Comparative analysis of neural transcriptomes and functional implication of unannotated intronic expression

Differences in growth, fillet quality, and fatty acid metabolism-related gene expression between juvenile male and female rainbow trout

Sexual maturation occurs at the expense of stored energy and nutrients, including lipids; however, little is known regarding sex effects on nutrient regulatory mechanisms in rainbow trout prior to maturity. Thirty-two, 14-month-old, male and female rainbow trout were sampled for growth, carcass yield, fillet composition, and gene expression of liver, white muscle, and visceral adipose tissue. Growth parameters, including gonadosomatic index, were not affected by sex. Females had higher percent separable muscle yield, but there were no sex effects on fillet proximate composition. Fillet shear force indicated females produce firmer fillets than males. Male livers had greater expression of three cofactors within the mTOR signaling pathway that act to inhibit TORC1 assembly; mo25, rictor, and pras40. Male liver also exhibited increased expression of β-oxidation genes cpt1b and ehhadh. These findings are indicative of increased mitochondrial β-oxidation in male liver. Females exhibited increased expression of the mTOR cofactor raptor in white muscle and had higher expression levels of several genes within the fatty acid synthesis pathway, including gpat, srebp1, scd1, and cd36. Female muscle also had increased expression of β-oxidation genes cpt1d and cpt2. Increased expression of both fatty acid synthesis and β-oxidation genes suggests female muscle may have greater fatty acid turnover. Differences between sexes were primarily associated with variation of gene expression within the mTOR signaling pathway. Overall, data suggest there is differential regulation of gene expression in male and female rainbow trout tissues prior to the onset of sexual maturity that may lead to nutrient repartitioning during maturation.

Genes, behavior and next-generation RNA sequencing

Advances in next-generation sequencing suggest that RNA-Seq is poised to supplant microarray-based approaches for transcriptome analysis. This article briefly reviews the use of microarrays in the brain-behavior context and then illustrates why RNA-Seq is a superior strategy. Compared with microarrays, RNA-Seq has a greater dynamic range, detects both coding and noncoding RNAs, is superior for gene network construction, detects alternative spliced transcripts, detects allele specific expression and can be used to extract genotype information, e.g. nonsynonymous coding single nucleotide polymorphisms. Examples of where RNA-Seq has been used to assess brain gene expression are provided. Despite the advantages of RNA-Seq, some disadvantages remain. These include the high cost of RNA-Seq and the computational complexities associated with data analysis. RNA-Seq embraces the complexity of the transcriptome and provides a mechanism to understand the underlying regulatory code; the potential to inform the brain-behavior relationship is substantial.