PLoS ONE (Jan 2013)
Transcriptome sequencing and analysis of wild Amur Ide (Leuciscus waleckii) inhabiting an extreme alkaline-saline lake reveals insights into stress adaptation.
Abstract
BackgroundAmur ide (Leuciscus waleckii) is an economically and ecologically important species in Northern Asia. The Dali Nor population inhabiting Dali Nor Lake, a typical saline-alkaline lake in Inner Mongolia, is well-known for its adaptation to extremely high alkalinity. Genome information is needed for conservation and aquaculture purposes, as well as to gain further understanding into the genetics of stress tolerance. The objective of the study is to sequence the transcriptome and obtain a well-assembled transcriptome of Amur ide.ResultsThe transcriptome of Amur ide was sequenced using the Illumina platform and assembled into 53,632 cDNA contigs, with an average length of 647 bp and a N50 length of 1,094 bp. A total of 19,338 unique proteins were identified, and gene ontology and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses classified all contigs into functional categories. Open Reading Frames (ORFs) were detected from 34,888 (65.1%) of contigs with an average length of 577 bp, while 9,638 full-length cDNAs were identified. Comparative analyses revealed that 31,790 (59.3%) contigs have a significant similarity to zebrafish proteins, and 27,096 (50.5%), 27,524 (51.3%) and 27,996 (52.2%) to teraodon, medaka and three-spined stickleback proteins, respectively. A total of 10,395 microsatellites and 34,299 SNPs were identified and classified. A dN/dS analysis on unigenes was performed, which identified that 61 of the genes were under strong positive selection. Most of the genes are associated with stress adaptation and immunity, suggesting that the extreme alkaline-saline environment resulted in fast evolution of certain genes.ConclusionsThe transcriptome of Amur ide had been deeply sequenced, assembled and characterized, providing a valuable resource for a better understanding of the Amur ide genome. The transcriptome data will facilitate future functional studies on the Amur ide genome, as well as provide insight into potential mechanisms for adaptation to an extreme alkaline-saline environment.