bioRxivGenomicsPreprint
Widespread transcription initiation within coding sequences marks tissue identity and accessible chromatin
Xutong WangiD, Jingbo DuaniD, Chancelor B. ClarkiD, Wanjie FengiD, Jianxin MaiD
Abstract
Alternative transcription initiation (ATI) appears to be a ubiquitous regulatory mechanism of gene expression in eukaryotes, but the extent to which it affects the products of gene expression, and how it evolves and is regulated remain unknown. We first identified transcription start sites (TSSs) in eight soybean tissues using recently developed STRIPE-seq and then analyzed ATI in the context of tissue identity and chromatin architecture. We defined 193,579 TSS clusters/regions (TSRs) in 37,911 annotated genes, with 56.5% located in putative regulatory regions upstream of start codons and 43.5% from start codons to 3 untranslated regions, which, together, are responsible for changes in open reading frames of 24,131 genes. Overall, duplicated genes possess more TSRs, exhibited lower degrees of tissue-specificity, and have undergone stronger purifying selection than singletons. Strikingly, 6,845 genes possess ATI within coding sequences (CDSs). These CDS-TSRs are highly tissue-specific, shorter than those located in canonical regulatory regions, and do not have TATA-boxes typical for the core promoters. Furthermore, the CDS-TSRs are embedded in nucleosome-free regions and flanked by nucleosomes with enhanced levels of active histone marks associated with transcriptionally active chromatin, suggesting that non-canonical ATI is epigenetically regulated and largely responsible for tissue-specific functions and tissue identity. Our study highlights the genomic and epigenomic factors shaping the distribution patterns and tissue-specificity of ATI in regulatory and coding sequences, as well as the significance of ATI in the alternation of proteins encoded by tissue-specifically expressed genes in the context of genome duplication and fractionation.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: variant calling
- approach: statistical model
- Citations
- 0
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