Genomic approaches to trace the history of human brain evolution with an emerging opportunity for transposon profiling of ancient humans

Author:

Wang Yilan,Zhao Boxun,Choi Jaejoon,Lee Eunjung AliceORCID

Abstract

AbstractTransposable elements (TEs) significantly contribute to shaping the diversity of the human genome, and lines of evidence suggest TEs as one of driving forces of human brain evolution. Existing computational approaches, including cross-species comparative genomics and population genetic modeling, can be adapted for the study of the role of TEs in evolution. In particular, diverse ancient and archaic human genome sequences are increasingly available, allowing reconstruction of past human migration events and holding the promise of identifying and tracking TEs among other evolutionarily important genetic variants at an unprecedented spatiotemporal resolution. However, highly degraded short DNA templates and other unique challenges presented by ancient human DNA call for major changes in current experimental and computational procedures to enable the identification of evolutionarily important TEs. Ancient human genomes are valuable resources for investigating TEs in the evolutionary context, and efforts to explore ancient human genomes will potentially provide a novel perspective on the genetic mechanism of human brain evolution and inspire a variety of technological and methodological advances. In this review, we summarize computational and experimental approaches that can be adapted to identify and validate evolutionarily important TEs, especially for human brain evolution. We also highlight strategies that leverage ancient genomic data and discuss unique challenges in ancient transposon genomics.

Funder

National Institute on Aging

NIH Office of the Director

the Suh Kyungbae Foundation

the Paul G. Allen Frontiers Group

Charles H. Hood Foundation

Manton Center for Orphan Disease Research, Boston Children's Hospital

Publisher

Springer Science and Business Media LLC

Subject

Molecular Biology

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