High-throughput genotyping with the GoldenGate assay in the complex genome of soybean

Twisted Sister1: an agravitropic mutant of bread wheat (Triticum aestivum) with altered root and shoot architectures

We identified a mutant of hexaploid wheat (Triticum aestivum) with impaired responses to gravity. The mutant, named Twisted Sister1 (TS1), had agravitropic roots that were often twisted along with altered shoot phenotypes. Roots of TS1 were insensitive to externally applied auxin, with the genetics and physiology suggestive of a mutated AUX/IAA transcription factor gene. Hexaploid wheat possesses over 80 AUX/IAA genes, and sequence information did not identify an obvious candidate. Bulked segregant analysis of an F2 population mapped the mutation to chromosome 5A, and subsequent mapping located the mutation to a 41 Mbp region. RNA-seq identified the TraesCS5A03G0149800 gene encoding a TaAUX/IAA protein to be mutated in the highly conserved domain II motif. We confirmed TraesCS5A03G0149800 as underlying the mutant phenotype by generating transgenic Arabidopsis thaliana. Analysis of RNA-seq data suggested broad similarities between Arabidopsis and wheat for the role of AUX/IAA genes in gravity responses, although there were marked differences. Here we show that the sequenced wheat genome, along with previous knowledge of the physiology of gravity responses from other plant species, gene mapping, RNA-seq, and expression in Arabidopsis have enabled the cloning of a key wheat gene that defines plant architecture.

The auxin efflux carrier PIN1a regulates vascular patterning in cereal roots

Barley (Hordeum vulgare) is an important global cereal crop and a model in genetic studies. Despite advances in characterising barley genomic resources, few mutant studies have identified genes controlling root architecture and anatomy, which plays a critical role in capturing soil resources. Our phenotypic screening of a TILLING mutant collection identified line TM5992 exhibiting a short-root phenotype compared with wild-type (WT) Morex background. Outcrossing TM5992 with barley variety Proctor and subsequent SNP array-based bulk segregant analysis, fine mapped the mutation to a cM scale. Exome sequencing pinpointed a mutation in the candidate gene HvPIN1a, further confirming this by analysing independent mutant alleles. Detailed analysis of root growth and anatomy in Hvpin1a mutant alleles exhibited a slower growth rate, shorter apical meristem and striking vascular patterning defects compared to WT. Expression and mutant analyses of PIN1 members in the closely related cereal brachypodium (Brachypodium distachyon) revealed that BdPIN1a and BdPIN1b were redundantly expressed in root vascular tissues but only Bdpin1a mutant allele displayed root vascular defects similar to Hvpin1a. We conclude that barley PIN1 genes have sub-functionalised in cereals, compared to Arabidopsis (Arabidopsis thaliana), where PIN1a sequences control root vascular patterning.

Identification of Gene-Allele System Conferring Alkali-Tolerance at Seedling Stage in Northeast China Soybean Germplasm

Salinization of cultivated soils may result in either high salt levels or alkaline conditions, both of which stress crops and reduce performance. We sampled genotypes included in the Northeast China soybean germplasm population (NECSGP) to identify possible genes that affect tolerance to alkaline soil conditions. In this study, 361 soybean accessions collected in Northeast China were tested under 220 mM NaHCO3:Na2CO3 = 9:1 (pH = 9.8) to evaluate the alkali-tolerance (ATI) at the seedling stage in Mudanjiang, Heilongjiang, China. The restricted two-stage multi-locus model genome-wide association study (RTM-GWAS) with gene-allele sequences as markers (6503 GASMs) based on simplified genome resequencing (RAD-sequencing) was accomplished. From this analysis, 132 main effect candidate genes with 359 alleles and 35 Gene × Environment genes with 103 alleles were identified, explaining 90.93% and 2.80% of the seedling alkali-tolerance phenotypic variation, respectively. Genetic variability of ATI in NECSGP was observed primarily within subpopulations, especially in ecoregion B, from which 80% of ATI-tolerant accessions were screened out. The biological functions of 132 candidate genes were classified into eight functional categories (defense response, substance transport, regulation, metabolism-related, substance synthesis, biological process, plant development, and unknown function). From the ATI gene-allele system, six key genes-alleles were identified as starting points for further study on understanding the ATI gene network.

A conditional mutation in a wheat (Triticum aestivum L.) gene regulating root morphology

KEY MESSAGE

Characterisation and genetic mapping of a key gene defining root morphology in bread wheat. Root morphology is central to plants for the efficient uptake up of soil water and mineral nutrients. Here we describe a conditional mutant of hexaploid wheat (Triticum aestivum L.) that when grown in soil with high Ca2+ develops a larger rhizosheath accompanied with shorter roots than the wild type. In wheat, rhizosheath size is a reliable surrogate for root hair length and this was verified in the mutant which possessed longer root hairs than the wild type when grown in high Ca2+ soil. We named the mutant Stumpy and showed it to be due to a single semi-dominant mutation. The short root phenotype at high Ca2+ was due to reduced cellular elongation which might also explain the long root hair phenotype. Analysis of root cell walls showed that the polysaccharide composition of Stumpy roots is remodelled when grown at non-permissive (high) Ca2+ concentrations. The mutation mapped to chromosome 7B and sequencing of the 7B chromosomes in both wild type and Stumpy identified a candidate gene underlying the Stumpy mutation. As part of the process to determine whether the candidate gene was causative, we identified wheat lines in a Cadenza TILLING population with large rhizosheaths but accompanied with normal root length. This finding illustrates the potential of manipulating the gene to disconnect root length from root hair length as a means of developing wheat lines with improved efficiency of nutrient and water uptake. The Stumpy mutant will be valuable for understanding the mechanisms that regulate root morphology in wheat.

Identification of genetic loci conferring seed coat color based on a high-density map in soybean

Seed coat color is a typical evolutionary trait. Identification of the genetic loci that control seed coat color during the domestication of wild soybean could clarify the genetic variations between cultivated and wild soybean. We used 276 F10 recombinant inbred lines (RILs) from the cross between a cultivated soybean (JY47) and a wild soybean (ZYD00321) as the materials to identify the quantitative trait loci (QTLs) for seed coat color. We constructed a high-density genetic map using re-sequencing technology. The average distance between adjacent markers was 0.31 cM on this map, comprising 9,083 bin markers. We identified two stable QTLs (qSC08 and qSC11) for seed coat color using this map, which, respectively, explained 21.933 and 26.934% of the phenotypic variation. Two candidate genes (CHS3C and CHS4A) in qSC08 were identified according to the parental re-sequencing data and gene function annotations. Five genes (LOC100786658, LOC100801691, LOC100806824, LOC100795475, and LOC100787559) were predicted in the novel QTL qSC11, which, according to gene function annotations, might control seed coat color. This result could facilitate the identification of beneficial genes from wild soybean and provide useful information to clarify the genetic variations for seed coat color in cultivated and wild soybean.

Identification of superior haplotypes in a diverse natural population for breeding desirable plant height in soybean

KEY MESSAGE

Plant height of soybean is associated with a haplotype block on chromosome 19, which classified 211 soybean accessions into five distinct groups showing significant differences for the target trait. Genetic variation is pivotal for crop improvement. Natural populations are precious genetic resources. However, efficient strategies for the targeted utilization of these resources for quantitative traits, such as plant height (PH), are scarce. Being an important agronomic trait associated with soybean yield and quality, it is imperative to unravel the genetic mechanisms underlying PH in soybean. Here, a genome-wide association study (GWAS) was performed to identify single nucleotide polymorphisms (SNPs) significantly associated with PH in a natural population of 211 cultivated soybeans, which was genotyped with NJAU 355 K Soy SNP Array and evaluated across six environments. A total of 128 SNPs distributed across 17 chromosomes were found to be significantly associated with PH across six environments and a combined environment. Three significant SNPs were consistently identified in at least three environments on Chr.02 (AX-93958260), Chr.17 (AX-94154834), and Chr.19 (AX-93897200). Genomic regions of ~ 130 kb flanking these three consistent SNPs were considered as stable QTLs, which included 169 genes. Of these, 22 genes (including Dt1) were prioritized and defined as putative candidates controlling PH. The genomic region flanking 12 most significant SNPs was in strong linkage disequilibrium (LD). These SNPs formed a single haplotype block containing five haplotypes for PH, namely Hap-A, Hap-B, Hap-C, Hap-D, and Hap-E. Deployment of such superior haplotypes in breeding programs will enable development of improved soybean varieties with desirable plant height.

Dissection of the practical soybean breeding pipeline by developing ZDX1, a high-throughput functional array

KEY MESSAGE

We developed the ZDX1 high-throughput functional soybean array for high accuracy evaluation and selection of both parents and progeny, which can greatly accelerate soybean breeding. Microarray technology facilitates rapid, accurate, and economical genotyping. Here, using resequencing data from 2214 representative soybean accessions, we developed the high-throughput functional array ZDX1, containing 158,959 SNPs, covering 90.92% of soybean genes and sites related to important traits. By application of the array, a total of 817 accessions were genotyped, including three subpopulations of candidate parental lines, parental lines and their progeny from practical breeding. The fixed SNPs were identified in progeny, indicating artificial selection during the breeding process. By identifying functional sites of target traits, novel soybean cyst nematode-resistant progeny and maturity-related novel sources were identified by allele combinations, demonstrating that functional sites provide an efficient method for the rapid screening of desirable traits or gene sources. Notably, we found that the breeding index (BI) was a good indicator for progeny selection. Superior progeny were derived from the combination of distantly related parents, with at least one parent having a higher BI. Furthermore, new combinations based on good performance were proposed for further breeding after excluding redundant and closely related parents. Genomic best linear unbiased prediction (GBLUP) analysis was the best analysis method and achieved the highest accuracy in predicting four traits when comparing SNPs in genic regions rather than whole genomic or intergenic SNPs. The prediction accuracy was improved by 32.1% by using progeny to expand the training population. Collectively, a versatile assay demonstrated that the functional ZDX1 array provided efficient information for the design and optimization of a breeding pipeline for accelerated soybean breeding.

ENHANCED GRAVITROPISM 2 encodes a STERILE ALPHA MOTIF-containing protein that controls root growth angle in barley and wheat

To date, the potential of utilizing root traits in plant breeding remains largely untapped. In this study, we cloned and characterized the ENHANCED GRAVITROPISM2 (EGT2) gene of barley that encodes a STERILE ALPHA MOTIF domain–containing protein. We demonstrated that EGT2 is a key gene of root growth angle regulation in response to gravity, which is conserved in barley and wheat and could be a promising target for crop improvement in cereals.

The root growth angle defines how roots grow toward the gravity vector and is among the most important determinants of root system architecture. It controls water uptake capacity, nutrient use efficiency, stress resilience, and, as a consequence, yield of crop plants. We demonstrated that the egt2 (enhanced gravitropism 2) mutant of barley exhibits steeper root growth of seminal and lateral roots and an auxin-independent higher responsiveness to gravity compared to wild-type plants. We cloned the EGT2 gene by a combination of bulked-segregant analysis and whole genome sequencing. Subsequent validation experiments by an independent CRISPR/Cas9 mutant allele demonstrated that egt2 encodes a STERILE ALPHA MOTIF domain–containing protein. In situ hybridization experiments illustrated that EGT2 is expressed from the root cap to the elongation zone. We demonstrated the evolutionary conserved role of EGT2 in root growth angle control between barley and wheat by knocking out the EGT2 orthologs in the A and B genomes of tetraploid durum wheat. By combining laser capture microdissection with RNA sequencing, we observed that seven expansin genes were transcriptionally down-regulated in the elongation zone. This is consistent with a role of EGT2 in this region of the root where the effect of gravity sensing is executed by differential cell elongation. Our findings suggest that EGT2 is an evolutionary conserved regulator of root growth angle in barley and wheat that could be a valuable target for root-based crop improvement strategies in cereals.

Genome-Wide Association Study for Ultraviolet-B Resistance in Soybean (Glycine max L.)

The depletion of the stratospheric ozone layer is a major environmental issue and has increased the dosage of ultraviolet-B (UV-B) radiation reaching the Earth’s surface. Organisms are negatively affected by enhanced UV-B radiation, and especially in crop plants this may lead to severe yield losses. Soybean (Glycine max L.), a major legume crop, is sensitive to UV-B radiation, and therefore, it is required to breed the UV-B-resistant soybean cultivar. In this study, 688 soybean germplasms were phenotyped for two categories, Damage of Leaf Chlorosis (DLC) and Damage of Leaf Shape (DLS), after supplementary UV-B irradiation for 14 days. About 5% of the germplasms showed strong UV-B resistance, and GCS731 was the most resistant genotype. Their phenotypic distributions showed similar patterns to the normal, suggesting UV-B resistance as a quantitative trait governed by polygenes. A total of 688 soybean germplasms were genotyped using the Axiom^® Soya 180K SNP array, and a genome-wide association study (GWAS) was conducted to identify SNPs significantly associated with the two traits, DLC and DLS. Five peaks on chromosomes 2, 6, 10, and 11 were significantly associated with either DLC or DLS, and the five adjacent genes were selected as candidate genes responsible for UV-B resistance. Among those candidate genes, Glyma.02g017500 and Glyma.06g103200 encode cryptochrome (CRY) and cryptochrome 1 (CRY1), respectively, and are known to play a role in DNA repair during photoreactivation. Real-time quantitative RT-PCR (qRT-PCR) results revealed that CRY1 was expressed significantly higher in the UV-B-resistant soybean compared to the susceptible soybean after 6 h of UV-B irradiation. This study is the first GWAS report on UV-B resistance in soybean, and the results will provide valuable information for breeding UV-B-resistant soybeans in preparation for climate change.

Integration of Infinium and Axiom SNP array data in the outcrossing species Malus × domestica and causes for seemingly incompatible calls

Background

Single nucleotide polymorphism (SNP) array technology has been increasingly used to generate large quantities of SNP data for use in genetic studies. As new arrays are developed to take advantage of new technology and of improved probe design using new genome sequence and panel data, a need to integrate data from different arrays and array platforms has arisen. This study was undertaken in view of our need for an integrated high-quality dataset of Illumina Infinium® 20 K and Affymetrix Axiom® 480 K SNP array data in apple (Malus × domestica). In this study, we qualify and quantify the compatibility of SNP calling, defined as SNP calls that are both accurate and concordant, across both arrays by two approaches. First, the concordance of SNP calls was evaluated using a set of 417 duplicate individuals genotyped on both arrays starting from a set of 10,295 robust SNPs on the Infinium array. Next, the accuracy of the SNP calls was evaluated on additional germplasm (n = 3141) from both arrays using Mendelian inconsistent and consistent errors across thousands of pedigree links. While performing this work, we took the opportunity to evaluate reasons for probe failure and observed discordant SNP calls.

Results

Concordance among the duplicate individuals was on average of 97.1% across 10,295 SNPs. Of these SNPs, 35% had discordant call(s) that were further curated, leading to a final set of 8412 (81.7%) SNPs that were deemed compatible. Compatibility was highly influenced by the presence of alternate probe binding locations and secondary polymorphisms. The impact of the latter was highly influenced by their number and proximity to the 3′ end of the probe.

Conclusions

The Infinium and Axiom SNP array data were mostly compatible. However, data integration required intense data filtering and curation. This work resulted in a workflow and information that may be of use in other data integration efforts. Such an in-depth analysis of array concordance and accuracy as ours has not been previously described in the literature and will be useful in future work on SNP array data integration and interpretation, and in probe/platform development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07565-7.

Identification of QTN and Candidate Gene for Seed-flooding Tolerance in Soybean [Glycine max (L.) Merr.] using Genome-Wide Association Study (GWAS)

Seed-flooding stress is one of the major abiotic constraints severely affecting soybean yield and quality. Understanding the molecular mechanism and genetic basis underlying seed-flooding tolerance will be of greatly importance in soybean breeding. However, very limited information is available about the genetic basis of seed-flooding tolerance in soybean. The present study performed Genome-Wide Association Study (GWAS) to identify the quantitative trait nucleotides (QTNs) associated with three seed-flooding tolerance related traits, viz., germination rate (GR), normal seedling rate (NSR) and electric conductivity (EC), using a panel of 347 soybean lines and the genotypic data of 60,109 SNPs with MAF > 0.05. A total of 25 and 21 QTNs associated with all three traits were identified via mixed linear model (MLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) in three different environments (JP14, HY15, and Combined). Among these QTNs, three major QTNs, viz., QTN13, qNSR-10 and qEC-7-2, were identified through both methods MLM and mrMLM. Interestingly, QTN13 located on Chr.13 has been consistently identified to be associated with all three studied traits in both methods and multiple environments. Within the 1.0 Mb physical interval surrounding the QTN13, nine candidate genes were screened for their involvement in seed-flooding tolerance based on gene annotation information and available literature. Based on the qRT-PCR and sequence analysis, only one gene designated as GmSFT (Glyma.13g248000) displayed significantly higher expression level in all tolerant genotypes compared to sensitive ones under flooding treatment, as well as revealed nonsynonymous mutation in tolerant genotypes, leading to amino acid change in the protein. Additionally, subcellular localization showed that GmSFT was localized in the nucleus and cell membrane. Hence, GmSFT was considered as the most likely candidate gene for seed-flooding tolerance in soybean. In conclusion, the findings of the present study not only increase our knowledge of the genetic control of seed-flooding tolerance in soybean, but will also be of great utility in marker-assisted selection and gene cloning to elucidate the mechanisms of seed-flooding tolerance.

Deciphering the Genetic Architecture of Plant Height in Soybean Using Two RIL Populations Sharing a Common M8206 Parent

Plant height (PH) is an important agronomic trait that is closely related to soybean yield and quality. However, it is a complex quantitative trait governed by multiple genes and is influenced by environment. Unraveling the genetic mechanism involved in PH, and developing soybean cultivars with desirable PH is an imperative goal for soybean breeding. In this regard, the present study used high-density linkage maps of two related recombinant inbred line (RIL) populations viz., MT and ZM evaluated in three different environments to detect additive and epistatic effect quantitative trait loci (QTLs) as well as their interaction with environments for PH in Chinese summer planting soybean. A total of eight and 12 QTLs were detected by combining the composite interval mapping (CIM) and mixed-model based composite interval mapping (MCIM) methods in MT and ZM populations, respectively. Among these QTLs, nine QTLs viz., QPH-2, qPH-6-2_MT, QPH-6, qPH-9-1_ZM, qPH-10-1_ZM, qPH-13-1_ZM, qPH-16-1_MT, QPH-17 and QPH-19 were consistently identified in multiple environments or populations, hence were regarded as stable QTLs. Furthermore, Out of these QTLs, three QTLs viz., qPH-4-2_ZM, qPH-15-1_MT and QPH-17 were novel. In particular, QPH-17 could detect in both populations, which was also considered as a stable and major QTL in Chinese summer planting soybean. Moreover, eleven QTLs revealed significant additive effects in both populations, and out of them only six showed additive by environment interaction effects, and the environment-independent QTLs showed higher additive effects. Finally, six digenic epistatic QTLs pairs were identified and only four additive effect QTLs viz., qPH-6-2_MT, qPH-19-1_MT/QPH-19, qPH-5-1_ZM and qPH-17-1_ZM showed epistatic effects. These results indicate that environment and epistatic interaction effects have significant influence in determining genetic basis of PH in soybean. These results would not only increase our understanding of the genetic control of plant height in summer planting soybean but also provide support for implementing marker assisted selection (MAS) in developing cultivars with ideal plant height as well as gene cloning to elucidate the mechanisms of plant height.

Association Mapping Analysis for Fruit Quality Traits in Prunus persica Using SNP Markers

The identification of genes involved in variation of peach fruit quality would assist breeders to create new cultivars with improved fruit quality. Peach is a genetic and genomic model within the Rosaceae. A large quantity of useful data suitable for fine mapping using Single Nucleotide Polymorphisms (SNPs) from the peach genome sequence was used in this study. A set of 94 individuals from a peach germplasm collection was phenotyped and genotyped, including local Spanish and modern cultivars maintained at the Experimental Station of Aula Dei, Spain. Phenotypic evaluation based on agronomical, pomological and fruit quality traits was performed at least 3 years. A set of 4,558 out of a total of 8,144 SNPs markers developed by the Illumina Infinium BeadArray (v1.0) technology platform, covering the peach genome, were analyzed for population structure analysis and genome-wide association studies (GWAS). Population structure analysis identified two subpopulations, with admixture within them. While one subpopulation contains only modern cultivars, the other one is formed by local Spanish and several modern cultivars from international breeding programs. To test the marker trait associations between markers and phenotypic traits, four models comprising both general linear model (GLM) and mixed linear model (MLM) were selected. The MLM approach using co-ancestry values from population structure and kinship estimates (K model) identified a maximum of 347 significant associations between markers and traits. The associations found appeared to map within the interval where many candidate genes involved in different pathways are predicted in the peach genome. These results represent a promising situation for GWAS in the identification of SNP variants associated to fruit quality traits, potentially applicable in peach breeding programs.

Genome-Wide Association Studies for Dynamic Plant Height and Number of Nodes on the Main Stem in Summer Sowing Soybeans

Plant height (PH) and the number of nodes on the main stem (NN) serve as major plant architecture traits affecting soybean seed yield. Although many quantitative trait loci for the two traits have been reported, their genetic controls at different developmental stages in soybeans remain unclear. Here, 368 soybean breeding lines were genotyped using 62,423 single nucleotide polymorphism (SNP) markers and phenotyped for the two traits at three different developmental stages over two locations in order to identify their quantitative trait nucleotides (QTNs) using compressed mixed linear model (CMLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) approaches. As a result, 11 and 13 QTNs were found by CMLM to be associated with PH and NN, respectively. Among these QTNs, 8, 3, and 4 for PH and 6, 6, and 8 for NN were found at the three stages, and 3 and 6 were repeatedly detected for PH and NN. In addition, 34 and 30 QTNs were found by mrMLM to be associated with PH and NN, respectively. Among these QTNs, 11, 13, and 16 for PH and 11, 15, and 8 for NN were found at the three stages. A majority of these QTNs overlapped with the previously reported loci. Moreover, one QTN within the known E2 locus for flowering time was detected for the two traits at all three stages, and another that overlapped with the Dt1 locus for stem growth habit was also identified for the two traits at the mature stage. This may explain the highly significant correlation between the two traits. Our findings provide evidence for mixed major plus polygenes inheritance for dynamic traits and an extended understanding of their genetic architecture for molecular dissection and breeding utilization in soybeans.

Accelerating genetic gains in legumes for the development of prosperous smallholder agriculture: integrating genomics, phenotyping, systems modelling and agronomy

Grain legumes form an important component of the human diet, provide feed for livestock, and replenish soil fertility through biological nitrogen fixation. Globally, the demand for food legumes is increasing as they complement cereals in protein requirements and possess a high percentage of digestible protein. Climate change has enhanced the frequency and intensity of drought stress, posing serious production constraints, especially in rainfed regions where most legumes are produced. Genetic improvement of legumes, like other crops, is mostly based on pedigree and performance-based selection over the past half century. To achieve faster genetic gains in legumes in rainfed conditions, this review proposes the integration of modern genomics approaches, high throughput phenomics, and simulation modelling in support of crop improvement that leads to improved varieties that perform with appropriate agronomy. Selection intensity, generation interval, and improved operational efficiencies in breeding are expected to further enhance the genetic gain in experimental plots. Improved seed access to farmers, combined with appropriate agronomic packages in farmers' fields, will deliver higher genetic gains. Enhanced genetic gains, including not only productivity but also nutritional and market traits, will increase the profitability of farming and the availability of affordable nutritious food especially in developing countries.

Mapping of new quantitative trait loci for sudden death syndrome and soybean cyst nematode resistance in two soybean populations

KEY MESSAGE

Novel QTL conferring resistance to both the SDS and SCN was detected in two RIL populations. Dual resistant RILs could be used in breeding programs for developing resistant soybean cultivars. Soybean cultivars, susceptible to the fungus Fusarium virguliforme, which causes sudden death syndrome (SDS), and to the soybean cyst nematode (SCN) (Heterodera glycines), suffer yield losses valued over a billion dollars annually. Both pathogens may occur in the same production fields. Planting of cultivars genetically resistant to both pathogens is considered one of the most effective means to control the two pathogens. The objective of the study was to map quantitative trait loci (QTL) underlying SDS and SCN resistances. Two recombinant inbred line (RIL) populations were developed by crossing 'A95-684043', a high-yielding maturity group (MG) II line resistant to SCN, with 'LS94-3207' and 'LS98-0582' of MG IV, resistant to both F. virguliforme and SCN. Two hundred F7 derived recombinant inbred lines from each population AX19286 (A95-684043 × LS94-3207) and AX19287 (A95-684043 × LS98-0582) were screened for resistance to each pathogen under greenhouse conditions. Five hundred and eighty and 371 SNP markers were used for mapping resistance QTL in each population. In AX19286, one novel SCN resistance QTL was mapped to chromosome 8. In AX19287, one novel SDS resistance QTL was mapped to chromosome 17 and one novel SCN resistance QTL was mapped to chromosome 11. Previously identified additional SDS and SCN resistance QTL were also detected in the study. Lines possessing superior resistance to both pathogens were also identified and could be used as germplasm sources for breeding SDS- and SCN-resistant soybean cultivars.

Revolution in Genotyping Platforms for Crop Improvement

In the past decade, the application of high-throughput sequencing to crop genotyping has given rise to novel platforms capable of genotyping tens of thousands of genome-wide DNA markers. Coupled with the decreasing costs of sequencing, this rapid increase in markers allows accelerated and highly accurate genotyping of entire crop populations and diversity sets using single nucleotide polymorphisms (SNPs). These revolutionary advances accelerate crop improvement by facilitating a more precise connection of phenotype to genotype through association studies, linkage mapping and diversity analysis. The platforms driving the advances in genotyping are array technologies and genotyping by sequencing (GBS) methods, which include both low-coverage whole genome resequencing (skim sequencing) and reduced representation sequencing (RRS) approaches. Here, we outline and compare these genotyping platforms and provide a perspective on the promising future of crop genotyping. While SNP arrays provide high quality, simple handling, and unchallenging analysis, the lower cost of RRS and the greater data volume produced by skim sequencing suggest that use of GBS will become more prevalent in crop genomics as sequencing costs decrease and data analysis becomes more streamlined. Graphical Abstract.

Identification of Major Quantitative Trait Loci for Seed Oil Content in Soybeans by Combining Linkage and Genome-Wide Association Mapping

Soybean oil is the most widely produced vegetable oil in the world and its content in soybean seed is an important quality trait in breeding programs. More than 100 quantitative trait loci (QTLs) for soybean oil content have been identified. However, most of them are genotype specific and/or environment sensitive. Here, we used both a linkage and association mapping methodology to dissect the genetic basis of seed oil content of Chinese soybean cultivars in various environments in the Jiang-Huai River Valley. One recombinant inbred line (RIL) population (NJMN-RIL), with 104 lines developed from a cross between M8108 and NN1138-2, was planted in five environments to investigate phenotypic data, and a new genetic map with 2,062 specific-locus amplified fragment markers was constructed to map oil content QTLs. A derived F2 population between MN-5 (a line of NJMN-RIL) and NN1138-2 was also developed to confirm one major QTL. A soybean breeding germplasm population (279 lines) was established to perform a genome-wide association study (GWAS) using 59,845 high-quality single nucleotide polymorphism markers. In the NJMN-RIL population, 8 QTLs were found that explained a range of phenotypic variance from 6.3 to 26.3% in certain planting environments. Among them, qOil-5-1, qOil-10-1, and qOil-14-1 were detected in different environments, and qOil-5-1 was further confirmed using the secondary F2 population. Three loci located on chromosomes 5 and 20 were detected in a 2-year long GWAS, and one locus that overlapped with qOil-5-1 was found repeatedly and treated as the same locus. qOil-5-1 was further localized to a linkage disequilibrium block region of approximately 440 kb. These results will not only increase our understanding of the genetic control of seed oil content in soybean, but will also be helpful in marker-assisted selection for breeding high seed oil content soybean and gene cloning to elucidate the mechanisms of seed oil content.

Characterization and genetics of multiple soybean aphid biotype resistance in five soybean plant introductions

KEY MESSAGE

Five soybean plant introductions expressed antibiosis resistance to multiple soybean aphid biotypes. Two introductions had resistance genes located in the Rag1, Rag2, and Rag3 regions; one introduction had resistance genes located in the Rag1, Rag2, and rag4 regions; one introduction had resistance genes located in the Rag1 and Rag2 regions; and one introduction had a resistance gene located in the Rag2 region. Soybean aphid (Aphis glycines Matsumura) is the most important soybean [Glycine max (L.) Merr.] insect pest in the USA. The objectives of this study were to characterize the resistance expressed in five plant introductions (PIs) to four soybean aphid biotypes, determine the mode of resistance inheritance, and identify markers associated with genes controlling resistance in these accessions. Five soybean PIs, from an initial set of 3000 PIs, were tested for resistance against soybean aphid biotypes 1, 2, 3, and 4 in choice and no-choice tests. Of these five PIs, PI 587663, PI 587677, and PI 587685 expressed antibiosis against all four biotypes, while PI 587972 and PI 594592 expressed antibiosis against biotypes 1, 2, and 3. F2 populations derived from PI 587663 and PI 587972 were evaluated for resistance against soybean aphid biotype 1, and populations derived from PIs 587677, 587685, and 594592 were tested against biotype 3. In addition, F2:3 plants were tested against biotypes 2 and 3. Genomic DNA from F2 plants was screened with markers linked to Rag1, Rag2, Rag3, and rag4 soybean aphid-resistance genes. Results showed that PI 587663 and PI 594592 each had three genes with variable gene action located in the Rag1, Rag2, and Rag3 regions. PI 587677 had three genes with variable gene action located in the Rag1, Rag2 and rag4 regions. PI 587685 had one dominant gene located in the Rag1 region and an additive gene in the Rag2 region. PI 587972 had one dominant gene located in the Rag2 region controlling antixenosis- or antibiosis-type resistance to soybean aphid biotypes 1, 2, or 3. PIs 587663, 587677, and 587685 also showed antibiosis-type resistance against biotype 4. Information on multi-biotype aphid resistance and resistance gene markers will be useful for improving soybean aphid resistance in commercial soybean cultivars.

Fine mapping of a Phytophthora-resistance gene RpsWY in soybean (Glycine max L.) by high-throughput genome-wide sequencing

KEY MESSAGE

Using a combination of phenotypic screening, genetic and statistical analyses, and high-throughput genome-wide sequencing, we have finely mapped a dominant Phytophthora resistance gene in soybean cultivar Wayao. Phytophthora root rot (PRR) caused by Phytophthora sojae is one of the most important soil-borne diseases in many soybean-production regions in the world. Identification of resistant gene(s) and incorporating them into elite varieties are an effective way for breeding to prevent soybean from being harmed by this disease. Two soybean populations of 191 F2 individuals and 196 F7:8 recombinant inbred lines (RILs) were developed to map Rps gene by crossing a susceptible cultivar Huachun 2 with the resistant cultivar Wayao. Genetic analysis of the F2 population indicated that PRR resistance in Wayao was controlled by a single dominant gene, temporarily named RpsWY, which was mapped on chromosome 3. A high-density genetic linkage bin map was constructed using 3469 recombination bins of the RILs to explore the candidate genes by the high-throughput genome-wide sequencing. The results of genotypic analysis showed that the RpsWY gene was located in bin 401 between 4466230 and 4502773 bp on chromosome 3 through line 71 and 100 of the RILs. Four predicted genes (Glyma03g04350, Glyma03g04360, Glyma03g04370, and Glyma03g04380) were found at the narrowed region of 36.5 kb in bin 401. These results suggest that the high-throughput genome-wide resequencing is an effective method to fine map PRR candidate genes.

Gene-based SNP discovery in tepary bean (Phaseolus acutifolius) and common bean (P. vulgaris) for diversity analysis and comparative mapping

Background

Common bean (Phaseolus vulgaris) is an important grain legume and there has been a recent resurgence in interest in its relative, tepary bean (P. acutifolius), owing to this species’ ability to better withstand abiotic stresses. Genomic resources are scarce for this minor crop species and a better knowledge of the genome-level relationship between these two species would facilitate improvement in both. High-throughput genotyping has facilitated large-scale single nucleotide polymorphism (SNP) identification leading to the development of molecular markers with associated sequence information that can be used to place them in the context of a full genome assembly.

Results

Transcript-based SNPs were identified from six common bean and two tepary bean accessions and a subset were used to generate a 768-SNP Illumina GoldenGate assay for each species. The tepary bean assay was used to assess diversity in wild and cultivated tepary bean and to generate the first gene-based map of the tepary bean genome. Genotypic analyses of the diversity panel showed a clear separation between domesticated and cultivated tepary beans, two distinct groups within the domesticated types, and P. parvifolius was confirmed to be distinct. The genetic map of tepary bean was compared to the common bean genome assembly to demonstrate high levels of collinearity between the two species with differences limited to a few intra-chromosomal rearrangements.

Conclusions

The development of the first set of genomic resources specifically for tepary bean has allowed for greater insight into the structure of this species and its relationship to its agriculturally more prominent relative, common bean. These resources will be helpful in the development of efficient breeding strategies for both species and will facilitate the introgression of agriculturally important traits from one crop into the other.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2499-3) contains supplementary material, which is available to authorized users.

Quantitative trait loci underlying host responses of soybean to Fusarium virguliforme toxins that cause foliar sudden death syndrome

KEY MESSAGE

Soybean deploys multiple genetic mechanisms to confer tolerance to Fusarium virguliforme toxins. This study revealed that F. virguliforme culture filtrates could be used in mapping QTL underlying foliar SDS resistance. Sudden death syndrome (SDS) is a major soybean disease throughout most of the soybean growing regions in the world including the United States. The disease is caused by the fungal pathogen, Fusarium virguliforme (Fv). The fungus produces several toxins that are responsible for development of interveinal leaf chlorosis and necrosis, which are typical foliar SDS symptoms. Growing of resistant cultivars has been the most effective method in controlling the disease. The objective of the present study was to identify quantitative trait loci (QTL) underlying host responses of soybean to Fv toxins present in culture filtrates. To accomplish this objective, two recombinant inbred line (RIL) populations, AX19286 (A95-684043 × LS94-3207) and AX19287 (A95-684043 × LS98-0582), segregating for SDS resistance were evaluated for foliar symptom development by applying two screening protocols, the stem cutting and the root feeding assays. The AX19286 population revealed two major and seven minor QTL for SDS resistance. In the AX19287 population, we identified five major QTL and three minor QTL. The two QTL mapped to Chromosome 7 [molecular linkage group (MLG) M] and Chromosome 20 (MLG I) are most likely novel, and were detected through screening of the AX19287 population with stem cutting and root feeding assays, respectively. This study established that Fv culture filtrates could be employed in mapping QTL underlying foliar SDS resistance. The outcomes of the research also suggest that multiple genetic mechanisms might be used by soybean to overcome the toxic effects of the toxins secreted by the pathogen into culture filtrates.

High density linkage mapping of genomic and transcriptomic SNPs for synteny analysis and anchoring the genome sequence of chickpea

This study presents genome-wide discovery of SNPs through next generation sequencing of the genome of Cicer reticulatum. Mapping of the C. reticulatum sequenced reads onto the draft genome assembly of C. arietinum (desi chickpea) resulted in identification of 842,104 genomic SNPs which were utilized along with an additional 36,446 genic SNPs identified from transcriptome sequences of the aforementioned varieties. Two new chickpea Oligo Pool All (OPAs) each having 3,072 SNPs were designed and utilized for SNP genotyping of 129 Recombinant Inbred Lines (RILs). Using Illumina GoldenGate Technology genotyping data of 5,041 SNPs were generated and combined with the 1,673 marker data from previously published studies, to generate a high resolution linkage map. The map comprised of 6698 markers distributed on eight linkage groups spanning 1083.93 cM with an average inter-marker distance of 0.16 cM. Utility of the present map was demonstrated for improving the anchoring of the earlier reported draft genome sequence of desi chickpea by ~30% and that of kabuli chickpea by 18%. The genetic map reported in this study represents the most dense linkage map of chickpea , with the potential to facilitate efficient anchoring of the draft genome sequences of desi as well as kabuli chickpea varieties.

A bi-filtering method for processing single nucleotide polymorphism array data improves the quality of genetic map and accuracy of quantitative trait locus mapping in doubled haploid populations of polyploid Brassica napus

Background

Single nucleotide polymorphism (SNP) markers have a wide range of applications in crop genetics and genomics. Due to their polyploidy nature, many important crops, such as wheat, cotton and rapeseed contain a large amount of repeat and homoeologous sequences in their genomes, which imposes a huge challenge in high-throughput genotyping with sequencing and/or array technologies. Allotetraploid Brassica napus (AACC, 2n = 4x = 38) comprises of two highly homoeologous sub-genomes derived from its progenitor species B. rapa (AA, 2n = 2x = 20) and B. oleracea (CC, 2n = 2x = 18), and is an ideal species to exploit methods for reducing the interference of extensive inter-homoeologue polymorphisms (mHemi-SNPs and Pseudo-simple SNPs) between closely related sub-genomes.

Results

Based on a recent B. napus 6K SNP array, we developed a bi-filtering procedure to identify unauthentic lines in a DH population, and mHemi-SNPs and Pseudo-simple SNPs in an array data matrix. The procedure utilized both monomorphic and polymorphic SNPs in the DH population and could effectively distinguish the mHemi-SNPs and Pseudo-simple SNPs that resulted from superposition of the signals from multiple SNPs. Compared with conventional procedure for array data processing, the bi-filtering method could minimize the pseudo linkage relationship caused by the mHemi-SNPs and Pseudo-simple SNPs, thus improving the quality of SNP genetic map. Furthermore, the improved genetic map could increase the accuracies of mapping of QTLs as demonstrated by the ability to eliminate non-real QTLs in the mapping population.

Conclusions

The bi-filtering analysis of the SNP array data represents a novel approach to effectively assigning the multi-loci SNP genotypes in polyploid B. napus and may find wide applications to SNP analyses in polyploid crops.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1559-4) contains supplementary material, which is available to authorized users.

QTL for seed protein and amino acids in the Benning × Danbaekkong soybean population

KEY MESSAGE

We identified QTL associated with protein and amino acids in a soybean mapping population that was grown in five environments. These QTL could be used in MAS to improve these traits. Soybean, rather than nitrogen-containing forages, is the primary source of quality protein in feed formulations for domestic swine, poultry, and dairy industries. As a sole dietary source of protein, soybean is deficient in the amino acids lysine (Lys), threonine (Thr), methionine (Met), and cysteine (Cys). Increasing these amino acids would benefit the feed industry. The objective of the present study was to identify quantitative trait loci (QTL) associated with crude protein (cp) and amino acids in the 'Benning' × 'Danbaekkong' population. The population was grown in five southern USA environments. Amino acid concentrations as a fraction of cp (Lys/cp, Thr/cp, Met/cp, Cys/cp, and Met + Cys/cp) were determined by near-infrared reflectance spectroscopy. Four QTL associated with the variation in crude protein were detected on chromosomes (Chr) 14, 15, 17, and 20, of which, a QTL on Chr 20 explained 55 % of the phenotypic variation. In the same chromosomal region, QTL for Lys/cp, Thr/cp, Met/cp, Cys/cp and Met + Cys/cp were detected. At these QTL, the Danbaekkong allele resulted in reduced levels of these amino acids and increased protein concentration. Two additional QTL for Lys/cp were detected on Chr 08 and 20, and three QTL for Thr/cp on Chr 01, 09, and 17. Three QTL were identified on Chr 06, 09 and 10 for Met/cp, and one QTL was found for Cys/cp on Chr 10. The study provides information concerning the relationship between crude protein and levels of essential amino acids and may allow for the improvement of these traits in soybean using marker-assisted selection.

A combinatorial approach of comprehensive QTL-based comparative genome mapping and transcript profiling identified a seed weight-regulating candidate gene in chickpea

High experimental validation/genotyping success rate (94-96%) and intra-specific polymorphic potential (82-96%) of 1536 SNP and 472 SSR markers showing in silico polymorphism between desi ICC 4958 and kabuli ICC 12968 chickpea was obtained in a 190 mapping population (ICC 4958 × ICC 12968) and 92 diverse desi and kabuli genotypes. A high-density 2001 marker-based intra-specific genetic linkage map comprising of eight LGs constructed is comparatively much saturated (mean map-density: 0.94 cM) in contrast to existing intra-specific genetic maps in chickpea. Fifteen robust QTLs (PVE: 8.8-25.8% with LOD: 7.0-13.8) associated with pod and seed number/plant (PN and SN) and 100 seed weight (SW) were identified and mapped on 10 major genomic regions of eight LGs. One of 126.8 kb major genomic region harbouring a strong SW-associated robust QTL (Caq'SW1.1: 169.1-171.3 cM) has been delineated by integrating high-resolution QTL mapping with comprehensive marker-based comparative genome mapping and differential expression profiling. This identified one potential regulatory SNP (G/A) in the cis-acting element of candidate ERF (ethylene responsive factor) TF (transcription factor) gene governing seed weight in chickpea. The functionally relevant molecular tags identified have potential to be utilized for marker-assisted genetic improvement of chickpea.

Unlimited Thirst for Genome Sequencing, Data Interpretation, and Database Usage in Genomic Era: The Road towards Fast-Track Crop Plant Improvement

The number of sequenced crop genomes and associated genomic resources is growing rapidly with the advent of inexpensive next generation sequencing methods. Databases have become an integral part of all aspects of science research, including basic and applied plant and animal sciences. The importance of databases keeps increasing as the volume of datasets from direct and indirect genomics, as well as other omics approaches, keeps expanding in recent years. The databases and associated web portals provide at a minimum a uniform set of tools and automated analysis across a wide range of crop plant genomes. This paper reviews some basic terms and considerations in dealing with crop plant databases utilization in advancing genomic era. The utilization of databases for variation analysis with other comparative genomics tools, and data interpretation platforms are well described. The major focus of this review is to provide knowledge on platforms and databases for genome-based investigations of agriculturally important crop plants. The utilization of these databases in applied crop improvement program is still being achieved widely; otherwise, the end for sequencing is not far away.

SNP discovery in complex allotetraploid genomes (Gossypium spp., Malvaceae) using genotyping by sequencing

PREMISE OF THE STUDY

Single-nucleotide polymorphism (SNP) marker discovery in plants with complex allotetraploid genomes is often confounded by the presence of homeologous loci (along with paralogous and orthologous loci). Here we present a strategy to filter for SNPs representing orthologous loci.

METHODS AND RESULTS

Using Illumina next-generation sequencing, 54 million reads were collected from restriction enzyme-digested DNA libraries of a diversity of Gossypium taxa. Loci with one to three SNPs were discovered using the Stacks software package, yielding 25,529 new cotton SNP combinations, including those that are polymorphic at both interspecific and intraspecific levels. Frequencies of predicted dual-homozygous (aa/bb) marker polymorphisms ranged from 6.7-11.6% of total shared fragments in intraspecific comparisons and from 15.0-16.4% in interspecific comparisons.

CONCLUSIONS

This resource provides dual-homozygous (aa/bb) marker polymorphisms. Both in silico and experimental validation efforts demonstrated that these markers are enriched for single orthologous loci that are homozygous for alternative alleles.

Development, validation and genetic analysis of a large soybean SNP genotyping array

Cultivated soybean (Glycine max) suffers from a narrow germplasm relative to other crop species, probably because of under-use of wild soybean (Glycine soja) as a breeding resource. Use of a single nucleotide polymorphism (SNP) genotyping array is a promising method for dissecting cultivated and wild germplasms to identify important adaptive genes through high-density genetic mapping and genome-wide association studies. Here we describe a large soybean SNP array for use in diversity analyses, linkage mapping and genome-wide association analyses. More than four million high-quality SNPs identified from high-depth genome re-sequencing of 16 soybean accessions and low-depth genome re-sequencing of 31 soybean accessions were used to select 180,961 SNPs for creation of the Axiom(®) SoyaSNP array. Validation analysis for a set of 222 diverse soybean lines showed that 170,223 markers were of good quality for genotyping. Phylogenetic and allele frequency analyses of the validation set data indicated that accessions showing an intermediate morphology between cultivated and wild soybeans collected in Korea were natural hybrids. More than 90 unanchored scaffolds in the current soybean reference sequence were assigned to chromosomes using this array. Finally, dense average spacing and preferential distribution of the SNPs in gene-rich chromosomal regions suggest that this array may be suitable for genome-wide association studies of soybean germplasm. Taken together, these results suggest that use of this array may be a powerful method for soybean genetic analyses relating to many aspects of soybean breeding.

Use of the Illumina GoldenGate assay for single nucleotide polymorphism (SNP) genotyping in cereal crops

Highly parallel genotyping assays, such as the GoldenGate assay developed by Illumina, capable of interrogating up to 3,072 single nucleotide polymorphisms (SNPs) simultaneously, have greatly facilitated genome-wide studies, particularly for crops with large and complex genome structures. In this report, we provide detailed information and guidelines regarding genomic DNA preparation, SNP assay design, SNP assay protocols, and genotype calling using Illumina's GenomeStudio software.

Identification of quantitative trait loci underlying resistance to southern root-knot and reniform nematodes in soybean accession PI 567516C

Soybean cyst nematode (SCN, Heterodera glycine Ichinohe), southern root-knot nematode [SRKN, Meloidogyne incognita (Kofoid and White) Chitwood] and reniform nematode (RN, Rotylenchulus reniformis Linford and Oliveira) are three important plant-parasitic pests in soybean. Previous study showed that plant introduction (PI) 567516C harbored novel quantitative trait loci (QTL) conferring SCN resistance to soybean. However, QTL underlying resistance to SRKN and RN in PI 567516C remain unknown. The objectives of this study were to identify QTL for resistance to SRKN and RN in PI 567516C. Two hundred and forty-seven F_6:9 recombinant inbred lines, derived from a cross between cultivar Magellan and PI 567516C, were evaluated for resistance to SRKN and RN. Two hundred and thirty-eight simple sequence repeats and 687 single nucleotide polymorphism markers were used to construct a genetic linkage map. Three significant QTL associated with resistance to SRKN were mapped on chromosomes (Chrs.) 10, 13 and 17. Two significant QTL associated with resistance to RN were detected on Chrs. 11 and 18. Whole-genome resequencing revealed that there might be Peking-type Rhg1 in PI 567516C. Our study provides useful information to employ PI 567516C in soybean breeding in order to develop new cultivars with resistance to multiple nematodes.

Identification and evaluation of quantitative trait loci underlying resistance to multiple HG types of soybean cyst nematode in soybean PI 437655

KEY MESSAGE

We performed QTL analysis for SCN resistance in PI 437655 in two mapping populations, characterized CNV of Rhg1 through whole-genome resequencing and evaluated the effects of QTL pyramiding to enhance resistance. Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most serious pests of soybean worldwide. PI 437655 has broader resistance to SCN HG types than PI 88788. The objectives of this study were to identify quantitative trait loci (QTL) underlying SCN resistance in PI 437655, and to evaluate the QTL for their contribution to SCN resistance. Two F6:7 recombinant inbred line populations, derived from cv. Williams 82 × PI 437655 and cv. Hutcheson × PI 437655 crosses, were evaluated for resistance to SCN HG types 1.2.5.7 (PA2), 0 (PA3), 1.3.5.6.7 (PA14), and 1.2.3.4.5.6.7 (LY2). The 1,536 SNP array was used to genotype the mapping populations and construct genetic linkage maps. Two significant QTL were consistently mapped on chromosomes (Chr.) 18 and 20 in these two populations. One QTL on Chr. 18, which corresponds to the known Rhg1 locus, contributed resistance to SCN HG types 1.2.5.7, 0, 1.3.5.6.7, and 1.2.3.4.5.6.7 (PA2, PA3, PA14, and LY2, respectively). Copy number variation (CNV) analysis by whole-genome resequencing showed that PI 437655 and PI 88788 had similar CNV at the Rhg1 locus. The QTL on Chr. 20 contributed resistance to SCN HG types 1.3.5.6.7 (PA14) and 1.2.3.4.5.6.7 (LY2). Evaluation of both QTL showed that pyramiding of Rhg1 and the QTL on Chr. 20 significantly improved the resistance to SCN HG types 1.3.5.6.7 (PA14) and 1.2.3.4.5.6.7 (LY2) in both populations. Our studies provided useful information for deploying PI 437655 as a donor for SCN resistance in soybean breeding through marker-assisted selection.

Identification of quantitative trait loci for phosphorus use efficiency traits in rice using a high density SNP map

Background

Soil phosphorus (P) deficiency is one of the major limiting factors to crop production. The development of crop varieties with improved P use efficiency (PUE) is an important strategy for sustainable agriculture. The objectives of this research were to identify quantitative trait loci (QTLs) linked to PUE traits using a high-density single nucleotide polymorphism (SNP) map and to estimate the epistatic interactions and environmental effects in rice (Oryza sativa L.).

Results

We conducted a two-year field experiment under low and normal P conditions using a recombinant inbred population of rice derived from Zhenshan 97 and Minghui 63 (indica). We investigated three yield traits, biomass (BIOM), harvest index (HI), and grain yield (Yield), and eight PUE traits: total P uptake (PUP), P harvest index (PHI), grain P use efficiency (gPUE) based on P accumulation in grains, straw P use efficiency (strPUE) based on P accumulation in straw, P use efficiency for biomass (PUEb) and for grain yield (PUEg) based on P accumulation in the whole plant, P translocation (PT), and P translocation efficiency (PTE). Of the 36 QTLs and 24 epistatic interactions identified, 26 QTLs and 12 interactions were detected for PUE traits. The environment affected seven QTLs and three epistatic interactions. Four QTLs (qPHI1 and qPHI2 for PHI, qPUEg2 for PUEg, and qPTE8 for PTE) with strong effects were environmentally independent. By comparing our results with similar QTLs in previous studies, three QTLs for PUE traits (qPUP1 and qPUP10 for PUP, and qPHI6 for PHI) were found across various genetic backgrounds. Seven regions were shared by QTLs for yield and PUE traits.

Conclusion

Most QTLs linked to PUE traits were different from those linked to yield traits, suggesting different genetic controls underlying these two traits. Those chromosomal regions with large effects that are not affected by different environments are promising for improving P use efficiency. The seven regions shared by QTLs linked to yield and PUE traits imply the possibility of the simultaneous improvement of yield and PUE traits.

Assessment of genetic variation within a global collection of lentil (Lens culinaris Medik.) cultivars and landraces using SNP markers

Background

Lentil is a self-pollinated annual diploid (2n = 2× = 14) crop with a restricted history of genetic improvement through breeding, particularly when compared to cereal crops. This limited breeding has probably contributed to the narrow genetic base of local cultivars, and a corresponding potential to continue yield increases and stability. Therefore, knowledge of genetic variation and relationships between populations is important for understanding of available genetic variability and its potential for use in breeding programs. Single nucleotide polymorphism (SNP) markers provide a method for rapid automated genotyping and subsequent data analysis over large numbers of samples, allowing assessment of genetic relationships between genotypes.

Results

In order to investigate levels of genetic diversity within lentil germplasm, 505 cultivars and landraces were genotyped with 384 genome-wide distributed SNP markers, of which 266 (69.2%) obtained successful amplification and detected polymorphisms. Gene diversity and PIC values varied between 0.108-0.5 and 0.102-0.375, with averages of 0.419 and 0.328, respectively. On the basis of clarity and interest to lentil breeders, the genetic structure of the germplasm collection was analysed separately for cultivars and landraces. A neighbour-joining (NJ) dendrogram was constructed for commercial cultivars, in which lentil cultivars were sorted into three major groups (G-I, G-II and G-III). These results were further supported by principal coordinate analysis (PCoA) and STRUCTURE, from which three clear clusters were defined based on differences in geographical location. In the case of landraces, a weak correlation between geographical origin and genetic relationships was observed. The landraces from the Mediterranean region, predominantly Greece and Turkey, revealed very high levels of genetic diversity.

Conclusions

Lentil cultivars revealed clear clustering based on geographical origin, but much more limited correlation between geographic origin and genetic diversity was observed for landraces. These results suggest that selection of divergent parental genotypes for breeding should be made actively on the basis of systematic assessment of genetic distance between genotypes, rather than passively based on geographical distance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-014-0150-3) contains supplementary material, which is available to authorized users.

Genome-wide SNP-genotyping array to study the evolution of the human pathogen Vibrio vulnificus biotype 3

Vibrio vulnificus is an aquatic bacterium and an important human pathogen. Strains of V. vulnificus are classified into three different biotypes. The newly emerged biotype 3 has been found to be clonal and restricted to Israel. In the family Vibrionaceae, horizontal gene transfer is the main mechanism responsible for the emergence of new pathogen groups. To better understand the evolution of the bacterium, and in particular to trace the evolution of biotype 3, we performed genome-wide SNP genotyping of 254 clinical and environmental V. vulnificus isolates with worldwide distribution recovered over a 30-year period, representing all phylogeny groups. A custom single-nucleotide polymorphism (SNP) array implemented on the Illumina GoldenGate platform was developed based on 570 SNPs randomly distributed throughout the genome. In general, the genotyping results divided the V. vulnificus species into three main phylogenetic lineages and an additional subgroup, clade B, consisting of environmental and clinical isolates from Israel. Data analysis suggested that 69% of biotype 3 SNPs are similar to SNPs from clade B, indicating that biotype 3 and clade B have a common ancestor. The rest of the biotype 3 SNPs were scattered along the biotype 3 genome, probably representing multiple chromosomal segments that may have been horizontally inserted into the clade B recipient core genome from other phylogroups or bacterial species sharing the same ecological niche. Results emphasize the continuous evolution of V. vulnificus and support the emergence of new pathogenic groups within this species as a recurrent phenomenon. Our findings contribute to a broader understanding of the evolution of this human pathogen.

Construction of a high-density genetic map based on large-scale markers developed by specific length amplified fragment sequencing (SLAF-seq) and its application to QTL analysis for isoflavone content in Glycine max

BACKGROUND

Quantitative trait locus (QTL) mapping is an efficient approach to discover the genetic architecture underlying complex quantitative traits. However, the low density of molecular markers in genetic maps has limited the efficiency and accuracy of QTL mapping. In this study, specific length amplified fragment sequencing (SLAF-seq), a new high-throughput strategy for large-scale SNP discovery and genotyping based on next generation sequencing (NGS), was employed to construct a high-density soybean genetic map using recombinant inbred lines (RILs, Luheidou2×Nanhuizao, F5:8). With this map, the consistent QTLs for isoflavone content across various environments were identified.

RESULTS

In total, 23 Gb of data containing 87,604,858 pair-end reads were obtained. The average coverage for each SLAF marker was 11.20-fold for the female parent, 12.51-fold for the male parent, and an average of 3.98-fold for individual RILs. Among the 116,216 high-quality SLAFs obtained, 9,948 were polymorphic. The final map consisted of 5,785 SLAFs on 20 linkage groups (LGs) and spanned 2,255.18 cM in genome size with an average distance of 0.43 cM between adjacent markers. Comparative genomic analysis revealed a relatively high collinearity of 20 LGs with the soybean reference genome. Based on this map, 41 QTLs were identified that contributed to the isoflavone content. The high efficiency and accuracy of this map were evidenced by the discovery of genes encoding isoflavone biosynthetic enzymes within these loci. Moreover, 11 of these 41 QTLs (including six novel loci) were associated with isoflavone content across multiple environments. One of them, qIF20-2, contributed to a majority of isoflavone components across various environments and explained a high amount of phenotypic variance (8.7%-35.3%). This represents a novel major QTL underlying isoflavone content across various environments in soybean.

CONCLUSIONS

Herein, we reported a high-density genetic map for soybean. This map exhibited high resolution and accuracy. It will facilitate the identification of genes and QTLs underlying essential agronomic traits in soybean. The novel major QTL for isoflavone content is useful not only for further study on the genetic basis of isoflavone accumulation, but also for marker-assisted selection (MAS) in soybean breeding in the future.

Genetic mapping of legume orthologs reveals high conservation of synteny between lentil species and the sequenced genomes of Medicago and chickpea

Lentil (Lens culinaris Medik.) is a global food crop with increasing importance for food security in south Asia and other regions. Lens ervoides, a wild relative of cultivated lentil, is an important source of agronomic trait variation. Lens is a member of the galegoid clade of the Papilionoideae family, which includes other important dietary legumes such as chickpea (Cicer arietinum) and pea (Pisum sativum), and the sequenced model legume Medicago truncatula. Understanding the genetic structure of Lens spp. in relation to more fully sequenced legumes would allow leveraging of genomic resources. A set of 1107 TOG-based amplicons were identified in L. ervoides and a subset thereof used to design SNP markers for mapping. A map of L. ervoides consisting of 377 SNP markers spread across seven linkage groups was developed using a GoldenGate genotyping array and single SNP marker assays. Comparison with maps of M. truncatula and L. culinaris documented considerable shared synteny and led to the identification of a few major translocations and a major inversion that distinguish Lens from M. truncatula, as well as a translocation that distinguishes L. culinaris from L. ervoides. The identification of chromosome-level differences among Lens spp. will aid in the understanding of introgression of genes from L. ervoides into cultivated L. culinaris, furthering genetic research and breeding applications in lentil.

Identical substitutions in magnesium chelatase paralogs result in chlorophyll-deficient soybean mutants

The soybean [Glycine max (L.) Merr.] chlorophyll-deficient line MinnGold is a spontaneous mutant characterized by yellow foliage. Map-based cloning and transgenic complementation revealed that the mutant phenotype is caused by a nonsynonymous nucleotide substitution in the third exon of a Mg-chelatase subunit gene (ChlI1a) on chromosome 13. This gene was selected as a candidate for a different yellow foliage mutant, T219H (Y11y11), that had been previously mapped to chromosome 13. Although the phenotypes of MinnGold and T219H are clearly distinct, sequencing of ChlI1a in T219H identified a different nonsynonymous mutation in the third exon, only six base pairs from the MinnGold mutation. This information, along with previously published allelic tests, were used to identify and clone a third yellow foliage mutation, CD-5, which was previously mapped to chromosome 15. This mutation was identified in the ChlI1b gene, a paralog of ChlI1a. Sequencing of the ChlI1b allele in CD-5 identified a nonsynonymous substitution in the third exon that confers an identical amino acid change as the T219H substitution at ChlI1a. Protein sequence alignments of the two Mg-chelatase subunits indicated that the sites of amino acid modification in MinnGold, T219H, and CD-5 are highly conserved among photosynthetic species. These results suggest that amino acid alterations in this critical domain may create competitive inhibitory interactions between the mutant and wild-type ChlI1a and ChlI1b proteins.

Genome wide SNP identification in chickpea for use in development of a high density genetic map and improvement of chickpea reference genome assembly

BACKGROUND

In the whole genome sequencing, genetic map provides an essential framework for accurate and efficient genome assembly and validation. The main objectives of this study were to develop a high-density genetic map using RAD-Seq (Restriction-site Associated DNA Sequencing) genotyping-by-sequencing (RAD-Seq GBS) and Illumina GoldenGate assays, and to examine the alignment of the current map with the kabuli chickpea genome assembly.

RESULTS

Genic single nucleotide polymorphisms (SNPs) totaling 51,632 SNPs were identified by 454 transcriptome sequencing of Cicer arietinum and Cicer reticulatum genotypes. Subsequently, an Illumina GoldenGate assay for 1,536 SNPs was developed. A total of 1,519 SNPs were successfully assayed across 92 recombinant inbred lines (RILs), of which 761 SNPs were polymorphic between the two parents. In addition, the next generation sequencing (NGS)-based GBS was applied to the same population generating 29,464 high quality SNPs. These SNPs were clustered into 626 recombination bins based on common segregation patterns. Data from the two approaches were used for the construction of a genetic map using a population derived from an intraspecific cross. The map consisted of 1,336 SNPs including 604 RAD recombination bins and 732 SNPs from Illumina GoldenGate assay. The map covered 653 cM of the chickpea genome with an average distance between adjacent markers of 0.5 cM. To date, this is the most extensive genetic map of chickpea using an intraspecific population. The alignment of the map with the CDC Frontier genome assembly revealed an overall conserved marker order; however, a few local inconsistencies within the Cicer arietinum pseudochromosome 1 (Ca1), Ca5 and Ca8 were detected. The map enabled the alignment of 215 unplaced scaffolds from the CDC Frontier draft genome assembly. The alignment also revealed varying degrees of recombination rates and hotspots across the chickpea genome.

CONCLUSIONS

A high-density genetic map using RAD-Seq GBS and Illumina GoldenGate assay was developed and aligned with the existing kabuli chickpea draft genome sequence. The analysis revealed an overall conserved marker order, although some localized inversions between draft genome assembly and the genetic map were detected. The current analysis provides an insight of the recombination rates and hotspots across the chickpea genome.

A high-throughput SNP array in the amphidiploid species Brassica napus shows diversity in resistance genes

Single-nucleotide polymorphisms (SNPs)are molecular markers based on nucleotide variation and can be used for genotyping assays across populations and to track genomic inheritance. SNPs offer a comprehensive genotyping alternative to whole-genome sequencing for both agricultural and research purposes including molecular breeding and diagnostics, genome evolution and genetic diversity analyses, genetic mapping, and trait association studies. Here genomic SNPs were discovered between four cultivars of the important amphidiploid oilseed species Brassica napus and used to develop a B. napus Infinium™ array containing 5,306 SNPs randomly dispersed across the genome. Assay success was high, with >94 % of these producing a reproducible, polymorphic genotype in the 1,070 samples screened. Although the assay was designed to B. napus, successful SNP amplification was achieved in the B. napus progenitor species, Brassica rapa and Brassica oleracea, and to a lesser extent in the related species Brassica nigra. Phylogenetic analysis was consistent with the expected relationships between B. napus individuals. This study presents an efficient custom SNP assay development pipeline in the complex polyploid Brassica genome and demonstrates the utility of the array for high-throughput genotyping in a number of related Brassica species. It also demonstrates the utility of this assay in genotyping resistance genes on chromosome A7, which segregate amongst the 1,070 samples.

Identification of quantitative trait loci controlling linolenic acid concentration in PI483463 (Glycine soja)

KEY MESSAGE

The QTLs controlling alpha-linolenic acid concentration from wild soybean were mapped on nine soybean chromosomes with various phenotypic variations. New QTLs for alpha-linolenic acid were detected in wild soybean. Alpha-linolenic acid (ALA) is a polyunsaturated fatty acid desired in human and animal diets. Some wild soybean (Glycine soja) genotypes are high in ALA. The objective of this study was to identify quantitative trait loci (QTLs) controlling ALA concentration in a wild soybean accession, PI483463. In total, 188 recombinant inbred lines of F5:6, F5:7, and F5:8 generations derived from a cross of wild soybean PI483463 (~15 % ALA) and cultivar Hutcheson (~9 % ALA) were planted in four environments. Harvested seeds were used to measure fatty acid concentration. Single nucleotide polymorphism markers of the universal soybean linkage panel (USLP 1.0) and simple sequence repeat markers were used for molecular genotyping. Nine putative QTLs were identified that controlled ALA concentration by model-based composite interval mapping and mapped to different soybean chromosomes. The QTLs detected in four environments explained 2.4-7.9 % of the total phenotypic variation (PV). Five QTLs, qALA5_3, qALA6_1, qALA14_1, qALA15_1, and qALA17_1, located on chromosomes 5, 6, 14, 15, and 17 were identified by model-based composite interval mapping and composite interval mapping in two individual environments. Among them, qALA6_1 showed the highest contribution to the PV with 10.0-10.2 % in two environments. The total detected QTLs for additive and epistatic effects explained 52.4 % of the PV for ALA concentration. These findings will provide useful information for understanding genetic structure and marker-assisted breeding programs to increase ALA concentration in seeds derived from wild soybean PI483463.

Integrating omic approaches for abiotic stress tolerance in soybean

Soybean production is greatly influenced by abiotic stresses imposed by environmental factors such as drought, water submergence, salt, and heavy metals. A thorough understanding of plant response to abiotic stress at the molecular level is a prerequisite for its effective management. The molecular mechanism of stress tolerance is complex and requires information at the omic level to understand it effectively. In this regard, enormous progress has been made in the omics field in the areas of genomics, transcriptomics, and proteomics. The emerging field of ionomics is also being employed for investigating abiotic stress tolerance in soybean. Omic approaches generate a huge amount of data, and adequate advancements in computational tools have been achieved for effective analysis. However, the integration of omic-scale information to address complex genetics and physiological questions is still a challenge. In this review, we have described advances in omic tools in the view of conventional and modern approaches being used to dissect abiotic stress tolerance in soybean. Emphasis was given to approaches such as quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). Comparative genomics and candidate gene approaches are also discussed considering identification of potential genomic loci, genes, and biochemical pathways involved in stress tolerance mechanism in soybean. This review also provides a comprehensive catalog of available online omic resources for soybean and its effective utilization. We have also addressed the significance of phenomics in the integrated approaches and recognized high-throughput multi-dimensional phenotyping as a major limiting factor for the improvement of abiotic stress tolerance in soybean.

Identification and characterization of transcript polymorphisms in soybean lines varying in oil composition and content

BACKGROUND

Variation in seed oil composition and content among soybean varieties is largely attributed to differences in transcript sequences and/or transcript accumulation of oil production related genes in seeds. Discovery and analysis of sequence and expression variations in these genes will accelerate soybean oil quality improvement.

RESULTS

In an effort to identify these variations, we sequenced the transcriptomes of soybean seeds from nine lines varying in oil composition and/or total oil content. Our results showed that 69,338 distinct transcripts from 32,885 annotated genes were expressed in seeds. A total of 8,037 transcript expression polymorphisms and 50,485 transcript sequence polymorphisms (48,792 SNPs and 1,693 small Indels) were identified among the lines. Effects of the transcript polymorphisms on their encoded protein sequences and functions were predicted. The studies also provided independent evidence that the lack of FAD2-1A gene activity and a non-synonymous SNP in the coding sequence of FAB2C caused elevated oleic acid and stearic acid levels in soybean lines M23 and FAM94-41, respectively.

CONCLUSIONS

As a proof-of-concept, we developed an integrated RNA-seq and bioinformatics approach to identify and functionally annotate transcript polymorphisms, and demonstrated its high effectiveness for discovery of genetic and transcript variations that result in altered oil quality traits. The collection of transcript polymorphisms coupled with their predicted functional effects will be a valuable asset for further discovery of genes, gene variants, and functional markers to improve soybean oil quality.

Biparental resequencing coupled with SNP genotyping of a segregating population offers insights into the landscape of recombination and fixed genomic regions in elite soybean

Identification of genes underlying agronomic traits is dependent on the segregation of quantitative trait loci (QTL). A popular hypothesis is that elite lines are becoming increasingly similar to each other, resulting in large genomic regions with fixed genes. Here, we resequenced two parental modern elite soybean lines [ZhongHuang13 (ZH) and ZhongPin03-5373 (ZP)] and discovered 794,876 SNPs with reference to the published Williams82 genome. SNPs were distributed unevenly across the chromosomes, with 87.1% of SNPs clustering in 4.9% of the soybean reference genome. Most of the regions with a high density of SNP polymorphisms were located in the chromosome arms. Moreover, seven large regions that were highly similar between parental lines were identified. A GoldenGate SNP genotyping array was designed using 384 SNPs and the 254 recombinant inbred lines (F8) derived from the cross of ZP × ZH were genotyped. We constructed a genetic linkage map using a total of 485 molecular markers, including 313 SNPs from the array, 167 simple sequence repeats (SSRs), 4 expressed sequence tag-derived SSRs, and 1 insertion/deletion marker. The total length of the genetic map was 2594.34 cM, with an average marker spacing of 5.58 cM. Comparing physical and genetic distances, we found 20 hotspot and 14 coldspot regions of recombination. Our results suggest that the technology of resequencing of parental lines coupled with high-throughput SNP genotyping could efficiently bridge the genotyping gap and provide deep insights into the landscape of recombination and fixed genomic regions in biparental segregating populations of soybean with implications for fine mapping of QTL.

Highly efficient genotyping of rice biparental populations by GoldenGate assays based on parental resequencing

A new time- and cost-effective strategy was developed for medium-density SNP genotyping of rice biparental populations, using GoldenGate assays based on parental resequencing. Since the advent of molecular markers, crop researchers and breeders have dedicated huge amounts of effort to detecting quantitative trait loci (QTL) in biparental populations for genetic analysis and marker-assisted selection (MAS). In this study, we developed a new time- and cost-effective strategy for genotyping a population of progeny from a rice cross using medium-density single nucleotide polymorphisms (SNPs). Using this strategy, 728,362 "high quality" SNPs were identified by resequencing Teqing and Lemont, the parents of the population. We selected 384 informative SNPs that were evenly distributed across the genome for genotyping the biparental population using the Illumina GoldenGate assay. 335 (87.2 %) validated SNPs were used for further genetic analyses. After removing segregation distortion markers, 321 SNPs were used for linkage map construction and QTL mapping. This strategy generated SNP markers distributed more evenly across the genome than previous SSR assays. Taking the GW5 gene that controls grain shape as an example, our strategy provided higher accuracy (0.8 Mb) and significance (LOD 5.5 and 10.1) in QTL mapping than SSR analysis. Our study thus provides a rapid and efficient strategy for genetic studies and QTL mapping using SNP genotyping assays.

A genome-wide association study of seed protein and oil content in soybean

BACKGROUND

Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content.

RESULTS

A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r2) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil.

CONCLUSIONS

This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise marker-assisted allele selection and will expedite positional cloning of the causal gene(s).

Inheritance of soybean aphid resistance in 21 soybean plant introductions

KEY MESSAGE

The Rag2 region was frequently identified among 21 F 2 populations evaluated for soybean aphid resistance, and dominant gene action and single-gene resistance were also commonly identified. The soybean aphid [Aphis glycines Matsumura (Hemiptera: Aphididae)] is one of the most important insect pests of soybean [Glycine max (L.) Merr] in the northern USA and southern Canada, and four resistance loci (Rag1-rag4) have been discovered since the pest was identified in the USA in 2000. The objective of this research was to determine whether resistance expression in recently identified soybean aphid-resistant plant introductions (PIs) was associated with the four Rag loci using a collection of 21 F2 populations. The F2 populations were phenotyped with soybean aphid biotype 1, which is avirulent on plants having any of the currently identified Rag genes, using choice tests in the greenhouse and were tested with genetic markers linked to the four Rag loci. The phenotyping results indicate that soybean aphid resistance is controlled by a single dominant gene in 14 PIs, by two genes in three PIs, and four PIs had no clear Mendelian inheritance patterns. Genetic markers flanking Rag2 were significantly associated with aphid resistance in 20 PIs, the Rag1 region was significantly identified in five PIs, and the Rag3 region was identified in one PI. These results show that single dominant gene action at the Rag2 region may be a major source for aphid resistance in the USDA soybean germplasm collection.