RT Journal Article
SR Electronic
T1 <em>De novo</em> transcriptomic characterization of <em>Betta splendens</em> for identifying sex-biased genes potentially involved in aggressive behavior modulation and EST-SSR maker development
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 355354
DO 10.1101/355354
A1 Wei Yang
A1 Yaorong Wang
A1 Chunhua Zhu
A1 Guangli Li
A1 Hai Huang
A1 Huapu Chen
YR 2018
UL http://biorxiv.org/content/early/2018/06/25/355354.abstract
AB Betta splendens is not only a commercially important labyrinth fish but also a nice research model for understanding the biological underpinnings of aggressive behavior. However, the shortage of basic genetic resource severely inhibits investigations on the molecular mechanism in sexual dimorphism of aggressive behavior typicality, which are essential for further behavior-related studies. There is a lack of knowledge regarding the functional genes involved in aggression expression. The scarce marker resource also impedes research progress of population genetics and genomics. In order to enrich genetic data and sequence resources, transcriptomic analysis was conducted for mature B. splendens using a multiple-tissues mixing strategy. A total of 105,505,486 clean reads were obtained and by de novo assembly, 69,836 unigenes were generated. Of which, 35,751 unigenes were annotated in at least one of queried databases. The differential expression analysis resulted in 17,683 transcripts differentially expressed between males and females. Plentiful sex-biased genes involved in aggression exhibition were identified via a screening from Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways, such as htr, drd, gabr, cyp11a1, cyp17a1, hsd17b3, dax1, sf-1, hsd17b7, gsdf1 and fem1c. These putative genes would make good starting points for profound mechanical exploration on aggressive behavioral regulation. Moreover, 12,751 simple sequence repeats were detected from 9,617 unigenes for marker development. Nineteen of the 100 randomly selected primer pairs were demonstrated to be polymorphic. The large amount of transcript sequences will considerably increase available genomic information for gene mining and function analysis, and contribute valuable microsatellite marker resources to in-depth studies on molecular genetics and genomics in the future.