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Yao X, Sun S, Zi Y, Liu Y, Yang J, Ren L, Chen G, Cao Z, Hou W, Song Y, Shang J, Jiang H, Li Z, Wang H, Zhang P, Shi L, Li QZ, Yu Y, Zheng Y. Comprehensive microRNA-seq transcriptomic profiling across 11 organs, 4 ages, and 2 sexes of Fischer 344 rats. Sci Data 2022; 9:201. [PMID: 35551205 PMCID: PMC9098487 DOI: 10.1038/s41597-022-01285-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 03/04/2022] [Indexed: 11/08/2022] Open
Abstract
Rat is one of the most widely-used models in chemical safety evaluation and biomedical research. However, the knowledge about its microRNA (miRNA) expression patterns across multiple organs and various developmental stages is still limited. Here, we constructed a comprehensive rat miRNA expression BodyMap using a diverse collection of 320 RNA samples from 11 organs of both sexes of juvenile, adolescent, adult and aged Fischer 344 rats with four biological replicates per group. Following the Illumina TruSeq Small RNA protocol, an average of 5.1 million 50 bp single-end reads was generated per sample, yielding a total of 1.6 billion reads. The quality of the resulting miRNA-seq data was deemed to be high from raw sequences, mapped sequences, and biological reproducibility. Importantly, aliquots of the same RNA samples have previously been used to construct the mRNA BodyMap. The currently presented miRNA-seq dataset along with the existing mRNA-seq dataset from the same RNA samples provides a unique resource for studying the expression characteristics of existing and novel miRNAs, and for integrative analysis of miRNA-mRNA interactions, thereby facilitating better utilization of rats for biomarker discovery.
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Affiliation(s)
- Xintong Yao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Shanyue Sun
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Yi Zi
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Yaqing Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Jingcheng Yang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Luyao Ren
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Guangchun Chen
- Department of Immunology, Microarray and Immune Phenotyping Core Facility, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Zehui Cao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Wanwan Hou
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Yueqiang Song
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Jun Shang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - He Jiang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Zhihui Li
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Haiyan Wang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Peipei Zhang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Quan-Zhen Li
- Department of Immunology, Microarray and Immune Phenotyping Core Facility, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
| | - Ying Yu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China.
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China.
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Dou T, Yan S, Liu L, Wang K, Jian Z, Xu Z, Zhao J, Wang Q, Sun S, Talpur MZ, Duan X, Gu D, He Y, Du Y, Abdulwahid AM, Li Q, Rong H, Cao W, Su Z, Zhao G, Liu R, Zhao S, Huang Y, Te Pas MFW, Ge C, Jia J. Integrative analysis of transcriptomics and metabolomics to reveal the melanogenesis pathway of muscle and related meat characters in Wuliangshan black-boned chickens. BMC Genomics 2022; 23:173. [PMID: 35236293 PMCID: PMC8892760 DOI: 10.1186/s12864-022-08388-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Accepted: 02/03/2022] [Indexed: 12/02/2022] Open
Abstract
Background Melanin is an important antioxidant in food and has been used in medicine and cosmetology. Chicken meat with high melanin content from black-boned chickens have been considered a high nutritious food with potential medicinal properties. The molecular mechanism of melanogenesis of skeletal muscle in black-boned chickens remain poorly understood. This study investigated the biological gene-metabolite associations regulating the muscle melanogenesis pathways in Wuliangshan black-boned chickens with two normal boned chicken breeds as control. Results We identified 25 differentially expressed genes and 11 transcription factors in the melanogenesis pathways. High levels of the meat flavor compounds inosine monophosphate, hypoxanthine, lysophospholipid, hydroxyoctadecadienoic acid, and nicotinamide mononucleotide were found in Wuliangshan black-boned chickens. Conclusion Integrative analysis of transcriptomics and metabolomics revealed the dual physiological functions of the PDZK1 gene, involved in pigmentation and/or melanogenesis and regulating the phospholipid signaling processes in muscle of black boned chickens. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08388-w.
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Affiliation(s)
- Tengfei Dou
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Shixiong Yan
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Lixian Liu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China.,Yunnan Vocational and Technical College of Agriculture, Kunming, 650031, Yunnan Province, People's Republic of China
| | - Kun Wang
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Zonghui Jian
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Zhiqiang Xu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China.,College of Food Science, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Jingying Zhao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Qiuting Wang
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Shuai Sun
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Mir Zulqarnain Talpur
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Xiaohua Duan
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China.,Yunnan University of Traditional Chinese Medical, Kunming, 650500, Yunnan Province, People's Republic of China
| | - Dahai Gu
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China.,College of Food Science, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Yang He
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Yanli Du
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Alsoufi Mohammed Abdulwahid
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Qihua Li
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Hua Rong
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Weina Cao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Zhengchang Su
- Department of Bioinformatics and Genomics, College of Computing and Informatics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Guiping Zhao
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Ranran Liu
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Sumei Zhao
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Ying Huang
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China
| | - Marinus F W Te Pas
- Wageningen Livestock Research, Wageningen UR, Wageningen, 238050, The Netherlands. .,Visiting Professor Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China.
| | - Changrong Ge
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China.
| | - Junjing Jia
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, Yunnan Province, People's Republic of China.
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Gong B, Xu J, Tong W. Landscape of circRNAs Across 11 Organs and 4 Ages in Fischer 344 Rats. Chem Res Toxicol 2020; 34:240-246. [PMID: 32692164 DOI: 10.1021/acs.chemrestox.0c00144] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Circular RNAs (circRNAs) are a class of endogenous noncoding RNAs with a covalently closed loop. Aside from their recognized regulatory functions (e.g., sponging microRNAs to reduce their activity, and altering parental gene transcription by competing with the canonical splicing of pre-mRNA), expression of circRNAs is abundant, diverse, and conservative across species, rendering them as potential biomarker candidates. Consequently, the landscape of circRNAs has been studied for several species. Although the rat is one of the most important animal models for drug safety and toxicological research, few attempts have been made to understand the landscape of rat circRNAs. One noticeable challenge in analyzing circRNAs with next-generation sequencing (NGS) data is to find ways to use rapidly advancing bioinformatics approaches to improve accuracy while also reducing the number of resulting false positives that occur in circRNA identification with these new methods. Here, we applied two of the most advanced circRNA bioinformatics pipelines to provide a landscape of circRNAs in rats by analyzing an RNA-seq data set for 11 organs (adrenal gland, brain, heart, kidney, liver, lung, muscle, spleen, thymus, and testis or uterus) from Fischer 344 rats of both sexes in four age groups (juvenile, adolescence, adult, and aged). The circRNAs displayed organ-specific patterns and sex differences in most organs. Lowest numbers of circRNAs were seen in the liver and muscle, while highest numbers of circRNAs occurred in the brain, which correlated to gene expression patterns seen across those organs. Concordance of circRNAs between males and females was approximately 50% in nonsex organs, implying that some caution needs to be exercised when selecting specific circRNAs as biomarkers for both sexes. The number of common circRNAs between sexes increased with age for most organs except heart, spleen, and thymus. A dramatic drop in the number of circRNAs in kidney, thymus, and testis was observed in aged rats, suggesting that the regulatory function of circRNAs is age dependent. From the 1595 circRNAs identified with high confidence, only 6 appeared in all 9 of the nonsex organs in both sexes and four age groups. Forty-one and 48 circRNAs were identified in more than 5 nonsex organs in males and females, respectively, while close to 280 circRNAs were found in an organ for more than 2 age groups in both sexes. This study offers an overview of rat circRNAs, which contributes to the effort of identifying circRNAs as potential biomarkers for safety and risk assessment.
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Affiliation(s)
- Binsheng Gong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, Arkansas 72079, United States
| | - Joshua Xu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, Arkansas 72079, United States
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, Arkansas 72079, United States
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Fraik AK, Quackenbush C, Margres MJ, Comte S, Hamilton DG, Kozakiewicz CP, Jones M, Hamede R, Hohenlohe PA, Storfer A, Kelley JL. Transcriptomics of Tasmanian Devil ( Sarcophilus Harrisii) Ear Tissue Reveals Homogeneous Gene Expression Patterns across a Heterogeneous Landscape. Genes (Basel) 2019; 10:E801. [PMID: 31614864 PMCID: PMC6826840 DOI: 10.3390/genes10100801] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 10/03/2019] [Accepted: 10/08/2019] [Indexed: 02/06/2023] Open
Abstract
In an era of unprecedented global change, exploring patterns of gene expression among wild populations across their geographic range is crucial for characterizing adaptive potential. RNA-sequencing studies have successfully characterized gene expression differences among populations experiencing divergent environmental conditions in a wide variety of taxa. However, few of these studies have identified transcriptomic signatures to multivariate, environmental stimuli among populations in their natural environments. Herein, we aim to identify environmental and sex-driven patterns of gene expression in the Tasmanian devil (Sarcophilus harrisii), a critically endangered species that occupies a heterogeneous environment. We performed RNA-sequencing on ear tissue biopsies from adult male and female devils from three populations at the extremes of their geographic range. There were no transcriptome-wide patterns of differential gene expression that would be suggestive of significant, environmentally-driven transcriptomic responses. The general lack of transcriptome-wide variation in gene expression levels across the devil's geographic range is consistent with previous studies that documented low levels of genetic variation in the species. However, genes previously implicated in local adaptation to abiotic environment in devils were enriched for differentially expressed genes. Additionally, three modules of co-expressed genes were significantly associated with either population of origin or sex.
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Affiliation(s)
- Alexandra K Fraik
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA.
| | - Corey Quackenbush
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA.
| | - Mark J Margres
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA.
- Department of Biological Sciences, Clemson University, Clemson, SC 29634, USA.
| | - Sebastien Comte
- School of Natural Sciences, Hobart, TAS 7001, Australia.
- Vertebrate Pest Research Unit, NSW Department of Primary Industries, 1447 Forest Road, Orange, NSW 2800, Australia.
| | | | | | - Menna Jones
- School of Natural Sciences, Hobart, TAS 7001, Australia.
| | - Rodrigo Hamede
- School of Natural Sciences, Hobart, TAS 7001, Australia.
| | - Paul A Hohenlohe
- Department of Biological Sciences, University of Idaho, Institute for Bioinformatics and Evolutionary Studies, University of Idaho, 875 Perimeter Drive, Moscow, ID 83844, USA.
| | - Andrew Storfer
- Department of Biological Sciences, University of Idaho, Institute for Bioinformatics and Evolutionary Studies, University of Idaho, 875 Perimeter Drive, Moscow, ID 83844, USA.
| | - Joanna L Kelley
- Department of Biological Sciences, University of Idaho, Institute for Bioinformatics and Evolutionary Studies, University of Idaho, 875 Perimeter Drive, Moscow, ID 83844, USA.
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