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      Comprehensive annotation of the Chinese tree shrew genome by large-scale RNA sequencing and long-read isoform sequencing

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          Abstract

          The Chinese tree shrew ( Tupaia belangeri chinensis) is emerging as an important experimental animal in multiple fields of biomedical research. Comprehensive reference genome annotation for both mRNA and long non-coding RNA (lncRNA) is crucial for developing animal models using this species. In the current study, we collected a total of 234 high-quality RNA sequencing (RNA-seq) datasets and two long-read isoform sequencing (ISO-seq) datasets and improved the annotation of our previously assembled high-quality chromosome-level tree shrew genome. We obtained a total of 3 514 newly annotated coding genes and 50 576 lncRNA genes. We also characterized the tissue-specific expression patterns and alternative splicing patterns of mRNAs and lncRNAs and mapped the orthologous relationships among 11 mammalian species using the current annotated genome. We identified 144 tree shrew-specific gene families, including interleukin 6 ( IL6) and STT3 oligosaccharyltransferase complex catalytic subunit B ( STT3B), which underwent significant changes in size. Comparison of the overall expression patterns in tissues and pathways across four species (human, rhesus monkey, tree shrew, and mouse) indicated that tree shrews are more similar to primates than to mice at the tissue-transcriptome level. Notably, the newly annotated purine rich element binding protein A ( PURA) gene and the STT3B gene family showed dysregulation upon viral infection. The updated version of the tree shrew genome annotation (KIZ version 3: TS_3.0) is available at http://www.treeshrewdb.org and provides an essential reference for basic and biomedical studies using tree shrew animal models.

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          Most cited references108

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

                Author and article information

                Contributors
                Journal
                Zool Res
                Zool Res
                ZR
                Zoological Research
                Science Press (16 Donghuangchenggen Beijie, Beijing 100717, China )
                2095-8137
                18 November 2021
                : 42
                : 6
                : 692-709
                Affiliations
                [1 ] Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650204, China
                [2 ] Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
                [3 ] National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
                [4 ] State Key Laboratory of Veterinary Etiological Biology, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou, Gansu 730046, China
                Author notes

                #Authors contributed equally to this work

                Article
                zr-42-6-692
                10.24272/j.issn.2095-8137.2021.272
                8645884
                34581030
                1d66281c-702c-4ac1-8471-0d34e95c47fa
                Editorial Office of Zoological Research, Kunming Institute of Zoology, Chinese Academy of Sciences

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 2 September 2021
                : 24 September 2021
                Funding
                This study was supported by the National Natural Science Foundation of China (U1902215 to Y.G.Y. and 31970542 to Y.F.), Chinese Academy of Sciences (Light of West China Program xbzg-zdsys-201909 to Y.G.Y.), and Yunnan Province (202001AS070023 and 2018FB046 to D.D.Y. and 202002AA100007 to Y.G.Y.)
                Categories
                Article

                tree shrew,genome annotation,transcriptome,gene family,virus infection

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