Predicted Archaic 3D Genome Organization Reveals Genes Related to Head and Spinal Cord Separating Modern from Archaic Humans

Batyrev, Daniel; Lapid, Elisheva; Carmel, Liran; Meshorer, Eran

doi:10.3390/cells9010048

Cited by 10 publications

(7 citation statements)

References 22 publications

(29 reference statements)

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“…We have previously used patterns of cytosine degradation in ancient samples to reconstruct whole-genome archaic DNA methylation maps ( Gokhman et al, 2020 ; Gokhman et al, 2014 ; Gokhman et al, 2016 ). However, despite various approaches to extract regulatory information from ancient genomes ( Yan and McCoy, 2020 ; Colbran, 2019 ; Gokhman et al, 2016 ; Barker et al, 2020 ; Batyrev et al, 2019 ; Pedersen et al, 2014 ; Silvert et al, 2019 ; Moriano and Boeckx, 2020 ), our understanding of gene regulation in archaic humans remains minimal, with most archaic regulatory information being currently inaccessible ( Yan and McCoy, 2020 ). Additionally, whereas expression quantitative trait locus (eQTL) mapping can be used to identify variants that drive differential expression between individuals, it can only be applied to loci that are variable within the present-day human population.…”

Section: Introductionmentioning

confidence: 99%

The cis-regulatory effects of modern human-specific variants

Weiss

Harshman

Inoue

et al. 2021

eLife

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The Neanderthal and Denisovan genomes enabled the discovery of sequences that differ between modern and archaic humans, the majority of which are noncoding. However, our understanding of the regulatory consequences of these differences remains limited, in part due to the decay of regulatory marks in ancient samples. Here, we used a massively parallel reporter assay in embryonic stem cells, neural progenitor cells, and bone osteoblasts to investigate the regulatory effects of the 14,042 single-nucleotide modern human-specific variants. Overall, 1791 (13%) of sequences containing these variants showed active regulatory activity, and 407 (23%) of these drove differential expression between human groups. Differentially active sequences were associated with divergent transcription factor binding motifs, and with genes enriched for vocal tract and brain anatomy and function. This work provides insight into the regulatory function of variants that emerged along the modern human lineage and the recent evolution of human gene expression.

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Section: Introductionmentioning

confidence: 99%

The cis-regulatory effects of modern human-specific variants

Weiss

Harshman

Inoue

et al. 2021

eLife

View full text Add to dashboard Cite

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“…We have previously used patterns of cytosine degradation in ancient samples to reconstruct whole-genome archaic DNA methylation maps 12,20,21 . However, despite various approaches to extract regulatory information from ancient genomes 5,13,[21][22][23][24][25][26] , our understanding of gene regulation in archaic humans remains minimal, with most archaic regulatory information being currently inaccessible 5 . Additionally, whereas expression quantitative locus (eQTL) mapping can be used to identify variants that drive differential expression between individuals, it can only be applied to loci that are variable within the present-day human population.…”

Section: Introductionmentioning

confidence: 99%

Thecis-regulatory effects of modern human-specific variants

Weiss

Harshman

Inoue

et al. 2020

Preprint

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The Neanderthal and Denisovan genomes enabled the discovery of sequences that differ between modern and archaic humans, the majority of which are noncoding. However, our understanding of the regulatory consequences of these differences remains limited, in part due to the decay of regulatory marks in ancient samples. Here, we used a massively parallel reporter assay in embryonic stem cells, neural progenitor cells and bone osteoblasts to investigate the regulatory effects of the 14,042 single-nucleotide modern human-specific variants. Overall, 1,791 (13%) of sequences containing these variants showed active regulatory activity, and 407 (23%) of these drove differential expression between human groups. Differentially active sequences were associated with divergent transcription factor binding motifs, and with genes enriched for vocal tract and brain anatomy and function. This work provides insight into the regulatory function of variants that emerged along the modern human lineage and the recent evolution of human gene expression.

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“…The three-dimensional (3D) organization of the genome is increasingly recognized as a key mediator of gene expression by facilitating interactions between distal and proximal cis-regulatory elements (Bonev and Cavalli, 2016; Dekker et al, 2023; Ibrahim and Mundlos, 2020). Consequently, disruption of genome folding has been associated with human disease (Lupiáñez et al, 2015; Norton and Phillips-Cremins, 2017) and variation in genome folding underlies traits that differ between humans and other species (Batyrev et al, 2020; Keough et al, 2022; McArthur et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Sequence-based machine learning reveals 3D genome differences between bonobos and chimpanzees

Brand,

Kuang,

Gilbertson

et al. 2023

Preprint

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Phenotypic divergence between closely related species, including bonobos and chimpanzees (genus Pan), is largely driven by variation in gene regulation. The 3D structure of the genome mediates gene expression; however, genome folding differences in Pan are not well understood. Here, we apply machine learning to predict genome-wide 3D genome contact maps from DNA sequence for 56 bonobos and chimpanzees, encompassing all five extant lineages. We use a pairwise approach to estimate 3D divergence between individuals from the resulting contact maps in 4,420 1 Mb genomic windows. While most pairs were similar, ~17% were predicted to be substantially divergent in genome folding. The most dissimilar maps were largely driven by single individuals with rare variants that produce unique 3D genome folding in a region. We also identified 89 genomic windows where bonobo and chimpanzee contact maps substantially diverged, including several windows harboring genes associated with traits implicated in Pan phenotypic divergence. We used in silico mutagenesis to identify 51 3D-modifying variants in these bonobo-chimpanzee divergent windows, finding that 34 or 66.67% induce genome folding changes via CTCF binding motif disruption. Our results reveal 3D genome variation at the population-level and identify genomic regions where changes in 3D folding may contribute to phenotypic differences in our closest living relatives.

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Predicted Archaic 3D Genome Organization Reveals Genes Related to Head and Spinal Cord Separating Modern from Archaic Humans

Cited by 10 publications

References 22 publications

The cis-regulatory effects of modern human-specific variants

The cis-regulatory effects of modern human-specific variants

Thecis-regulatory effects of modern human-specific variants

Sequence-based machine learning reveals 3D genome differences between bonobos and chimpanzees

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