A whole‐genome,radiation hybrid mapping resource of hexaploid wheat

Generating a contiguous, ordered reference sequence of a complex genome such as hexaploid wheat (2n = 6x = 42; approximately 17 GB) is a challenging task due to its large, highly repetitive, and allopolyploid genome. In wheat, ordering of whole‐genome or hierarchical shotgun sequencing contigs is primarily based on recombination and comparative genomics‐based approaches. However, comparative genomics approaches are limited to syntenic inference and recombination is suppressed within the pericentromeric regions of wheat chromosomes, thus, precise ordering of physical maps and sequenced contigs across the whole‐genome using these approaches is nearly impossible. We developed a whole‐genome radiation hybrid (WGRH) resource and tested it by genotyping a set of 115 randomly selected lines on a high‐density single nucleotide polymorphism (SNP) array. At the whole‐genome level, 26 299 SNP markers were mapped on the RH panel and provided an average mapping resolution of approximately 248 Kb/cR₁₅₀₀ with a total map length of 6866 cR₁₅₀₀. The 7296 unique mapping bins provided a five‐ to eight‐fold higher resolution than genetic maps used in similar studies. Most strikingly, the RH map had uniform bin resolution across the entire chromosome(s), including pericentromeric regions. Our research provides a valuable and low‐cost resource for anchoring and ordering sequenced BAC and next generation sequencing (NGS) contigs. The WGRH developed for reference wheat line Chinese Spring (CS‐WGRH), will be useful for anchoring and ordering sequenced BAC and NGS based contigs for assembling a high‐quality, reference sequence of hexaploid wheat. Additionally, this study provides an excellent model for developing similar resources for other polyploid species.     

Natural variation in a calreticulin gene causes reduced resistance to Ca2+ deficiency‐induced tipburn in Chinese cabbage (Brassica rapa ssp. pekinensis)

Tipburn is an irreversible physiological disorder of Chinese cabbage that decreases crop value. Because of a strong environmental component, tipburn‐resistant cultivars are the only solution, although tipburn resistance genes are unknown in Chinese cabbage. We studied three populations of Chinese cabbage over four growing seasons under field conditions: (a) 194 diverse inbred lines, (b) a doubled haploid (DH100) population, and (c) an F₂ population. The 194 lines were genotyped using single nucleotide polymorphism markers, and genome‐wide‐association mapping showed that 24 gQTLs were significantly associated with tipburn disease index. Analysis of the DH100 and F₂ populations identified a shared tipburn‐associated locus, gqbTRA06, that was found to cover the region defined by one of the 24 gQTLs. Of 35 genes predicted in the 0.14‐Mb quantitative trait locus region, Bra018575 (calreticulin family protein, BrCRT2) showed higher expression levels during disease development. We cloned the two BrCRT2 alleles from tipburn‐resistant (BrCRT2^R) and tipburn‐susceptible (BrCRT2^S) lines and identified a 51‐bp deletion in BrCRT2^S. Overexpression of BrCRT2^R increased Ca²⁺ storage in the Arabidopsis crt2 mutant and also reduced cell death in leaf tips and margins under Ca²⁺‐depleted conditions. Our results suggest that BrCRT2 is a possible candidate gene for controlling tipburn in Chinese cabbage.     

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Kernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10^?6) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10^?3) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable‐effect SNPs and the co‐localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co‐localized SNPs, of which zma‐miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize.     

Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non‐invasive phenotyping

Hitherto, most quantitative trait loci of maize growth and biomass yield have been identified for a single time point, usually the final harvest stage. Through this approach cumulative effects are detected, without considering genetic factors causing phase‐specific differences in growth rates. To assess the genetics of growth dynamics, we employed automated non‐invasive phenotyping to monitor the plant sizes of 252 diverse maize inbred lines at 11 different developmental time points; 50 k SNP array genotype data were used for genome‐wide association mapping and genomic selection. The heritability of biomass was estimated to be over 71%, and the average prediction accuracy amounted to 0.39. Using the individual time point data, 12 main effect marker‐trait associations (MTAs) and six pairs of epistatic interactions were detected that displayed different patterns of expression at various developmental time points. A subset of them also showed significant effects on relative growth rates in different intervals. The detected MTAs jointly explained up to 12% of the total phenotypic variation, decreasing with developmental progression. Using non‐parametric functional mapping and multivariate mapping approaches, four additional marker loci affecting growth dynamics were detected. Our results demonstrate that plant biomass accumulation is a complex trait governed by many small effect loci, most of which act at certain restricted developmental phases. This highlights the need for investigation of stage‐specific growth affecting genes to elucidate important processes operating at different developmental phases.     

A novel noninvasive procedure for high‐throughput screening of major seed traits

The large numbers of samples processed in breeding and biodiversity programmes require the development of efficient methods for the nondestructive evaluation of basic seed properties. Near‐infrared spectroscopy is the state‐of‐the‐art solution for this analytical demand, but it also has some limitations. Here, we present a novel, rapid, accurate procedure based on time domain‐nuclear magnetic resonance (TD‐NMR), designed to simultaneously quantify a number of basic seed traits without any seed destruction. Using a low‐field, benchtop ¹H‐NMR instrument, the procedure gives a high‐accuracy measurement of oil content (R² = 0.98), carbohydrate content (R² = 0.99), water content (R² = 0.98) and both fresh and dry weight of seeds/grains (R² = 0.99). The method requires a minimum of ~20 mg biomass per sample and thus enables to screen individual, intact seeds. When combined with an automated sample delivery system, a throughput of ~1400 samples per day is achievable. The procedure has been trialled as a proof of concept on cereal grains (collection of ~3000 accessions of Avena spp. curated at the IPK genebank). A mathematical multitrait selection approach has been designed to simplify the selection of outlying (most contrasting) accessions. To provide deeper insights into storage oil topology, some oat accessions were further analysed by three‐dimensional seed modelling and lipid imaging. We conclude that the novel TD‐NMR‐based screening tool opens perspectives for breeding and plant biology in general.     

Genome‐wide association mapping and examination of possible maternal effect for the pace trait of horses

Previously, a single nucleotide polymorphism (SNP) related to gait type was identified at position 22 999 655 of chromosome 23 in the coding region of DMRT3 (DMRT3:Ser301Ter) by showing that a cytosine (C) to adenine (A) mutation of this SNP induced pace in the Icelandic horse. We investigated the effect of DMRT3:Ser301Ter on the gait of Hokkaido Native Horses, a Japanese native breed, and examined genetic factors other than DMRT3 by exploring genome‐wide SNPs related to gait determination. All animals exhibiting pace were AA for DMRT3:Ser301Ter, confirming the association of DMRT3:Ser301Ter with gait determination; however, 14.3% of the animals exhibiting trot also had AA for DMRT3:Ser301Ter, suggesting the presence of another factor(s) cooperatively working with DMRT3:Ser301Ter for gait determination. SNPs on chromosomes 13 and 23 were detected by genome‐wide association analysis (false discovery rate <0.05), although SNPs on chromosome 23 were all located in the vicinity of DMRT3:Ser301Ter, confirming the association with DMRT3. A genome‐wide association study targeting only animals with AA for DMRT3:Ser301Ter to examine genetic factors cooperatively working with DMRT3:Ser301Ter for gait determination suggested associations of 23 SNPs on six chromosomes. In a series of analyses of the effect of a maternal factor (dam's gait) on gait determination, the effect was suggested in comparison of the frequencies of exhibiting pace in gait checks in only two animal groups having dams with different DMRT3:Ser301Ter genotypes (P < 0.05), suggesting that the gait of the dam does not have a major effect on whether progeny homozygous for the DMRT3:Ser301Ter mutation will preferentially pace or trot.     

Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations

Currently, there is much debate on the genetic architecture of quantitative traits in wild populations. Is trait variation influenced by many genes of small effect or by a few genes of major effect? Where is additive genetic variation located in the genome? Do the same loci cause similar phenotypic variation in different populations? Great tits (Parus major) have been studied extensively in long‐term studies across Europe and consequently are considered an ecological ‘model organism’. Recently, genomic resources have been developed for the great tit, including a custom SNP chip and genetic linkage map. In this study, we used a suite of approaches to investigate the genetic architecture of eight quantitative traits in two long‐term study populations of great tits—one in the Netherlands and the other in the United Kingdom. Overall, we found little evidence for the presence of genes of large effects in either population. Instead, traits appeared to be influenced by many genes of small effect, with conservative estimates of the number of contributing loci ranging from 31 to 310. Despite concordance between population‐specific heritabilities, we found no evidence for the presence of loci having similar effects in both populations. While population‐specific genetic architectures are possible, an undetected shared architecture cannot be rejected because of limited power to map loci of small and moderate effects. This study is one of few examples of genetic architecture analysis in replicated wild populations and highlights some of the challenges and limitations researchers will face when attempting similar molecular quantitative genetic studies in free‐living populations.     

Identification of loci governing eight agronomic traits using a GBS‐GWAS approach and validation by QTL mapping in soya bean

Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome‐wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping‐by‐sequencing (GBS) approach was used to provide dense genome‐wide marker coverage (>47 000 SNPs) for a panel of 304 short‐season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.     

Imputation of 3 million SNPs in the Arabidopsis regional mapping population

Natural variation has become a prime resource to identify genetic variants that contribute to phenotypic variation. The regional mapping (RegMap) population is one of the most important populations for studying natural variation in Arabidopsis thaliana, and has been used in a large number of association studies and in studies on climatic adaptation. However, only 413 RegMap accessions have been completely sequenced, as part of the 1001 Genomes (1001G) Project, while the remaining 894 accessions have only been genotyped with the Affymetrix 250k chip. As a consequence, most association studies involving the RegMap are either restricted to the sequenced accessions, reducing power, or rely on a limited set of SNPs. Here we impute millions of SNPs to the 894 accessions that are exclusive to the RegMap, using the 1135 accessions of the 1001G Project as the reference panel. We assess imputation accuracy using a novel cross‐validation scheme, which we show provides a more reliable measure of accuracy than existing methods. After filtering out low accuracy SNPs, we obtain high‐quality genotypic information for 2029 accessions and 3 million markers. To illustrate the benefits of these imputed data, we reconducted genome‐wide association studies on five stress‐related traits and could identify novel candidate genes.     

Genetic dissection of drought and heat‐responsive agronomic traits in wheat

High yield and wide adaptation are principal targets of wheat breeding but are hindered by limited knowledge on genetic basis of agronomic traits and abiotic stress tolerances. In this study, 277 wheat accessions were phenotyped across 30 environments with non‐stress, drought‐stressed, heat‐stressed, and drought‐heat‐stressed treatments and were subjected to genome‐wide association study using 395 681 single nucleotide polymorphisms. We detected 295 associated loci including consistent loci for agronomic traits across different treatments and eurytopic loci for multiple abiotic stress tolerances. A total of 22 loci overlapped with quantitative trait loci identified by biparental quantitative trait loci mapping. Six loci were simultaneously associated with agronomic traits and abiotic stress tolerance, four of which fell within selective sweep regions. Selection in Chinese wheat has increased the frequency of superior marker alleles controlling yield‐related traits in the four loci during past decades, which conversely diminished favourable genetic variation controlling abiotic stress tolerance in the same loci; two promising candidate paralogous genes colocalized with such loci, thereby providing potential targets for studying the molecular mechanism of stress tolerance–productivity trade‐off. These results uncovering promising alleles controlling agronomic traits and/or multiple abiotic stress tolerances, providing insights into heritable covariation between yield and abiotic stress tolerance, will accelerate future efforts for wheat improvement.     

Copy number variations of CBF genes at the Fr‐A2 locus are essential components of winter hardiness in wheat

Winter hardiness is important for the adaptation of wheat to the harsh winter conditions in temperate regions and is thus also an important breeding goal. Here, we employed a panel of 407 European winter wheat cultivars to dissect the genetic architecture of winter hardiness. We show that copy number variation (CNV) of CBF (C‐repeat Binding Factor) genes at the Fr‐A2 locus is the essential component for winter survival, with CBF‐A14 CNV being the most likely causal polymorphism, accounting for 24.3% of the genotypic variance. Genome‐wide association mapping identified several markers in the Fr‐A2 chromosomal region, which even after accounting for the effects of CBF‐A14 copy number explained approximately 15% of the genotypic variance. This suggests that additional, as yet undiscovered, polymorphisms are present at the Fr‐A2 locus. Furthermore, CNV of Vrn‐A1 explained an additional 3.0% of the genotypic variance. The allele frequencies of all loci associated with winter hardiness were found to show geographic patterns consistent with their role in adaptation. Collectively, our results from the candidate gene analysis, association mapping and genome‐wide prediction show that winter hardiness in wheat is a quantitative trait, but with a major contribution of the Fr‐A2 locus.     

Association between putative functional variants in the PSMB9 gene and risk of melanoma – re‐analysis of published melanoma genome‐wide association studies

To mine possibly hidden causal single‐nucleotide polymorphisms (SNPs) of melanoma, we investigated the association of SNPs in 76 M/G1 transition genes with melanoma risk using our published genome‐wide association study (GWAS) data set with 1804 melanoma cases and 1026 cancer‐free controls. We found multiple SNPs with P < 0.01 and performed validation studies for 18 putative functional SNPs in PSMB9 in two other GWAS data sets. Two SNPs (rs1351383 and rs2127675) were associated with melanoma risk in the GenoMEL data set (P = 0.013 and 0.004, respectively), but failed in validation using the Australian data set. Genotype–phenotype analysis revealed these two SNPs were significantly correlated with mRNA expression level of PSMB9. Further experiments revealed that SNP rs2071480, which is in high LD with rs1351383 and rs2127675, may have a weak effect on the promoter activity of PSMB9. Taken together, our data suggested that functional variants in PSMB9 may contribute to melanoma susceptibility.     

Pleiotropy informed adaptive association test of multiple traits using genome‐wide association study summary data

Genetic variants associated with disease outcomes can be used to develop personalized treatment. To reach this precision medicine goal, hundreds of large‐scale genome‐wide association studies (GWAS) have been conducted in the past decade to search for promising genetic variants associated with various traits. They have successfully identified tens of thousands of disease‐related variants. However, in total these identified variants explain only part of the variation for most complex traits. There remain many genetic variants with small effect sizes to be discovered, which calls for the development of (a) GWAS with more samples and more comprehensively genotyped variants, for example, the NHLBI Trans‐Omics for Precision Medicine (TOPMed) Program is planning to conduct whole genome sequencing on over 100 000 individuals; and (b) novel and more powerful statistical analysis methods. The current dominating GWAS analysis approach is the “single trait” association test, despite the fact that many GWAS are conducted in deeply phenotyped cohorts including many correlated and well‐characterized outcomes, which can help improve the power to detect novel variants if properly analyzed, as suggested by increasing evidence that pleiotropy, where a genetic variant affects multiple traits, is the norm in genome‐phenome associations. We aim to develop pleiotropy informed powerful association test methods across multiple traits for GWAS. Since it is generally very hard to access individual‐level GWAS phenotype and genotype data for those existing GWAS, due to privacy concerns and various logistical considerations, we develop rigorous statistical methods for pleiotropy informed adaptive multitrait association test methods that need only summary association statistics publicly available from most GWAS. We first develop a pleiotropy test, which has powerful performance for truly pleiotropic variants but is sensitive to the pleiotropy assumption. We then develop a pleiotropy informed adaptive test that has robust and powerful performance under various genetic models. We develop accurate and efficient numerical algorithms to compute the analytical P‐value for the proposed adaptive test without the need of resampling or permutation. We illustrate the performance of proposed methods through application to joint association test of GWAS meta‐analysis summary data for several glycemic traits. Our proposed adaptive test identified several novel loci missed by individual trait based GWAS meta‐analysis. All the proposed methods are implemented in a publicly available R package.     

Genome‐wide prediction of age at puberty and reproductive longevity in sows

Traditional selection for sow reproductive longevity is ineffective due to low heritability and late expression of the trait. Incorporation of DNA markers into selection programs is potentially a more practical approach for improving sow lifetime productivity. Using a resource population of crossbred gilts, we explored pleiotropic sources of variation that influence age at puberty and reproductive longevity. Of the traits recorded before breeding, only age at puberty significantly affected the probability that females would produce a first parity litter. The genetic variance explained by 1‐Mb windows of the sow genome, compared across traits, uncovered regions that influence both age at puberty and lifetime number of parities. Allelic variants of SNPs located on SSC5 (27–28 Mb), SSC8 (36–37 Mb) and SSC12 (1.2–2 Mb) exhibited additive effects and were associated with both early expression of puberty and a greater than average number of lifetime parities. Combined analysis of these SNPs showed that an increase in the number of favorable alleles had positive impact on reproductive longevity, increasing number of parities by up to 1.36. The region located on SSC5 harbors non‐synonymous alleles in the arginine vasopressin receptor 1A (AVPR1A) gene, a G‐protein‐coupled receptor associated with social and reproductive behaviors in voles and humans and a candidate for the observed effects. This region is characterized by high levels of linkage disequilibrium in different lines and could be exploited in marker‐assisted selection programs across populations to increase sow reproductive longevity.     

Genome‐wide association study of six quality traits reveals the association of the TaRPP13L1 gene with flour colour in Chinese bread wheat

Flour colour, kernel hardness, grain protein content and wet gluten content are important quality properties that determine end use in bread wheat. Here, a wheat 90K genotyping assay was used for a genome‐wide association study (GWAS) of the six quality‐related traits in Chinese wheat cultivars in eight environments over four years. A total of 846 significant single nucleotide polymorphisms (SNPs) were identified, explaining approximately 30% of the phenotypic variation on average, and 103 multienvironment‐significant SNPs were detected in more than four environments. Quantitative trait loci (QTL) mapping in the biparent population confirmed some important SNP loci. Moreover, it was determined that some important genes were associated with the six quality traits, including some known functional genes and annotated unknown functional genes. Of the annotated unknown functional genes, it was verified that TaRPP13L1 was associated with flour colour. Wheat cultivars or lines with TaRPP13L1‐B1a showed extremely significantly higher flour redness and lower yellowness than those with TaRPP13L1‐B1b in the Chinese wheat natural population and the doubled haploid (DH) population. Two tetraploid wheat lines with premature stop codons of the TaRPP13L1 gene mutagenized by ethyl methanesulfonate (EMS) showed extremely significantly higher flour redness and lower yellowness than wild type. Our data suggest that the TaRPP13L1 gene plays an important role in modulating wheat flour colour. This study provides useful information for further dissection of the genetic basis of flour colour and also provides valuable genes or genetic loci for marker‐assisted selection to improve the process of breeding quality wheat in China.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.