Alternative Isoform Regulation in Human Tissue Transcriptomes

By Eric T. Wang, Rickard Sandberg, Shujun J Luo, I. Khrebtukova, Lu Zhang, Christine Mayr, Stephen Kingsmore, Gary P. Schroth, C. Burge. Nature, 2008

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Through alternative processing of pre-messenger RNAs, individual mammalian genes often produce multiple mRNA and protein isoforms that may have related, distinct or even opposing functions. Here we report an in-depth analysis of 15 diverse human tissue and cell line transcriptomes on the basis of deep sequencing of complementary DNA fragments, yielding a digital inventory of gene and mRNA isoform expression. Analyses in which sequence reads are mapped to exon–exon junctions indicated that 92–94% of human genes undergo alternative splicing, ∼86% with a minor isoform frequency of 15% or more. Differences in isoform-specific read densities indicated that most alternative splicing and alternative cleavage and polyadenylation events vary between tissues, whereas variation between individuals was approximately twofold to threefold less common. Extreme or ‘switch-like’ regulation of splicing between tissues was associated with increased sequence conservation in regulatory regions and with generation of full-length open reading frames. Patterns of alternative splicing and alternative cleavage and polyadenylation were strongly correlated across tissues, suggesting coordinated regulation of these processes, and sequence conservation of a subset of known regulatory motifs in both alternative introns and 3′ untranslated regions suggested common involvement of specific factors in tissue-level regulation of both splicing and polyadenylation.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2615097c06a257afc7b488147995feea06e242f3

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Citations in the corpus

A scaling normalization method for differential expression analysis of RNA-seq data (2010, positive): “It has also been demonstrated that splicing variants [ 1 ,2] and single nucleotide polymorphisms [3] can be detected through sequencing the transcriptome, opening up the opportunity to interrogate allele-specific expression and RNA editing.”
Predicting Splicing from Primary Sequence with Deep Learning. (2019, background): “Tissue-Specific Alternative Splicing Frequently Arises from Weak Cryptic Splice Variants Alternative splicing is a major mode of gene regulation that serves to increase the diversity of transcripts in different tissues and developmental stages, and its dysregulation is associated with disease proces”
Widespread intron retention in mammals functionally tunes transcriptomes (2014, background): “These results reveal that the frequency of IR compares with the frequency of cassette exon AS (Pan et al. 2008) and is far more prevalent inmammalian cells and tissues than previously detected using lower coverage RNA-seq data (Wang et al. 2008).”
Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes (2012, background): “19,714 distinct transcript isoforms (Wang et al., 2008) corresponding to 12,659 genes (Figure S1C) were tracked for the entire time course, and their dynamic expression response was classified into either autocorrelated (I) and spike sets, further subdivided as displaying maxima (II) or minima (III)”
Improving RNA-Seq expression estimates by correcting for fragment bias (2011, background): “In the first experiment [20], which we will refer to by its accession SRA008403, the sample was sequenced from one library preparation.”
A highly conserved program of neuronal microexons is misregulated in autistic brains (2014, background): “For example, transcripts from over 95% of human multiexon genes undergo AS, and most of the resulting mRNA splice variants are variably expressed between different cell and tissue types (Pan et al., 2008; Wang et al., 2008).”
Integrative omics for health and disease (2018, background): “However, for clinical applications, it is ideal to study tissues that are relevant for a particular disease as gene expression varies considerably across tissues 96,97 (FIG.”