Biology subjects

Farh, K. K.-H.

Publications and source records attributed to Farh, K. K.-H..

5 recordsLinked to original sources

bioRxiv2026

A unified framework for quantitative splicing and transcript prediction

RNA splicing is frequently disrupted by genetic variation, contributing to a wide range of human diseases. Identifying the variants responsible for altered splicing is therefore crucial but has long been challenging. Deep learning models that predict splicing from genomic sequence have substantially advanced their detection, but accurately resolving their quantitative effects on splicing and the resulting transcripts remains an unmet need. Here we introduce SpliceAI2, a deep learning model trained end-to-end on splice site, splice junction, and transcript usage across multiple mammalian species. SpliceAI2 reconstructs complete transcripts directly from genomic sequence and considerably improves identification of splice-altering variants and quantification of their effects in diverse benchmarks spanning cryptic splicing, splicing quantitative trait loci, and massively parallel reporter assays. Human population datasets provide independent validation of these predicted functional effects through evidence of natural selection and associated changes in plasma protein abundance. Application to a rare disease cohort reveals that predicted splice-altering variants are highly enriched in disease-associated genes and account for 15% of the excess genetic burden, with approximately half residing in deep intronic regions likely missed by exome sequencing. Together, these findings establish SpliceAI2 as a major step forward in interpreting splice-altering variants across the human genome.

genomics↗

bioRxiv2025

Flexibly Modeling Rare Variant Pathogenicity Improves Gene Discovery for Complex Traits

Rare variant burden tests can directly identify genes that influence complex traits, but their power is limited by our ability to separate functional from benign alleles. We introduce FlexRV, an approach that greatly improves the power to detect gene-based associations in rare variant aggregation tests by modelling nonlinear relationships between functional annotations and phenotype. Across 62 quantitative and 44 disease traits in the UK Biobank, we show that FlexRV outperforms previous approaches such as DeepRVAT, STAAR, and Regenie, discovering 51% more quantitative and 102% more disease trait associations than the widely used Regenie method. Compared to discoveries from other methods, gene-phenotype associations identified by FlexRV replicated at a higher rate in the independent All of Us cohort and were more highly enriched at genes nominated by common variant genome-wide association studies. We explore the genetic architecture of complex traits using FlexRV burden tests, finding nearly equal contributions from missense and loss of function variants to rare variant burden heritability. FlexRV weights can also be incorporated into rare variant polygenic scores, improving their ability to identify individuals with extreme phenotypes. Our study illustrates the benefits of modelling nonlinear relationships between annotated variant effects and their downstream phenotypes in rare variant studies.

genetics↗

bioRxiv2025

The genomic landscape of spider monkeys and northern muriquis from a conservation perspective

BackgroundMost populations of spider monkeys (Ateles) and muriquis (Brachyteles), two Neotropical primate genera, are under severe anthropogenic threats. Yet, taxon-wide population-level studies leveraging their degree of endangerment linked to their genetic diversity patterns and demographic history are lacking. To properly address this, there is a need to expand from morphological and genetic marker-based studies. ResultsWe generated high-coverage genome sequencing for 58 individuals sampled across 8 Atelidae species, in the first population-wide study of all extant spider monkey species, in the wild and captivity, alongside northern muriquis (Brachyteles hypoxanthus). Additionally, we present a high-contiguity reference genome for Ateles hybridus. Here, we observe the overall levels of genetic diversity and genetic load of the analyzed populations do not align to their IUCN endangerment category. Moreover, we show that in the wild, genetic load is overall higher compared to the captive populations analyzed. Then, we depict two main trans and cis-Andean sister clades in Ateles, and further structure and dynamics outlined by the Madeira River in the latter clade. Lastly, we find that genes in highly divergent regions between Ateles and B. hypoxanthus are involved in central nervous system development and photorreception. ConclusionsOur study shows i) the lack of concordance between the genetic diversity levels and extinction risk of these populations, suggestive of recent and strong external drivers; ii) increased genetic load in the wild in contrast to effective captive management, indicating mostly past demographic events; iii) structure and dynamics in spider monkeys that agrees with common biogeographical patterns and iv) genetic divergence between Ateles and Brachyteles potentially linked to distinct environmental light levels.

genomics↗

bioRxiv2023

Whole genome approach to the structure and dynamics of Cacajao wild populations

Despite showing the greatest primate diversity on the planet, genomic studies on Amazonian primates show very little representation in the literature. With 48 geolocalized high coverage whole genomes from wild uakari monkeys, we present the first population-level study on platyrrhines using whole genome data. In a very restricted range of the Amazon rainforest, eight uakari species (Cacajao genus) have been described and categorized into bald and black uakaris, based on phenotypic and ecological differences. Despite a slight habitat overlap, we show that posterior to their split 0.92 Mya, bald and black uakaris have remained independent, without gene flow. Nowadays, these two groups present distinct genetic diversity and group-specific variation linked to pathogens. We propose differing hydrology patterns and effectiveness of geographic barriers have modulated the intra-group connectivity and structure of uakari populations. Beyond increasing their representation, with this work we explored the effects of the Amazon rainforests dynamism on platyrrhine species.

evolutionary biology↗

bioRxiv2021

Variation in predicted COVID-19 risk among lemurs and lorises

The novel coronavirus SARS-CoV-2, which in humans leads to the disease COVID-19, has caused global disruption and more than 1.5 million fatalities since it first emerged in late 2019. As we write, infection rates are currently at their highest point globally and are rising extremely rapidly in some areas due to more infectious variants. The primary viral target is the cellular receptor angiotensin-converting enzyme-2 (ACE2). Recent sequence analyses of the ACE2 gene predicts that many nonhuman primates are also likely to be highly susceptible to infection. However, the anticipated risk is not equal across the Order. Furthermore, some taxonomic groups show high ACE2 amino acid conservation, while others exhibit high variability at this locus. As an example of the latter, analyses of strepsirrhine primate ACE2 sequences to date indicate large variation among lemurs and lorises compared to other primate clades despite low sampling effort. Here, we report ACE2 gene and protein sequences for 71 individual strepsirrhines, spanning 51 species and 19 genera. Our study reinforces previous results and finds additional variability in other strepsirrhine species, and suggests several clades of lemurs have high potential susceptibility to SARS-CoV-2 infection. Troublingly, some species, including the rare and Endangered aye-aye (Daubentonia madagascariensis), as well as those in the genera Avahi and Propithecus, may be at high risk. Given that lemurs are endemic to Madagascar and among the primates at highest risk of extinction globally, further understanding of the potential threat of COVID-19 to their health should be a conservation priority. All feasible actions should be taken to limit their exposure to SARS-CoV-2.

genetics↗