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The 3D structure of the genome is an important mediator of gene expression. As phenotypic divergence is largely driven by gene regulatory variation, comparing genome 3D contacts across species can further understanding of the molecular basis of species differences. However, while experimental data on genome 3D contacts in humans are increasingly abundant, only a handful of 3D genome contact maps exist for other species. Here, we demonstrate that human experimental data can be used to close this data gap. We apply a machine learning model that predicts 3D genome contacts from DNA sequence to the genomes from 56 bonobos and chimpanzees and identify species-specific patterns of genome folding. We estimated 3D divergence between individuals from the resulting contact maps in 4,420 1 Mb genomic windows, of which ∼17% were substantially divergent in predicted genome contacts. Bonobos and chimpanzees diverged at 89 windows, overlapping genes associated with multiple traits implicated in Pan phenotypic divergence. We discovered 51 bonobo-specific variants that individually produce the observed bonobo contact pattern in bonobo-chimpanzee divergent windows. Our results demonstrate that machine learning methods can leverage human data to fill in data gaps across species, offering the first look at population-level 3D genome variation in nonhuman primates. We also identify loci where changes in 3D folding may contribute to phenotypic differences in our closest living relatives.

The fastest-evolving regions in the human and chimpanzee genomes show a remarkable excess of weak (A,T) to strong (G,C) nucleotide substitutions since divergence from their common ancestor. We investigated the phylogenetic extent and possible causes of this weak to strong (W → S) bias in divergent sequences (BDS) using recently sequenced genomes and recombination maps from eight trios of eukaryotic species. To quantify evidence for BDS, we inferred substitution histories using an efficient maximum likelihood approach with a context-dependent evolutionary model. We then annotated all lineage-specific substitutions in terms of W → S bias and density on the chromosomes. Finally, we used the inferred substitutions to calculate a BDS score-a log odds ratio between substitution type and density-and assessed its statistical significance with Fisher's exact test. Applying this approach, we found significant BDS in the coding and noncoding sequence of human, mouse, dog, stickleback, fruit fly, and worm. We also observed a significant lack of W → S BDS in chicken and yeast. The BDS score varies between species and across the chromosomes within each species. It is most strongly correlated with different genomic features in different species, but a strong correlation with recombination rates is found in several species. Our results demonstrate that a W → S substitution bias in fast-evolving sequences is a widespread phenomenon. The patterns of BDS observed suggest that a recombination-associated process, such as GC-biased gene conversion, is involved in the production of the bias in many species, but the strength of the BDS likely depends on many factors, including genome stability, variability in recombination rate over time and across the genome, the frequency of meiosis, and the amount of outcrossing in each species.

Fast evolving regions of many metazoan genomes show a bias toward substitutions that change weak (A,T) into strong (G,C) base pairs. Single-nucleotide polymorphisms (SNPs) do not share this pattern, suggesting that it results from biased fixation rather than biased mutation. Supporting this hypothesis, analyses of polymorphism in specific regions of the human genome have identified a positive correlation between weak to strong (W→S) SNPs and derived allele frequency (DAF), suggesting that SNPs become increasingly GC biased over time, especially in regions of high recombination. Using polymorphism data generated by the 1000 Genomes Project from 179 individuals from 4 human populations, we evaluated the extent and distribution of ongoing GC-biased evolution in the human genome. We quantified GC fixation bias by comparing the DAFs of W→S mutations and S→W mutations using a Mann-Whitney U test. Genome-wide, W→S SNPs have significantly higher DAFs than S→W SNPs. This pattern is widespread across the human genome but varies in magnitude along the chromosomes. We found extreme GC-biased evolution in neighborhoods of recombination hot spots, a significant correlation between GC bias and recombination rate, and an inverse correlation between GC bias and chromosome arm length. These findings demonstrate the presence of ongoing fixation bias favoring G and C alleles throughout the human genome and suggest that the bias is caused by a recombination-associated process, such as GC-biased gene conversion.