Biology subjects

Gokhman, D.

Publications and source records attributed to Gokhman, D..

9 recordsLinked to original sources

bioRxiv2026

Immune context unmasks regulatory effects of Neanderthal and Denisovan introgression

Neanderthal and Denisovan introgression have left a pervasive footprint in the human genome, yet its regulatory consequences remain poorly understood. Here we use a massively parallel reporter assay to characterize the cis-regulatory activity of 4,161 high-frequency introgressed variants across respiratory (A549), hepatic (HepG2), and hematopoietic (K562) cells exposed to immune and infectious stimuli. We find that ~18% of variants show differential activity between archaic and modern alleles, including 94 whose effects are revealed or modulated by stimulation, often in a cell type-specific manner. We identify loci, including STAT2, IL23A, and RNF41, where clusters of introgressed alleles exert coordinated regulatory effects consistent with adaptive programs. Finally, we dissect the mechanisms underlying the association between Neanderthal introgression and COVID-19 severity and show that the risk allele rs17713054-A, which displays the strongest effect in our assay, increases activity of a TNF--responsive enhancer in lung epithelial cells, directly upregulating SLC6A20.Together, these findings reveal widespread context-dependent regulatory effects of archaic introgression, with broad evolutionary and biomedical implications.

evolutionary biology↗

bioRxiv2026

An information content principle explains regulatory patterns of gene expression across human tissues

Gene expression patterns range from broadly expressed housekeeping genes to highly tissue-specific ones. Notably, many genes exhibit intermediate specificity, characterized by elevated expression in some tissues while low or absent in others. Understanding how regulatory demands scale with tissue specificity offers a valuable opportunity to uncover fundamental principles of genome regulation. By analyzing cis-regulatory element (CRE) counts across human genes with varying tissue specificity, we observed a nonlinear pattern: genes with intermediate specificity harbor the highest CRE count, suggesting distinct regulatory strategies across the expression spectrum. Motivated by this observation, we used the Minimum Description Length (MDL) principle from information theory, together with a maximum parsimony approach from phylogenetics, to quantify regulatory demands across tissues. Our analysis revealed that MDL-based regulatory demand scales consistently with diverse regulatory features, including CRE count, transcription-factor and microRNA targeting, and gene structure. To test whether this scaling changes across the expression spectrum, we partitioned genes by expression breadth. Two patterns emerged: features scaling with MDL in selectively expressed genes tend to act as on/off switches, whereas those in ubiquitous genes serve as fine-tuning knobs. Evolutionary analysis revealed that these regulatory patterns vary with gene age, with alignment between MDL and CRE counts peaking in intermediate-aged genes. Collectively, these results establish MDL combined with maximum parsimony as a powerful framework linking regulatory architecture, expression specificity, and evolutionary age, offering novel insights into the organizational principles underlying genome regulation.

genomics↗

bioRxiv2026

The causes and consequences of human-specific DNA methylation

The vast collection of human-specific traits- such as our unique morphology, cognition, behavior, and diseases- has long been attributed to gene expression divergence between us and our closest living relatives, chimpanzees. Theory suggests that changes to cis-regulatory elements such as promoters and enhancers may drive evolutionary adaptation, and DNA methylation is a key factor in transcriptional cis-regulation. However, we still lack an understanding of 1) how species-specific methylation patterns arise; 2) their downstream effects; and 3) whether they are a common target of natural selection. In this study, we investigated these three questions. By combining a novel hypothesis testing framework with DNA methylation data from six human and chimpanzee cell types, as well as fused interspecies hybrid cells, we disentangled cis- vs. trans-acting methylation divergence across the genome. Across cell types, we found that methylation divergence is primarily driven in cis, which can be linked in some cases to nearby sequence variants such as CpG gains and losses. Although less common, regions with trans-acting methylation divergence were enriched for specific transcription factor (TF) binding motifs, suggesting a role of TFs such as FOXM1 in these differences. Having established these causes of methylation divergence, we then examined the functional consequences of differential methylation. Although methylation lacks a consistent relationship with transcription, we observed that associations between methylation and gene expression are stronger for genes with cis-regulatory divergence. Moreover, we identified lineage-specific selection shaping promoter methylation at the level of entire pathways including those associated with human-specific traits such as speech, cognition, and susceptibility to infection with hepatitis C. Collectively, our findings provide a mechanistic framework suggesting that DNA methylation may occupy a key position, mediating the effects of both cis- and trans-acting factors on transcriptional networks, including those contributing to human-specific traits.

evolutionary biology↗

bioRxiv2024

Candidate Denisovan fossils identified through gene regulatory phenotyping

Denisovans are an extinct group of humans whose morphology is mostly unknown. The scarcity of verified Denisovan fossils makes it challenging to study their anatomy, and how well they were adapted to their environment. We previously developed a genetic phenotyping approach to gain insight into Denisovan anatomy by detecting gene regulatory changes that likely altered Denisovan skeletal morphology. Here, we scan Middle Pleistocene crania for unclassified or disputed specimens that match predicted Denisovan morphology and thus might be related to Denisovans. We found that Harbin, Dali, and Kabwe 1 show a particularly good alignment with the Denisovan profile, with most of their phenotypes matching predicted Denisovan anatomy. We conclude that our genetic phenotyping approach could help classify unidentified specimens, and that Harbin, Dali, and Kabwe 1 exhibit a Denisovan-like morphology and could be closely linked to the Denisovan lineage.

genetics↗

bioRxiv2024

Predicting the direction of phenotypic difference

Predicting phenotypes from genomic data is a key goal in genetics, but for most complex phenotypes, predictions are hampered by incomplete genotype-to-phenotype mapping. Here, we describe a more attainable approach than quantitative predictions, which is aimed at qualitatively predicting phenotypic differences. Despite incomplete genotype-to-phenotype mapping, we show that it is relatively easy to determine which of two individuals has a greater phenotypic value. This question is central in many scenarios, e.g., comparing disease risk between individuals, the yield of crop strains, or the anatomy of extinct vs extant species. To evaluate prediction accuracy, i.e., the probability that the individual with the greater predicted phenotype indeed has a greater phenotypic value, we developed an estimator of the ratio between known and unknown effects on the phenotype. We evaluated prediction accuracy using human data from tens of thousands of individuals from either the same family or the same population, as well as data from different species. We found that, in many cases, even when only a small fraction of the loci affecting a phenotype is known, the individual with the greater phenotypic value can be identified with over 90% accuracy. Our approach also circumvents some of the limitations in transferring genetic association results across populations. Overall, we introduce an approach that enables accurate predictions of key information on phenotypes -- the direction of phenotypic difference -- and suggest that more phenotypic information can be extracted from genomic data than previously appreciated.

genetics↗

bioRxiv2022

Accounting for cis-regulatory constraint prioritizes genes likely to affect species-specific traits

Measuring allele-specific expression in interspecies hybrids is a powerful way to detect cis-regulatory changes underlying adaptation. However, it remains difficult to identify genes most likely to explain species-specific traits. Here, we outline a simple strategy that leverages population-scale allele-specific RNA-seq data to identify genes that have constrained cis- regulation within species yet show divergence between species. Applying this strategy to data from human-chimpanzee hybrid cortical spheroids, we identify signatures of lineage-specific selection on genes related to cellular proliferation, speech, and glucose metabolism. We also highlight cis-regulatory divergence in CUX1 and EDNRB that may shape the unique trajectory of human brain development.

evolutionary biology↗

bioRxiv2020

The cis-regulatory effects of modern human-specific variants

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.

evolutionary biology↗

bioRxiv2017

Gene ORGANizer: Linking Genes to the Organs They Affect

One of the biggest challenges in studying how genes work is understanding their effect on the physiology and anatomy of the body. Existing tools try to address this using indirect features, such as expression levels and biochemical pathways. Here, we present Gene ORGANizer (geneorganizer.huji.ac.il), a phenotype-based tool that directly links human genes to the body parts they affect. It is built upon an exhaustive curated database that links more than 7,000 genes to [~]150 anatomical parts using >150,000 gene-organ associations. The tool offers user-friendly platforms to analyze the anatomical effects of individual genes, and identify trends within groups of genes. We demonstrate how Gene ORGANizer can be used to make new discoveries, showing that chromosome X is enriched with genes affecting facial features, that positive selection targets genes with more constrained phenotypic effects, and more. We expect Gene ORGANizer to be useful in a variety of evolutionary, medical and molecular studies aimed at understanding the phenotypic effects of genes.

bioinformatics↗

bioRxiv2017

Recent Regulatory Changes Shaped the Human Facial and Vocal Anatomy

SummaryRegulatory changes are broadly accepted as key drivers of phenotypic divergence. However, identifying regulatory changes that underlie human-specific traits has proven very challenging. Here, we use 63 DNA methylation maps of ancient and present-day humans, as well as of six chimpanzees, to detect differentially methylated regions that emerged in modern humans after the split from Neanderthals and Denisovans. We show that genes affecting the face and vocal tract went through particularly extensive methylation changes. Specifically, we identify widespread hypermethylation in a network of face- and voice-affecting genes (SOX9, ACAN, COL2A1, NFIX and XYLT1). We propose that these repression patterns appeared after the split from Neanderthals and Denisovans, and that they might have played a key role in shaping the modern human face and vocal tract.View Full Text

evolutionary biology↗