MicroRNAs: Genomics, Biogenesis, Mechanism, and Function

MicroRNAs are a family of small, non-coding RNAs that regulate gene expression in a sequence-specific manner. The two founding members of the microRNA family were originally identified in Caenorhabditis elegans as genes that were required for the timed regulation of developmental events. Since then, hundreds of microRNAs have been identified in almost all metazoan genomes, including worms, flies, plants and mammals. MicroRNAs have diverse expression patterns and might regulate various developmental and physiological processes. Their discovery adds a new dimension to our understanding of complex gene regulatory networks.

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MicroRNAs: small RNAs with a big role in gene regulation

I MicroRNAs (miRNAs) are an abundant class of small non-protein-coding RNAs that function as negative gene regulators. They regulate diverse biological processes, and bioinformatic data indicates that each miRNA can control hundreds of gene targets, underscoring the potential influence of miRNAs on almost every genetic pathway. Recent evidence has shown that miRNA mutations or mis-expression correlate with various human cancers and indicates that miRNAs can function as tumour suppressors and oncogenes. miRNAs have been shown to repress the expression of important cancer-related genes and might prove useful in the diagnosis and treatment of cancer.

Oncomirs : microRNAs with a role in cancer

MicroRNAs (miRNAs) are an abundant class of small non-protein-coding RNAs that function as negative gene regulators They regulate diverse biological processes, and bioinformatic data indicates that each miRNA can control hundreds of gene targets, underscoring the potential influence of miRNAs on almost every genetic pathway Recent evidence has shown that miRNA mutations or mis-expression correlate with various human cancers and indicates that miRNAs can function as tumour suppressors and oncogenes miRNAs have been shown to repress the expression of important cancer-related genes and might prove useful in the diagnosis and treatment of cancer

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Oncomirs — microRNAs with a role in cancer

MicroRNAs (miRNAs) interact with target mRNAs at specific sites to induce cleavage of the message or inhibit translation. The specific function of most mammalian miRNAs is unknown. We have predicted target sites on the 3′ untranslated regions of human gene transcripts for all currently known 218 mammalian miRNAs to facilitate focused experiments. We report about 2,000 human genes with miRNA target sites conserved in mammals and about 250 human genes conserved as targets between mammals and fish. The prediction algorithm optimizes sequence complementarity using position-specific rules and relies on strict requirements of interspecies conservation. Experimental support for the validity of the method comes from known targets and from strong enrichment of predicted targets in mRNAs associated with the fragile X mental retardation protein in mammals. This is consistent with the hypothesis that miRNAs act as sequence-specific adaptors in the interaction of ribonuclear particles with translationally regulated messages. Overrepresented groups of targets include mRNAs coding for transcription factors, components of the miRNA machinery, and other proteins involved in translational regulation, as well as components of the ubiquitin machinery, representing novel feedback loops in gene regulation. Detailed information about target genes, target processes, and open-source software for target prediction (miRanda) is available at http://www.microrna.org. Our analysis suggests that miRNA genes, which are about 1% of all human genes, regulate protein production for 10% or more of all human genes.

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Human MicroRNA Targets

https://pure.mpg.de/pubman/item/item_641885_3/component/file_641884/124826.pdf

The small RNA profile during Drosophila melanogaster development

Analyzing proteins in the context of all available genome and transcript sequence data has the potential to reveal functional properties not accessible through protein sequence analysis alone. To analyze the impact of alternative splicing on transcription factor (TF) protein structure, we constructed a comprehensive database of splice variants in the mouse transcriptome, called MouSDB3 containing 461 TF loci. Our analysis revealed that 62% of these loci in MouSDB3 have variant exons, compared to 29% of all loci. These variant TF loci contain a total of 324 alternative exons, of which 23% are in-frame. When excluded, 80% of in-frame alternative exons alter the domain architecture of the protein as computed by SMART (simple modular architecture research tool). Sixty-eight % of these exons directly affect the coding regions of domains important for TF function. Seventy-five % of the domains affected are DNA-binding domains. Tissue distribution analyses of variant mouse TFs reveal that they have more alternatively spliced forms in 14 of the 18 tissues analyzed when compared to all the loci in MouSDB3. Further, TF isoforms are homogenous within a given single tissue and are heterogeneous across different tissues, indicating their tissue specificity. Our study provides quantitative evidence that alternative splicing preferentially adds or deletes domains important to the DNA-binding function of the TFs. Analyses described here reveal the presence of tissue-specific alternative splicing throughout the mouse transcriptome. Our findings provide significant biological insights into control of transcription and regulation of tissue-specific gene expression by alternative splicing via creation of tissue-specific TF isoforms.

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Alternative splicing of mouse transcription factors affects their DNA-binding domain architecture and is tissue specific

Comparative analyses of alternative splicing across species can provide significant biological insight not only to evolution of alternative splicing, but also to its regulation and functional significance. For comprehensive analyses of human and mouse alternatively spliced genes, we developed two databases of the human and the mouse transcriptomes, HumanSDB3 and MouSDB5 respectively. We showed that alternative splicing events in both of the transcriptomes are mainly due to the presence or absence of internal cassette exons. Our databases allow in-depth analyses of alternative and constitutive exons within alternatively spliced genes. Interactive web implementation of our databases brings to end-user the ability to instantly identify orthologous human-mouse gene pairs with their corresponding exons. This is a novel visualization method which provides easy access to conserved alternative splicing data and a tool to explore the evolution of this important biological process.

Databases for comparative analysis of human-mouse orthologous alternative splicing

Here, we present an analysis of alternatively spliced transcript distribution within human and mouse transcriptomes. In this analysis two alternative splicing databases of human and mouse are used to screen all the transcript isoforms contained for a total of 16,826 human genes and a total of 14,869 mouse genes. Overall both transcriptomes are screened for a total of 13 different tissues. All genes analyzed from both genomes have been shown to exhibit alternative splicing and transcript isoforms are specified based on their alternative exon—intron architectures. Our transcriptome wide screenings indicate that there generally exists only one specific isoform per given tissue, both in human and in mouse transcriptomes. Based on the available data, in all 13 tissues analyzed, we observe that for majority of the genes (80%) there is a single dominant isoform per gene, independent of transcript sequence sampling depths. A total of 69% of alternatively spliced human genes and a total of 73% of alternatively spliced mouse genes, have one single isoform within each single tissue from which they have transcript sequence data.

Distribution of Alternatively Spliced Transcript Isoforms within Human and Mouse Transcriptomes

Alternative splicing is a widespread cellular phenomenon, which regulates gene expression in eukaryotic genomes. Availability of accumulating transcript and genomic sequence data has lead to generation of a wide-range of alternative splicing databases. Generally the available databases focus on mammalian transcriptomes. Here, we present two new alternative splicing databases for the model organisms, Drosophila melanogaster and Caenorhabditis elengans. Databases presented here allow the end-users to perform in-depth analysis of the alternative splicing events for their gene of interest. Utility of our databases are illustrated by presenting the extensively alternatively spliced DSCAM gene from Drosophila melanogaster and alternative splicing of the splicing regulatory factors U2AF, rsp-7 and swp-1 of Caenorhabditis elengans. In addition, using these two new splicing databases, we show that the majority of alternative splicing in both genomes is due to cassette exons.

Ben Snyder

Papers

The small RNA profile during Drosophila melanogaster development

Alternative splicing of mouse transcription factors affects their DNA-binding domain architecture and is tissue specific

Databases for comparative analysis of human-mouse orthologous alternative splicing

Distribution of Alternatively Spliced Transcript Isoforms within Human and Mouse Transcriptomes

Alternative Splicing in the Fly and the Worm: Splicing Databases for Drosophila melanogaster and Caenorhabditis elegans