似距离.采用不加权类平均法（UPGMA）进行系统聚类,用多次聚类随机取样法构建核心种质库.以水稻DH群体111个基因型8个农艺性状、175个分子标记位点的数据为实例,按四种抽样比率（25%,20%,15%,10%）构建了四个核心种质库,比较了核心种质库与整个群体的分子标记多样性及数量性状的遗传变异,评价了所用方法的有效性。     

Association analysis of historical bread wheat germplasm using additive genetic covariance of relatives and population structure

Linkage disequilibrium can be used for identifying associations between traits of interest and genetic markers. This study used mapped diversity array technology (DArT) markers to find associations with resistance to stem rust, leaf rust, yellow rust, and powdery mildew, plus grain yield in five historical wheat international multienvironment trials from the International Maize and Wheat Improvement Center (CIMMYT). Two linear mixed models were used to assess marker-trait associations incorporating information on population structure and covariance between relatives. An integrated map containing 813 DArT markers and 831 other markers was constructed. Several linkage disequilibrium clusters bearing multiple host plant resistance genes were found. Most of the associated markers were found in genomic regions where previous reports had found genes or quantitative trait loci (QTL) influencing the same traits, providing an independent validation of this approach. In addition, many new chromosome regions for disease resistance and grain yield were identified in the wheat genome. Phenotyping across up to 60 environments and years allowed modeling of genotype x environment interaction, thereby making possible the identification of markers contributing to both additive and additive x additive interaction effects of traits.     

Comparison of Statistical Tests for Association between Rare Variants and Binary Traits

Genome-wide association studies have found thousands of common genetic variants associated with a wide variety of diseases and other complex traits. However, a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some of the missing variation is due to the effects of rare variants. Nonetheless, the statistical analysis of rare variants is challenging. A commonly used method is to contrast, within the same region (gene), the frequency of minor alleles at rare variants between cases and controls. However, this strategy is most useful under the assumption that the tested variants have similar effects. We previously proposed a method that can accommodate heterogeneous effects in the analysis of quantitative traits. Here we extend this method to include binary traits that can accommodate covariates. We use simulations for a variety of causal and covariate impact scenarios to compare the performance of the proposed method to standard logistic regression, C-alpha, SKAT, and EREC. We found that i) logistic regression methods perform well when the heterogeneity of the effects is not extreme and ii) SKAT and EREC have good performance under all tested scenarios but they can be computationally intensive. Consequently, it would be more computationally desirable to use a two-step strategy by (i) selecting promising genes by faster methods and ii) analyzing selected genes using SKAT/EREC. To select promising genes one can use (1) regression methods when effect heterogeneity is assumed to be low and the covariates explain a non-negligible part of trait variability, (2) C-alpha when heterogeneity is assumed to be large and covariates explain a small fraction of trait's variability and (3) the proposed trend and heterogeneity test when the heterogeneity is assumed to be non-trivial and the covariates explain a large fraction of trait variability.     

Genetic Markers and Quantitative Genetic Variation in Medicago Truncatula (Leguminosae): A Comparative Analysis of Population Structure

Two populations of the selfing annual Medicago truncatula Gaertn. (Leguminoseae), each subdivided into three subpopulations, were studied for both metric traits (quantitative characters) and genetic markers (random amplified polymorphic DNA and one morphological, single-locus marker). Hierarchical analyses of variance components show that (1) populations are more differentiated for quantitative characters than for marker loci, (2) the contribution of both within and among subpopulations components of variance to overall genetic variance of these characters is reduced as compared to markers, and (3) at the population level, within population structure is slightly but not significantly larger for markers than for quantitative traits. Under the hypothesis that most markers are neutral, such comparisons may be used to make hypotheses about the strength and heterogeneity of natural selection in the face of genetic drift and gene flow. We thus suggest that in these populations, quantitative characters are under strong divergent selection among populations, and that gene flow is restricted among populations and subpopulations.     

Linkage analysis of quantitative traits in an interspecific cross of tomato (lycopersicon esculentum x lycopersicon pimpinellifolium) by means of genetic markers

Linkage relationships between loci affecting quantitative traits (QTL) and marker loci were examined in an interspecific cross between Lycopersicon esculentum and Lycopersicon pimpinellifolium. Parental lines differed for six morphological markers and for four electrophoretic markers. Almost 1700 F-2 plants were scored with respect to the genetic markers and also with respect to 18 quantitative traits. Major genes affecting the quantitative traits were not found, but out of 180 possible marker x trait combinations, 85 showed significant quantitative effects associated with the genetic markers. The average marker-associated main effect was on the order of 6% of the mean value of the trait. Most of the main effects were apparently due to linkage of QTL to the marker loci rather than to pleiotropy. Fourteen of the traits showed at least one highly significant effect of opposite sign to the overall difference between the parental lines, demonstrating the ability of this design to uncover cryptic genetic variation. Significant variance and skewness effects on the quantitative traits were found to be associated with the genetic markers, suggesting the possible presence of loci affecting the variance and shape of quantitative trait distribution in a population. Most marker-associated quantitative effects showed some degree of dominance, generally in the direction of the L. pimpinellifolium parent. When the significant marker-associated effects were examined in pairs, 12% showed significant interaction effects. The results of this study illustrate the potential usefulness of this type of analysis for the detailed genetic investigation of quantitative trait variation in suitably marked populations.     

An anchored AFLP- and retrotransposon-based map of diploid Avena.

A saturated genetic map of diploid oat was constructed based on a recombinant inbred (RI) population developed from a cross between Avena strigosa (Cereal Introduction, C.I. 3815) and A. wiestii (C.I. 1994). This 513-locus map includes 372 AFLP (amplified fragment length polymorphism) and 78 S-SAP (sequence-specific-amplification polymorphism) markers, 6 crown-rust resistance loci, 8 resistance-gene analogs (RGAs), one morphological marker, one RAPD (random amplified polymorphic DNA) marker, and is anchored by 45 grass-genome RFLP (restriction fragment length polymorphism) markers. This new A. strigosa x A. wiestii RI map is colinear with a diploid Avena map from an A. atlantica x A. hirtula F2 population. However, some linkage blocks were rearranged as compared to the RFLP map derived from the progenitor A. strigosa x A. wiestii F2 population. Mapping of Bare-1-like sequences via sequence-specific AFLP indicated that related retrotransposons had considerable heterogeneity and widespread distribution in the diploid Avena genome. Novel amplified fragments detected in the RI population suggested that some of these retrotransposon-like sequences are active in diploid Avena. Three markers closely linked to the Pca crown-rust resistance cluster were identified via AFLP-based bulk-segregant analysis. The derived STS (sequence-tagged-site) marker, Agx4, cosegregates with Pc85, the gene that provides resistance specificity to crown-rust isolate 202 at the end of the cluster. This framework map will be useful in gene cloning, genetic mapping of qualitative genes, and positioning QTL (quantitative trait loci) of agricultural importance.     

Genetic Diversity and the Survival of Populations

Abstract: In this comprehensive review, a range of factors is considered that may influence the significance of genetic diversity for the survival of a population. Genetic variation is essential for the adaptability of a population in which quantitatively inherited, fitness-related traits are crucial. Therefore, the relationship between genetic diversity and fitness should be studied in order to make predictions on the importance of genetic diversity for a specific population. The level of genetic diversity found in a population highly depends on the mating system, the evolutionary history of a species and the population history (the latter is usually unknown), and on the level of environmental heterogeneity. An accurate estimation of fitness remains complex, despite the availability of a range of direct and indirect fitness parameters. There is no general relationship between genetic diversity and various fitness components. However, if a lower level of heterozygosity represents an increased level of inbreeding, a reduction in fitness can be expected. Molecular markers can be used to study adaptability or fitness, provided that they represent a quantitative trait locus (QTL) or are themselves functional genes involved in these processes. Next to a genetic response of a population to environmental change, phenotypic plasticity in a genotype can affect fitness. The relative importance of plasticity to genetic diversity depends on the species and population under study and on the environmental conditions. The possibilities for application of current knowledge on genetic diversity and population survival for the management of natural populations are discussed.     

Spatial autocorrelation of allozyme and quantitative markers within a natural population of Centaurea jacea (Asteraceae)

This paper compares the fine‐scale genetic structure of quantitative traits and allozyme markers within a natural population of Centaurea jacea s.l. To that end, a spatial autocorrelation approach is developed based on pairwise correlation coefficients between individuals and using sib families. Statistical properties of the proposed statistics are investigated with numerical simulations. Our results show that most quantitative traits have a significant spatial structure for their genetic component. On average, allozyme markers and the genetic component of quantitative traits have similar patterns of spatial autocorrelation that are consistent with a neutral model of isolation by distance. We also show evidence that environmental heterogeneity generates a spatial structure for the environmental component of quantitative traits. Results are discussed in terms of mechanisms generating spatial structure and are compared with those obtained on a large geographical scale.     

Utility of RAPD markers in identifying genetic linkages to genes of economic interest in peach

The identification of molecular markers linked to economically important traits for use in crop improvement is very important in long-lived perennial species. Three-hundred-and-sixty RAPD primers were used with bulked segregant analysis to identify markers linked to loci of specific interest in peach [(Prunus persica) L. Batch] and peach x almond [(Prunus dulcis) Batch] crosses. The traits analyzed included flesh color, adhesion, and texture; pollen fertility; plant stature; and three isozyme loci. The Mendelian behavior of the RAPD loci was established, and RAPD markers were mapped relative to the loci controlling flesh color, adhesion, and texture, and the isozyme loci Mdh-1, 6Pgd-2 and Aat-1, as well as the existing RFLP genetic linkage map constructed previously using a peach x almond F₂ population. This technique has facilitated rapid identification of RAPD and RFLP markers that are linked to the traits under study. Loci controlling these traits mapped predominantly to linkage groups 2 and 3 of the peach genetic linkage map. Linkages to genes with both dominant and co-dominant alleles were identified, but linkages to dominant genes were more difficult to find. In several crosses, RAPD marker bands proved to be allelic. One co-dominant RAPD formed a heteroduplex band in heterozygous individuals and in mixtures of alternate homozygotes. The Mendelian behavior of the RAPD loci studied was established and the results suggest that RAPD markers will be useful for plant improvement in peach.     

Marker analysis of quantitative traits in maize by ISSR-PCR

The segregating maize population (GK26 x Mo17)F2 has been used for identification of ISSR markers able to reveal a significant difference between alleles by a quantitative index. Confidence ranges have been determined for variation in 17 quantitative traits. Variations in the traits under study correlate with the inheritance of 16 marker loci have been found. The nature of these correlations and the possibility of chromosomal mapping of genetic markers are discussed.     

Combining population genomics and quantitative genetics: finding the genes underlying ecologically important traits

A central challenge in evolutionary biology is to identify genes underlying ecologically important traits and describe the fitness consequences of naturally occurring variation at these loci. To address this goal, several novel approaches have been developed, including 'population genomics,' where a large number of molecular markers are scored in individuals from different environments with the goal of identifying markers showing unusual patterns of variation, potentially due to selection at linked sites. Such approaches are appealing because of (1) the increasing ease of generating large numbers of genetic markers, (2) the ability to scan the genome without measuring phenotypes and (3) the simplicity of sampling individuals without knowledge of their breeding history. Although such approaches are inherently applicable to non-model systems, to date these studies have been limited in their ability to uncover functionally relevant genes. By contrast, quantitative genetics has a rich history, and more recently, quantitative trait locus (QTL) mapping has had some success in identifying genes underlying ecologically relevant variation even in novel systems. QTL mapping, however, requires (1) genetic markers that specifically differentiate parental forms, (2) a focus on a particular measurable phenotype and (3) controlled breeding and maintenance of large numbers of progeny. Here we present current advances and suggest future directions that take advantage of population genomics and quantitative genetic approaches - in both model and non-model systems. Specifically, we discuss advantages and limitations of each method and argue that a combination of the two provides a powerful approach to uncovering the molecular mechanisms responsible for adaptation.     

Latitudinal divergence of common frog (Rana temporaria) life history traits by natural selection: evidence from a comparison of molecular and quantitative genetic data

The relative roles of natural selection and direct environmental induction, as well as of natural selection and genetic drift, in creating clinal latitudinal variation in quantitative traits have seldom been assessed in vertebrates. To address these issues, we compared molecular and quantitative genetic differentiation between six common frog (Rana temporaria) populations along an approximately 1600 km long latitudinal gradient across Scandinavia. The degree of population differentiation (QST approximately 0.81) in three heritable quantitative traits (age and size at metamorphosis, growth rate) exceeded that in eight (neutral) microsatellite loci (FST = 0.24). Isolation by distance was clear for both neutral markers and quantitative traits, but considerably stronger for one of the three quantitative traits than for neutral markers. QST estimates obtained using animals subjected to different rearing conditions (temperature and food treatments) revealed some environmental dependency in patterns of population divergence in quantitative traits, but in general, these effects were weak in comparison to overall patterns. Pairwise comparisons of FST and QST estimates across populations and treatments revealed that the degree of quantitative trait differentiation was not generally predictable from knowledge of that in molecular markers. In fact, both positive and negative correlations were observed depending on conditions where the quantitative genetic variability had been measured. All in all, the results suggest a very high degree of genetic subdivision both in neutral marker genes and genes coding quantitative traits across a relatively recently (< 9000 years) colonized environmental gradient. In particular, they give evidence for natural selection being the primary agent behind the observed latitudinal differentiation in quantitative traits.     

Environmental influence on the genetic correlations between life-history traits in Caenorhabditis elegans

Empirical evidence is mounting to suggesting that genetic correlations between life-history traits are environment specific. However, detailed knowledge about the loci underlying genetic correlations in different environments is scant. Here, we studied the influence of temperature (12 degrees C and 24 degrees C) on the genetic correlations between egg size, egg number and body mass in the nematode Caenorhabditis elegans. We used a quantitative trait loci (QTL) approach based on a genetic map with evenly spaced single nucleotide polymorphism markers in an N2 x CB4856 recombinant inbred panel. Significant genetic correlations between various traits were found at both temperatures. We detected pleiotropic or closely linked QTL, which supported the negative correlation between egg size and egg number at 12 degrees C, the positive correlation across temperatures for body mass, and the positive correlation between body mass and egg size at 12 degrees C. The results indicate that specific loci control the covariation in these life-history traits and the locus control is prone to environmental conditions.     

Analysis of genetic mapping in a waxy/dent maize RIL population using SSR and SNP markers

A maize genetic linkage map was generated using SSR and SNP markers in a F_7:8 recombinant inbred line (RIL) population derived from a cross of waxy corn (KW7) and dent corn (Mo17). A total of 465 markers, including 459 SSR and 6 SNP markers, were assigned to 10 linkage groups which spanned 2,656.5 cM with an average genetic distance between markers of 5.7 cM, and the number of loci per linkage group ranged from 39 to 55. The SSR (85.4%) and SNP (83.3%) markers showed Mendelian segregation ratios in the RIL population at a 5% significance threshold. In linkage analysis of six SNP loci associated with kernel starch synthesis genes (ae1, bt2, sh1, sh2, su1, and wx1), all six loci were successfully mapped and are closely linked with SSR markers in chromosomes 3 (sh2), 4 (su1 and bt2), 5 (ae1), and 9 (sh1 and wx1). The SSR markers linked with genes in starch synthesis may be utilized in marker assisted breeding programs. The resulting genetic map will be useful in dissection of quantitative traits and the identification of superior QTLs from the waxy hybrid corn. Additionally, these data support further genetic analysis and development of maize breeding programs.     

Genetic ancestry,population sub-structure,and cardiovascular disease-related traits among African-American participants in the CARDIA Study

African-American populations are genetically admixed. Studies performed among unrelated individuals from ethnically admixed populations may be both vulnerable to confounding by population stratification, but offer an opportunity for efficiently mapping complex traits through admixture linkage disequilibrium. By typing 42 ancestry-informative markers and estimating genetic ancestry, we assessed genetic admixture and heterogeneity among African-American participants in the Coronary Artery Risk Development in Young Adults (CARDIA) cohort. We also assessed associations between individual genetic ancestry and several quantitative and binary traits related to cardiovascular risk. We found evidence of population sub-structure and excess inter-marker linkage disequilibrium, consistent with recent admixture. The estimated group admixture proportions were 78.1% African and 22.9% European, but differed according to geographic region. In multiple regression models, African ancestry was significantly associated with decreased total cholesterol, decreased LDL-cholesterol, and decreased triglycerides, and also with increased risk of insulin resistance. These observed associations between African ancestry and several lipid traits are consistent with the general tendency of individuals of African descent to have healthier lipid profiles compared to European-Americans. There was no association between genetic ancestry and hypertension, BMI, waist circumference, CRP level, or coronary artery calcification. These results demonstrate the potential for confounding of genetic associations with some cardiovascular disease-related traits in large studies involving US African-Americans.     

Quantitative trait loci for floral morphology in Arabidopsis thaliana

A central question in biology is how genes control the expression of quantitative variation. We used statistical methods to estimate genetic variation in eight Arabidopsis thaliana floral characters (fresh flower mass, petal length, petal width, sepal length, sepal width, long stamen length, short stamen length, and pistil length) in a cosmopolitan sample of 15 ecotypes. In addition, we used genome-wide quantitative trait locus (QTL) mapping to evaluate the genetic basis of variation in these same traits in the Landsberg erecta x Columbia recombinant inbred line population. There was significant genetic variation for all traits in both the sample of naturally occurring ecotypes and in the Ler x Col recombinant inbred line population. In addition, broad-sense genetic correlations among the traits were positive and high. A composite interval mapping (CIM) analysis detected 18 significant QTL affecting at least one floral character. Eleven QTL were associated with several floral traits, supporting either pleiotropy or tight linkage as major determinants of flower morphological integration. We propose several candidate genes that may underlie these QTL on the basis of positional information and functional arguments. Genome-wide QTL mapping is a promising tool for the discovery of candidate genes controlling morphological development, the detection of novel phenotypic effects for known genes, and in generating a more complete understanding of the genetic basis of floral development.     

Verification of selective DNA pooling methodology through identification and estimation of the DGAT1 effect

The discovery of markers linked to genes that are responsible for traits of interest to the dairy industry might prove useful because they could aid in selection and breeding decisions. We have developed a selective DNA pooling methodology to allow us to efficiently screen the bovine genome in order to find genes responsible for production traits. Using markers on chromosome 14 as a test case, we identified a gene (DGAT1) previously known to affect three traits (fat yield, protein yield and total milk yield). Furthermore, we predicted similar effects to those previously shown for DGAT1 in a New Zealand Holstein-Friesian herd. Additionally, we showed a low error rate (1.6%) for the pooling procedure. Hence we are confident that we can apply this procedure to an entire genome scan in the search for quantitative trait loci (QTL).     

鲤饲料转化率性状的QTL 定位及遗传效应分析

数量性状(QTL)定位是实现分子标记辅助育种、基因选择和定位、培育新品种及加快性状遗传研究进展的重要手段。饲料转化率是鲤鱼的重要经济性状和遗传改良的主要目标, 而通过QTL 定位获得与饲料转化率性状紧密连锁的分子标记以及相关基因是遗传育种的重要工具。研究利用SNP、SSR、EST-SSR 等分子标记构建鲤鱼(Cyprinus carpio L.)遗传连锁图谱并对重要经济性状进行QTL 定位。选用174 个SSR 标记、41 个EST-SSR 标记、345 个SNP 标记对德国镜鲤F2 代群体68 个个体进行基因型检测, 用JoinMap4.0 软件包构建鲤鱼遗传连锁图谱。再用MapQTL5.0 的区间作图法(Interval mapping, IM)和多QTL 区间定位法(MQMMapping, MQM)对饲料转化率性状进行QTL 区间检测, 通过置换实验(1000 次重复)确定连锁群显著性水平阈值。结果显示, 在对饲料转化率性状的多QTL 区间定位中, 共检测到15 个QTLs 区间, 分布在9 个连锁群上, 解释表型变异范围为17.70%—52.20%, 解释表型变异最大的QTLs 区间在第48 连锁群上, 为52.20%。HLJE314-SNP0919(LG25)区间标记覆盖的图距最小, 为0.164 cM; 最大的是HLJ1439-HLJ1438(LG39)区间,覆盖图距为24.922 cM。其中区间HLJ1439-HLJ1438、HLJ922 -SNP0711 解释表型变异均超过50.00%, 可能是影响饲料转化率性状的主效QTLs 区间。与饲料转化率相关的15 个QTLs 的加性效应方向并不一致, 有3个区间具有负向加性效应, 平均为?0.027; 12 个正向加性效应, 平均值为0.06。研究检测出的与鲤鱼饲料转化率性状相关的QTL 位点可为鲤鱼分子标记辅助育种和更进一步的QTL 精细定位打下基础。       

Transmission/disequilibrium tests using multiple tightly linked markers

Transmission/disequilibrium tests have attracted much attention in genetic studies of complex traits because (a) their power to detect genes having small to moderate effects may be greater than that of other linkage methods and (b) they are robust against population stratification. Highly polymorphic markers have become available throughout the human genome, and many such markers can be studied within short physical distances. Studies using multiple tightly linked markers are more informative than those using single markers. However, such information has not been fully utilized by existing statistical methods, resulting in possibly substantial loss of information in the identification of genes underlying complex traits. In this article, we propose novel statistical methods to analyze multiple tightly linked markers. Simulation studies comparing our methods versus existing methods suggest that our methods are more powerful. Finally, we apply the proposed methods to study genetic linkage between the dopamine D2 receptor locus and alcoholism.     

The influence of space in genetic-environmental relationships when environmental heterogeneity and seed dispersal occur at similar scale

We tested the importance of microenvironmental topographic parameters as predictors of emmer wheat genetic variation using three classes of single-locus (or at most several-loci) genetic markers (allozymes, glutenins, and qualitative traits) and two classes of markers of polygenic inheritance (phenological and morphological traits). Canonical correspondence analysis (CCA) and redundancy analysis (RDA) detected a significant effect of spatially structured environmental variation on genetic differences between plants for allozymes, glutenins, and quantitative morphological and phenological traits. However, after removing a spatial component of variation in partial CCA and partial RDA, the relationship of the remaining environmental variation with these genetic markers could be explained by chance alone, allowing us to rule out microniche topographic specialization in emmer wheat. Topographic autocorrelation exhibited a certain degree of similarity with genetic marker autocorrelation, indicating similar scales of environmental heterogeneity and seed flow. The detected population genetic structure agrees with one expected under isolation by distance as a result of limited gene flow. A negative relationship of genetic similarity with the logarithm of distance between plants was detected for both molecular markers and quantitative traits, which differed in the strength but not the pattern of association.