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      Genome-Wide Association Study of Resistance to Soybean Cyst Nematode ( Heterodera glycines) HG Type 2.5.7 in Wild Soybean ( Glycine soja)

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          Abstract

          Soybean cyst nematode (SCN) is the most destructive soybean pest worldwide. Host plant resistance is the most environmentally friendly and cost-effective way of mitigating SCN damage to soybeans. However, overuse of the resistant soybean [ Glycine max (L.) Merr.] cultivars from limited genetic resources has resulted in SCN race shifts in many soybean-growing areas. Thus, exploration of novel sources of SCN resistance and dissection of the genetic basis are urgently needed. In this study, we screened 235 wild soybean ( Glycine soja Sieb. & Zucc.) accessions to identify genotypes resistant to SCN HG Type 2.5.7 (race 5), a less investigated type but is prevalent in the southeastern US. We also dissected the genetic basis of SCN resistance using a genome-wide association study with SNPs genotyped by SoySNP50k iSelect BeadChip. In total, 43 resistant accessions (female index < 30) were identified, with 10 SNPs being significantly associated with SCN HG 2.5.7 resistance in this wild species. Furthermore, four significant SNPs were localized to linked regions of the known quantitative trait locus (QTL) rhg1 on chromosome 18. The other four SNPs on chromosome 18 and two SNPs on chromosome 19 are novel. Genes encoding disease resistance-related proteins with a leucine-rich region, a mitogen-activated protein kinase (MAPK) on chromosome 18, and a MYB transcription factor on chromosome 19 were identified as promising candidate genes. The identified SNPs and candidate genes will benefit future marker-assisted breeding and dissection of the molecular mechanisms underlying the soybean-SCN interaction.

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          Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic diversity and selection.

          We report a large-scale analysis of the patterns of genome-wide genetic variation in soybeans. We re-sequenced a total of 17 wild and 14 cultivated soybean genomes to an average of approximately ×5 depth and >90% coverage using the Illumina Genome Analyzer II platform. We compared the patterns of genetic variation between wild and cultivated soybeans and identified higher allelic diversity in wild soybeans. We identified a high level of linkage disequilibrium in the soybean genome, suggesting that marker-assisted breeding of soybean will be less challenging than map-based cloning. We report linkage disequilibrium block location and distribution, and we identified a set of 205,614 tag SNPs that may be useful for QTL mapping and association studies. The data here provide a valuable resource for the analysis of wild soybeans and to facilitate future breeding and quantitative trait analysis.
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            RNA-Seq Atlas of Glycine max: A guide to the soybean transcriptome

            Background Next generation sequencing is transforming our understanding of transcriptomes. It can determine the expression level of transcripts with a dynamic range of over six orders of magnitude from multiple tissues, developmental stages or conditions. Patterns of gene expression provide insight into functions of genes with unknown annotation. Results The RNA Seq-Atlas presented here provides a record of high-resolution gene expression in a set of fourteen diverse tissues. Hierarchical clustering of transcriptional profiles for these tissues suggests three clades with similar profiles: aerial, underground and seed tissues. We also investigate the relationship between gene structure and gene expression and find a correlation between gene length and expression. Additionally, we find dramatic tissue-specific gene expression of both the most highly-expressed genes and the genes specific to legumes in seed development and nodule tissues. Analysis of the gene expression profiles of over 2,000 genes with preferential gene expression in seed suggests there are more than 177 genes with functional roles that are involved in the economically important seed filling process. Finally, the Seq-atlas also provides a means of evaluating existing gene model annotations for the Glycine max genome. Conclusions This RNA-Seq atlas extends the analyses of previous gene expression atlases performed using Affymetrix GeneChip technology and provides an example of new methods to accommodate the increase in transcriptome data obtained from next generation sequencing. Data contained within this RNA-Seq atlas of Glycine max can be explored at http://www.soybase.org/soyseq.
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              Impacts of genetic bottlenecks on soybean genome diversity.

              Soybean has undergone several genetic bottlenecks. These include domestication in Asia to produce numerous Asian landraces, introduction of relatively few landraces to North America, and then selective breeding over the past 75 years. It is presumed that these three human-mediated events have reduced genetic diversity. We sequenced 111 fragments from 102 genes in four soybean populations representing the populations before and after genetic bottlenecks. We show that soybean has lost many rare sequence variants and has undergone numerous allele frequency changes throughout its history. Although soybean genetic diversity has been eroded by human selection after domestication, it is notable that modern cultivars have retained 72% of the sequence diversity present in the Asian landraces but lost 79% of rare alleles (frequency
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                17 August 2016
                2016
                : 7
                : 1214
                Affiliations
                [1] 1Bao-Hua Song Lab, Department of Biological Sciences, University of North Carolina at Charlotte Charlotte, NC, USA
                [2] 2Eric Davis Lab, Department of Plant Pathology, North Carolina State University Raleigh, NC, USA
                [3] 3Institute of Industrial Crops, Henan Academy of Agricultural Sciences, National Subcenter for Soybean Improvement/Key Laboratory of Oil Crops Zhengzhou, China
                [4] 4SAS Institute Cary, NC, USA
                Author notes

                Edited by: Naveen C. Bisht, National Institute of Plant Genome Research, India

                Reviewed by: Humira Sonah, Laval University, Canada; Rupesh Kailasrao Deshmukh, University of Missouri, Canada

                *Correspondence: Bao-Hua Song bsong5@ 123456uncc.edu

                This article was submitted to Plant Genetics and Genomics, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2016.01214
                4987380
                907f87ae-9cde-4a4a-b0fc-6b73286d1ed9
                Copyright © 2016 Zhang, Li, Davis, Wang, Griffin, Kofsky and Song.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 June 2016
                : 02 August 2016
                Page count
                Figures: 4, Tables: 1, Equations: 0, References: 62, Pages: 11, Words: 7771
                Funding
                Funded by: North Carolina Biotechnology Center 10.13039/100005562
                Award ID: 2014-CFG-8005
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                genome-wide association analysis,soybean cyst nematode,scn,wild soybean,glycine soja,resistance

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