Post-transcriptional regulation is a complex mechanism that plays a central role in defining multiple cellular identities starting from a common genome - recently modifications in the 3'UTR lengths of transcripts have been found to have a role in this conundrum: a shorter 3'UTR could lead to miRNAs targeting escape, different cellular localizations and so on. A tendency toward expressing genes with shorter UTRs has been found in proliferating tissues and cancers; being able to identify the genes that change their lengths in biological and pathological conditions could lead to interesting insights about their nature. We propose a strategy to identify those genes using RNA sequencing data obtained from standard libraries, thus widely applicable on data that are obtained to perform classical differential expression analyses. Our approach detects already known shortened genes in various comparisons, such as in human testis compared to brain and in breast cancer compared to normal breast tissue. We have developed a Bioconductor package that allows to easily apply our suggested pipeline starting from alignment data and polyadenylation sites annotations.
Roar: detecting 3'UTR shortening with standard RNAseq data
GRASSI, ELENA;PROVERO, Paolo
2013-01-01
Abstract
Post-transcriptional regulation is a complex mechanism that plays a central role in defining multiple cellular identities starting from a common genome - recently modifications in the 3'UTR lengths of transcripts have been found to have a role in this conundrum: a shorter 3'UTR could lead to miRNAs targeting escape, different cellular localizations and so on. A tendency toward expressing genes with shorter UTRs has been found in proliferating tissues and cancers; being able to identify the genes that change their lengths in biological and pathological conditions could lead to interesting insights about their nature. We propose a strategy to identify those genes using RNA sequencing data obtained from standard libraries, thus widely applicable on data that are obtained to perform classical differential expression analyses. Our approach detects already known shortened genes in various comparisons, such as in human testis compared to brain and in breast cancer compared to normal breast tissue. We have developed a Bioconductor package that allows to easily apply our suggested pipeline starting from alignment data and polyadenylation sites annotations.
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