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      Transcriptome Analysis of Salt Tolerant Common Bean (Phaseolus vulgaris L.) under Saline Conditions

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      PLoS ONE

      Public Library of Science

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          Salinity is one of the important abiotic stress factors that limit crop production. Common bean, Phaseolus vulgaris L., a major protein source in developing countries, is highly affected by soil salinity and the information on genes that play a role in salt tolerance is scarce. We aimed to identify differentially expressed genes (DEGs) and related pathways by comprehensive analysis of transcriptomes of both root and leaf tissues of the tolerant genotype grown under saline and control conditions in hydroponic system. We have generated a total of 158 million high-quality reads which were assembled into 83,774 all-unigenes with a mean length of 813 bp and N50 of 1,449 bp. Among the all-unigenes, 58,171 were assigned with Nr annotations after homology analyses. It was revealed that 6,422 and 4,555 all-unigenes were differentially expressed upon salt stress in leaf and root tissues respectively. Validation of the RNA-seq quantifications (RPKM values) was performed by qRT-PCR (Quantitative Reverse Transcription PCR) analyses. Enrichment analyses of DEGs based on GO and KEGG databases have shown that both leaf and root tissues regulate energy metabolism, transmembrane transport activity, and secondary metabolites to cope with salinity. A total of 2,678 putative common bean transcription factors were identified and classified under 59 transcription factor families; among them 441 were salt responsive. The data generated in this study will help in understanding the fundamentals of salt tolerance in common bean and will provide resources for functional genomic studies.

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          Most cited references 83

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            Massively-parallel cDNA sequencing has opened the way to deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here, we present the Trinity methodology for de novo full-length transcriptome reconstruction, and evaluate it on samples from fission yeast, mouse, and whitefly – an insect whose genome has not yet been sequenced. Trinity fully reconstructs a large fraction of the transcripts present in the data, also reporting alternative splice isoforms and transcripts from recently duplicated genes. In all cases, Trinity performs better than other available de novo transcriptome assembly programs, and its sensitivity is comparable to methods relying on genome alignments. Our approach provides a unified and general solution for transcriptome reconstruction in any sample, especially in the complete absence of a reference genome.
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              Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research.

              We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. Blast2GO is freely available via Java Web Start at -> Evaluation.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                20 March 2014
                : 9
                : 3

                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.

                Pages: 13
                This work was financially supported by The Scientific and Technological Research Council of Turkey (TUBITAK 110T922) and Bogazici University Research Funds (BAP 6674). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article
                Biology and Life Sciences
                Agricultural Methods
                Sustainable Agriculture
                Plant Biotechnology
                Plant Genomics
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Plant Genetics
                Crop Genetics
                Gene Identification and Analysis
                Molecular Genetics
                Plant Science



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