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      SNP Discovery in the Transcriptome of White Pacific Shrimp Litopenaeus vannamei by Next Generation Sequencing

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          Abstract

          The application of next generation sequencing technology has greatly facilitated high throughput single nucleotide polymorphism (SNP) discovery and genotyping in genetic research. In the present study, SNPs were discovered based on two transcriptomes of Litopenaeus vannamei ( L. vannamei) generated from Illumina sequencing platform HiSeq 2000. One transcriptome of L. vannamei was obtained through sequencing on the RNA from larvae at mysis stage and its reference sequence was de novo assembled. The data from another transcriptome were downloaded from NCBI and the reads of the two transcriptomes were mapped separately to the assembled reference by BWA. SNP calling was performed using SAMtools. A total of 58,717 and 36,277 SNPs with high quality were predicted from the two transcriptomes, respectively. SNP calling was also performed using the reads of two transcriptomes together, and a total of 96,040 SNPs with high quality were predicted. Among these 96,040 SNPs, 5,242 and 29,129 were predicted as non-synonymous and synonymous SNPs respectively. Characterization analysis of the predicted SNPs in L. vannamei showed that the estimated SNP frequency was 0.21% (one SNP per 476 bp) and the estimated ratio for transition to transversion was 2.0. Fifty SNPs were randomly selected for validation by Sanger sequencing after PCR amplification and 76% of SNPs were confirmed, which indicated that the SNPs predicted in this study were reliable. These SNPs will be very useful for genetic study in L. vannamei, especially for the high density linkage map construction and genome-wide association studies.

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          Most cited references29

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          A genome-wide association study identifies novel risk loci for type 2 diabetes.

          Type 2 diabetes mellitus results from the interaction of environmental factors with a combination of genetic variants, most of which were hitherto unknown. A systematic search for these variants was recently made possible by the development of high-density arrays that permit the genotyping of hundreds of thousands of polymorphisms. We tested 392,935 single-nucleotide polymorphisms in a French case-control cohort. Markers with the most significant difference in genotype frequencies between cases of type 2 diabetes and controls were fast-tracked for testing in a second cohort. This identified four loci containing variants that confer type 2 diabetes risk, in addition to confirming the known association with the TCF7L2 gene. These loci include a non-synonymous polymorphism in the zinc transporter SLC30A8, which is expressed exclusively in insulin-producing beta-cells, and two linkage disequilibrium blocks that contain genes potentially involved in beta-cell development or function (IDE-KIF11-HHEX and EXT2-ALX4). These associations explain a substantial portion of disease risk and constitute proof of principle for the genome-wide approach to the elucidation of complex genetic traits.
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            Whole-genome patterns of common DNA variation in three human populations.

            D A Hinds (2005)
            Individual differences in DNA sequence are the genetic basis of human variability. We have characterized whole-genome patterns of common human DNA variation by genotyping 1,586,383 single-nucleotide polymorphisms (SNPs) in 71 Americans of European, African, and Asian ancestry. Our results indicate that these SNPs capture most common genetic variation as a result of linkage disequilibrium, the correlation among common SNP alleles. We observe a strong correlation between extended regions of linkage disequilibrium and functional genomic elements. Our data provide a tool for exploring many questions that remain regarding the causal role of common human DNA variation in complex human traits and for investigating the nature of genetic variation within and between human populations.
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              SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries.

              High-density single-nucleotide polymorphism (SNP) arrays have revolutionized the ability of genome-wide association studies to detect genomic regions harboring sequence variants that affect complex traits. Extensive numbers of validated SNPs with known allele frequencies are essential to construct genotyping assays with broad utility. We describe an economical, efficient, single-step method for SNP discovery, validation and characterization that uses deep sequencing of reduced representation libraries (RRLs) from specified target populations. Using nearly 50 million sequences generated on an Illumina Genome Analyzer from DNA of 66 cattle representing three populations, we identified 62,042 putative SNPs and predicted their allele frequencies. Genotype data for these 66 individuals validated 92% of 23,357 selected genome-wide SNPs, with a genotypic and sequence allele frequency correlation of r = 0.67. This approach for simultaneous de novo discovery of high-quality SNPs and population characterization of allele frequencies may be applied to any species with at least a partially sequenced genome.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                30 January 2014
                : 9
                : 1
                : e87218
                Affiliations
                [1 ]Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
                [2 ]University of Chinese Academy of Sciences, Beijing, China
                Chinese Academy of Fishery Sciences, China
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: FL JX. Performed the experiments: YY JW XZ JL. Analyzed the data: YY JW CL. Contributed reagents/materials/analysis tools: JW CL. Wrote the paper: YY FL.

                Article
                PONE-D-13-39710
                10.1371/journal.pone.0087218
                3907553
                46d97fa8-52cb-4190-9834-53d968ac6f7d
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 26 September 2013
                : 18 December 2013
                Page count
                Pages: 9
                Funding
                This work is supported by National High Technology Research and Development Program (863 Program) of China (2012AA10A404, 2012AA092205). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Agriculture
                Aquaculture
                Biology
                Computational Biology
                Genomics
                Genome Analysis Tools
                Gene Ontologies
                Genetic Screens
                Trait Locus Analysis
                Transcriptomes
                Molecular Genetics
                Genetics
                Genetic Mutation
                Mutation Types
                Population Genetics
                Genetic Polymorphism
                Animal Genetics
                Genetic Screens
                Marine Biology

                Uncategorized
                Uncategorized

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