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      Transcriptome analysis reveals molecular mechanisms responsive to acute cold stress in the tropical stenothermal fish tiger barb ( Puntius tetrazona)

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          Abstract

          Background

          Tropical stenothermal fish exhibit special tolerance and response to cold stress. However current knowledge of the molecular mechanisms response to cold stress in aquatic ectotherms is largely drawn from eurythermal or extreme stenothermal species. The tiger barb Puntius tetrazona is a tropical stenothermal fish, with great popularity in aquarium trade and research.

          Results

          To investigate the response mechanism of P. tetrazona to low temperature, fish were exposed to increasing levels of acute cold stress. Histopathological analysis showed that the brain, gill, liver and muscle tissues appeared serious damage after cold stress (13 °C). Brain, gill, liver and muscle tissues from control (CTRL) groups (27 °C) and COLD stress groups (13 °C) of eight-month fish (gender-neutral) were sampled and assessed for transcriptomic profiling by high-throughput sequencing. 83.0 Gb of raw data were generated, filtered and assembled for de novo transcriptome assembly. According to the transcriptome reference, we obtained 392,878 transcripts and 238,878 unigenes, of which 89.29% of the latter were annotated. There were 23,743 differently expressed genes (DEGs) been filtered from four pairs of tissues (brain, gill, liver and muscle) between these cold stress and control groups. These DEGs were mainly involved in circadian entrainment, circadian rhythm, biosynthesis of steroid and fatty acid. There were 64 shared DEGs between the four pairs of groups, and five were related to ubiquitylation/deubiquitylation. Our results suggested that ubiquitin-mediated protein degradation might be necessary for tropical stenothermal fish coping with acute cold stress. Also, the significant cold-induced expression of heat shock 70 kDa protein ( HSP70) and cold-induced RNA-binding protein ( CIRBP) was verified. These results suggested that the expression of the molecular chaperones HSP70 and CIRBP in P. tetrazona might play a critical role in coping with acute cold stress.

          Conclusions

          This is the first transcriptome analysis of P. tetrazona using RNA-Seq technology. Novel findings about tropical stenothermal fish under cold stress (such as HSP70 and CIRBP genes) are presented here. This study contributes new insights into the molecular mechanisms of tropical stenothermal species response to acute cold stress .

          Supplementary information

          Supplementary information accompanies this paper at 10.1186/s12864-020-07139-z.

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          Most cited references75

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          RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

          Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
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            Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data

            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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              Differential expression analysis for sequence count data

              High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. We propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, DESeq, as an R/Bioconductor package.
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                Author and article information

                Contributors
                Lilyinmay@163.com
                53781451@qq.com
                wxw211@126.com
                zhuhua@bjfishery.com
                tzhhui@126.com
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                23 October 2020
                23 October 2020
                2020
                : 21
                : 737
                Affiliations
                GRID grid.418260.9, ISNI 0000 0004 0646 9053, Beijing Key Laboratory of Fishery Biotechnology, , Beijing Fisheries Research Institute, ; Beijing, 100068 China
                Author information
                http://orcid.org/0000-0003-1427-8102
                Article
                7139
                10.1186/s12864-020-07139-z
                7584086
                33096997
                e49bac3a-9da1-48d6-bdbd-f2d2e4d4ef86
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 5 November 2019
                : 11 October 2020
                Funding
                Funded by: Beijing Natural Science Foundation
                Award ID: 6194032
                Award Recipient :
                Funded by: Beijing Postdoctoral Research Foundation (CN)
                Award ID: 2018ZZ058
                Award Recipient :
                Funded by: Beijing Innovation Team of Ornamental Fish Industry Technology System
                Award ID: BAIC03-20200210
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100010038, Earmarked Fund for China Agriculture Research System;
                Award ID: CARS-45-31
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Genetics
                cold stress,multiple tissues,tropical stenothermal fish,ubiquitin-mediated protein degradation,heat shock 70 kda protein,cold-induced rna-binding protein

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