Identification and validation of genomic regions influencing kernel zinc and iron in maize

Key message

Genome-wide association study (GWAS) on 923 maize lines and validation in bi-parental populations identified significant genomic regions for kernel-Zinc and-Iron in maize.

Abstract

Bio-fortification of maize with elevated Zinc (Zn) and Iron (Fe) holds considerable promise for alleviating under-nutrition among the world’s poor. Bio-fortification through molecular breeding could be an economical strategy for developing nutritious maize, and hence in this study, we adopted GWAS to identify markers associated with high kernel-Zn and Fe in maize and subsequently validated marker-trait associations in independent bi-parental populations. For GWAS, we evaluated a diverse maize association mapping panel of 923 inbred lines across three environments and detected trait associations using high-density Single nucleotide polymorphism (SNPs) obtained through genotyping-by-sequencing. Phenotyping trials of the GWAS panel showed high heritability and moderate correlation between kernel-Zn and Fe concentrations. GWAS revealed a total of 46 SNPs (Zn-20 and Fe-26) significantly associated (P?≤?5.03?×?10^?05) with kernel-Zn and Fe concentrations with some of these associated SNPs located within previously reported QTL intervals for these traits. Three double-haploid (DH) populations were developed using lines identified from the panel that were contrasting for these micronutrients. The DH populations were phenotyped at two environments and were used for validating significant SNPs (P?≤?1?×?10^?03) based on single marker QTL analysis. Based on this analysis, 11 (Zn) and 11 (Fe) SNPs were found to have significant effect on the trait variance (P?≤?0.01, R²?≥?0.05) in at least one bi-parental population. These findings are being pursued in the kernel-Zn and Fe breeding program, and could hold great value in functional analysis and possible cloning of high-value genes for these traits in maize.

     

Analysis of the genetic architecture of maize ear and grain morphological traits by combined linkage and association mapping

Key message

Using combined linkage and association mapping, 26 stable QTL and six stable SNPs were detected across multiple environments for eight ear and grain morphological traits in maize. One QTL, PKS2, might play an important role in maize yield improvement.

Abstract

In the present study, one bi-parental population and an association panel were used to identify quantitative trait loci (QTL) for eight ear and grain morphological traits. A total of 108 QTL related to these traits were detected across four environments using an ultra-high density bin map constructed using recombinant inbred lines (RILs) derived from a cross between Ye478 and Qi319, and 26 QTL were identified in more than two environments. Furthermore, 64 single nucleotide polymorphisms (SNPs) were found to be significantly associated with the eight ear and grain morphological traits (?log₁₀(P)?>?4) in an association panel of 240 maize inbred lines. Combining the two mapping populations, a total of 17 pleiotropic QTL/SNPs (pQTL/SNPs) were associated with various traits across multiple environments. PKS2, a stable locus influencing kernel shape identified on chromosome 2 in a genome-wide association study (GWAS), was within the QTL confidence interval defined by the RILs. The candidate region harbored a short 13-Kb LD block encompassing four SNPs (SYN11386, PHM14783.16, SYN11392, and SYN11378). In the association panel, 13 lines derived from the hybrid PI78599 possessed the same allele as Qi319 at the PHM14783.16 (GG) locus, with an average value of 0.21 for KS, significantly lower than that of the 34 lines derived from Ye478 that carried a different allele (0.25, P?<?0.05). Therefore, further fine mapping of PKS2 will provide valuable information for understanding the genetic components of grain yield and improving molecular marker-assisted selection (MAS) in maize.

     

Genome-wide association study identifies candidate genes that affect plant height in Chinese elite maize (Zea mays L.) inbred lines

Background

The harvest index for many crops can be improved through introduction of dwarf stature to increase lodging resistance, combined with early maturity. The inbred line Shen5003 has been widely used in maize breeding in China as a key donor line for the dwarf trait. Also, one major quantitative trait locus (QTL) controlling plant height has been identified in bin 5.05–5.06, across several maize bi-parental populations. With the progress of publicly available maize genome sequence, the objective of this work was to identify the candidate genes that affect plant height among Chinese maize inbred lines with genome wide association studies (GWAS).

Methods and Findings

A total of 284 maize inbred lines were genotyped using over 55,000 evenly spaced SNPs, from which a set of 41,101 SNPs were filtered with stringent quality control for further data analysis. With the population structure controlled in a mixed linear model (MLM) implemented with the software TASSEL, we carried out a genome-wide association study (GWAS) for plant height. A total of 204 SNPs (P≤0.0001) and 105 genomic loci harboring coding regions were identified. Four loci containing genes associated with gibberellin (GA), auxin, and epigenetic pathways may be involved in natural variation that led to a dwarf phenotype in elite maize inbred lines. Among them, a favorable allele for dwarfing on chromosome 5 (SNP PZE-105115518) was also identified in six Shen5003 derivatives.

Conclusions

The fact that a large number of previously identified dwarf genes are missing from our study highlights the discovery of the consistently significant association of the gene harboring the SNP PZE-105115518 with plant height (P = 8.91e-10) and its confirmation in the Shen5003 introgression lines. Results from this study suggest that, in the maize breeding schema in China, specific alleles were selected, that have played important roles in maize production.     

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 at bx1 controls DIMBOA content in maize

The main hydroxamic acid in maize (Zea mays L.) is 2-4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA). DIMBOA confers resistance to leaf-feeding by several corn borers. Most genes involved in the DIMBOA metabolic pathway are located on the short arm of chromosome 4, and quantitative trait loci (QTLs) involved in maize resistance to leaf-feeding by corn borers have been localized to that region. However, the low resolution of QTL linkage mapping does not allow convincing proof that genetic variation at bx loci was responsible for the variability for resistance. This study addressed the following objectives: to determine the QTLs involved in DIMBOA synthesis across genetically divergent maize inbreds using eight RIL families from the nested association mapping population, to check the stability of QTLs for DIMBOA content across years by evaluating two of those RIL families in 2 years, and to test the involvement of bx1 by performing association mapping with a panel of 281 diverse inbred lines. QTLs were stable across different environments. A genetic model including eight markers explained approximately 34% of phenotypic variability across eight RIL families and the position of the largest QTL co-localizes with the majority of structural genes of the DIMBOA pathway. Candidate association analysis determined that sequence polymorphisms at bx1 greatly affects variation of DIMBOA content in a diverse panel of maize inbreds, but the specific causal polymorphism or polymorphisms responsible for the QTL detected in the region 4.01 were not identified. This result may be because the causal polymorphism(s) were not sequenced, identity is masked by linkage disequilibrium, adjustments for population structure reduce significance of causal polymorphisms or multiple causal polymorphisms affecting bx1 segregate among inbred lines.     

The Genetic Architecture of Maize Stalk Strength

Stalk strength is an important trait in maize (Zea mays L.). Strong stalks reduce lodging and maximize harvestable yield. Studies show rind penetrometer resistance (RPR), or the force required to pierce a stalk rind with a spike, is a valid approximation of strength. We measured RPR across 4,692 recombinant inbreds (RILs) comprising the maize nested association mapping (NAM) panel derived from crosses of diverse inbreds to the inbred, B73. An intermated B73×Mo17 family (IBM) of 196 RILs and a panel of 2,453 diverse inbreds from the North Central Regional Plant Introduction Station (NCRPIS) were also evaluated. We measured RPR in three environments. Family-nested QTL were identified by joint-linkage mapping in the NAM panel. We also performed a genome-wide association study (GWAS) and genomic best linear unbiased prediction (GBLUP) in each panel. Broad sense heritability computed on a line means basis was low for RPR. Only 8 of 26 families had a heritability above 0.20. The NCRPIS diversity panel had a heritability of 0.54. Across NAM and IBM families, 18 family-nested QTL and 141 significant GWAS associations were identified for RPR. Numerous weak associations were also found in the NCRPIS diversity panel. However, few were linked to loci involved in phenylpropanoid and cellulose synthesis or vegetative phase transition. Using an identity-by-state (IBS) relationship matrix estimated from 1.6 million single nucleotide polymorphisms (SNPs) and RPR measures from 20% of the NAM panel, genomic prediction by GBLUP explained 64±2% of variation in the remaining RILs. In the NCRPIS diversity panel, an IBS matrix estimated from 681,257 SNPs and RPR measures from 20% of the panel explained 33±3% of variation in the remaining inbreds. These results indicate the high genetic complexity of stalk strength and the potential for genomic prediction to hasten its improvement.     

QTL mapping and GWAS reveal candidate genes controlling capsaicinoid content in Capsicum

Capsaicinoids are unique compounds produced only in peppers (Capsicum spp.). Several studies using classical quantitative trait loci (QTLs) mapping and genomewide association studies (GWAS) have identified QTLs controlling capsaicinoid content in peppers; however, neither the QTLs common to each population nor the candidate genes underlying them have been identified due to the limitations of each approach used. Here, we performed QTL mapping and GWAS for capsaicinoid content in peppers using two recombinant inbred line (RIL) populations and one GWAS population. Whole‐genome resequencing and genotyping by sequencing (GBS) were used to construct high‐density single nucleotide polymorphism (SNP) maps. Five QTL regions on chromosomes 1, 2, 3, 4 and 10 were commonly identified in both RIL populations over multiple locations and years. Furthermore, a total of 109 610 SNPs derived from two GBS libraries were used to analyse the GWAS population consisting of 208 C. annuum‐clade accessions. A total of 69 QTL regions were identified from the GWAS, 10 of which were co‐located with the QTLs identified from the two biparental populations. Within these regions, we were able to identify five candidate genes known to be involved in capsaicinoid biosynthesis. Our results demonstrate that QTL mapping and GBS‐GWAS represent a powerful combined approach for the identification of loci controlling complex traits.     

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.     

Beyond pathways: genetic dissection of tocopherol content in maize kernels by combining linkage and association analyses

Although tocopherols play an important role in plants and animals, the genetic architecture of tocopherol content in maize kernels has remained largely unknown. In this study, linkage and association analyses were conducted to examine the genetic architecture of tocopherol content in maize kernels. Forty‐one unique quantitative trait loci (QTLs) were identified by linkage mapping in six populations of recombinant inbred lines (RILs). In addition, 32 significant loci were detected via genome‐wide association study (GWAS), 18 of which colocalized with the QTLs identified by linkage mapping. Fine mapping of a major QTL validated the accuracy of GWAS and QTL mapping results and suggested a role for nontocopherol pathway genes in the modulation of natural tocopherol variation. We provided genome‐wide evidence that genes involved in fatty acid metabolism, chlorophyll metabolism and chloroplast function may affect natural variation in tocopherols. These findings were confirmed through mutant analysis of a particular gene from the fatty acid pathway. In addition, the favourable alleles for many of the significant SNPs/QTLs represented rare alleles in natural populations. Together, our results revealed many novel genes that are potentially involved in the variation of tocopherol content in maize kernels. Pyramiding of the favourable alleles of the newly elucidated genes and the well‐known tocopherol pathway genes would greatly improve tocopherol content in maize.     

A Multi-Trait,Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature,Fatness and Reproduction in Beef Cattle

Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The meta-analysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t''V⁻¹t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups.     

Genetic diversity and evolution of reduced sulfur storage during domestication of maize

The domestication of maize has spanned a period of over 9000 years, during which time its wild relative teosinte underwent natural and artificial selection. We hypothesize that environmental conditions could have played a major role in this process. One factor of environmental variation is soil composition, which includes sulfur availability. Sulfur is reduced during photosynthesis and is used to synthesize cysteine and methionine, which drive the accumulation of δ10 (Zm00001d045937), δ18 (Zm00001d037436), β15 (Zm00001d035760), γ16 (Zm00001d005793), γ27 (Zm00001d020592), and γ50 (Zm00001d020591) zeins, representing the zein2 fraction (z2) of storage proteins in maize seeds. In this study, polymorphisms and haplotypes were detected based on six z2 genes in 60 maize and teosintes lines. Haplotypes were unevenly distributed, and abundant genetic diversity was found in teosintes. Polymorphism was highest in z2δ18, whereas for z2β15 single nucleotide polymorphism (SNP) density and insertion/deletion (indel) abundance were the lowest, indicating differential roles in seed evolution. Indels showed a clustered distribution, and most of these derived from teosintes. The indels not only led to tandem repeat polymorphisms, but also to frameshift mutations, which could also be used as null variants. In addition, neutral evolutionary tests, phylogenetic analyses, and population structures indicated that z2δ10 and z2γ50 had undergone natural selection. Indeed, a natural selection imprint could also be found with z2γ27 and z2γ16, whereas z2δ18 and z2β15 tended to be under neutral evolution. These results suggested that genetic diversity and evolution of a subset of sulfur‐rich zeins could be under environmental adaptation during maize domestication.     

Genetic‐based dissection of arsenic accumulation in maize using a genome‐wide association analysis method

Understanding the mechanism of arsenic (As) accumulation in plants is important in reducing As's toxicity to plants and its potential risks to human health. Here, we performed a genome‐wide association study to dissect the genetic basis of the As contents of different maize tissues in Xixian, which was irrigated with As‐rich surface water, and Changge using an association population consisting of 230 representative maize inbred lines. Phenotypic data revealed a wide normal distribution and high repeatability for the As contents in maize tissues. The As concentrations in maize tissues followed the same trend in the two locations: kernels < axes < stems < bracts < leaves. In total, 15, 16 and 15 non‐redundant quantitative trait loci (QTL s) associated with As concentrations were identified (P  ≤ 2.04 × 10^?6) in five tissues from Xixian, Changge, and the combination of the locations, respectively, explaining 9.70%–24.65% of the phenotypic variation for each QTL , on average. Additionally, four QTL s [involving 15 single nucleotide polymorphisms (SNP s)] were detected in the single and the combined locations, indicating that these loci/SNP s might be stable across different environments. The candidate genes associated with these four loci were predicted. In addition, four non‐redundant QTL s (6 SNP s), including a QTL that was detected in multiple locations according to the genome‐wide association study, were found to co‐localize with four previously reported QTL intervals. These results are valuable to understand the genetic architecture of As mechanism in maize and facilitate the genetic improvement of varieties without As toxicity.     

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.     

Precise mapping of quantitative trait loci for resistance to southern leaf blight, caused by Cochliobolus heterostrophus race O, and flowering time using advanced intercross maize lines

The intermated B73 × Mo17 (IBM) population, an advanced intercross recombinant inbred line population derived from a cross between the maize lines B73 (susceptible) and Mo17 (resistant), was evaluated in four environments for resistance to southern leaf blight (SLB) disease caused by Cochliobolus heterostrophus race O. Two environments were artificially inoculated, while two were not inoculated and consequently had substantially lower disease pressure. Four common SLB resistance quantitative trait loci (QTL) were identified in all environments, two in bin 3.04 and one each in bins 1.10 and 8.02/3. There was no significant correlation between disease resistance and days to anthesis. A direct comparison was made between SLB QTL detected in two populations, independently derived from the same parental cross: the IBM advanced intercross population and a conventional recombinant inbred line population. Several QTL for SLB resistance were detected in both populations, with the IBM providing between 5 and, in one case, 50 times greater mapping resolution.     

Limits on the reproducibility of marker associations with southern leaf blight resistance in the maize nested association mapping population

Background

A previous study reported a comprehensive quantitative trait locus (QTL) and genome wide association study (GWAS) of southern leaf blight (SLB) resistance in the maize Nested Association Mapping (NAM) panel. Since that time, the genomic resources available for such analyses have improved substantially. An updated NAM genetic linkage map has a nearly six-fold greater marker density than the previous map and the combined SNPs and read-depth variants (RDVs) from maize HapMaps 1 and 2 provided 28.5 M genomic variants for association analysis, 17 fold more than HapMap 1. In addition, phenotypic values of the NAM RILs were re-estimated to account for environment-specific flowering time covariates and a small proportion of lines were dropped due to genotypic data quality problems. Comparisons of original and updated QTL and GWAS results confound the effects of linkage map density, GWAS marker density, population sample size, and phenotype estimates. Therefore, we evaluated the effects of changing each of these parameters individually and in combination to determine their relative impact on marker-trait associations in original and updated analyses.

Results

Of the four parameters varied, map density caused the largest changes in QTL and GWAS results. The updated QTL model had better cross-validation prediction accuracy than the previous model. Whereas joint linkage QTL positions were relatively stable to input changes, the residual values derived from those QTL models (used as inputs to GWAS) were more sensitive, resulting in substantial differences between GWAS results. The updated NAM GWAS identified several candidate genes consistent with previous QTL fine-mapping results.

Conclusions

The highly polygenic nature of resistance to SLB complicates the identification of causal genes. Joint linkage QTL are relatively stable to perturbations of data inputs, but their resolution is generally on the order of tens or more Mbp. GWAS associations have higher resolution, but lower power due to stringent thresholds designed to minimize false positive associations, resulting in variability of detection across studies. The updated higher density linkage map improves QTL estimation and, along with a much denser SNP HapMap, greatly increases the likelihood of detecting SNPs in linkage with causal variants. We recommend use of the updated genetic resources and results but emphasize the limited repeatability of small-effect associations.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1068) contains supplementary material, which is available to authorized users.     

Genome-wide association mapping of QTLs implied in potato virus Y population sizes in pepper: evidence for widespread resistance QTL pyramiding

In this study, we looked for genetic factors in the pepper (Capsicum annuum) germplasm that control the number of potato virus Y (PVY) particles entering the plant (i.e. effective population size at inoculation) and the PVY accumulation at the systemic level (i.e. census population size). Using genotyping-by-sequencing (GBS) in a core collection of 256 pepper accessions, we obtained 10 307 single nucleotide polymorphisms (SNPs) covering the whole genome. Genome-wide association studies (GWAS) detected seven SNPs significantly associated with the virus population size at inoculation and/or systemic level on chromosomes 4, 6, 9 and 12. Two SNPs on chromosome 4 associated with both PVY population sizes map closely to the major resistance gene pvr2 encoding the eukaryotic initiation factor 4E. No obvious candidates for resistance were identified in the confidence intervals for the other chromosomes. SNPs detected on chromosomes 6 and 12 colocalized with resistance quantitative trait loci (QTLs) previously identified with a biparental population. These results show the efficiency of GBS and GWAS in C. annuum, indicate highly consistent results between GWAS and classical QTL mapping, and suggest that resistance QTLs identified with a biparental population are representative of a much larger collection of pepper accessions. Moreover, the resistance alleles at these different loci were more frequently combined than expected by chance in the core collection, indicating widespread pyramiding of resistance QTLs and widespread combination of resistance QTLs and major effect genes. Such pyramiding may increase resistance efficiency and/or durability.     

Genome-wide association study reveals the genetic architecture of flowering time in rapeseed (Brassica napus L.)

Flowering time adaptation is a major breeding goal in the allopolyploid species Brassica napus. To investigate the genetic architecture of flowering time, a genome-wide association study (GWAS) of flowering time was conducted with a diversity panel comprising 523 B. napus cultivars and inbred lines grown in eight different environments. Genotyping was performed with a Brassica 60K Illumina Infinium SNP array. A total of 41 single-nucleotide polymorphisms (SNPs) distributed on 14 chromosomes were found to be associated with flowering time, and 12 SNPs located in the confidence intervals of quantitative trait loci (QTL) identified in previous researches based on linkage analyses. Twenty-five candidate genes were orthologous to Arabidopsis thaliana flowering genes. To further our understanding of the genetic factors influencing flowering time in different environments, GWAS was performed on two derived traits, environment sensitivity and temperature sensitivity. The most significant SNPs were found near Bn-scaff_16362_1-p380982, just 13 kb away from BnaC09g41990D, which is orthologous to A. thaliana CONSTANS (CO), an important gene in the photoperiod flowering pathway. These results provide new insights into the genetic control of flowering time in B. napus and indicate that GWAS is an effective method by which to reveal natural variations of complex traits in B. napus.     

Mapping of quantitative trait loci for kernel row number in maize across seven environments

Genetic factors controlling quantitative inheritance of grain yield and its components have been intensively investigated during recent decades using diverse populations in maize (Zea mays L.). Notwithstanding this, quantitative trait loci (QTL) for kernel row number (KRN) with large and consistent effect have not been identified. In this study, a linkage map of 150 simple sequence repeat (SSR) loci was constructed by using a population of 500 F2 individuals derived from a cross between elite inbreds Ye478 and Dan340. The linkage map spanned a total of 1478 cM with an average interval of 10.0 cM. A total of 397 F2:3 lines were evaluated across seven diverse environments for mapping QTL for KRN. Some QTL for grain yield and its components had previously been confirmed with this population across environments. A total of 13 QTL for KRN were identified, with each QTL explaining from 3.0 to 17.9% of phenotypic variance. The gene action for KRN was mainly additive to partial dominance. A large-effect QTL (qkrn7) with partial dominance effect accounting for 17.9% of the phenotypic variation for KRN was identified on chromosome 7 near marker umc1865 with consistent gene effect across seven diverse environments. This study has laid a foundation for map-based cloning of this major QTL and for developing molecular markers for marker-assisted selection of high KRN.     

A Genome-Wide Association Study of the Maize Hypersensitive Defense Response Identifies Genes That Cluster in Related Pathways

Much remains unknown of molecular events controlling the plant hypersensitive defense response (HR), a rapid localized cell death that limits pathogen spread and is mediated by resistance (R-) genes. Genetic control of the HR is hard to quantify due to its microscopic and rapid nature. Natural modifiers of the ectopic HR phenotype induced by an aberrant auto-active R-gene (Rp1-D21), were mapped in a population of 3,381 recombinant inbred lines from the maize nested association mapping population. Joint linkage analysis was conducted to identify 32 additive but no epistatic quantitative trait loci (QTL) using a linkage map based on more than 7000 single nucleotide polymorphisms (SNPs). Genome-wide association (GWA) analysis of 26.5 million SNPs was conducted after adjusting for background QTL. GWA identified associated SNPs that colocalized with 44 candidate genes. Thirty-six of these genes colocalized within 23 of the 32 QTL identified by joint linkage analysis. The candidate genes included genes predicted to be in involved programmed cell death, defense response, ubiquitination, redox homeostasis, autophagy, calcium signalling, lignin biosynthesis and cell wall modification. Twelve of the candidate genes showed significant differential expression between isogenic lines differing for the presence of Rp1-D21. Low but significant correlations between HR-related traits and several previously-measured disease resistance traits suggested that the genetic control of these traits was substantially, though not entirely, independent. This study provides the first system-wide analysis of natural variation that modulates the HR response in plants.     

Genome-wide association study for soybean cyst nematode resistance in Chinese elite soybean cultivars

Soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is a highly recalcitrant endoparasite of soybean roots, causing more yield loss than any other pest. To identify quantitative trait loci (QTL) controlling resistance to SCN (HG type 2.5.7, race 1), a genome-wide association study (GWAS) was performed. The association panel, consisting of 120 Chinese soybean cultivars, was genotyped with 7189 single nucleotide polymorphism (SNPs). A total of 6204 SNPs with minor allele frequency >0.05 were used to estimate linkage disequilibrium (LD) and population structure. The mean level of LD measured by r ² declined very rapidly to half its maximum value (0.51) at 220 kb. The overall population structure was approximately coincident with geographic origin. The GWAS results identified 13 SNPs in 7 different genomic regions significantly associated with SCN resistance. Of these, three SNPs were localized in previously mapped QTL intervals, including rhg1 and Rhg4. The GWAS results also detected 10 SNPs in 5 different genomic regions associated with SCN resistance. The identified loci explained an average of 95.5% of the phenotypic variance. The proportion of phenotypic variance was due to additive genetic variance of the validated SNPs. The present study identified multiple new loci and refined chromosomal regions of known loci associated with SCN resistance. The loci and trait-associated SNPs identified in this study can be used for developing soybean cultivars with durable resistance against SCN.