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BackgroundBi-parental mapping populations have been commonly utilized to identify and characterize quantitative trait loci (QTL) controlling resistance to soybean cyst nematode (SCN, Heterodera glycines Ichinohe). Although this approach successfully mapped a large number of SCN resistance QTL, it captures only limited allelic diversity that exists in parental lines, and it also has limitations for genomic resolution. In this study, a genome-wide association study (GWAS) was performed using a diverse set of 553 soybean plant introductions (PIs) belonging to maturity groups from III to V to detect QTL/genes associated with SCN resistance to HG Type 0.ResultsOver 45,000 single nucleotide polymorphism (SNP) markers generated by the SoySNP50K iSelect BeadChip (http//www.soybase.org) were utilized for analysis. GWAS identified 14 loci distributed over different chromosomes comprising 60 SNPs significantly associated with SCN resistance. Results also confirmed six QTL that were previously mapped using bi-parental populations, including the rhg1 and Rhg4 loci. GWAS identified eight novel QTL, including QTL on chromosome 10, which we have previously mapped by using a bi-parental population. In addition to the known loci for four simple traits, such as seed coat color, flower color, pubescence color, and stem growth habit, two traits, like lodging and pod shattering, having moderately complex inheritance have been confirmed with great precision by GWAS.ConclusionsThe study showed that GWAS can be employed as an effective strategy for identifying complex traits in soybean and for narrowing GWAS-defined genomic regions, which facilitates positional cloning of the causal gene(s).Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1811-y) contains supplementary material, which is available to authorized users.

Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is a serious soybean pest. The use of resistant cultivars is an effective approach for preventing yield loss. In this study, 19,652 publicly available soybean accessions that were previously genotyped with the SoySNP50K iSelect BeadChip were used to evaluate the phylogenetic diversity of SCN resistance genes Rhg1 and Rhg4 in an attempt to identify novel sources of resistance. The sequence information of soybean lines was utilized to develop KASPar (KBioscience Competitive Allele-Specific PCR) assays from single nucleotide polymorphisms (SNPs) of Rhg1, Rhg4, and other novel quantitative trait loci (QTL). These markers were used to genotype a diverse set of 95 soybean germplasm lines and three recombinant inbred line (RIL) populations. SNP markers from the Rhg1 gene were able to differentiate copy number variation (CNV), such as resistant-high copy (PI 88788-type), low copy (Peking-type), and susceptible-single copy (Williams 82) numbers. Similarly, markers for the Rhg4 gene were able to detect Peking-type (resistance) genotypes. The phylogenetic information of SCN resistance loci from a large set of soybean accessions and the gene/QTL specific markers that were developed in this study will accelerate SCN resistance breeding programs.

In this paper, a new robotic architecture for plant phenotyping is being introduced. The architecture consists of two robotic platforms: an autonomous ground vehicle (Vinobot) and a mobile observation tower (Vinoculer). The ground vehicle collects data from individual plants, while the observation tower oversees an entire field, identifying specific plants for further inspection by the Vinobot. The advantage of this architecture is threefold: first, it allows the system to inspect large areas of a field at any time, during the day and night, while identifying specific regions affected by biotic and/or abiotic stresses; second, it provides high-throughput plant phenotyping in the field by either comprehensive or selective acquisition of accurate and detailed data from groups or individual plants; and third, it eliminates the need for expensive and cumbersome aerial vehicles or similarly expensive and confined field platforms. As the preliminary results from our algorithms for data collection and 3D image processing, as well as the data analysis and comparison with phenotype data collected by hand demonstrate, the proposed architecture is cost effective, reliable, versatile, and extendable.

Drought is a major constraint to maintaining yield stability of wheat in rain fed and limited irrigation agro-ecosystems. Genetic improvement for drought tolerance in wheat has been difficult due to quantitative nature of the trait involving multiple genes with variable effects and lack of effective selection strategies employing molecular markers. Here, a framework molecular linkage map was constructed using 173 DNA markers randomly distributed over the 21 wheat chromosomes. Grain yield and other drought-responsive shoot and root traits were phenotyped for 2 years under drought stress and well-watered conditions on a mapping population of recombinant inbred lines (RILs) derived from a cross between drought-sensitive semidwarf variety "WL711" and drought-tolerant traditional variety "C306". Thirty-seven genomics region were identified for 10 drought-related traits at 18 different chromosomal locations but most of these showed small inconsistent effects. A consistent genomic region associated with drought susceptibility index (qDSI.4B.1) was mapped on the short arm of chromosome 4B, which also controlled grain yield per plant, harvest index, and root biomass under drought. Transcriptome profiling of the parents and two RIL bulks with extreme phenotypes revealed five genes underlying this genomic region that were differentially expressed between the parents as well as the two RIL bulks, suggesting that they are likely candidates for drought tolerance. Syntenic genomic regions of barley, rice, sorghum, and maize genomes were identified that also harbor genes for drought tolerance. Markers tightly linked to this genomic region in combination with other important regions on group 7 chromosomes may be used in marker-assisted breeding for drought tolerance in wheat.