Genome-wide association mapping of agronomic traits in relevant barley germplasm in Uruguay

The genetic basis of agronomic traits determining adaptation to specific production conditions is a key factor for the improvement of crops, including malting barley (Hordeum vulgare L.). The aim of this study was to determine the genome-wide genetic components associated with agronomic phenotypes of local and global significance in a population of 76 barley genotypes that have been introduced into Uruguay in different chronological periods. The phenotypic database was obtained from five field experiments, planted in 2 years and in two locations, where a total of 13 agronomic traits were determined. The population was genotyped with 1,033 single nucleotide polymorphisms. We found a total of 41 quantitative trait loci (QTL) in a combined analysis using all datasets and 79 QTL if we considered all the trait/experiment combinations analyzed. The highest concentration of QTL was detected on chromosomes 2H and 4H. Most QTL were detected for grain plumpness and weight. Two linkage disequilibrium (LD) blocks associated with a large number of traits were detected on 2HS. The largest LD block was composed of three haplotypes, possibly derived from three ancestors of different geographical origin. We also detected three genomic regions in different chromosomes (2H, 5H and 7H) in LD between them, associated with agronomic traits. This study provides a contribution to the understanding of the genetics of barley adaptation in the southern cone of South America. Our results showed that elite varieties have favorable alleles at different QTL, indicating that gains can be made through plant breeding.     

Genome-wide association mapping of agronomic traits in sugar beet

Recent results indicate that association mapping in populations from applied plant breeding is a powerful tool to detect QTL which are of direct relevance for breeding. The focus of this study was to unravel the genetic architecture of six agronomic traits in sugar beet. To this end, we employed an association mapping approach, based on a very large population of 924 elite sugar beet lines from applied plant breeding, fingerprinted with 677 single nucleotide polymorphism (SNP) markers covering the entire genome. We show that in this population linkage disequilibrium decays within a short genetic distance and is sufficient for the detection of QTL with a large effect size. To increase the QTL detection power and the mapping resolution a much higher number of SNPs is required. We found that for QTL detection, the mixed model including only the kinship matrix performed best, even in the presence of a considerable population structure. In genome-wide scans, main effect QTL and epistatic QTL were detected for all six traits. Our full two-dimensional epistasis scan revealed that for complex traits there appear to be epistatic master regulators, loci which are involved in a large number of epistatic interactions throughout the genome.     

Genome-wide association mapping and agronomic impact of cowpea root architecture

Key message

Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance.

Abstract

Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga (Striga gesnerioides) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.

     

Genome-wide association mapping of three important traits using bread wheat elite breeding populations

The exponential development of molecular markers enables a more effective study of the genetic architecture of traits of economic importance, like test weight in wheat (Triticum aestivum L.), for which a high value is desired by most end-users. The association mapping (AM) method now allows more precise exploration of the entire genome. AM requires populations with substantial genetic variability of the traits of interest. The breeding lines at the end of a selection cycle, characterized for numerous traits, represent a potentially useful population for AM studies. Using three elite line populations, selected by several breeders and genotyped with about 2,500 Diversity Arrays Technology markers, several associations were identified between these markers and test weight, grain yield and heading date. To minimize spurious associations, we compared the general linear model and mixed linear model (MLM), which adjust for population structure and kinship differently. The MLM model with the kinship matrix was the most efficient. Finally, elite lines from several breeding programs had sufficient genetic variability to allow for the mapping of several chromosomal regions involved in the variation of three important traits.     

Genome-wide association mapping of blood cell traits in mice

Genetic variations in blood cell parameters can impact clinical traits. We report here the mapping of blood cell traits in a panel of 100 inbred strains of mice of the Hybrid Mouse Diversity Panel (HMDP) using genome-wide association (GWA). We replicated a locus previously identified in using linkage analysis in several genetic crosses for mean corpuscular volume (MCV) and a number of other red blood cell traits on distal chromosome 7. Our peak for SNP association to MCV occurred in a linkage disequilibrium (LD) block spanning from 109.38 to 111.75 Mb that includes Hbb-b1, the likely causal gene. Altogether, we identified five loci controlling red blood cell traits (on chromosomes 1, 7, 11, 12, and 16), and four of these correspond to loci for red blood cell traits reported in a recent human GWA study. For white blood cells, including granulocytes, monocytes, and lymphocytes, a total of six significant loci were identified on chromosomes 1, 6, 8, 11, 12, and 15. An average of ten candidate genes were found at each locus and those were prioritized by examining functional variants in the HMDP such as missense and expression variants. These results provide intermediate phenotypes and candidate loci for genetic studies of atherosclerosis and cancer as well as inflammatory and immune disorders in mice.     

Genome-wide association studies of agronomic and quality traits in a set of German winter barley (Hordeum vulgare L.) cultivars using Diversity Arrays Technology (DArT)

A set of about 100 winter barley (Hordeum vulgare L.) cultivars, comprising diverse and economically important German barley elite germplasm released during the last six decades, was previously genotypically characterized by single nucleotide polymorphism (SNP) markers using the Illumina GoldenGate BeadArray Technology to detect associations with phenotypic data estimated in three-year field trials at 12 locations. In order to identify further associations and to obtain information on whether the marker type influences the outcome of association genetics studies, the set of winter barley cultivars was re-analyzed using Diversity Arrays Technology (DArT) markers. As with the analysis of the SNPs, only polymorphic markers present at an allele frequency >5 % were included to detect associations in a mixed linear model (MLM) approach using the TASSEL software (P?≤?0.001). The population structure and kinship matrix were estimated on 72 simple sequence repeats (SSRs) covering the whole barley genome. The respective average linkage disequilibrium (LD) analyzed with DArT markers was estimated at 5.73 cM. A total of 52 markers gave significant associations with at least one of the traits estimated which, therefore, may be suitable for marker-assisted breeding. In addition, by comparing the results to those generated using the Illumina GoldenGate BeadArray Technology, it turned out that a different number of associations for respective traits is detected, depending on the marker system. However, as only a few of the respective DArT and Illumina markers are present in a common map, no comprehensive comparison of the detected associations was feasible, but some were probably detected in the same chromosomal regions. Because of the identification of additional marker–trait associations, it may be recommended to use both marker techniques in genome-wide association studies.     

Genome-wide association study reveals the genetic architecture of 27 agronomic traits in tomato

Tomato (Solanum lycopersicum) is a highly valuable fruit crop, and yield is one of the most important agronomic traits. However, the genetic architecture underlying tomato yield-related traits has not been fully addressed. Based on ∼4.4 million single nucleotide polymorphisms obtained from 605 diverse accessions, we performed a comprehensive genome-wide association study for 27 agronomic traits in tomato. A total of 239 significant associations corresponding to 129 loci, harboring many previously reported and additional genes related to vegetative and reproductive development, were identified, and these loci explained an average of ∼8.8% of the phenotypic variance. A total of 51 loci associated with 25 traits have been under selection during tomato domestication and improvement. Furthermore, a candidate gene, Sl-ACTIVATED MALATE TRANSPORTER15, that encodes an aluminum-activated malate transporter was functionally characterized and shown to act as a pivotal regulator of leaf stomata formation, thereby affecting photosynthesis and drought resistance. This study provides valuable information for tomato genetic research and breeding.

A large-scale genome-wide association study sheds light on genetic and genomic bases underlying important yield-related traits in tomato.     

Genome-wide association mapping of yield components and drought tolerance-related traits in cotton

Drought causes serious yield losses in cotton production throughout the world. Association mapping allows identification and localization of the genes controlling drought-related traits which will be helpful in cotton breeding. In the present study, genetic diversity analysis and association mapping of yield and drought traits were performed on a panel of 99 upland cotton genotypes using 177 SSR (simple sequence repeat) markers. Yield parameters and drought tolerance-related traits were evaluated for two seasons under two watering regimes: water-stressed and well-watered. The traits included seed cotton yield (SCY), lint yield (LY), lint percentage (LP), water-use efficiency (WUE), yield potential (YP), yield reduction (YR), yield index (YI), drought sensitivity index (DSI), stress tolerance index (STI), harmonic mean (HM), and geometric mean productivity (GMP). The genotypes with the least change in seed cotton yield under drought stress were Zeta 2, Delcerro, Nazilli 87, and DAK 66/3 which were also the most water-use efficient cultivars. The average genetic diversity of the panel was 0.38. The linkage disequilibrium decayed relatively rapidly at 20–30 cM (r²?≥?0.5). We identified 30 different SSR markers associated with the traits. Fifteen and 23 SSR markers were linked to the traits under well-watered and water-stress conditions, respectively. To our knowledge, most of these quantitative yield and drought tolerance-associated loci were newly identified. The genetic diversity and association mapping results should facilitate the development of drought-tolerant cotton lines with high yield in molecular breeding programs.     

Population structure and association mapping of yield contributing agronomic traits in foxtail millet

Key message

Association analyses accounting for population structure and relative kinship identified eight SSR markers ( p < 0.01) showing significant association ( R ²  = 18 %) with nine agronomic traits in foxtail millet.

Abstract

Association mapping is an efficient tool for identifying genes regulating complex traits. Although association mapping using genomic simple sequence repeat (SSR) markers has been successfully demonstrated in many agronomically important crops, very few reports are available on marker-trait association analysis in foxtail millet. In the present study, 184 foxtail millet accessions from diverse geographical locations were genotyped using 50 SSR markers representing the nine chromosomes of foxtail millet. The genetic diversity within these accessions was examined using a genetic distance-based and a general model-based clustering method. The model-based analysis using 50 SSR markers identified an underlying population structure comprising five sub-populations which corresponded well with distance-based groupings. The phenotyping of plants was carried out in the field for three consecutive years for 20 yield contributing agronomic traits. The linkage disequilibrium analysis considering population structure and relative kinship identified eight SSR markers (p < 0.01) on different chromosomes showing significant association (R ² = 18 %) with nine agronomic traits. Four of these markers were associated with multiple traits. The integration of genetic and physical map information of eight SSR markers with their functional annotation revealed strong association of two markers encoding for phospholipid acyltransferase and ubiquitin carboxyl-terminal hydrolase located on the same chromosome (5) with flag leaf width and grain yield, respectively. Our findings on association mapping is the first report on Indian foxtail millet germplasm and this could be effectively applied in foxtail millet breeding to further uncover marker-trait associations with a large number of markers.     

茄子果实相关农艺性状全基因组关联分析研究进展与展望

茄子是重要的园艺作物,也是茄科植物中种植最广泛的蔬菜之一。茄子果实相关农艺性状是一种复杂的数量性状,传统育种选育效率低、周期长。高通量测序技术与生物信息学技术的快速发展,使得全基因组关联分析(genome-wide association study, GWAS)在解析茄子果实相关复杂农艺性状的遗传规律方面展现出巨大的应用前景。本文对全基因组关联分析在茄子的果形、果色等果实相关农艺性状中的研究进展进行了综述;针对茄子数量性状遗传研究中普遍存在的“丢失遗传力”(missing heritability)问题,从4个GWAS策略在茄子果实相关农艺性状研究中的应用热点出发,提出了未来茄子GWAS的发展对策;并结合当前茄子遗传改良的实践需求,展望了GWAS策略在茄子分子育种领域的广阔应用前景。本文为今后利用GWAS解析各种茄子果实相关性状的遗传基础以及选育符合消费者需求的果实材料提供了理论依据和参考。     

Genome-wide association mapping of fruit-quality traits using genotyping-by-sequencing approach in citrus landraces,modern cultivars,and breeding lines in Japan

Association mapping is an attractive method to identify QTLs in perennial horticultural crops such as citrus, as it does not need a designed cross between parental genotypes and can save time and labor to construct a segregating population. It usually requires more genetic markers than linkage-based QTL mapping owing to a lower degree of linkage disequilibrium (LD). However, recent advances in next-generation sequencing offer high-throughput, cost-effective methods, including genotyping-by-sequencing (GBS), for genotyping massive amounts of single nucleotide polymorphisms (SNPs). In this study, we performed a genome-wide association study (GWAS) of fruit-quality traits in citrus using SNPs obtained by GBS. We evaluated 110 citrus accessions, including landraces, modern cultivars, and breeding lines, for eight fruit-quality traits (fruit weight, fruit skin color, fruit surface texture, peelability, pulp firmness, segment firmness, sugar content, and acid content) during 2005 to 2012 (except 2007). GBS found 2309 SNPs, which we anchored to the clementine reference genome. We evaluated LD in the 110 accessions and confirmed that GBS gave enough SNPs to conduct GWAS. We identified seven QTLs, including four novel ones, comprising four significant QTLs for fruit weight and one QTL each for fruit skin color, pulp firmness, and segment firmness. These QTLs offer promise for use in citrus crossbreeding.     

Genome-wide association study identifies various loci underlying agronomic and morphological traits in diversified potato panel

Potato is one of the most important food crops all over the world. Breeding activities for this crop are mainly aimed to improve the quality and yield of tuber. However, genetic architecture of various traits contributing to the quality and yield of potato are not yet completely understood. Genome wide association studies provides a broader way to identify the genomic regions associated with various traits. Panels of 237 tetraploid potato genotypes from different countries were grown for two consecutive years 2016 and 2017 at experimental research area of Potato research center Niğde, Turkey. A genome wide association study using SolCAP 12K array was performed for various morpho-agronomic traits. Structure algorithm and neighborhood joining analysis clearly divided all genotypes into 4 clusters on the basis of their origin. For the marker trait association, Mixed Linear Model in TASSEL was performed and 36 genomic regions were found for the traits under study. The mean r2 value was found to be 0.92 and mean significant LD was 47.5% in the populations. LD patterns reflected the breeding history of potato. The findings of present study provide a framework which could be useful for future potato breeding programs to enhance the production and to reduce the challenges in the coming years to feed world’s population.     

Genome-wide association mapping of Fusarium head blight resistance in contemporary barley breeding germplasm

Utilization of quantitative trait loci (QTL) identified in bi-parental mapping populations has had limited success for improving complex quantitative traits with low to moderate heritability. Association mapping in contemporary breeding germplasm may lead to more effective marker strategies for crop improvement. To test this approach, we conducted association mapping of two complex traits with moderate heritability; Fusarium head blight (FHB) severity and the grain concentration of mycotoxin associated with disease, deoxynivalenol (DON). To map FHB resistance in barley, 768 breeding lines were evaluated in 2006 and 2007 in four locations. All lines were genotyped with 1,536 SNP markers and QTL were mapped using a mixed model that accounts for relatedness among lines. Average linkage disequilibrium within the breeding germplasm extended beyond 4 cM. Four QTL were identified for FHB severity and eight QTL were identified for the DON concentration in two independent sets of breeding lines. The QTL effects were small, explaining 1–3% of the phenotypic variation, as might be expected for complex polygenic traits. We show that using breeding germplasm to map QTL can complement bi-parental mapping studies by providing independent validation, mapping QTL with more precision, resolving questions of linkage and pleiotropy, and identifying genetic markers that can be applied immediately in crop improvement.     

Genome-wide association study-based identification genes influencing agronomic traits in rice (Oryza sativa L.)

Rice is one of the most important cereal crops, providing the daily dietary intake for approximately 50% of the global human population. Here, we re-sequenced 259 rice accessions, generating 1371.65 Gb of raw data. Furthermore, we performed genome-wide association studies (GWAS) on 13 agronomic traits using 2.8 million single nucleotide polymorphisms (SNPs) characterized in 259 rice accessions. Phenotypic data and best linear unbiased prediction (BLUP) values of each of the 13 traits over two years of each trait were used for the GWAS. The results showed that 816 SNP signals were significantly associated with the 13 agronomic traits. Then we detected candidate genes related to target traits within 200 kb upstream and downstream of the associated SNP loci, based on linkage disequilibrium (LD) blocks in the whole rice genome. These candidate genes were further identified through haplotype block constructions. This comprehensive study provides a timely and important genomic resource for breeding high yielding rice cultivars.     

Association mapping in structured populations

The use, in association studies, of the forthcoming dense genomewide collection of single-nucleotide polymorphisms (SNPs) has been heralded as a potential breakthrough in the study of the genetic basis of common complex disorders. A serious problem with association mapping is that population structure can lead to spurious associations between a candidate marker and a phenotype. One common solution has been to abandon case-control studies in favor of family-based tests of association, such as the transmission/disequilibrium test (TDT), but this comes at a considerable cost in the need to collect DNA from close relatives of affected individuals. In this article we describe a novel, statistically valid, method for case-control association studies in structured populations. Our method uses a set of unlinked genetic markers to infer details of population structure, and to estimate the ancestry of sampled individuals, before using this information to test for associations within subpopulations. It provides power comparable with the TDT in many settings and may substantially outperform it if there are conflicting associations in different subpopulations.     

Mapping QTL for agronomic traits in breeding populations

Detection of quantitative trait loci (QTL) in breeding populations offers the advantage that these QTL are of direct relevance for the improvement of crops via knowledge-based breeding. As phenotypic data are routinely generated in breeding programs and the costs for genotyping are constantly decreasing, it is tempting to exploit this information to unravel the genetic architecture underlying important agronomic traits in crops. This review characterizes the germplasm from breeding populations available for QTL detection, provides a classification of the different QTL mapping approaches that are available, and highlights important considerations concerning study design and biometrical models suitable for QTL analysis.