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      Comparative Transcriptome Analysis Reveals Sex-Biased Gene Expression in Juvenile Chinese Mitten Crab Eriocheir sinensis

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          Abstract

          Sex-biased genes are considered to account for most of phenotypic differences between males and females. In order to explore the sex-biased gene expression in crab, we performed the whole-body transcriptome analysis in male and female juveniles of the Chinese mitten crab Eriocheir sinensis using next-generation sequencing technology. Of the 23,349 annotated unigenes, 148 were identified as sex-related genes. A total of 29 candidate genes involved in primary sex determination pathways were detected, indicating the sex determination cascade of the mitten crab might be more complex than previously supposed. Differential expression analysis showed 448 differentially expressed genes (DEGs) between the two transcriptomes. Most of DEGs were involved in processes such as metabolism and immunity, and not associated with obvious sexual function. The pathway predominantly enriched for DEGs were related to lysosome, which might reflect the differences in metabolism between males and females. Of the immune DGEs, 18 up-regulated genes in females were humoral immune factors, and eight up-regulated genes in males were pattern recognition receptors, suggesting sex differences of immune defense might exist in the mitten crab. In addition, two reproduction-related genes, vitellogenin and insulin-like androgenic gland factor, were identified to express in both sexes but with significantly higher level in males. Our research provides the first whole-body RNA sequencing of sex-specific transcriptomes for juvenile E. sinensis and will facilitate further studies on molecular mechanisms of crab sexual dimorphism.

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          Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.).

          A software tool was developed for the identification of simple sequence repeats (SSRs) in a barley ( Hordeum vulgare L.) EST (expressed sequence tag) database comprising 24,595 sequences. In total, 1,856 SSR-containing sequences were identified. Trimeric SSR repeat motifs appeared to be the most abundant type. A subset of 311 primer pairs flanking SSR loci have been used for screening polymorphisms among six barley cultivars, being parents of three mapping populations. As a result, 76 EST-derived SSR-markers were integrated into a barley genetic consensus map. A correlation between polymorphism and the number of repeats was observed for SSRs built of dimeric up to tetrameric units. 3'-ESTs yielded a higher portion of polymorphic SSRs (64%) than 5'-ESTs did. The estimated PIC (polymorphic information content) value was 0.45 +/- 0.03. Approximately 80% of the SSR-markers amplified DNA fragments in Hordeum bulbosum, followed by rye, wheat (both about 60%) and rice (40%). A subset of 38 EST-derived SSR-markers comprising 114 alleles were used to investigate genetic diversity among 54 barley cultivars. In accordance with a previous, RFLP-based, study, spring and winter cultivars, as well as two- and six-rowed barleys, formed separate clades upon PCoA analysis. The results show that: (1) with the software tool developed, EST databases can be efficiently exploited for the development of cDNA-SSRs, (2) EST-derived SSRs are significantly less polymorphic than those derived from genomic regions, (3) a considerable portion of the developed SSRs can be transferred to related species, and (4) compared to RFLP-markers, cDNA-SSRs yield similar patterns of genetic diversity.
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            Computational methods for transcriptome annotation and quantification using RNA-seq.

            High-throughput RNA sequencing (RNA-seq) promises a comprehensive picture of the transcriptome, allowing for the complete annotation and quantification of all genes and their isoforms across samples. Realizing this promise requires increasingly complex computational methods. These computational challenges fall into three main categories: (i) read mapping, (ii) transcriptome reconstruction and (iii) expression quantification. Here we explain the major conceptual and practical challenges, and the general classes of solutions for each category. Finally, we highlight the interdependence between these categories and discuss the benefits for different biological applications.
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              eggNOG v3.0: orthologous groups covering 1133 organisms at 41 different taxonomic ranges

              Orthologous relationships form the basis of most comparative genomic and metagenomic studies and are essential for proper phylogenetic and functional analyses. The third version of the eggNOG database (http://eggnog.embl.de) contains non-supervised orthologous groups constructed from 1133 organisms, doubling the number of genes with orthology assignment compared to eggNOG v2. The new release is the result of a number of improvements and expansions: (i) the underlying homology searches are now based on the SIMAP database; (ii) the orthologous groups have been extended to 41 levels of selected taxonomic ranges enabling much more fine-grained orthology assignments; and (iii) the newly designed web page is considerably faster with more functionality. In total, eggNOG v3 contains 721 801 orthologous groups, encompassing a total of 4 396 591 genes. Additionally, we updated 4873 and 4850 original COGs and KOGs, respectively, to include all 1133 organisms. At the universal level, covering all three domains of life, 101 208 orthologous groups are available, while the others are applicable at 40 more limited taxonomic ranges. Each group is amended by multiple sequence alignments and maximum-likelihood trees and broad functional descriptions are provided for 450 904 orthologous groups (62.5%).
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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, CA USA )
                1932-6203
                20 July 2015
                2015
                : 10
                : 7
                : e0133068
                Affiliations
                [1 ]Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
                [2 ]National & Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao, China
                [3 ]University of Chinese Academy of Sciences, Beijing, China
                Zhejiang University, CHINA
                Author notes

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

                Conceived and designed the experiments: Y. Liu ZC. Performed the experiments: Y. Liu DL CS. Analyzed the data: Y. Liu MH. Contributed reagents/materials/analysis tools: Y. Li LL. Wrote the paper: Y. Liu.

                Article
                PONE-D-15-07058
                10.1371/journal.pone.0133068
                4507985
                26193085
                9033a1d1-28a2-4ba3-b7de-0d24d44067a4
                Copyright @ 2015

                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
                : 15 February 2015
                : 23 June 2015
                Page count
                Figures: 4, Tables: 4, Pages: 21
                Funding
                This work was supported by grants from the Chinese National "863" Project (No. 2012AA10A409, http://www.most.gov.cn/eng/) and National Natural Science Foundation of China (41276165 and 41206147, http://www.nsfc.gov.cn/publish/portal1/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                All data were deposited into the Sequence Read Archive (SRA) database ( http://www.ncbi.nlm.nih.gov/Traces/sra/) under accession numbers SRX554564 and SR554562 and all other relevant data are within the paper and its Supporting Information files.

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