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Soybean is the world’s leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We developed a 40-mating soybean nested association mapping (NAM) population of 5,600 inbred lines that were characterized by single nucleotide polymorphism (SNP) markers and six agronomic traits in field trials in 22 environments. Analysis of the yield, agronomic, and SNP data revealed 23 significant marker-trait associations for yield, 19 for maturity, 15 for plant height, 17 for plant lodging, and 29 for seed mass. A higher frequency of estimated positive yield alleles was evident from elite founder parents than from exotic founders, although unique desirable alleles from the exotic group were identified, demonstrating the value of expanding the genetic base of US soybean breeding.

Using molecular markers in soybean [Glycine max (L.) Merr.] has lead to the identification of major loci controlling quantitative and qualitative traits that include: disease resistance, insect resistance and tolerance to abiotic stresses. Yield has been considered as one of the most important quantitative traits in soybean breeding. Unfortunately, yield is a very complex trait and most yield quantitative trait loci (QTL) that have been identified have had only limited success for marker assisted selection (MAS). The objective of this study was to identify QTL associated with soybean seed yield in preliminary yield trials grown in different environments and to evaluate their effective use for MAS using a yield prediction model (YPM), which included epistasis. To achieve this objective, 875 F5:9 recombinant inbred lines (RIL) from a population developed from a cross between two prominent ancestors of the North American soybean (Essex and Williams 82) were used. The 875 RIL and check cultivars were divided into four groups based on maturity and each group was grown in Knoxville, TN and one other location that had an environment in which the maturity group (MG) was adapted to be grown. Each RIL was genotyped with >50,000 single nucleotide polymorphic markers (SNPs) of which 17,232 were polymorphic across the population. Yield QTL were detected using a single factor (SF) analysis of variance (ANOVA) and composite interval mapping (CIM). Based on CIM, 23 yield QTL were identified. Twenty-one additional QTL were detected using SF ANOVA. Individually, these QTL explained from 4.5% to 11.9% of the phenotypic variation for yield. QTL were identified on all 20 chromosomes and five of the 46 QTL have not been previously reported. This study provides new information concerning yield QTL in soybean and may offer important insights into MAS strategies for soybean.

Soybean [Glycine max (L.) Merr.] is the primary source of meal used in animal feed in the U.S. However, few studies have been conducted to evaluate genomic regions controlling amino acid composition is soybean. Designing soybean seed compositions that will benefit animal production is essential. The objective of this study was to identify genomic regions controlling essential and non-essential amino acid composition in soybean seed proteins. To achieve this objective, 282 F5:9 recombinant inbred lines (RILs) developed from a cross of Essex × Williams 82 were used. Ground soybean seed samples were analyzed for amino acids and statistically significant differences (p < 0.05) were found among genotypes in the population for all amino acid concentrations. The Universal Soy Linkage Panel (USLP) 1.0 of 1,536 single nucleotide polymorphism (SNP) DNA markers were used to genotype the 282 RILs and identify 480 useful genetic markers. The software R/qtl was used to identify candidate quantitative trait loci (QTL), which were validated using R/MQM. A total of ten QTL were detected on chromosomes 5, 7, 9, 10, 13 and 20 that explained 5 to 14% of the total phenotypic variation for a particular amino acid. Using SNPs from the USLP 1.0 to detect QTL for amino acids in soybean provides additional information to select genotypes with enhanced amino acid profiles that will benefit animal production.

Co-segregation analysis and high-throughput genotyping using SNP, SSR, and KASP markers demonstrated genetic linkage between Ur-14 and Co-3 4 /Phg-3 loci conferring resistance to the rust, anthracnose and angular leaf spot diseases of common bean. Rust, anthracnose, and angular leaf spot are major diseases of common bean in the Americas and Africa. The cultivar Ouro Negro has the Ur-14 gene that confers broad spectrum resistance to rust and the gene cluster Co-3 4 /Phg-3 containing two tightly linked genes conferring resistance to anthracnose and angular leaf spot, respectively. We used co-segregation analysis and high-throughput genotyping of 179 F2:3 families from the Ruda (susceptible) × Ouro Negro (resistant) cross-phenotyped separately with races of the rust and anthracnose pathogens. The results confirmed that Ur-14 and Co-3 4 /Phg-3 cluster in Ouro Negro conferred resistance to rust and anthracnose, respectively, and that Ur-14 and the Co-3 4 /Phg-3 cluster were closely linked. Genotyping the F2:3 families, first with 5398 SNPs on the Illumina BeadChip BARCBEAN6K_3 and with 15 SSR, and eight KASP markers, specifically designed for the candidate region containing Ur-14 and Co-3 4 /Phg-3, permitted the creation of a high-resolution genetic linkage map which revealed that Ur-14 was positioned at 2.2 cM from Co-3 4 /Phg-3 on the short arm of chromosome Pv04 of the common bean genome. Five flanking SSR markers were tightly linked at 0.1 and 0.2 cM from Ur-14, and two flanking KASP markers were tightly linked at 0.1 and 0.3 cM from Co-3 4 /Phg-3. Many other SSR, SNP, and KASP markers were also linked to these genes. These markers will be useful for the development of common bean cultivars combining the important Ur-14 and Co-3 4 /Phg-3 genes conferring resistance to three of the most destructive diseases of common bean.

We estimated average genetic diversity of twoGlycineannual and six perennial species based upon 76 orthologous gene sets and performed phylogenetic analysis, divergence analysis and tests for departure from neutrality of the eight species using 52 orthologous gene sets. In addition, 367 orthologous gene sets were used to estimate the relationships of 11G. canescensaccessions. Among the perennials,G. canescensshowed the highest nucleotide diversity and the other perennials exceptG. tomentellahad higher nucleotide diversity than the two annuals. Phylogenetic analysis of theGlycineshowed a similar genome grouping with the previous report exceptG. cyrtolobaandG. stenophitaformed a sister clade in the study. Divergence analysis supported the phylogenetic relationships,G. falcatawas the most divergent fromG. max, followed byG. cyrtoloba,G. syndetika,G. tomentellaD3,G. stenophitaandG. canescens. Neutrality selection tests within species showed that most genes were subjected to a recent directional selection due to a selective sweep or rapid population expansion. Although most gene sequence had negative and significant Tajima’s D, the sequences were homogeneous in the levels of polymorphism and divergence betweenG. maxand otherGlycinespecies based on the HKA test, thus,Glycineperennials may have experienced very similar evolutionary selection as inferred by trans-specific mutation analysis. The greater genetic diversity of most perennialGlycinespecies and their origins from the warmer and drier climates of Australia suggested the perennials as potential sources of heat and drought resistance that will be of value in the face of climate change.

This paper proposes the construction of a genetic linkage map with 376 recombinant inbred lines (RILs) derived from a cross between Mesoamerican × Andean common bean (Phaseolus vulgaris L) parents based on single nucleotide polymorphism (SNP) markers; and to detect quantitative trait loci (QTLs) associated with seven morpho-agronomic traits: number of days to flowering (DF), number of days to maturity (DM) or crop cycle; plant architecture (ARC); seed yield (YLD); degree of seed flatness (SF); seed shape (SS); and 100-seed weight (SW). A total of 3060 polymorphic SNP markers were used and 2041 segregated at a 1:1 ratio in the RIL population, as expected. These markers were subjected to linkage analysis in each chromosome. The genetic linkage analysis resulted in linkage maps with a total of 1962 markers spanning 1079.21 cM. A total of 29 QTLs associated with seven morpho-agronomic traits were detected on the 11 chromosomes, which explained between 3.83 and 32.92% of the phenotypic variation in DF. A total of 18 candidate genes associated with the detected QTLs were identified and related with biological processes, molecular functions and cellular components.

Stearic acid (ST) is one of the saturated fatty acids (FAs) in soybean [Glycine max (L.) Merr.] oil; lowering ST content may be helpful to reduce the potential health risks. In this study, recombinant inbred lines (RILs) derived from “Jidou 12” × “Heidou” cross were used to identify the QTL underlying ST content. As a result, two quantitative trait loci (QTL), designated as qSTE_6_1 and qSTE_14_1, were identified. The QTL qSTE_14_1 was also validated using residual heterozygous lines (RHLs) derived from the RILs. Analysis of the RHLs showed that two simple sequence repeats (SSR) markers, BARCSOYSSR_14_1033 and BARCSOYSSR_14_1079, located on chromosome 14, were tightly linked with qSTE_14_1 and could explain 50.2% and 43.1% of ST content variance at two locations. The allele from “Heidou” decreased the ST content from 3.28% to 2.92% at one location and from 3.55% to 3.01% at the other location. No significant effect of qSTE_14_1 on other FA contents was detected at either location. This study will ...

Snap bean (Phaseolus vulgaris L.) breeding programs are tasked with developing cultivars that meet the standards of the vegetable processing industry and ultimately that of the consumer, all the while matching or exceeding the field performance of existing cultivars. While traditional breeding methods have had a long history of meeting these requirements, genetic marker technology, combined with the knowledge of important quantitative trait loci (QTL), can accelerate breeding efforts. In contrast to dry bean, snap bean immature pods and seeds are consumed as a vegetable. Several pod traits are important in snap bean including: reduced pod wall fiber, absence of pod suture strings, and thickened, succulent pod walls. In addition, snap bean pods are selected for round pod cross section, and pods tend to be longer with cylindrical seed shape. Seed color is an important trait in snap bean, especially those used for processing, as processors prefer white-seeded cultivars. The objective of this study was to investigate the genetic control of traits important to snap bean producers and processors. RR6950, a small seeded brown indeterminate type IIIA dry bean accession, was crossed to the Oregon State University (OSU) breeding line OSU5446, a type I Blue Lake four-sieve breeding line to produce the RR138 F4:6 recombinant inbred (RI) mapping population. We evaluated the RR138 RI population for processing and morphological traits, especially those affecting pods. The RR138 population was genotyped with the BARCBean6K_3 Beadchip, and single nucleotide polymorphisms (SNPs) were used to assemble a linkage map, and identify QTL for pod traits. The linkage map produced from this study contained 1689 SNPs across 1196cM. The map was populated with an average of one SNP per 1.4 cM, spanning 11 linkage groups. Seed and flower color genes B and P were located on Pv02 and Pv07, respectively. A QTL for string:pod length (PL) ratio was found on Pv02 controlling 32% of total genetic variation. QTL for a suite of important processing traits including pod wall fiber, pod height, pod width, and pod wall thickness were found clustering on Pv04 and controlled 21%, 26%, 18%, and 16% of genetic variation for each of these respective traits. A QTL for PL was found on Pv09 controlling 5% of genetic variation.

Soybean quantitative trait loci for ozone response. Ground-level ozone reduces yield in crops such as soybean (Glycine max (L.) Merr.). Phenotypic variation has been observed for this trait in multiple species; however, breeding for ozone tolerance has been limited. A recombinant inbred population was developed from soybean genotypes differing in tolerance to ozone: tolerant Fiskeby III and sensitive Mandarin (Ottawa). Plants were exposed to ozone treatment for 5 days in greenhouse chambers followed by visual scoring for foliar injury. Mean injury score in the mid-canopy was 16 % for Fiskeby III, and 81 % for Mandarin (Ottawa). Injury scores were lower in younger leaves for both parents and progeny, compared to scores in the older leaves. Segregation was consistent with multigenic inheritance. Correlation coefficients for injury between leaf positions ranged from 0.34 to 0.81, with the closer leaf positions showing the greater correlation. Narrow sense heritability within an ozone treatment chamber was 0.59, 0.40, 0.29, 0.30, 0.19, and 0.35 for the 2nd, 3rd, 4th, 5th, 6th, and combined 3rd–5th main stem leaf positions (numbered acropetally), respectively, based on genotypic means over three independent replications. Quantitative trait loci (QTL) analysis showed that loci were associated with distinct leaf developmental stages. QTL were identified on Chromosome 17 for the 2nd and 3rd leaf positions, and on Chromosome 4 for the 5th and 6th leaf positions. Additional loci were identified on Chromosomes 6, 18, 19, and 20. Interacting loci were identified on Chromosomes 5 and 15 for injury on trifoliate 4. The ozone sensitive parent contributed one favorable allele for ozone response.

There is limited information on the influence of genetic and environmental variability on soybean protein composition. This study aimed to determine the role of genotype (G), environments (E), and the interrelationship of genotype and environment (G×E) on soybean seed protein. Three sets of nine soybean genotypes were grown in replicated trials at Maryland, South Carolina, and South Dakota. At each location, the nine genotypes were grown with two planting/sowing dates. We applied two-dimensional gel electrophoresis and mass spectrometry to study the variability of soybean storage and allergen proteins. Statistical analysis of 47 storage and 8 allergen proteins, in terms of differentially expressed protein spots significant at the p

Ureides are the N-rich products of N-fixation that are transported from soybean nodules to the shoot. Ureides are known to accumulate in leaves in response to water-deficit stress, and this has been used to identify genotypes with reduced N-fixation sensitivity to drought. Our objectives in this research were to determine shoot ureide concentrations in 374 Maturity Group IV soybean accessions and to identify genomic regions associated with shoot ureide concentration. The accessions were grown at two locations (Columbia, MO, and Stuttgart, AR) in 2 yr (2009 and 2010) and characterized for ureide concentration at beginning flowering to full bloom. Average shoot ureide concentrations across all four environments (two locations and two years) and 374 accessions ranged from 12.4 to 33.1 µmol g−1 and were comparable to previously reported values. SNP–ureide associations within and across the four environments were assessed using 33,957 SNPs with a MAF ≥0.03. In total, 53 putative loci on 18 chromosomes were identified as associated with ureide concentration. Two of the putative loci were located near previously reported QTL associated with ureide concentration and 30 loci were located near genes associated with ureide metabolism. The remaining putative loci were not near chromosomal regions previously associated with shoot ureide concentration and may mark new genes involved in ureide metabolism. Ultimately, confirmation of these putative loci will provide new sources of variation for use in soybean breeding programs.

root rot diseases of bean (Phaseolus vulgaris L.) are a constraint to dry and snap bean production. We developed the rr138 rI mapping population from the cross of oSU5446, a susceptible line that meets current snap bean processing industry standards, and rr6950, a root rot resistant dry bean with small brown seeds. We evaluated the rr138 rI population beginning in the F6 generation for resistance to Fusarium solani f. sp. phaseoli (Burk.) root rot in oregon and Aphanomyces euteiches (Drechsler) root rot in Wisconsin. The population was evaluated for a set of root architecture traits at the oregon location. Fusarium solani root rot resistance was evaluated in three seasons, whereas A. euteiches resistance was evaluated in two seasons. For each disease, rr6950 was resistant and oSU 5446 was susceptible. The recombinant inbred (rI) population was normally distributed for reaction to both diseases. We assembled a high-density linkage map using 1689 single-nucleotide polymorphisms (SNps) from an Illumina 6000-SNp BArCbean6K_3 Beadchip. The map spanned 1196 cM over 11 linkage groups at a density of one SNp per 1.4 cM. Three quantitative trait loci (QTL) associated with A. euteiches were identified, each accounting for 5 to 15% of the total genetic variation, and two QTL associated with F. solani resistance accounted for 9 and 22% of the total genetic variation. A QTL for taproot diameter (TD) and one QTL for basal root angle were identified. The QTL for resistance to the two diseases mapped to different genome locations indicating a different genetic control. C.H. Hagerty, Dep. of Botany and Plant Pathology, Oregon State Univ., Corvallis, OR 97331; J.R. Myers, Dep. of Horticulture, Oregon State Univ., Corvallis, OR 97331; A. Cuesta-Marcos, Dep. of Crop and Soil Science, Oregon State Univ., Corvallis, OR 97331; P.B. Cregan and Q. Song, USDA–ARS, Soybean Genomics and Improvement Lab., Beltsville, MD 20705; P. McClean, Dep. of Plant Sciences, North Dakota State Univ., Fargo, ND 58108; S. Noffsinger, Seneca Foods Corporation, 799 E. Washington Ave., Dayton, WA 99328. Received 29 Nov. 2014. Accepted 11 May 2015. *Corresponding author ( james. myers@oregonstate.edu). Abbreviations: ARR, Aphanomyces euteiches resistance; CIM, composite interval mapping; CTAB, hexadecyltrimethyl ammonium bromide; FRR, Fusarium solani resistance; HARS, Hancock Agricultural Research Station; LOD, logarithm of the odds; LR, likelihood ratio; OSU, Oregon State University; QTL, quantitative trait loci; RAPD, random amplified polymorphic DNA; RCBD, randomized complete block design; RI, recombinant inbred; SNP, single-nucleotide polymorphism; TD, taproot diameter; VRF, Vegetable Research Farm. Published in Crop Sci. 55:1969–1977 (2015). doi: 10.2135/cropsci2014.11.0805 Freely available online through the author-supported open-access option. © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Published August 17, 2015

Soybean [Glycine max (L.) Merr.] rust is caused by the fungal pathogen Phakopsora pachyrhizi. Six rust resistance loci (Rpp1, 2, 3, 4, 5, and 6) have been reported. Crosses were made between 75 resistant plant introductions (PIs) and a susceptible elite line or cultivar. Bulked segregant analysis (BSA) was used to determine if the PI resistance genes mapped to a previously identified locus or to an unreported locus. Fifty-two PIs had resistance genes that mapped to the Rpp3 region on chromosome 6 of the soybean genome. A set of P. pachyrhizi isolates was used to further characterize the resistance of these PIs. Forty-two of the PIs exhibited the same reaction profiles as either PI 462312 (Rpp3) or ‘Hyuuga’ (Rpp3 and Rpp5) to the panel of isolates. The fine mapping of Rpp1, Rpp3, and Rpp4 and the availability of the SoySNP50K Infinium Chip data on the USDA Soybean Germplasm Collection made it possible to use BSA and isolate data on these PIs to determine in retrospect how effective haplotype analysis would be in narrowing down the PIs to those likely to have a unique source of resistance. Thirty-seven of the 52 PIs (71%) mapping to the Rpp3 region had a haplotype identical to that of PI 462312. A combination of these analyses could prove useful in more rapidly narrowing down resistant PIs to those likely to carry a unique resistance gene.

The United States Department of Agriculture, Soybean Germplasm Collection includes 18,480 domesticated soybean and 1168 wild soybean accessions introduced from 84 countries or developed in the United States. This collection was genotyped with the SoySNP50K BeadChip containing greater than 50K single-nucleotide polymorphisms. Redundant accessions were identified in the collection, and distinct genetic backgrounds of soybean from different geographic origins were observed that could be a unique resource for soybean genetic improvement. We detected a dramatic reduction of genetic diversity based on linkage disequilibrium and haplotype structure analyses of the wild, landrace, and North American cultivar populations and identified candidate regions associated with domestication and selection imposed by North American breeding. We constructed the first soybean haplotype block maps in the wild, landrace, and North American cultivar populations and observed that most recombination events occurred in the regions between haplotype blocks. These haplotype maps are crucial for association mapping aimed at the identification of genes controlling traits of economic importance. A case-control association test delimited potential genomic regions along seven chromosomes that most likely contain genes controlling seed weight in domesticated soybean. The resulting dataset will facilitate germplasm utilization, identification of genes controlling important traits, and will accelerate the creation of soybean varieties with improved seed yield and quality.

Genetic improvement toward optimized and stable agronomic performance of soybean genotypes is desirable for food security. Understanding how genotypes perform in different environmental conditions helps breeders develop sustainable cultivars adapted to target regions. Complex traits of importance are known to be controlled by a large number of genomic regions with small effects whose magnitude and direction are modulated by environmental factors. Knowledge of the constraints and undesirable effects resulting from genotype by environmental interactions is a key objective in improving selection procedures in soybean breeding programs. In this study, the genetic basis of soybean grain yield responsiveness to environmental factors was examined in a large soybean nested association population. For this, a genome-wide association to performance stability estimates generated from a Finlay-Wilkinson analysis and the inclusion of the interaction between marker genotypes and environmental factors was implemented. Genomic footprints were investigated by analysis and meta-analysis using a recently published multiparent model. Results indicated that specific soybean genomic regions were associated with stability, and that multiplicative interactions were present between environments and genetic background. Seven genomic regions in six chromosomes were identified as being associated with genotype-by-environment interactions. This study provides insight into genomic assisted breeding aimed at achieving a more stable agronomic performance of soybean, and documented opportunities to exploit genomic regions that were specifically associated with interactions involving environments and subpopulations.

A set of nested association mapping (NAM) families was developed by crossing 40 diverse soybean [ (L.) Merr.] genotypes to the common cultivar. The 41 parents were deeply sequenced for SNP discovery. Based on the polymorphism of the single-nucleotide polymorphisms (SNPs) and other selection criteria, a set of SNPs was selected to be included in the SoyNAM6K BeadChip for genotyping the parents and 5600 RILs from the 40 families. Analysis of the SNP profiles of the RILs showed a low average recombination rate. We constructed genetic linkage maps for each family and a composite linkage map based on recombinant inbred lines (RILs) across the families and identified and annotated 525,772 high confidence SNPs that were used to impute the SNP alleles in the RILs. The segregation distortion in most families significantly favored the alleles from the female parent, and there was no significant difference of residual heterozygosity in the euchromatic vs. heterochromatic regions. The genotypic datasets for the RILs and parents are publicly available and are anticipated to be useful to map quantitative trait loci (QTL) controlling important traits in soybean.

Soybean aphid (Aphis glycines Matsumura) has become one of the major pests of soybean [Glycine max (L.) Merr.] in North America since 2000. At least four biotypes of soybean aphid have been confirmed in the United States. Genetic characterization of new sources of soybean aphid resistance will facilitate the expansion of soybean gene pool for soybean aphid resistance and thus will help to develop soybean aphid resistant cultivars. To characterize the genetic basis of soybean aphid resistance in PI 603712, a newly identified resistant germplasm line, 142 F2 plants derived from the cross ‘Roberts’ × PI 603712 and their parents were evaluated for soybean aphid resistance in the greenhouse, and were genotyped with BARCSoySNP6K Illumina Infinium II BeadChip. A genome-wide molecular linkage map was constructed with 1495 polymorphic SNP markers. QTL analysis revealed that PI 603712 possessed two major loci associated with soybean aphid resistance, located on chromosome 7 and 16, respectively. The locus on chromosome 7 was dominantly expressed and positioned about one Mega-base-pair distant from the previously identified resistance locus Rag1. The locus on chromosome 16 was positioned near the previously identified resistance locus Rag3 and expressed partially dominance or additive effect. Interestingly, two minor loci were also detected on chromosomes 13 and 17 but the alleles from PI 603712 decreased the resistance. In developing soybean aphid resistant cultivars through marker-assisted selection, an appropriate combination of resistance loci should be selected when PI 603712 is used as a donor parent of resistance.

Using genome-wide association studies, 39 SNP markers likely tagging 21 different loci for carbon isotope ratio (δ (13) C) were identified in soybean. Water deficit stress is a major factor limiting soybean [Glycine max (L.) Merr.] yield. Soybean genotypes with improved water use efficiency (WUE) may be used to develop cultivars with increased yield under drought. A collection of 373 diverse soybean genotypes was grown in four environments (2 years and two locations) and characterized for carbon isotope ratio (δ(13)C) as a surrogate measure of WUE. Population structure was assessed based on 12,347 single nucleotide polymorphisms (SNPs), and genome-wide association studies (GWAS) were conducted to identify SNPs associated with δ(13)C. Across all four environments, δ(13)C ranged from a minimum of -30.55‰ to a maximum of -27.74‰. Although δ(13)C values were significantly different between the two locations in both years, results were consistent among genotypes across years and locations. Diversity analysis indicated that eight subpopulations could contain all individuals and revealed that within-subpopulation diversity, rather than among-subpopulation diversity, explained most (80%) of the diversity among the 373 genotypes. A total of 39 SNPs that showed a significant association with δ(13)C in at least two environments or for the average across all environments were identified by GWAS. Fifteen of these SNPs were located within a gene. The 39 SNPs likely tagged 21 different loci and demonstrated that markers for δ(13)C can be identified in soybean using GWAS. Further research is necessary to confirm the marker associations identified and to evaluate their usefulness for selecting genotypes with increased WUE.

Empoasca species leafhoppers are a major insect pest of common bean ( Phaseolus vul- garis L.), that cause significant economic losses in both tropical ( E. kraemeri) and temperate ( E. fabae) regions of the Americas. The objective of this study was to use Insertion-Deletion (InDel) and single-nucleotide polymorphism (SNp) markers from the BArCBean6K_3 Beadchip to identify quantitative trait loci (QTL) associ - ated with traits related to leafhopper resistance in common bean. Traits for leaf curl and leaf burn damage, as well as Empoasca spp. nymph counts, were evaluated in an inbred backcross line population (Matterhorn*/EMp 507) of beans in temperate (Michigan) and tropical ( puerto rico) climates. Fourteen QTL associated with resistance to E. fabae and E. kraemeri were identified on five chromosomes explaining up to 66.0% of the phenotypic variation for single resistance traits. A major QTL cluster associ - ated with multiple resistance traits and closely linked to the P color gene was detected for both leafhopper species in multiple seasons under both choice and no-choice treatments on p v07 (LH7.1, LH7.2, LH7.3), thus validating a similar QTL identified in previous studies. A novel QTL (LH2.2) for E. fabae nymph counts, identified on pv02 in three seasons, may be associated with antibiosis resistance. resistance to each leaf- hopper species appears to be controlled by sep - arate genetic mechanisms in common bean as there was little overlap of QTL regions between species. These QTL could be used to develop beans with leafhopper resistance as an alterna - tive to costly chemical controls while reducing risks to the environment and human health.

Soybean oil and meal are major contributors to world-wide food production. Consequently, the genetic basis for soybean seed composition has been intensely studied using family-based mapping. Population-based mapping approaches, in the form of genome-wide association (GWA) scans, have been able to resolve loci controlling moderately complex quantitative traits (QTL) in numerous crop species. Yet, it is still unclear how soybean’s unique population history will affect GWA scans. Using one of the populations in this study, we simulated phenotypes resulting from a range of genetic architectures. We found that with a heritability of 0.5, ∼100% and ∼33% of the 4 and 20 simulated QTL can be recovered, respectively, with a false-positive rate of less than ∼6×10−5 per marker tested. Additionally, we demonstrated that combining information from multi-locus mixed models and compressed linear-mixed models improves QTL identification and interpretation. We applied these insights to exploring seed composition in soybean, refining the linkage group I (chromosome 20) protein QTL and identifying additional oil QTL that may allow some decoupling of highly correlated oil and protein phenotypes. Because the value of protein meal is closely related to its essential amino acid profile, we attempted to identify QTL underlying methionine, threonine, cysteine, and lysine content. Multiple QTL were found that have not been observed in family-based mapping studies, and each trait exhibited associations across multiple populations. Chromosomes 1 and 8 contain strong candidate alleles for essential amino acid increases. Overall, we present these and additional data that will be useful in determining breeding strategies for the continued improvement of soybean’s nutrient portfolio.

Soybean (Glycine max (L.) Merr.) is a major source of plant protein for humans and livestock. Deficiency of sulfur-containing amino acids (cysteine and methionine) in soybean protein is a main limitation of soybean meal as an animal feed ingredient. The objectives of this study were to identify and validate quantitative trait loci (QTLs) associated with cysteine and methionine contents in two recombinant inbred line (RIL) populations, and to analyze the genetic effects of individual QTLs and QTL combinations in soybean. Both the mapping population of SD02-4-59 × A02-381100 and validation population of SD02-911 × SD00-1501 were evaluated for cysteine and methionine contents in multiple environments. Correlation analysis indicated that there was a highly positive correlation between cysteine and methionine contents. Significant positive correlations were also observed between the sulfur-containing amino acid contents and protein content. In the mapping population, eight QTLs for both cysteine and methionine contents were consistently detected in any individual environment and the average data over all three environments. Three of these QTLs were confirmed in the validation population. A comparison with the previous studies indicated that most of the genomic regions linked to the QTLs for the sulfur-containing amino acids were also associated with protein content. Cumulative effects of multiple QTLs for the traits were significant in both populations. This information should be useful for the improvement of the levels of protein and amino acids in soybean seeds.

Gene structural variation (SV) has recently emerged as a key genetic mechanism underlying several important phenotypic traits in crop species. We screened a panel of 41 soybean (Glycine max) accessions serving as parents in a soybean nested association mapping population for deletions and duplications in more than 53,000 gene models. Array hybridization and whole genome resequencing methods were used as complementary technologies to identify SV in 1528 genes, or approximately 2.8%, of the soybean gene models. Although SV occurs throughout the genome, SV enrichment was noted in families of biotic defense response genes. Among accessions, SV was nearly eightfold less frequent for gene models that have retained paralogs since the last whole genome duplication event, compared with genes that have not retained paralogs. Increases in gene copy number, similar to that described at the Rhg1 resistance locus, account for approximately one-fourth of the genic SV events. This assessment of soybean SV occurrence presents a target list of genes potentially responsible for rapidly evolving and/or adaptive traits.

Common bacterial blight (CBB) is a severe disease in common bean (Phaseolus vulgaris L.). New resistance quantitative trait loci (QTL) should facilitate development of cultivars with high levels of resistance. Our objectives were to (i) identify new resistance QTL in VAX 1 and verify its presence in VAX 3, (ii) determine the interaction between QTL with existing SAP6 and SU91 QTL, and (iii) examine the interaction between QTL with less aggressive ARX8AC and aggressive Xcp25 bacterial strains. Sixty-one F₆:₇ recombinant inbred lines (RIL) from ‘Othello’/VAX 1 and 100 RIL from Othello/VAX 3 were screened in the greenhouse. Disease severity of inoculated primary leaves, first and second trifoliolate leaves, and pods, was scored from 1 = no symptoms to 9 = completely diseased. Genotyping was performed using 5398 single nucleotide polymorphism (SNP) BeadChip and CBB resistance QTL-linked sequence characterized amplified region (SCAR) markers, SAP6 and SU91. A novel resistance QTL with major effect was detected on Pv11 linkage group in Othello/VAX 1 and verified in Othello/VAX 3. This Pv11 QTL, defined by the closest marker SNP47467 (45,059,806 bp), explained 23% of the phenotypic variance for resistance in primary and 18% in trifoliolate leaves in Othello/VAX 1, and 13% and 22%, respectively, in Othello/VAX 3 to ARX8AC. The Pv11 QTL, named Xa11.4ᴼⱽ¹,ᴼⱽ³, had greater influence against Xcp25, with respective values for variance for resistance explained in primary and trifoliolate leaves of 45% and 51% in Othello/VAX 1 and 26% and 37% in Othello/VAX 3. Conversely, SAP6 was only effective against ARX8AC in both populations, and surprisingly, SU91 was only effective against Xcp25 in Othello/VAX 3. SAP6 was the only QTL to condition resistance in pods. QTL interactions and differential reactions to strains indicate that the new Xa11.4ᴼⱽ¹,ᴼⱽ³ QTL is critical in breeding for stable and higher levels of foliage resistance to CBB in common bean.

Drought stress is the major limitation of common bean (Phaseolus vulgaris L.) grown in subsistence farming systems worldwide. The objective of this study was to use single nucleotide polymorphism (SNP) markers from the BARCBean6K_3 Beadchip to identify quantitative trait loci (QTL) associated with traits related to drought tolerance in common bean. An intergene pool recombinant inbred line (RIL) population from a cross of drought tolerant line SEA5 and CAL96 cultivar was evaluated in Rwanda for 3 yr under drought stress and nonstress and in Colombia for 1 yr under drought stress. Traits evaluated included the numbers of days to flower, maturity, and seed fill; harvest index and pod harvest index; yield and yield components including number of pods per plant, seeds per pod, 100 seed weight (SW), and seed yield per day. Harvest indices, and SW were stable regardless of water treatment while number of pods per plant, seeds per pod, and yield were significantly reduced by drought. A linkage map of the RIL population spanning 1351 cM was constructed using 2122 SNP markers. The map covered all eleven bean chromosomes with an average distance of 0.64 cM between markers. A total of 14 QTL for performance under drought were consistently identified in different environments. Quantitative trait loci associated with phenology and SW traits mapped near previously reported QTL. Linkage between SW and yield QTL SY3.3SC was observed on Pv03 and could be used to simultaneously select for seed yield and size in intergene pool crosses of common bean.

Sucrose is a desirable sugar in soybean seed that affects the quality of soyfoods and feed; therefore, soybean cultivars with high sucrose would be valuable for soyfood and soybean meal markets. The objective of this study was to identify quantitative trait loci (QTL) associated with seed sucrose content using simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers that can be used for indirect selection in breeding. A low sucrose line, MFS-553, was crossed with a high sucrose plant introduction, PI 243545, to develop an F₂–derived QTL mapping population. A total of 626 SSR primers covering 20 soybean chromosomes were used to screen the parents and 209 SSR markers were polymorphic. The polymorphic SSR markers were used to genotype 220 F₂:₃ lines. Subsequently, a total of 94 F₃:₄ lines derived from the initial F₂:₃ population were genotyped with 5361 SNP markers spanning 20 chromosomes, of which 2016 were polymorphic. Seed from the F₂:₃, F₃:₅, and F₃:₆ lines were analyzed for sucrose using high performance liquid chromatography (HPLC). Following the linkage map construction, composite interval mapping (CIM) and multiple interval mapping (MIM) were performed to locate sucrose QTL. Three novel QTLs for seed sucrose were mapped to chromosomes 5, 9, and 16, accounting for 46, 10 and 8%, respectively, of the phenotypic variation for sucrose content. SSR and SNP markers linked to these QTLs can be used for marker assisted selection (MAS) in breeding soybean lines with the desired sugar profile.

Circumlineatus (cl) in common bean (Phaseolus vulgaris L.) is identified by a precipitation line in the seedcoat at the boundary of the white and colored zones. Cl is recessive and is expressed in partly colored seedcoats (t) with restricted patterns such as virgarcus. In this study, amplified fragment length polymorphism (AFLP) and single nucleotide polymorphism (SNP) markers, and the common bean genome sequence were used in combination with bulk segregant analysis and bidirectional selective genotyping to identify the genetic location of Cl. Markers were identified that cosegregated with Cl using Cl/Cl and cl/cl F3 and F5 progeny bulks from the cross t z cl G b v virgarcus BC3 5-593 × t zsel Cl G b v sellatus BC3 5-593. Two bands from an AFLP primer combination, which yielded unambiguous polymorphisms between the bulks, were cloned and sequenced. The two sequences were used to interrogate the common bean whole genome sequence identifying a region also found through cosegregation analysis using bidirectional selective genotyping with SNPs. Thus, the Cl gene was localized on Pv09 using cosegregating AFLP and SNP markers, and the physical location was confirmed with the whole genome sequence.

phytophthora root rot (prr) is a devastating disease in soybean [Glycine max (L.) Merr.] production. Michigan elite soybean E00003 is resistant to Phytophthora sojae and has been used as a resistance source in breeding. Genetic control of prr resistance in this source is unknown. To facilitate marker-assisted selection (MAS), the prr resistance loci in E00003 and their map locations need to be determined. In this study, a genetic mapping approach was used to identify major prr-resistant loci in E00003. The mapping population consists of 240 F4–derived lines developed by crossing E00003 with the P. sojae susceptible line pI 567543C. In 2009 and 2010, the mapping population was evaluated in the greenhouse for prr resistance against P. sojae races 1, 4, and 7, using modified rice (Oryza sativa L.) grain inoculation method. The population was genotyped with seven simple sequence repeat (SSr) and three single nucleotide polymorphism (SNp) markers derived from bulk segregant analysis. The heritability of resistance in the population ranged from 83 to 94%. A major locus, contributing 50 to 76% of the phenotypic variation, was mapped within a 3 cM interval in the Rps1 region. The interval was further saturated with more BArCSoY SSrs and SNps with TaqMan assays. Two SSrs and three SNps within the Rps1k gene were highly associated with prr resistance in the mapping population. The major resistance gene in E00003 is either allelic or tightly linked to Rps1k.The molecular markers located in the Rps1k gene can be used to improve MAS for prr resistance. Z. Zhang, J. Hao, J. Yuan, C. Gu, and D. Wang, Dep. of Plant, Soil and Microbial Sciences, Michigan State Univ., East Lansing, MI 48824; Q.J. Song, D.L. Hyten, and P.B. Cregan, USDA –ARS Soybean Genomics and Improvement Laboratory, Beltsville, MD 20705; G. Zhang, Agricultural Research Center–Hays, Kansas State Univ., Hays, KS 67601; M. Li, Division of Biostatistics, Dep. of Pediatrics, Univ. of Arkansas for Medical Sciences, Little Rock, AR 72202. Received 12 Nov. 2013. *Corresponding author (wangdech@msu.edu). Abbreviations: BSA, bulked segregant analysis; CIM, composite interval mapping; GI, germination index; LOD, logarithm of odds; MAS, marker-assisted selection; PCR, polymerase chain reaction; PRR, Phytophthora root rot; QTL, quantitative trait loci; RIL, recombinant inbred line; SI, survival index; ∆SI, adjusted survival index; SNP, single nucleotide polymorphism; SSR, simple sequence repeat. Published in Crop Sci. 54:492–499 (2014). doi: 10.2135/cropsci2012.11.0631 © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Interest in soybean [Glycine max (L.) Merr.] isoflavones has increased in recent years owing to numerous reported health benefits. Consequently, quantitative trait loci (QTL) detection for marker-assisted breeding for isoflavones is being examined for genetic gains. This study sought to detect QTL for soybean isoflavones in a population of 274 recombinant inbred lines derived from a cross between ‘Essex’ and ‘Williams 82’ that were subdivided and tested by maturity (early, mid, and late). The field tests were conducted in three environments in 2009 (Knoxville, TN; Harrisburg, IL; and Stuttgart, Ar). The population was genotyped with 480 polymorphic single nucleotide polymorphism markers. Isoflavones for each replicate were analyzed by near infrared reflectance spectroscopy, whose prediction equation was based on high performance liquid chromatography. Each maturity test, containing 91 or 92 recombinant inbred lines, was analyzed separately for QTL. In total, 21 QTL were detected: 7 for genistein (chromosomes 5, 6, 9, 13, 17, and 19), 5 for daidzein (chromosomes 5, 6, 9, 13, and 19), 3 for glycitein (chromosomes 6, 9, and 20), and 6 for total isoflavone content (chromosomes 5, 6, 9, 13, and 19). of these 21 QTL, 12 were confirmed or positional confirmations from other studies. Utilization of these QTL could potentially lead to marker-assisted selection approaches for genetic gains in improving soybean isoflavones. C.J. Smallwood, D.A. Kopsell, C.E. Sams, D.R. West, and V.R. Pantalone, Dep. of Plant Sciences, Univ. of Tennessee, 2431 Joe Johnson Drive, Knoxville, TN 37996; C.N. Nyinyi, Monsanto, 140 W. Industrial Drive, Harrisburg, SD 57032; P. Chen, Dep. of Crop, Soil, and Environmental Sciences, 115 Plant Science Building, Univ. of Arkansas, Fayetteville, AR 72701; S.K. Kantartzi, Dep. of Plant, Soil and Ag. Systems, Southern Illinois Univ., Carbondale, IL 62901; P.B. Cregan and D.L. Hyten, USDA, ARS, Soybean Genomics and Improvement Lab, Beltsville, MD 20705; D.L. Hyten, present address: Dupont Pioneer, 8305 NW 62nd Ave., PO Box 7060, Johnston, IA 50131. Received 23 May 2013. *Corresponding author (csmallw1@utk.edu). Abbreviations: CIM, composite interval mapping; E, environment; ETREC, East Tennessee Research and Education Center; G, genotype; HPLC, high performance liquid chromatography; LOD, logarithm of odds; LSMEAN, least squares mean; MAS, marker-assisted selection; Mbp, mega base pair; NIRS, near-infrared reflectance spectroscopy; QTL, quantitative trait loci; RIL, recombinant inbred line; SNP, single nucleotide polymorphism; ST, stem termination. Published in Crop Sci. 54:595–606 (2014). doi: 10.2135/cropsci2013.05.0340 © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Soybean research has found that nodule traits, especially nodule biomass, are associated with N2 fixation ability. Two genotypes, differing in nodule number per plant and individual nodule weight, KS4895 and Jackson, were mated to create 17 F3- and 80 F5-derived RILs. The population was mapped with 664 informative markers with an average distance of less than 20 cM between adjacent markers. Nodule traits were evaluated in 3-year field trials. Broad-sense heritability for nodule number (no. plant−1), individual nodule dry weight (mg nodule−1), individual nodule size (mm nodule−1), and total nodule dry weight (g plant−1) was 0.41, 0.42, 0.45, and 0.27, respectively. Nodule number was negatively correlated with individual nodule weight and size. Nodule number, individual nodule weight, and size are major components which likely contributed to increased total nodule weight per plant. Composite interval mapping (CIM) identified eight QTLs for nodule number with R2 values ranging from 0.14 to 0.20. Multiple interval mapping (MIM) identified two QTLs for nodule number, one of which was located close to the QTL identified with CIM. Six QTLs for individual nodule weight were detected with CIM, and one QTL was identified with MIM. For nodule size, CIM identified seven QTLs with R2 values ranging from 0.14 to 0.27. Five QTLs for total nodule weight were detected with CIM, one of which was located close to a QTL identified with MIM. These results document the first QTL information on nodule traits in soybean from field experiments utilizing a dense, complete linkage map.

Soybean [Glycine max (L.) Merr.] is an important oilseed crop which produces about 30 % of the world’s edible vegetable oil. The quality of soybean oil is determined by its fatty acid composition. Soybean oil high in oleic and low in linolenic fatty acids is desirable for human consumption and other uses. The objectives of this study were to identify quantitative trait loci (QTLs) for unsaturated fatty acids and to evaluate the genetic effects of single QTL and QTL combinations in soybean. A population of recombinant inbred lines derived from the cross of SD02-4-59 × A02-381100 was evaluated for fatty acid content in seven environments. In total, 516 polymorphic single nucleotide polymorphism markers, 477 polymorphic simple sequence repeat markers and three GmFAD3 genes were used to genotype the mapping population. By using the composite interval mapping and/or the interval mapping method, a total of 15 QTLs for the three unsaturated fatty acids were detected in more than two environments. Two QTLs for oleic acid on linkage groups G [chromosome (Chr) 18] (qOLE-G) and J (Chr 16) (qOLE-J), three QTLs for linoleic acid on linkage groups A1 (Chr 5) (qLLE-A1) and G (Chr 18) (qLLE-G-1 and qLLE-G-2), and five QTLs for linolenic acid on linkage groups C2 (Chr 6), D1a (Chr 1), D1b (Chr 2), F (Chr 13) and G (Chr 18) were consistently detected in at least three individual environments and the average data over all environments. Significant QTL × QTL interactions were not detected. However, significant QTL × environment interactions were detected for all the QTLs which were repeatedly detected. Some QTLs reported previously were confirmed, and seven new QTLs (two for oleic acid, two for linoleic acid and three for linolenic acid) were identified in this study. Comparisons of two-locus and three-locus combinations indicated that cumulative effects of QTLs were significant for all the three unsaturated fatty acids. QTL pyramiding by molecular marker-assisted breeding would be an appropriate strategy for the improvement of unsaturated fatty acids in soybean.

Demand for soybean [Glycine max (L.) Merr.] meal has increased worldwide and soybean importers often offer premiums for soybean containing higher contents of protein and oil. objectives were to detect quantitative trait loci (QTL) associated with soybean seed protein, oil, and seed weight in a soybean mapping population and confirm detected QTL across genetic backgrounds and environments. Two populations of 216 and 156 recombinant inbred lines were developed from Magellan × pI 438489B and Magellan × pI 567516C crosses, respectively, and grown in two Missouri environments in 2008. More than 900 simple sequence repeat (SSr) and single nucleotide polymorphism (SNp) markers were used for mapping in each population. Across environments and genetic backgrounds, we have identified seven QTL for protein, six for oil, and four for seed weight. Two QTL were detected in common for protein and oil, one on chromosome (Chr.) 5 and another on Chr. 6. Additionally, we have detected one new seed weight QTL on Chr. 6, in the same region of protein and oil QTL. Confirmed protein and oil QTL on Chrs. 5 and 6 may be important targets to find candidate genes involved in modification of protein and oil contents and seed weight using genetic and genomic approaches. Also, SSr and SNp markers closely associated with these QTL can be useful for marker-assisted selection. S.M. Pathan and J.G. Shannon, National Center for Soybean Biotechnology (NCSB) and Division of Plant Sciences, Univ. of Missouri Delta Research Center, Portageville, MO 63873; T. Vuong, K. Clark, H.T. Nguyen, and D.A. Sleper, NCSB and Division of Plant Sciences, Univ. of Missouri, Columbia, MO 65211; C.A. Roberts, Division of Plant Sciences, Univ. of Missouri, Columbia, MO 65211; M.R. Ellersieck, Division of Statistics, Univ. of Missouri, Columbia, MO 65211; J.W. Burton, Soybean and Nitrogen Fixation Research Unit, USDA-ARS, Raleigh, NC 27607; D.L. Hyten, Pioneer Hi-Bred International Inc., Johnston, IA 50131; P.B. Cregan, Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD 20705; J.-D. Lee, School of Applied Biosciences, Kyungpook National Univ., Daegu 702-701, Republic of Korea. S.M. Pathan and T. Vuong contributed equally to the article. Received 5 Mar. 2012. *Corresponding author (sleperd@missouri.edu). Abbreviations: BREC, Bradford Research and Extension Center; Chr., chromosome; DRC, Delta Research Center; H2, broad-sense heritability; LOD, logarithm of the odds; MPB, Magellan × PI 438489B; MPC, Magellan × PI 567516C; MQM, multiple-QTL method; MU, University of Missouri–Columbia; NIR, near-infrared reflectance; QTL, quantitative trait loci; RIL, recombinant inbred line; SBM, soybean meal; SCN, soybean cyst nematode; SNP, single nucleotide polymorphism; SSR, simple sequence repeat. Published in Crop Sci. 53:765–774 (2013). doi: 10.2135/cropsci2012.03.0153 © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Two novel QTLs conferring aphid resistance were mapped and validated on soybean chromosomes 8 and 16, respectively. Closely linked markers were developed to assist breeding for aphid resistance. Soybean aphid, Aphis glycines Matsumura, is a highly destructive pest for soybean production. E08934, a soybean advanced breeding line derived from the wild soybean Glycine soja 85-32, has shown strong resistance to aphids. To dissect the genetic basis of aphid resistance in E08934, a mapping population (070020) consisting of 140 F3-derived lines was developed by crossing E08934 with an aphid-susceptible line E00003. This mapping population was evaluated for aphid resistance in a greenhouse trial in 2010 and three field trials in 2009, 2010, and 2011, respectively. The broad-sense heritability across the field trials was 0.84. In the mapping population 070020, two major quantitative trait loci (QTL) were detected as significantly associated with aphid resistance, and designated as Rag6 and Rag3c, respectively. Rag6 was mapped to a 10.5 centiMorgan (cM) interval between markers MSUSNP08-2 and Satt209 on chromosome 8, explaining 19.5–46.4% of the phenotypic variance in different trials. Rag3c was located at a 7.5 cM interval between markers MSUSNP16-10 and Sat_370 on chromosome 16, explaining 12.5–22.9% of the phenotypic variance in different trials. Rag3c had less resistance effect than Rag6 across all the trials. Furthermore, Rag6 and Rag3c were confirmed in two validation populations with different genetic backgrounds. No significant interaction was detected between Rag6 and Rag3c in either the mapping population or the validation populations. Both Rag6 and Rag3c were indicated as conferring antibiosis resistance to aphids by a no-choice test. The new aphid-resistance gene(s) derived from the wild germplasm G. soja 85-32 are valuable in improving soybeans for aphid resistance.

Background Soybean seed weight is not only a yield component, but also a critical trait for various soybean food products such as sprouts, edamame, soy nuts, natto and miso. Linkage analysis and genome-wide association study (GWAS) are two complementary and powerful tools to connect phenotypic differences to the underlying contributing loci. Linkage analysis is based on progeny derived from two parents, given sufficient sample size and biological replication, it usually has high statistical power to map alleles with relatively small effect on phenotype, however, linkage analysis of the bi-parental population can’t detect quantitative trait loci (QTL) that are fixed in the two parents. Because of the small seed weight difference between the two parents in most families of previous studies, these populations are not suitable to detect QTL that have considerable effects on seed weight. GWAS is based on unrelated individuals to detect alleles associated with the trait under investigation. The ability of GWAS to capture major seed weight QTL depends on the frequency of the accessions with small and large seed weight in the population being investigated. Our objective was to identify QTL that had a pronounced effect on seed weight using a selective population of soybean germplasm accessions and the approach of GWAS and fixation index analysis. Results We selected 166 accessions from the USDA Soybean Germplasm Collection with either large or small seed weight and could typically grow in the same location. The accessions were evaluated for seed weight in the field for two years and genotyped with the SoySNP50K BeadChip containing >42,000 SNPs. Of the 17 SNPs on six chromosomes that were significantly associated with seed weight in two years based on a GWAS of the selective population, eight on chromosome 4 or chromosome 17 had significant Fst values between the large and small seed weight sub-populations. The seed weight difference of the two alleles of these eight significant SNPs varied from 8.1 g to 11.7 g/100 seeds in two years. We also identified haplotypes in three haplotype blocks with significant effects on seed weight. These findings were validated in a panel with 3753 accessions from the USDA Soybean Germplasm Collection. Conclusion This study highlighted the usefulness of selective genotyping populations coupled with GWAS and fixation index analysis for the identification of QTL with substantial effects on seed weight in soybean. This approach may help geneticists and breeders to more efficiently identify major QTL controlling other traits. The major regions and haplotypes we have identified that control seed weight differences in soybean will facilitate the identification of genes regulating this important trait. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3922-0) contains supplementary material, which is available to authorized users.

Illustrating the consistency and pleiotropic effects of a quantitative trait locus (QTL) across multi-locations is important for breeding. In this study, a QTL qPH_6_1, underlying soybean plant height, was positioned on chromosome 6 using a BC2F5 family, which was developed using ‘Jidou 12’ as recurrent parent, and ‘Xinbada 2’ as donor parent. The residual heterozygous lines (RHLs) derived from BC2F5 plants that segregated at qPH_6_1 were used to validate and pinpoint the QTL at both locations. For RHLs, qPH_6_1 explained approximately 80% of the variance for plant height and number of nodes, and was positioned in a 3.5 cM interval co-segregated with Satt557, Satt489, Satt134 and Satt289. The analysis of near-isogenic lines, developed from RHLs, also showed that qPH_6_1 had a significant impact on plant height and number of nodes across the other ten locations in 2 years. A larger genetic effect was observed at locations in north China than in south. While, qPH_6_1 could only explain 1.6–30.4% of the phenotypic variation for 100-seed weight, protein content, oil content, and grain yield, and their effects varied with locations. The results provide information for breeding widely adapted soybean cultivars.

A brief history of classical and molecular genetic mapping in soybean [Glycine max (L.) Merr.] is followed by a description of the most current version of the soybean genetic linkage map, which is primarily based on simple sequence repeat (SSR) or microsatellite markers as well as single nucleotide polymorphism (SNP) markers. Like many plant and animal species, the first molecular map of soybean was based on restriction fragment length polymorphism (RFLP) markers. Because of the relatively low level of sequence diversity in soybean, the first RFLP maps were constructed in populations derived from crosses of cultivated (G. max) × wild soybean [G. soja (Seib. et Zucc.)]. Random amplified polymorphic DNA (RAPD) and amplified fragment length polymorphism loci were briefly used in map construction, but soybean was the first plant species in which SSR markers were employed and SSRs soon became the marker of choice in map development. SNP markers are now being widely used by plant and animal geneticists, and the most recent molecular genetic map of soybean incorporates a large number of SNPs from genic and nongenic regions.