4.6 Article

Characterization of Liaoning Cashmere Goat Transcriptome: Sequencing, De Novo Assembly, Functional Annotation and Comparative Analysis

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PLOS ONE
卷 8, 期 10, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0077062

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  1. National High Technology Research and Development Program of China (863 Program) [2011AA100303]

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Background: Liaoning cashmere goat is a famous goat breed for cashmere wool. In order to increase the transcriptome data and accelerate genetic improvement for this breed, we performed de novo transcriptome sequencing to generate the first expressed sequence tag dataset for the Liaoning cashmere goat, using next-generation sequencing technology. Results: Transcriptome sequencing of Liaoning cashmere goat on a Roche 454 platform yielded 804,601 high-quality reads. Clustering and assembly of these reads produced a non-redundant set of 117,854 unigenes, comprising 13,194 isotigs and 104,660 singletons. Based on similarity searches with known proteins, 17,356 unigenes were assigned to 6,700 GO categories, and the terms were summarized into three main GO categories and 59 sub-categories. 3,548 and 46,778 unigenes had significant similarity to existing sequences in the KEGG and COG databases, respectively. Comparative analysis revealed that 42,254 unigenes were aligned to 17,532 different sequences in NCBI non-redundant nucleotide databases. 97,236 (82.51%) unigenes were mapped to the 30 goat chromosomes. 35,551 (30.17%) unigenes were matched to 11,438 reported goat protein-coding genes. The remaining non-matched unigenes were further compared with cattle and human reference genes, 67 putative new goat genes were discovered. Additionally, 2,781 potential simple sequence repeats were initially identified from all unigenes. Conclusion: The transcriptome of Liaoning cashmere goat was deep sequenced, de novo assembled, and annotated, providing abundant data to better understand the Liaoning cashmere goat transcriptome. The potential simple sequence repeats provide a material basis for future genetic linkage and quantitative trait loci analyses.

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