MicroRNAs identification and bioinformatics analysis in large yellow croaker Larimichthys crocea using an integrated comparative and ab initio approach

Abstract

MicroRNAs (miRNAs) are a group of small, endogenous, single-stranded non-coding RNAs that post-transcriptionally regulate gene expression levels. Previous studies have revealed that miRNAs play key roles in multiple biological processes, such as growth and development in both animals and plants. Computational identification is an efficient method for miRNA prediction in organisms with a reference genome before high-throughput miRNA sequencing experiments. In this study, we employed an integrated strategy combining the homology-based and ab initio approaches to predict miRNAs from the genome and transcriptome of large yellow croaker, one of the most commercially important marine fish in China and East Asia. A total of 418 miRNA molecules, including 287 miRNAs by the homology-based method and 131 miRNAs by the ab initio approach, were identified for large yellow croaker. Additionally, 16 053 target genes were predicted and annotated for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Meanwhile, we analysed single nucleotide polymorphisms (SNPs) around large yellow croaker miRNA and found that the miRNA seed regions were significantly less prone to mutations, indicating that the miRNA sequences were under strict natural selection based on their essential regulation functions in living cells. Twenty-two SNPs were identified in large yellow croaker miRNA seed regions, which dramatically influenced the miRNA-gene regulation networks. This is the first reported miRNA detection from both the genome and transcriptome using the integrated strategy for large yellow croaker species, and the miRNA and SNP analyses in this work provide important resources and a reference for subsequent miRNA functional investigations in large yellow croaker.