Title |
Fish-T1K (Transcriptomes of 1,000 Fishes) Project: large-scale transcriptome data for fish evolution studies
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Published in |
Giga Science, May 2016
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DOI | 10.1186/s13742-016-0124-7 |
Pubmed ID | |
Authors |
Ying Sun, Yu Huang, Xiaofeng Li, Carole C. Baldwin, Zhuocheng Zhou, Zhixiang Yan, Keith A. Crandall, Yong Zhang, Xiaomeng Zhao, Min Wang, Alex Wong, Chao Fang, Xinhui Zhang, Hai Huang, Jose V. Lopez, Kirk Kilfoyle, Yong Zhang, Guillermo Ortí, Byrappa Venkatesh, Qiong Shi |
Abstract |
Ray-finned fishes (Actinopterygii) represent more than 50 % of extant vertebrates and are of great evolutionary, ecologic and economic significance, but they are relatively underrepresented in 'omics studies. Increased availability of transcriptome data for these species will allow researchers to better understand changes in gene expression, and to carry out functional analyses. An international project known as the "Transcriptomes of 1,000 Fishes" (Fish-T1K) project has been established to generate RNA-seq transcriptome sequences for 1,000 diverse species of ray-finned fishes. The first phase of this project has produced transcriptomes from more than 180 ray-finned fishes, representing 142 species and covering 51 orders and 109 families. Here we provide an overview of the goals of this project and the work done so far. |
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Geographical breakdown
Country | Count | As % |
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United Kingdom | 7 | 17% |
United States | 2 | 5% |
Germany | 2 | 5% |
Canada | 2 | 5% |
Chile | 1 | 2% |
Greece | 1 | 2% |
Norway | 1 | 2% |
Hong Kong | 1 | 2% |
France | 1 | 2% |
Other | 4 | 10% |
Unknown | 19 | 46% |
Demographic breakdown
Type | Count | As % |
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Scientists | 21 | 51% |
Members of the public | 17 | 41% |
Science communicators (journalists, bloggers, editors) | 3 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 1 | 2% |
Unknown | 61 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 11 | 18% |
Student > Ph. D. Student | 10 | 16% |
Student > Master | 7 | 11% |
Student > Doctoral Student | 5 | 8% |
Professor | 5 | 8% |
Other | 6 | 10% |
Unknown | 18 | 29% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 14 | 23% |
Computer Science | 5 | 8% |
Environmental Science | 2 | 3% |
Business, Management and Accounting | 1 | 2% |
Other | 2 | 3% |
Unknown | 21 | 34% |