Integrated analysis sheds light on evolutionary trajectories of young transcription start sites in the human genome
Author(s) -
Cai Li,
Boris Lenhard,
Nicholas M. Luscombe
Publication year - 2018
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.231449.117
Subject(s) - biology , genome , evolutionary biology , gene , human genome , evolvability , computational biology , genetics
Understanding the molecular mechanisms and evolution of the gene regulatory system remains a major challenge in biology. Transcription start sites (TSSs) are especially interesting because they are central to initiating gene expression. Previous studies revealed widespread transcription initiation and fast turnover of TSSs in mammalian genomes. Yet, how new TSSs originate and how they evolve over time remain poorly understood. To address these questions, we analyzed ∼200,000 human TSSs by integrating evolutionary (inter- and intra-species) and functional genomic data, particularly focusing on evolutionarily young TSSs that emerged in the primate lineage. TSSs were grouped according to their evolutionary age using sequence alignment information as a proxy. Comparisons of young and old TSSs revealed that (1) new TSSs emerge through a combination of intrinsic factors, like the sequence properties of transposable elements and tandem repeats, and extrinsic factors such as their proximity to existing regulatory modules; (2) new TSSs undergo rapid evolution that reduces the inherent instability of repeat sequences associated with a high propensity of TSS emergence; and (3) once established, the transcriptional competence of surviving TSSs is gradually enhanced, with evolutionary changes subject to temporal (fewer regulatory changes in younger TSSs) and spatial constraints (fewer regulatory changes in more isolated TSSs). These findings advance our understanding of how regulatory innovations arise in the genome throughout evolution and highlight the genomic robustness and evolvability in these processes.
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