Transcriptomics of mRNA and egg quality in farmed fish: Some recent developments and future directions

Abstract

Maternal mRNA transcripts deposited in growing oocytes regulate early development and are under intensive investigation as determinants of egg quality. The research has evolved from single gene studies to microarray and now RNA-Seq analyses in which mRNA expression by virtually every gene can be assessed and related to gamete quality. Such studies have mainly focused on genes changing two- to several-fold in expression between biological states, and have identified scores of candidate genes and a few gene networks whose functioning is related to successful development. However, ever-increasing yields of information from high throughput methods for detecting transcript abundance have far outpaced progress in methods for analyzing the massive quantities of gene expression data, and especially for meaningful relation of whole transcriptome profiles to gamete quality. We have developed a new approach to this problem employing artificial neural networks and supervised machine learning with other novel bioinformatics procedures to discover a previously unknown level of ovarian transcriptome function at which minute changes in expression of a few hundred genes is highly predictive of egg quality. In this paper, we briefly review the progress in transcriptomics of fish egg quality and discuss some future directions for this field of study.