Genome-wide Association Studies in Maize: Praise and Stargaze

Genome-wide association study dissects yield components associated with low-phosphorus stress tolerance in maize

Phosphorus deficiency in soil is a worldwide constraint threatening maize production. Through a genome-wide association study, we identified molecular markers and associated candidate genes and molecular pathways for low-phosphorus stress tolerance. Phosphorus deficiency in soils will severely affect maize (Zea mays L.) growth and development, thus decreasing the final yield. Deciphering the genetic basis of yield-related traits can benefit our understanding of maize tolerance to low-phosphorus stress. However, considering that yield-related traits should be evaluated under field condition with large populations rather than under hydroponic condition at a single-plant level, searching for appropriate field experimental sites and target traits for low-phosphorus stress tolerance is still very challenging. In this study, a genome-wide association analysis using two natural populations was performed to detect candidate genes in response to low-phosphorus stress at two experimental sites representative of different climate and soil types. In total, 259 candidate genes were identified and these candidate genes are mainly involved in four major pathways: transcriptional regulation, reactive oxygen scavenging, hormone regulation, and remodeling of cell wall. Among these candidate genes, 98 showed differential expression by transcriptome data. Based on a haplotype analysis of grain number under phosphorus deficiency condition, the positive haplotypes with favorable alleles across five loci increased grain number by 42% than those without favorable alleles. For further verifying the feasibility of genomic selection for improving maize low-phosphorus tolerance, we also validated the predictive ability of five genomic selection methods and suggested that moderate-density SNPs were sufficient to make accurate predictions for low-phosphorus tolerance traits. All these results will facilitate elucidating genetic basis of maize tolerance to low-phosphorus stress and improving marker-assisted selection efficiency in breeding process.

Genome-Wide Association Study for Spot Blotch Resistance in Hard Winter Wheat

Spot blotch (SB) caused by Cochliobolus sativus (anamorph: Bipolaris sorokiniana) is an economically important disease of wheat worldwide. Under a severe epidemic condition, the disease can cause yield losses up to 70%. Previous approaches like bi-parental mapping for identifying SB resistant genes/QTLs exploited only a limited portion of the available genetic diversity with a lower capacity to detect polygenic traits, and had a lower marker density. In this study, we performed genome-wide association study (GWAS) for SB resistance in hard winter wheat association mapping panel (HWWAMP) of 294 genotypes. The HWWAMP was evaluated for response to B. sorokiniana (isolate SD40), and a range of reactions was observed with 10 resistant, 38 moderately resistant, 120 moderately resistant- moderately susceptible, 111 moderately susceptible, and 15 susceptible genotypes. GWAS using 15,590 high-quality SNPs and 294 genotypes we identified six QTLs (p = <0.001) on chromosomes 2D, 3A, 4A, 4B, 5A, and 7B that collectively explained 30% of the total variation for SB resistance. Highly associated SNPs were identified for all six QTLs, QSb.sdsu-2D.1 (SNP: Kukri_c31121_1460, R2 = 4%), QSb.sdsu-3A.1 (SNP: Excalibur_c46082_440, R2 = 4%), QSb.sdsu-4A.1 (SNP: IWA8475, R2 = 5.5%), QSb.sdsu-4B.1 (SNP: Excalibur_rep_c79414_306, R2 = 4%), QSb.sdsu-5A.1 (SNP: Kukri_rep_c104877_2166, R2 = 6%), and QSb.sdsu-7B.1 (SNP: TA005844-0160, R2 = 6%). Our study not only validates three (2D, 5A, and 7B) genomic regions identified in previous studies but also provides highly associated SNP markers for marker assisted selection. In addition, we identified three novel QTLs (QSb.sdsu-3A.1, QSb.sdsu-4A.1, and QSb.sdsu-4B.1) for SB resistance in wheat. Gene annotation analysis of the candidate regions identified nine NBS-LRR and 38 other plant defense-related protein families across multiple QTLs, and these could be used for fine mapping and further characterization of SB resistance in wheat. Comparative analysis with barley indicated the SB resistance locus on wheat chromosomes 2D, 3A, 5A, and 7B identified in our study are syntenic to the previously identified SB resistance locus on chromosomes 2H, 3H, 5H, and 7H in barley. The 10 highly resistant genotypes and SNP markers identified in our study could be very useful resources for breeding of SB resistance in wheat.

Dissection of the genetic architecture of three seed-quality traits and consequences for breeding in Brassica napus

Genome-wide association studies (GWASs) combining high-throughput genome resequencing and phenotyping can accelerate the dissection of genetic architecture and identification of genes for plant complex traits. In this study, we developed a rapeseed genomic variation map consisting of 4 542 011 SNPs and 628 666 INDELs. GWAS was performed for three seed-quality traits, including erucic acid content (EAC), glucosinolate content (GSC) and seed oil content (SOC) using 3.82 million polymorphisms in an association panel. Six, 49 and 17 loci were detected to be associated with EAC, GSC and SOC in multiple environments, respectively. The mean total contribution of these loci in each environment was 94.1% for EAC and 87.9% for GSC, notably higher than that for SOC (40.1%). A high correlation was observed between phenotypic variance and number of favourable alleles for associated loci, which will contribute to breeding improvement by pyramiding these loci. Furthermore, candidate genes were detected underlying associated loci, based on functional polymorphisms in gene regions where sequence variation was found to correlate with phenotypic variation. Our approach was validated by detection of well-characterized FAE1 genes at each of two major loci for EAC on chromosomes A8 and C3, along with MYB28 genes at each of three major loci for GSC on chromosomes A9, C2 and C9. Four novel candidate genes were detected by correlation between GSC and SOC and observed sequence variation, respectively. This study provides insights into the genetic architecture of three seed-quality traits, which would be useful for genetic improvement of B. napus.

Large-scale replicated field study of maize rhizosphere identifies heritable microbes

In this very large-scale longitudinal field study of the maize rhizosphere microbiome, we identify heritable taxa. These taxa display variance in their relative abundances that can be partially explained by genetic differences between the maize lines, above and beyond the strong influences of field, plant age, and weather on the diversity of the rhizosphere microbiome. If these heritable taxa are associated with beneficial traits, they may serve as phenotypes in future breeding endeavors.

Soil microbes that colonize plant roots and are responsive to differences in plant genotype remain to be ascertained for agronomically important crops. From a very large-scale longitudinal field study of 27 maize inbred lines planted in three fields, with partial replication 5 y later, we identify root-associated microbiota exhibiting reproducible associations with plant genotype. Analysis of 4,866 samples identified 143 operational taxonomic units (OTUs) whose variation in relative abundances across the samples was significantly regulated by plant genotype, and included five of seven core OTUs present in all samples. Plant genetic effects were significant amid the large effects of plant age on the rhizosphere microbiome, regardless of the specific community of each field, and despite microbiome responses to climate events. Seasonal patterns showed that the plant root microbiome is locally seeded, changes with plant growth, and responds to weather events. However, against this background of variation, specific taxa responded to differences in host genotype. If shown to have beneficial functions, microbes may be considered candidate traits for selective breeding.

Functional Validation of Candidate Genes Detected by Genomic Feature Models

Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait variability to pinpoint loci that contribute to the quantitative trait. Because stringent genome-wide significance thresholds are applied to control the false positive rate, many true causal variants can remain undetected. To ameliorate this problem, many alternative approaches have been developed, such as genomic feature models (GFM). The GFM approach tests for association of set of genomic markers, and predicts genomic values from genomic data utilizing prior biological knowledge. We investigated to what degree the findings from GFM have biological relevance. We used the Drosophila Genetic Reference Panel to investigate locomotor activity, and applied genomic feature prediction models to identify gene ontology (GO) categories predictive of this phenotype. Next, we applied the covariance association test to partition the genomic variance of the predictive GO terms to the genes within these terms. We then functionally assessed whether the identified candidate genes affected locomotor activity by reducing gene expression using RNA interference. In five of the seven candidate genes tested, reduced gene expression altered the phenotype. The ranking of genes within the predictive GO term was highly correlated with the magnitude of the phenotypic consequence of gene knockdown. This study provides evidence for five new candidate genes for locomotor activity, and provides support for the reliability of the GFM approach.

Genome-Wide Association Study of Cadmium Accumulation at the Seedling Stage in Rapeseed (Brassica napus L.)

Cadmium is a potentially toxic heavy metal to human health. Rapeseed (Brassica napus L.), a vegetable and oilseed crop, might also be a Cd hyperaccumulator, but there is little information on this trait in rapeseed. We evaluated Cd accumulation in different oilseed accessions and employed a genome-wide association study to identify quantitative trait loci (QTLs) related to Cd accumulation. A total of 419 B. napus accessions and inbred lines were genotyped with a 60K Illumina Infinium SNP array of Brassica. Wide genotypic variations in Cd concentration and translocation were found. Twenty-five QTLs integrated with 98 single-nucleotide polymorphisms (SNPs) located at 15 chromosomes were associated with Cd accumulation traits. These QTLs explained 3.49-7.57% of the phenotypic variation observed. Thirty-two candidate genes were identified in these genomic regions, and they were 0.33-497.97 kb away from the SNPs. We found orthologs of Arabidopsis thaliana located near the significant SNPs on the B. napus genome, including NRAMP6 (natural resistance-associated macrophage protein 6), IRT1 (iron-regulated transporter 1), CAD1 (cadmium-sensitive 1), and PCS2 (phytochelatin synthase 2). Of them, four candidate genes were verified by qRT-PCR, the expression levels of which were significantly higher after exposure to Cd than in the controls. Our results might facilitate the study of the genetic basis of Cd accumulation and the cloning of candidate Cd accumulation genes, which could be used to help reduce Cd levels in edible plant parts and/or create more efficient hyperaccumulators.

An integrated multi-layered analysis of the metabolic networks of different tissues uncovers key genetic components of primary metabolism in maize

Primary metabolism plays a pivotal role in normal plant growth, development and reproduction. As maize is a major crop worldwide, the primary metabolites produced by maize plants are of immense importance from both calorific and nutritional perspectives. Here a genome-wide association study (GWAS) of 61 primary metabolites using a maize association panel containing 513 inbred lines identified 153 significant loci associated with the level of these metabolites in four independent tissues. The genome-wide expression level of 760 genes was also linked with metabolite levels within the same tissue. On average, the genetic variants at each locus or transcriptional variance of each gene identified here were estimated to have a minor effect (4.4-7.8%) on primary metabolic variation. Thirty-six loci or genes were prioritized as being worthy of future investigation, either with regard to functional characterization or for their utility for genetic improvement. This target list includes the well-known opaque 2 (O2) and lkr/sdh genes as well as many less well-characterized genes. During our investigation of these 36 loci, we analyzed the genetic components and variations underlying the trehalose, aspartate and aromatic amino acid pathways, thereby functionally characterizing four genes involved in primary metabolism in maize.

Genetic and Molecular Mechanisms of Quantitative Trait Loci Controlling Maize Inflorescence Architecture

The establishment of inflorescence architecture is critical for the reproduction of flowering plant species. The maize plant generates two types of inflorescences, the tassel and the ear, and their architectures have a large effect on grain yield and yield-related traits that are genetically controlled by quantitative trait loci (QTLs). Since ear and tassel architecture are deeply affected by the activity of inflorescence meristems, key QTLs and genes regulating meristematic activity have important impacts on inflorescence development and show great potential for optimizing grain yield. Isolation of yield trait-related QTLs is challenging, but these QTLs have direct application in maize breeding. Additionally, characterization and functional dissection of QTLs can provide genetic and molecular knowledge of quantitative variation in inflorescence architecture. In this review, we summarize currently identified QTLs responsible for the establishment of ear and tassel architecture and discuss the potential genetic control of four ear-related and four tassel-related traits. In recent years, several inflorescence architecture-related QTLs have been characterized at the gene level. We review the mechanisms of these characterized QTLs.

Genetic Properties of a Nested Association Mapping Population Constructed With Semi-Winter and Spring Oilseed Rapes

Nested association mapping (NAM) populations have been widely applied to dissect the genetic basis of complex quantitative traits in a variety of crops. In this study, we developed a Brassica napus NAM (BN-NAM) population consisting of 15 recombination inbred line (RIL) families with 2,425 immortal genotypes. Fifteen high-density genetic linkage maps were constructed by genotyping by sequencing (GBS) based on all RIL families, with further integration into a joint linkage map (JLM) having 30,209 unique markers in common with multiple linkage maps. Furthermore, an ultra-density whole-genome variation map was constructed by projecting 4,444,309 high-quality variants onto the JLM. The NAM population captured a total of 88,542 recombination events (REs). The uneven distribution of recombination rate along chromosomes is positively correlated with the densities of genes and markers, but negatively correlated with the density of transposable elements and linkage disequilibrium (LD). Analyses of population structure and principal components revealed that the BN-NAM population could be divided into three groups with weak stratification. The LD decay distance across genome varied between 170 and 2,400 Kb, with LD decay more rapid in the A than in the C sub-genome. The pericentromeric regions contained large LD blocks, especially in the C sub-genome. This NAM population provides a valuable resource for dissecting the genetic basis of important traits in rapeseed, especially in semi-winter oilseed rape.

Genome-Wide Association Study for Spot Blotch Resistance in Hard Winter Wheat

Spot blotch (SB) caused by Cochliobolus sativus (anamorph: Bipolaris sorokiniana) is an economically important disease of wheat worldwide. Under a severe epidemic condition, the disease can cause yield losses up to 70%. Previous approaches like bi-parental mapping for identifying SB resistant genes/QTLs exploited only a limited portion of the available genetic diversity with a lower capacity to detect polygenic traits, and had a lower marker density. In this study, we performed genome-wide association study (GWAS) for SB resistance in hard winter wheat association mapping panel (HWWAMP) of 294 genotypes. The HWWAMP was evaluated for response to B. sorokiniana (isolate SD40), and a range of reactions was observed with 10 resistant, 38 moderately resistant, 120 moderately resistant- moderately susceptible, 111 moderately susceptible, and 15 susceptible genotypes. GWAS using 15,590 high-quality SNPs and 294 genotypes we identified six QTLs (p = <0.001) on chromosomes 2D, 3A, 4A, 4B, 5A, and 7B that collectively explained 30% of the total variation for SB resistance. Highly associated SNPs were identified for all six QTLs, QSb.sdsu-2D.1 (SNP: Kukri_c31121_1460, R² = 4%), QSb.sdsu-3A.1 (SNP: Excalibur_c46082_440, R² = 4%), QSb.sdsu-4A.1 (SNP: IWA8475, R² = 5.5%), QSb.sdsu-4B.1 (SNP: Excalibur_rep_c79414_306, R² = 4%), QSb.sdsu-5A.1 (SNP: Kukri_rep_c104877_2166, R² = 6%), and QSb.sdsu-7B.1 (SNP: TA005844-0160, R² = 6%). Our study not only validates three (2D, 5A, and 7B) genomic regions identified in previous studies but also provides highly associated SNP markers for marker assisted selection. In addition, we identified three novel QTLs (QSb.sdsu-3A.1, QSb.sdsu-4A.1, and QSb.sdsu-4B.1) for SB resistance in wheat. Gene annotation analysis of the candidate regions identified nine NBS-LRR and 38 other plant defense-related protein families across multiple QTLs, and these could be used for fine mapping and further characterization of SB resistance in wheat. Comparative analysis with barley indicated the SB resistance locus on wheat chromosomes 2D, 3A, 5A, and 7B identified in our study are syntenic to the previously identified SB resistance locus on chromosomes 2H, 3H, 5H, and 7H in barley. The 10 highly resistant genotypes and SNP markers identified in our study could be very useful resources for breeding of SB resistance in wheat.

Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models

Maize starch plays a critical role in food processing and industrial application. The pasting properties, the most important starch characteristics, have enormous influence on fabrication property, flavor characteristics, storage, cooking, and baking. Understanding the genetic basis of starch pasting properties will be beneficial for manipulation of starch properties for a given purpose. Genome-wide association studies (GWAS) are becoming a powerful tool for dissecting the complex traits. Here, we carried out GWAS for seven pasting properties of maize starch with a panel of 230 inbred lines and 145,232 SNPs using one single-locus method, genome-wide efficient mixed model association (GEMMA), and three multi-locus methods, FASTmrEMMA, FarmCPU, and LASSO. We totally identified 60 quantitative trait nucleotides (QTNs) for starch pasting properties with these four GWAS methods. FASTmrEMMA detected the most QTNs (29), followed by FarmCPU (19) and LASSO (12), GEMMA detected the least QTNs (7). Of these QTNs, seven QTNs were identified by more than one method simultaneously. We further investigated locations of these significantly associated QTNs for possible candidate genes. These candidate genes and significant QTNs provide the guidance for further understanding of molecular mechanisms of starch pasting properties. We also compared the statistical powers and Type I errors of the four GWAS methods using Monte Carlo simulations. The results suggest that the multi-locus method is more powerful than the single-locus method and a combination of these multi-locus methods could help improve the detection power of GWAS.

A microsatellite diversity analysis and the development of core-set germplasm in a large hulless barley (Hordeum vulgare L.) collection

Background

Clarifying genetic diversity in a large germplasm resource plays important roles in experimental designs that provides flexible utility in fundamental research and breeding in crops. However, the work is limited due to small collections of barley that are insufficient representatives.

Results

In the present study, we collected 562 hulless barley (Hordeum vulgare L.) accessions with worldwide geographic origins and evaluated their genetic variability and relatedness based on 93 simple sequence repeat (SSR) markers. In an integrated analysis of the population structure, analysis of molecular variance (AMOVA) and pairwise F_ST, the 562 barley accessions exhibited a strong stratification that allowed for them to be divided into two major subpopulations (p1 and p2) and an admixture subpopulation, with 93, 408 and 61 accessions, respectively. In a neutral test, considerable proportions of SSR alleles expressed the strong non-neutrality in specific subpopulations (44 and 37), which are probably responsible for population differentiation. To reduce the diversity redundancy in large barley collections, we delicately selected a core set of 200 barley accessions as a tradeoff between diversity and representativeness in an easily handled population. In comparing the 562 barley accessions, the core barley set accounted for 96.2% of allelic diversity and 93% to 95% of phenotypic variability, whereas it exhibited a significant enhancement in minor allelic frequencies, which probably benefit association mapping in the barley core set.

Conclusions

The results provided additional insight into the genetic structure in a large barley germplasm resource, from which an easily manageable barley core set was identified, demonstrating the great potential for discovering key QTLs and ultimately facilitating barley breeding progress.

Electronic supplementary material

The online version of this article (10.1186/s12863-017-0563-x) contains supplementary material, which is available to authorized users.

Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives

There is a rapidly rising trend in the development and application of molecular marker assays for gene mapping and discovery in field crops and trees. Thus far, more than 50 SNP arrays and 15 different types of genotyping-by-sequencing (GBS) platforms have been developed in over 25 crop species and perennial trees. However, much less effort has been made on developing ultra-high-throughput and cost-effective genotyping platforms for applied breeding programs. In this review, we discuss the scientific bottlenecks in existing SNP arrays and GBS technologies and the strategies to develop targeted platforms for crop molecular breeding. We propose that future practical breeding platforms should adopt automated genotyping technologies, either array or sequencing based, target functional polymorphisms underpinning economic traits, and provide desirable prediction accuracy for quantitative traits, with universal applications under wide genetic backgrounds in crops. The development of such platforms faces serious challenges at both the technological level due to cost ineffectiveness, and the knowledge level due to large genotype-phenotype gaps in crop plants. It is expected that such genotyping platforms will be achieved in the next ten years in major crops in consideration of (a) rapid development in gene discovery of important traits, (b) deepened understanding of quantitative traits through new analytical models and population designs, (c) integration of multi-layer -omics data leading to identification of genes and pathways responsible for important breeding traits, and (d) improvement in cost effectiveness of large-scale genotyping. Crop breeding chips and genotyping platforms will provide unprecedented opportunities to accelerate the development of cultivars with desired yield potential, quality, and enhanced adaptation to mitigate the effects of climate change.