Quantitative trait loci for agronomic and physiological traits for a bread wheat population grown in environments with a range of salinity levels

Worldwide, salinity is a major environmental stress affecting agricultural production. Sodium (Na⁺) exclusion has long been recognised as a mechanism of salinity tolerance (ST) in cereals and several molecular markers have been suggested for breeding. However, there have been no empirical studies to show that selection for Na⁺ exclusion markers could improve grain yield in bread wheat under dryland salinity. In six field trials, a bread wheat mapping population was grown to validate Na⁺ exclusion quantitative trait loci (QTL) identified earlier in hydroponics, to determine the impact of Na⁺ exclusion on grain yield, and to identify QTL for yield-related traits. The traits included grain yield, grain number per m², 1,000-grain weight, maturity, plant height, and leaf Na⁺ and K⁺ concentrations. The presence of numerous QTL with minor effects for most traits indicated the genetic complexity of these traits, and thus limited prospects for pyramiding at present. Considerable QTL-by-environment interactions were observed, with the stable QTL generally being co-located with maturity or early vigour/height genes, which demonstrates the importance of measuring major agronomic traits in order to discover genuine QTL for ST. Several QTL for seedling biomass and Na⁺ exclusion identified earlier in hydroponics were also detected in field trials but with marginal impact on grain yield. These results suggest that selection for Na⁺ exclusion and the use of hydroponics-based seedling assays may not necessarily result in improved ST. However, as this is the first report of its kind, there is an urgent need for testing other mapping populations in realistic environments to discover novel ST-QTL for breeding programs. In the meantime, grain yield QTL independent of maturity and height may offer potential to improve ST.     

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 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 genomic regions associated with phenotypic traits in Canadian western spring wheat

We recently reported genomic regions associated with resistance to four wheat diseases and insensitivity to three Pyrenophora tritici-repentis toxins in an association mapping panel consisting of 81 diverse Canadian western spring wheat (Triticum aestivum L.) cultivars. Here, we report genomic regions and SNPs associated with days to heading, plant maturity, plant height, test weight (grain volume weight), grain yield, and grain protein content in the same population using genome-wide association studies (GWAS). The 81 spring wheat cultivars were evaluated for the above six traits across six environments and genotyped with 19,919 polymorphic SNPs and 14 gene-specific markers. Using mixed liner model and a threshold of p ≤ 3.1 × 10^?4, we identified a total of 139 significant marker-trait associations that were mapped at 19 genomic regions on 11 chromosomes for heading (3 regions), maturity (2), plant height (3), test weight (3), grain yield (6), and grain protein (2). Each region consisted of clusters of markers ranging from 2 to 33 and individually explained from 4.5 to 26.1% of the phenotypic variation averaged over six environments. Some the genomic regions identified in the present study are novel, while others, such as the regions for grain protein on 1B, days to heading on 5A, plant height on 4B, and test weight on 7A, were located close to either known genes or QTLs reported in previous studies, but direct comparisons in some cases were challenging due to lack of common set of markers and reliable physical positions among the different studies. Results from this study provide additional information to wheat researchers developing improved spring wheat cultivars.     

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.     

Association analysis for agronomic traits in wheat under terminal heat stress

Terminal heat stress causes irreversible damage to wheat crop productivity. It reduces the vegetative growth and flowering period that consequently declines the efficiency to capture available stem reserves (carbohydrates) in grains. Markers associated with thermotolerant traits ease in marker assisted selection (MAS) for crop improvement. It identifies the genomic regions associated with thermotolerant traits in wheat, but the scarcity of markers is the major hindrance in crop improvement. Therefore, 158 wheat genotypes were subjected to genotyping with 165 simple sequence repeat markers dispersed on three genomes (A, B and D). Allelic frequency and polymorphic information content values were highest on genome A (5.34 (14% greater than the lowest value at genome D) and 0.715 (3% greater than the lowest value at genome D)), chromosome 4 (5.40 (16% greater than the lowest value at chromosome 2) and 0.725 (5% greater than the lowest value at chromosome 6)) and marker xgwm44 (13.0 (84% greater than the lowest value at marker xbarc148) and 0.916 (46% greater than the lowest value at marker xbarc148)). Bayesian based population structure discriminated the wheat genotypes into seven groups based on genetic similarity indicating their ancestral origin and geographical ecotype. Linkage disequilibrium pattern had highest significant (P < 0.001) linked loci pairs 732 on genome A at r² > 0.1 whereas, 58 on genome B at r² > 0.5. Linkage disequilibrium decay (P < 0.01 and r² > 0.1) had larger LD block (5–10 cM) on genome A. Highly significant MTAs (P < 0.000061) under heat stress conditions were identified for flag leaf area (xwmc336), spikelet per spike (xwmc553), grains per spike (cxfa2147, xwmc418 and xwmc121), biomass (xbarc7) and grain yield (xcfa2147 and xwmc671). The identified markers in this study could facilitate in MAS and gene pyramiding against heat stress in wheat.     

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.     

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 study for growth traits in Nelore cattle

The objective of this study was to investigate the association of single nucleotide polymorphisms (SNPs) with birth weight, weight gain from birth to weaning and from weaning to yearling, yearling height and cow weight in Nelore cattle. Data from 5064 animals participating in the DeltaGen and PAINT breeding programs were used. The animals were genotyped with a panel of 777 962 SNPs (Illumina BovineHD BeadChip) and 412 993 SNPs remained after quality control analysis of the genomic data. A genome-wide association study was performed using a single-step methodology. The analyses were processed with the BLUPF90 family of programs. When applied to a genome-wide association studies, the single-step GBLUP methodology is an iterative process that estimates weights for the SNPs. The weights of SNPs were included in all analyses by iteratively applying the single-step GBLUP methodology and repeated twice so that the effect of the SNP and the effect of the animal were recalculated in order to increase the weight of SNPs with large effects and to reduce the weight of those with small effects. The genome-wide association results are reported based on the proportion of variance explained by windows of 50 adjacent SNPs. Considering the two iterations, only windows with an additive genetic variance >1.5% were presented in the results. Associations were observed with birth weight on BTA 14, with weight gain from birth to weaning on BTA 5 and 29, with weight gain from weaning to yearling on BTA 11, and with yearling height on BTA 8, showing the genes TMEM68 (transmembrane protein 8B) associated with birth weight and yearling height, XKR4 (XK, Kell blood group complex subunit-related family, member 4) associated with birth weight, NPR2 (natriuretic peptide receptor B) associated with yearling height, and REG3G (regenerating islet-derived 3-gamma) associated with weight gain from weaning to yearling. These genes play an important role in feed intake, weight gain and the regulation of skeletal growth.     

A genome‐wide association study of 23 agronomic traits in Chinese wheat landraces

Uncovering the genetic basis of agronomic traits in wheat landraces is important for ensuring global food security via the development of improved varieties. Here, 723 wheat landraces from 10 Chinese agro‐ecological zones were evaluated for 23 agronomic traits in six environments. All accessions could be clustered into five subgroups based on phenotypic data via discriminant function analysis, which was highly consistent with genotypic classification. A genome‐wide association study was conducted for these traits using 52 303 DArT‐seq markers to identify marker‐trait associations and candidate genes. Using both the general linear model and the mixed linear model, 149 significant markers were identified for 21 agronomic traits based on best linear unbiased prediction values. Considering the linkage disequilibrium decay distance in this study, significant markers within 10 cM were combined as a quantitative trait locus (QTL), with a total of 29 QTL identified for 15 traits. Of these, five QTL for heading date, flag leaf width, peduncle length, and thousand kernel weight had been reported previously. Twenty‐five candidate genes associated with significant markers were identified. These included the known vernalization genes VRN‐B1 and vrn‐B3 and the photoperiod response genes Ppd and PRR. Overall, this study should be helpful in elucidating the underlying genetic mechanisms of complex agronomic traits and performing marker‐assisted selection in wheat.     

Genome-wide association mapping of agronomic and morphologic traits in highly structured populations of barley cultivars

Genome-wide association study (GWAS) has become an obvious general approach for studying traits of agricultural importance in higher plants, especially crops. Here, we present a GWAS of 32 morphologic and 10 agronomic traits in a collection of 615 barley cultivars genotyped by genome-wide polymorphisms from a recently developed barley oligonucleotide pool assay. Strong population structure effect related to mixed sampling based on seasonal growth habit and ear row number is present in this barley collection. Comparison of seven statistical approaches in a genome-wide scan for significant associations with or without correction for confounding by population structure, revealed that in reducing false positive rates while maintaining statistical power, a mixed linear model solution outperforms genomic control, structured association, stepwise regression control and principal components adjustment. The present study reports significant associations for sixteen morphologic and nine agronomic traits and demonstrates the power and feasibility of applying GWAS to explore complex traits in highly structured plant samples.     

Genomic regions controlling yield-related traits in spring wheat: a mini review and a case study for rainfed environments in Australia and China

A genome-wide association study (GWAS) was performed in six environments to identify major or consistent alleles responsible for wheat yield traits in Australia and North China where rainfed farming system is adopted. A panel of 228 spring wheat varieties were genotyped by double digest restriction-site associated DNA genotyping-by-sequencing. A total of 223 significant marker-trait association (MTAs) and 46 candidate genes for large- or consistent-effect MTAs were identified. The results were compared with previous studies based on a mini-review of 23 GWAS analyses on wheat yield. A phenomenon seldom reported in previous studies was that MTAs responsible for the trait tended to cluster together at certain chromosome segments, and many candidate genes were in the form of gene clusters. Although linkage disequilibrium (LD) might contribute to the co-segregation of the regions, it also suggested that marker-assisted selection (MAS) or transgenic method targeting a single gene might not be as effective as MAS targeting a larger genomic region where all the genes or gene clusters underlying play important roles.     

Genome-wide association mapping reveals key genomic regions for physiological and yield-related traits under salinity stress in wheat (Triticum aestivum L.)

A genome-wide association study (GWAS) was conducted using six different multi-locus GWAS models and 35K SNP array to demarcate genomic regions underlying reproductive stage salinity tolerance. Marker-trait association analysis was performed for salt tolerance indices (STI) of 11 morpho-physiological traits, and the actual concentrations of Na⁺ and K⁺, and the Na⁺/K⁺ ratio in flag leaf. A total of 293 significantly associated quantitative trait nucleotides (QTNs) for 14 morpho-physiological traits were identified. Of these 293 QTNs, 12 major QTNs with R² ≥ 10.0% were detected in three or more GWAS models. Novel major QTNs were identified for plant height, number of effective tillers, biomass, grain yield, thousand grain weight, Na⁺ and K⁺ content, and the Na⁺/K⁺ ratio in flag leaf. Moreover, 48 candidate genes were identified from the associated genomic regions. The QTNs identified in this study could potentially be targeted for improving salinity tolerance in wheat.     

Polymorphism of TaSAP1-A1 and its association with agronomic traits in wheat

TaSAP1, a member of the stress association protein (SAP) gene family from wheat, is involved in response to several abiotic stresses, including drought, salt and cold. In this study, TaSAP1-A1, a TaSAP1 member on chromosome 7A, and its flanking sequences were isolated. Polymorphism analysis indicated that the average nucleotide diversity (π) of the whole region was 0.00296. The highest nucleotide diversity occurred in the promoter region (π = 0.00631) and no polymorphism was identified in the coding region. Three markers T7AM5, T7AM2606 and T7AM39 located in the promoter region, were developed from sequence variations (InDel5-1810, SNP-2606 and InDel39-1637). Six haplotypes were identified among 300 accessions based on the three markers. TaSAP1-A1 was located on chromosome 7A using marker T7AM39 and was flanked by markers Xwmc530 and Xbarc174. QTL for yield-related traits, including 1,000-grain weight, number of grains per spike and grain yield, were located in the same region. In marker- and haplotype-trait association analyses, TaSAP1-A1 was significantly associated with 1,000-grain weight, number of grains per spike, spike length, peduncle length and total number of spikelets per spike in multiple environments. These results provide useful information for marker-assisted selection for yield-related traits under well-watered and drought-stressed conditions.     

Genome-wide association study for growth and fatness traits in Chinese Sujiang pigs

Growth and fatness traits are complex and economically important traits in the pig industry. The molecular basis underlying porcine growth and fatness traits remains largely unknown. To uncover genetic loci and candidate genes for these traits, we explored the GeneSeek GGP Porcine 80K SNP chip to perform a GWAS for seven growth and fatness traits in 365 individuals from the Sujiang pig, a recently developed breed in China. We identified two, 17, one and 11 SNPs surpassing the suggestively significant threshold (P < 1.86 × 10⁻⁵) for body weight, chest circumference, chest width and backfat thickness respectively. Of these SNPs, 20 represent novel genetic loci, and five and four SNPs were respectively associated with chest circumference and backfat thickness at a genome-wide significant threshold (P < 9.31 × 10⁻⁷). Eight SNPs had a pleiotropic effect on both chest circumference and backfat thickness. The most remarkable locus resided in a region between 72.95 and 76.27 Mb on pig chromosome 4, harboring a number of previously reported quantitative trait loci related to backfat deposition. In addition to two reported genes (PLAG1 and TAS2R38), we identified four genes including GABRB3, ZNF106, XKR4 and MGAM as novel candidates for body weight and backfat thickness at the mapped loci. Our findings provide insights into the genetic architecture of porcine growth and fatness traits and potential markers for selective breeding of Chinese Sujiang pigs.     

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.