植物抗病遗传育种中的QTL定位和克隆(综述)

对植物抗病遗传育种中QTL定位与克隆研究进行综述。主要阐述了数量抗性的遗传学基础、作物抗病性QTL的定位作图、QTL作图的可靠性及应对措施、QTLs候选基因的证实和定位克隆等,并对植物抗病遗传育种未来的研究方向予以讨论。     

Genomic regions underlying agronomic traits in linseed (Linum usitatissimum L.) as revealed by association mapping OA简

The extreme climate of the Canadian Prairies poses a major challenge to improve yield. Although it is possible to breed for yield per se, focusing on yield‐related traits could be advantageous because of their simpler genetic architecture. The Canadian flax core collection of 390 accessions was genotyped with 464 simple sequence repeat markers, and phenotypic data for nine agronomic traits including yield, bolls per area, 1,000 seed weight, seeds per boll, start of flowering, end of flowering, plant height, plant branching, and lodging collected from up to eight environments was used for association mapping. Based on a mixed model (principal component analysis (PCA) + kinship matrix (K)), 12 significant marker‐trait associations for six agronomic traits were identified. Most of the associations were stable across environments as revealed by multivariate analyses. Statistical simulation for five markers associated with 1000 seed weight indicated that the favorable alleles have additive effects. None of the modern cultivars carried the five favorable alleles and the maximum number of four observed in any accessions was mostly in breeding lines. Our results confirmed the complex genetic architecture of yield‐related traits and the inherent difficulties associated with their identification while illustrating the potential for improvement through marker‐assisted selection.     

Optimizing purebred selection for crossbred performance using QTL with different degrees of dominance

A method was developed to optimize simultaneous selection for a quantitative trait with a known QTL within a male and a female line to maximize crossbred performance from a two-way cross. Strategies to maximize cumulative discounted response in crossbred performance over ten generations were derived by optimizing weights in an index of a QTL and phenotype. Strategies were compared to selection on purebred phenotype. Extra responses were limited for QTL with additive and partial dominance effects, but substantial for QTL with over-dominance, for which optimal QTL selection resulted in differential selection in male and female lines to increase the frequency of heterozygotes and polygenic responses. For over-dominant QTL, maximization of crossbred performance one generation at a time resulted in similar responses as optimization across all generations and simultaneous optimal selection in a male and female line resulted in greater response than optimal selection within a single line without crossbreeding. Results show that strategic use of information on over-dominant QTL can enhance crossbred performance without crossbred testing.     

A method to optimize selection on multiple identified quantitative trait loci

A mathematical approach was developed to model and optimize selection on multiple known quantitative trait loci (QTL) and polygenic estimated breeding values in order to maximize a weighted sum of responses to selection over multiple generations. The model allows for linkage between QTL with multiple alleles and arbitrary genetic effects, including dominance, epistasis, and gametic imprinting. Gametic phase disequilibrium between the QTL and between the QTL and polygenes is modeled but polygenic variance is assumed constant. Breeding programs with discrete generations, differential selection of males and females and random mating of selected parents are modeled. Polygenic EBV obtained from best linear unbiased prediction models can be accommodated. The problem was formulated as a multiple-stage optimal control problem and an iterative approach was developed for its solution. The method can be used to develop and evaluate optimal strategies for selection on multiple QTL for a wide range of situations and genetic models.     

The distribution of the effects of genes affecting quantitative traits in livestock

Meta-analysis of information from quantitative trait loci (QTL) mapping experiments was used to derive distributions of the effects of genes affecting quantitative traits. The two limitations of such information, that QTL effects as reported include experimental error, and that mapping experiments can only detect QTL above a certain size, were accounted for. Data from pig and dairy mapping experiments were used. Gamma distributions of QTL effects were fitted with maximum likelihood. The derived distributions were moderately leptokurtic, consistent with many genes of small effect and few of large effect. Seventeen percent and 35% of the leading QTL explained 90% of the genetic variance for the dairy and pig distributions respectively. The number of segregating genes affecting a quantitative trait in dairy populations was predicted assuming genes affecting a quantitative trait were neutral with respect to fitness. Between 50 and 100 genes were predicted, depending on the effective population size assumed. As data for the analysis included no QTL of small effect, the ability to estimate the number of QTL of small effect must inevitably be weak. It may be that there are more QTL of small effect than predicted by our gamma distributions. Nevertheless, the distributions have important implications for QTL mapping experiments and Marker Assisted Selection (MAS). Powerful mapping experiments, able to detect QTL of 0.1σ_p, will be required to detect enough QTL to explain 90% the genetic variance for a quantitative trait.     

Genetic analysis of seed size, yield and days to flowering in a chickpea recombinant inbred line population derived from a Kabuli × Desi cross

Quantitative traits, seed size, yield and days to flowering were studied in a chickpea intraspecific recombinant inbred line (RIL) population (F_6:7) derived from a Kabuli × Desi cross. The population was evaluated in two locations over 2 years. Days to flowering was also evaluated in the greenhouse under short-day conditions. Seed size was the most heritable trait (0.90), followed by days to flowering (0.36) and yield (0.14). Negative and significant correlation was found between yield and seed size in the second year where environmental homogeneity was tested by analysing the controls included in each assay. During the first year, the environment was not considered homogeneous for yield in either location. Quantitative trait loci (QTLs) for the three characters were detected in linkage group (LG) 4. In relation to seed size, two QTLs were located in LG4 (QTL_SW1) and LG8 (QTL_SW2). QTL_SW1 accounted 20.3% of the total phenotypic variation and QTL_SW2 explained 10.1%. A QTL for yield (QTL_YD) was located in LG4 explaining around 13% of variation. QTL_YD might be pleiotropic with QTL_SW1. For days to flowering, a QTL (QTL_DF1) was located in LG4 for all environments analysed explaining around 20% of variation. QTL_DF1 was closely linked to QTL_SW1 and QTL_YD in LG4.     

Moving from QTL experimental results to the utilization of QTL in breeding programmes

Results from quantitative trait loci studies cannot be readily implemented into breeding schemes through marker assisted selection because of uncertainty about whether the quantitative trait loci identified are real and whether the identified quantitative trait loci are segregating in the breeding population. The present paper outlines and discusses strategies to reduce uncertainty in the results from quantitative trait loci studies. One strategy to confirm results from quantitative trait loci studies is to combine P -values from many quantitative trait loci experiments, while another is to establish a confirmation study. The power of a confirmation study must be high to ensure that the postulated quantitative trait loci can be verified. In the calculation of the experimental power, there are many issues that have to be addressed: size of the quantitative trait loci to be detected, significance level required, experimental design and expected heterozygosity for the design. To ensure marker assisted selection can be quickly implemented once quantitative trait loci are confirmed, DNA samples should be retained from daughters, and the sires and dams of elite sires.     

Progress in the Study of Molecular Genetic Improvements of Poplar in China

The poplar is one of the most economically important and intensively studied tree species owing to its wide application in the timber industry and as a model material for the study of woody plants. The natural resource of poplars in China is replete. Over the past 10 years, the application of molecular biological techniques to genetic improvements in poplar species has been widely studied in China. Recent advances in molecular genetic improvements of poplar, including cDNA library construction, gene cloning and identification, genetic engineering, gene expression, genetic linkage map construction, mapping of quantitative trait loci （QTL） and molecular-assisted selection, are reviewed in the present paper. In addition, the application of modern biotechnology to molecular improvements in the genetic traits of the poplar and some unsolved problems are discussed.     

胚乳性状数量基因的定位方法

将三倍体胚乳性状的数量遗传模型和二倍体性状数量基因（QTL）图构建方法相结合,导出双侧标记基因型下有关胚乳性状QTL的遗传组成、平均数和遗传方差分量,据之提出以某一区间双侧标记基因型胚乳性状的平均值为依变数,以该区间内任一点假定存在的QTL的加性效应d、显性效应h1和／或h2的系数为自变数,进行有重复观察值的多元线性回归分析,根据多元线性回归的显著性测验该点是否存在QTL,并估计出QTL的遗传效应。给定区间内任一点,皆可以此进行分析,从而可在整条染色体上作图,并以之确定QTL的数目和最可能位置,同时,在检测某一区间时,利用多元线性回归方法将该区间外可能存在的QTL的干扰进行统计控制,以提高QTL检测的精度。此外,还讨论了如何将之推广应用于其他类型的DNA不对应资料以及具复杂遗传模型的胚乳性状资料。     

Epistasis plays an important role as genetic basis of heterosis in rice

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An integrative approach for the identification of quantitative trait loci

The genetic dissection of complex traits is one of the most difficult and most important challenges facing science today. We discuss here an integrative approach to quantitative trait loci (QTL) mapping in mice. This approach makes use of the wealth of genetic tools available in mice, as well as the recent advances in genome sequence data already available for a number of inbred mouse strains. We have developed mapping strategies that allow a stepwise narrowing of a QTL mapping interval, prioritizing candidate genes for further analysis with the potential of identifying the most probable candidate gene for the given trait. This approach integrates traditional mapping tools, fine mapping tools, sequence-based analysis, bioinformatics and gene expression.     

Identification of quantitative trait loci affecting resistance to gastrointestinal parasites in a double backcross population of Red Maasai and Dorper sheep

A genome‐wide scan for quantitative trait loci (QTL) affecting gastrointestinal nematode resistance in sheep was completed using a double backcross population derived from Red Maasai and Dorper ewes bred to F₁ rams. This design provided an opportunity to map potentially unique genetic variation associated with a parasite‐tolerant breed like Red Maasai, a breed developed to survive East African grazing conditions. Parasite indicator phenotypes (blood packed cell volume – PCV and faecal egg count – FEC) were collected on a weekly basis from 1064 lambs during a single 3‐month post‐weaning grazing challenge on infected pastures. The averages of last measurements for FEC (AVFEC) and PCV (AVPCV), along with decline in PCV from challenge start to end (PCVD), were used to select lambs (N = 371) for genotyping that represented the tails (10% threshold) of the phenotypic distributions. Marker genotypes for 172 microsatellite loci covering 25 of 26 autosomes (1560.7 cm ) were scored and corrected by Genoprob prior to qxpak analysis that included Box–Cox transformed AVFEC and arcsine transformed PCV statistics. Significant QTL for AVFEC and AVPCV were detected on four chromosomes, and this included a novel AVFEC QTL on chromosome 6 that would have remained undetected without Box–Cox transformation methods. The most significant P‐values for AVFEC, AVPCV and PCVD overlapped the same marker interval on chromosome 22, suggesting the potential for a single causative mutation, which remains unknown. In all cases, the favourable QTL allele was always contributed from Red Maasai, providing support for the idea that future marker‐assisted selection for genetic improvement of production in East Africa will rely on markers in linkage disequilibrium with these QTL.     

Genomic regions underlying agronomic traits in linseed （Linum usitatissimum L.） as revealed by association mapping

The extreme climate of the Canadian Prairies poses a major chal enge to improve yield. Although it is possible to breed for yield per se, focusing on yield-related traits could be advantageous because of their simpler genetic architecture. The Canadian flax core col ection of 390 accessions was genotyped with 464 simple sequence repeat markers, and phenotypic data for nine agronomic traits including yield, bol s per area, 1,000 seed weight, seeds per bol , start of flowering, end of flowering, plant height, plant branching, and lodging col ected from up to eight environments was used for association mapping. Based on a mixed model （principal component analysis （PCA） t kinship matrix （K））, 12 significant marker-trait associations for six agronomic traits were identi-fied. Most of the associations were stable across environments as revealed by multivariate analyses. Statistical simulation for five markers associated with 1000 seed weight indicated that the favorable al eles have additive effects. None of the modern cultivars carried the five favorable al eles and the maximum number of four observed in any accessions was mostly in＆amp;nbsp;breeding lines. Our results confirmed the complex genetic architecture of yield-related traits and the inherent difficulties associated with their identification while il ustrating the potential for improvement through marker-assisted selection.     

Power analysis of QTL detection in half-sib families using selective DNA pooling

Individual loci of economic importance (QTL) can be detected by comparing the inheritance of a trait and the inheritance of loci with alleles readily identifiable by laboratory methods (genetic markers). Data on allele segregation at the individual level are costly and alternatives have been proposed that make use of allele frequencies among progeny, rather than individual genotypes. Among the factors that may affect the power of the set up, the most important are those intrinsic to the QTL: the additive effect of the QTL, and its dominance, and distance between markers and QTL. Other factors are relative to the choice of animals and markers, such as the frequency of the QTL and marker alleles among dams and sires. Data collection may affect the detection power through the size of half-sib families, selection rate within families, and the technical error incurred when estimating genetic frequencies. We present results for a sensitivity analysis for QTL detection using pools of DNA from selected half-sibs. Simulations showed that conclusive detection may be achieved with families of at least 500 half-sibs if sires are chosen on the criteria that most of their marker alleles are either both missing, or one is fixed, among dams.     

Assessing the complex architecture of polygenic traits in diverged yeast populations

Phenotypic variation arising from populations adapting to different niches has a complex underlying genetic architecture. A major challenge in modern biology is to identify the causative variants driving phenotypic variation. Recently, the baker's yeast, Saccharomyces cerevisiae has emerged as a powerful model for dissecting complex traits. However, past studies using a laboratory strain were unable to reveal the complete architecture of polygenic traits. Here, we present a linkage study using 576 recombinant strains obtained from crosses of isolates representative of the major lineages. The meiotic recombinational landscape appears largely conserved between populations; however, strain-specific hotspots were also detected. Quantitative measurements of growth in 23 distinct ecologically relevant environments show that our recombinant population recapitulates most of the standing phenotypic variation described in the species. Linkage analysis detected an average of 6.3 distinct QTLs for each condition tested in all crosses, explaining on average 39% of the phenotypic variation. The QTLs detected are not constrained to a small number of loci, and the majority are specific to a single cross-combination and to a specific environment. Moreover, crosses between strains of similar phenotypes generate greater variation in the offspring, suggesting the presence of many antagonistic alleles and epistatic interactions. We found that subtelomeric regions play a key role in defining individual quantitative variation, emphasizing the importance of the adaptive nature of these regions in natural populations. This set of recombinant strains is a powerful tool for investigating the complex architecture of polygenic traits.     

RiceQTLPro: an integrated database for quantitative trait loci marker mapping in rice plant

The National Agricultural Biotechnology Information Center (NABIC) in South Korea reconstructed a RiceQTLPro database for gene positional analysis and structure prediction of the chromosomes. This database is an integrated web-based system providing information about quantitative trait loci (QTL) markers in rice plant. The RiceQTLPro has the three main features namely, (1) QTL markers list, (2) searching of markers using keyword, and (3) searching of marker position on the rice chromosomes. This updated database provides 112 QTL markers information with 817 polymorphic markers on each of the 12 chromosomes in rice.

Availability

The database is available for free at http://nabic.rda.go.kr/gere/rice/geneticMap/     

Identification of quantitative trait loci for growth and carcass composition in cattle

A genomic screening to detect quantitative trait loci (QTL) affecting growth, carcass composition and meat quality traits was pursued. Two hundred nineteen microsatellite markers were genotyped on 176 of 620 (28%) progeny from a Brahman x Angus sire mated to mostly MARC III dams. Selective genotyping, based on retail product yield (%) and fat yield (%), was used to select individuals to be genotyped. Traits included in the study were birth weight (kg), hot carcass weight (kg), retail product yield, fat yield, marbling score (400 = slight00 and 500 = small00), USDA yield grade, and estimated kidney, heart and pelvic fat (%). The QTL were classified as significant when the expected number of false positives (ENFP) was less than 0.05 (F-statistic greater than 17.3), and suggestive when the ENFP was <1 (F-statistic between 10.2 and 17.3). A significant QTL (F = 19; ENFP = 0.02) was detected for marbling score at centimorgan (cM) 54 on chromosome 2. Suggestive QTL were detected for fat yield at 50 cM, for retail product yield at 53 cM, and for USDA yield grade at 63 cM on chromosome 1, for marbling score at 56 cM, for retail product yield at 70 cM, and for estimated kidney, heart and pelvic fat at 79 cM on chromosome 3, for marbling score at 44 cM, for hot carcass weight at 49 cM, and for estimated kidney, heart and pelvic fat at 62 cM on chromosome 16, and for fat yield at 35 cM on chromosome 17. Two suggestive QTL for birth weight were identified, one at 12 cM on chromosome 20 and the other at 56 cM on chromosome 21. An additional suggestive QTL was detected for retail product yield, for fat yield, and for USDA yield grade at 26 cM on chromosome 26. Results presented here represent the initial search for quantitative trait loci in this family. Validation of detected QTL in other populations will be necessary.     

Application of Genomics Tools to Animal Breeding

The main goal in animal breeding is to select individuals that have high breeding values for traits of interest as parents to produce the next generation and to do so as quickly as possible. To date, most programs rely on statistical analysis of large data bases with phenotypes on breeding populations by linear mixed model methodology to estimate breeding values on selection candidates. However, there is a long history of research on the use of genetic markers to identify quantitative trait loci and their use in marker-assisted selection but with limited implementation in practical breeding programs. The advent of high-density SNP genotyping, combined with novel statistical methods for the use of this data to estimate breeding values, has resulted in the recent extensive application of genomic or whole-genome selection in dairy cattle and research to implement genomic selection in other livestock species is underway. The high-density SNP data also provides opportunities to detect QTL and to encover the genetic architecture of quantitative traits, in terms of the distribution of the size of genetic effects that contribute to trait differences in a population. Results show that this genetic architecture differs between traits but that for most traits, over 50% of the genetic variation resides in genomic regions with small effects that are of the order of magnitude that is expected under a highly polygenic model of inheritance.     

数量性状基因座位及其在家禽中的定位

近年来随着现代分子生物学的发展 ,一些高效的分子遗传标记将各种畜禽的遗传图谱研究推向深入。为高密度、覆盖面广的连锁图谱的构建及QTL的定位奠定了基础。有关QTL的基本理论、QTL定位的步骤、QTL的检测方法以及家禽中定位的QTL已经展开了深入的研究 ,但目前QTL定位中存在诸多问题的问题