Identification and Functional Prediction of Large Intergenic Noncoding RNAs (lincRNAs) in Rainbow Trout (<Emphasis Type="Italic">Oncorhynchus mykiss</Emphasis>)

Long noncoding RNAs (lncRNAs) have been recognized in recent years as key regulators of diverse cellular processes. Genome-wide large-scale projects have uncovered thousands of lncRNAs in many model organisms. Large intergenic noncoding RNAs (lincRNAs) are lncRNAs that are transcribed from intergenic regions of genomes. To date, no lincRNAs in non-model teleost fish have been reported. In this report, we present the first reference catalog of 9674 rainbow trout lincRNAs based on analysis of RNA-Seq data from 15 tissues. Systematic analysis revealed that lincRNAs in rainbow trout share many characteristics with those in other mammalian species. They are shorter and lower in exon number and expression level compared with protein-coding genes. They show tissue-specific expression pattern and are typically co-expressed with their neighboring genes. Co-expression network analysis suggested that many lincRNAs are associated with immune response, muscle differentiation, and neural development. The study provides an opportunity for future experimental and computational studies to uncover the functions of lincRNAs in rainbow trout.     

Conserved function of lincRNAs in vertebrate embryonic development despite rapid sequence evolution

Thousands of long intervening noncoding RNAs (lincRNAs) have been identified in mammals. To better understand the evolution and functions of these enigmatic RNAs, we used chromatin marks, poly(A)-site mapping and RNA-Seq data to identify more than 550 distinct lincRNAs in zebrafish. Although these shared many characteristics with mammalian lincRNAs, only 29 had detectable sequence similarity with putative mammalian orthologs, typically restricted to a single short region of high conservation. Other lincRNAs had conserved genomic locations without detectable sequence conservation. Antisense reagents targeting conserved regions of two zebrafish lincRNAs caused developmental defects. Reagents targeting splice sites caused the same defects and were rescued by adding either the mature lincRNA or its human or mouse ortholog. Our study provides a roadmap for identification and analysis of lincRNAs in model organisms and shows that lincRNAs play crucial biological roles during embryonic development with functionality conserved despite limited sequence conservation.     

Translational genetic approaches to substance use disorders: bridging the gap between mice and humans

While substance abuse disorders only occur in humans, mice and other model organisms can make valuable contributions to genetic studies of these disorders. In this review, we consider a few specific examples of how model organisms have been used in conjunction with studies in humans to study the role of genetic factors in substance use disorders. In some examples genes that were first discovered in mice were subsequently studied in humans. In other examples genes or specific polymorphisms in genes were first studied in humans and then modeled in mice. Using anatomically and temporally specific genetic, pharmacological and other environmental manipulations in conjunction with histological analyses, mechanistic insights that would be difficult to obtain in humans have been obtained in mice. We hope these examples illustrate how novel biological insights about the effect of genes on substance use disorders can be obtained when mouse and human genetic studies are successfully integrated.     

Genome-wide screening for gene function using RNAi in mammalian cells

Mammalian genome sequencing has identified numerous genes requiring functional annotation. The discovery that dsRNA can direct gene-specific silencing in both model organisms and mammalian cells through RNA interference (RNAi) has provided a platform for dissecting the function of independent genes. The generation of large-scale RNAi libraries targeting all predicted genes within mouse, rat and human cells, combined with the large number of cell-based assays, provides a unique opportunity to perform high-throughput genetics in these complex cell systems. Many different formats exist for the generation of genome-wide RNAi libraries for use in mammalian cells. Furthermore, the use of these libraries in either genetic screens or genetic selections allows for the identification of known and novel genes involved in complex cellular phenotypes and biological processes, some of which underpin human disease. In this review, we examine genome-wide RNAi libraries used in model organisms and mammalian cells and provide examples of how these information rich reagents can be used for determining gene function, discovering novel therapeutic targets and dissecting signalling pathways, cellular processes and complex phenotypes.     

Tissue-Specific Functional Networks for Prioritizing Phenotype and Disease Genes

Integrated analyses of functional genomics data have enormous potential for identifying phenotype-associated genes. Tissue-specificity is an important aspect of many genetic diseases, reflecting the potentially different roles of proteins and pathways in diverse cell lineages. Accounting for tissue specificity in global integration of functional genomics data is challenging, as “functionality” and “functional relationships” are often not resolved for specific tissue types. We address this challenge by generating tissue-specific functional networks, which can effectively represent the diversity of protein function for more accurate identification of phenotype-associated genes in the laboratory mouse. Specifically, we created 107 tissue-specific functional relationship networks through integration of genomic data utilizing knowledge of tissue-specific gene expression patterns. Cross-network comparison revealed significantly changed genes enriched for functions related to specific tissue development. We then utilized these tissue-specific networks to predict genes associated with different phenotypes. Our results demonstrate that prediction performance is significantly improved through using the tissue-specific networks as compared to the global functional network. We used a testis-specific functional relationship network to predict genes associated with male fertility and spermatogenesis phenotypes, and experimentally confirmed one top prediction, Mbyl1. We then focused on a less-common genetic disease, ataxia, and identified candidates uniquely predicted by the cerebellum network, which are supported by both literature and experimental evidence. Our systems-level, tissue-specific scheme advances over traditional global integration and analyses and establishes a prototype to address the tissue-specific effects of genetic perturbations, diseases and drugs.