Biology subjects

Sohail, M.

Publications and source records attributed to Sohail, M..

8 recordsLinked to original sources

bioRxiv2026

Sequence-Independent In Situ Imaging of GlycoRNA in Living Cells and Tissues based on COMPASS

Current methods for the imaging of glycosylated RNAs (glycoRNAs) focus on limited types with identified RNA sequences, making the distribution of global glycoRNAs at single-cell and tissue levels largely unexplored. To address this gap, we developed a co-metabolic proximity labeling assay (COMPASS) for sequence-independent imaging of glycoRNAs. COMPASS employs metabolic chemical reporters (MCRs) to label glycans and RNAs, followed by click-chemistry-based dye conjugation to generate Forster resonance energy transfer (FRET) signals. The MCR-enabled RNA labeling allows for sequence-independent imaging, and FRET ensures accurate localization of glycoRNA distributions. COMPASS facilitates glycoRNA imaging across multiple cell lines, cerebral organoids, and mouse tissues. We observed the downregulation of glycoRNAs in metastatic lung nodules and upregulation in original regions of brain development in cerebral organoids, suggesting their potential association with carcinogenesis and neurogenesis. COMPASS illuminates previously invisible glycoRNAs and offers a comprehensive profile of glycoRNA distribution for studying their functions.

bioengineering↗

bioRxiv2024

The multi-scale complexity of human genetic variation beyond continental groups

Traditional clustering and visualization approaches in human genetics often operate under frameworks that assume inherent, discrete groupings1,2. These methods can inadvertently simplify multifaceted relationships, functioning to entrench the idea of typological groups3. We introduce a network-based pipeline and visualization tool grounded in relational thinking4, which constructs networks from a variety of genetic similarity metrics. We identify communities at multiple resolutions, departing from typological models of analysis and interpretation that categorize individuals into a (predefined) number of sets. We applied our pipeline to a dataset merged from the 1000 Genomes and Human Genome Diversity Project5, revealing the limitations of traditional groupings and capturing the complexities introduced by demographic events and evolutionary processes. This method embraces the context-specificity of genetic similarities that are salient depending on the question, markers of interest, and study individuals. Different numbers of communities are revealed depending on the resolution chosen and metric used, underscoring a fluid spectrum of genetic relationships and challenging the notion of universal categorization. We provide a web application (https://sohail-lab.shinyapps.io/GG-NC/) for interactive visualization and engagement with these intricate genetic landscapes.

genomics↗

bioRxiv2024

Natural selection acting on complex traits hampers the predictive accuracy of polygenic scores in ancient samples

The prediction of phenotypes from ancient humans has gained interest due to its potential to investigate the evolution of complex traits. These predictions are commonly performed using polygenic scores computed with DNA information from ancient humans along with genome-wide association studies (GWAS) data from present-day humans. However, numerous evolutionary processes could impact the prediction of phenotypes from ancient humans based on polygenic scores. In this work we investigate how natural selection impacts phenotypic predictions on ancient individuals using polygenic scores. We use simulations of an additive trait to analyze how natural selection impacts phenotypic predictions with polygenic scores. We simulate a trait evolving under neutrality, stabilizing selection and directional selection. We find that stabilizing and directional selection have contrasting effects on ancient phenotypic predictions. Stabilizing selection accelerates the loss of large-effect alleles contributing to trait variation. Conversely, directional selection accelerates the loss of small and large-effect alleles that drive individuals farther away from the optimal phenotypic value. These effects result in specific shared genetic variation patterns between ancient and modern populations which hamper the accuracy of polygenic scores to predict phenotypes. Furthermore, we conducted simulations that include realistic strengths of stabilizing selection and heritability estimates to show how natural selection could impact the predictive accuracy of ancient polygenic scores for two widely studied traits: height and body mass index. We emphasize the importance of considering how natural selection can decrease the reliability of ancient polygenic scores to perform phenotypic predictions on an ancient population.

evolutionary biology↗

bioRxiv2023

The genetic architecture of the human skeletal form

The human skeletal form underlies our ability to walk on two legs, but unlike standing height, the genetic basis of limb lengths and skeletal proportions is less well understood. Here we applied a deep learning model to 31,221 whole body dual-energy X-ray absorptiometry (DXA) images from the UK Biobank (UKB) to extract 23 different image-derived phenotypes (IDPs) that include all long bone lengths as well as hip and shoulder width, which we analyzed while controlling for height. All skeletal proportions are highly heritable ([~]40-50%), and genome-wide association studies (GWAS) of these traits identified 179 independent loci, of which 102 loci were not associated with height. These loci are enriched in genes regulating skeletal development as well as associated with rare human skeletal diseases and abnormal mouse skeletal phenotypes. Genetic correlation and genomic structural equation modeling indicated that limb proportions exhibited strong genetic sharing but were genetically independent of width and torso proportions. Phenotypic and polygenic risk score analyses identified specific associations between osteoarthritis (OA) of the hip and knee, the leading causes of adult disability in the United States, and skeletal proportions of the corresponding regions. We also found genomic evidence of evolutionary change in arm-to-leg and hip-width proportions in humans consistent with striking anatomical changes in these skeletal proportions in the hominin fossil record. In contrast to cardiovascular, auto-immune, metabolic, and other categories of traits, loci associated with these skeletal proportions are significantly enriched in human accelerated regions (HARs), and regulatory elements of genes differentially expressed through development between humans and the great apes. Taken together, our work validates the use of deep learning models on DXA images to identify novel and specific genetic variants affecting the human skeletal form and ties a major evolutionary facet of human anatomical change to pathogenesis.

genomics↗

bioRxiv2022

Nationwide genomic biobank in Mexico unravels demographic history and complex trait architecture from 6,057 individuals

Latin America continues to be severely underrepresented in genomics research, and fine-scale genetic histories as well as complex trait architectures remain hidden due to the lack of Big Data. To fill this gap, the Mexican Biobank project genotyped 1.8 million markers in 6,057 individuals from 32 states and 898 sampling localities across Mexico with linked complex trait and disease information creating a valuable nationwide genotype-phenotype database. Through a suite of state-of-the-art methods for ancestry deconvolution and inference of identity-by-descent (IBD) segments, we inferred detailed ancestral histories for the last 200 generations in different Mesoamerican regions, unraveling native and colonial/post-colonial demographic dynamics. We observed large variations in runs of homozygosity (ROH) among genomic regions with different ancestral origins reflecting their demographic histories, which also affect the distribution of rare deleterious variants across Mexico. We analyzed a range of biomedical complex traits and identified significant genetic and environmental factors explaining their variation, such as ROH found to be significant predictors for trait variation in BMI and triglycerides.

genomics↗

bioRxiv2022

Investigating relative contributions to psychiatric disease architecture fromsequence elements originating across multiple evolutionary time-scales

Humans exhibit distinct characteristics compared to our primate and ancient hominin ancestors including bipedal locomotion and enhanced neurocognitive ability, but the timing of accelerated changes in these traits is uncertain. To investigate if specific trait-associated variation show enrichment during particular periods of human evolution, we combine genome wide association study (GWAS) data from 70 traits, spanning multiple categories including AI-based image-derived morphological phenotypes of the brain, heart, and skeletal tissues with data from 12 different evolutionary regions obtained from comparative functional genomics, multi-species alignments from long read sequencing, and ancient DNA reflecting 4 different major evolutionary divergence points. These regions cover epigenetic differences in the brain between humans and rhesus macaques, various human accelerated regions (HARs) including regions from the Zoonomia Project, ancient selective sweeps, and Neanderthal introgressed alleles. Using two complementary approaches to examine enrichment between GWAS loci and genomic regions, we show that more phenotypes are enriched in earlier periods of divergence of humans with macaques and chimps, and less so during the divergence with Neanderthals. These traits span respiratory, dermatological, reproductive, metabolic, and psychiatric domains along with skeletal and brain imaging traits, consistent with striking morphological changes between humans and other primates. Among brain imaging traits, we observe an enrichment of SNPs associated with the longitudinal fasciculus in human-gained epigenetic elements since macaques, the visual cortex in HARs, and the thalamus proper in Neanderthal introgressed alleles, implying associated functions such as language processing, decision making, relay of sensory signals, and motor control are enriched at different evolutionary depths.

evolutionary biology↗

bioRxiv2019

Fine-scale haplotype structure reveals strong signatures of positive selection in a recombining bacterial pathogen

Identifying the forces that create and shape ecologically meaningful variation in bacteria remains an important challenge. For recombining bacteria, the sign and strength of linkage provide a unique lens into ongoing selection. We show derived alleles less than 300bp apart in Neisseria gonorrhoeae exhibit more coupling linkage than repulsion linkage, a pattern that cannot be explained by limited recombination or neutrality as these couplings are significantly stronger for nonsynonymous alleles compared to synonymous alleles. While linkage is shaped by many evolutionary processes, extensive simulations show only two distinct forms of positive selection can drive an excess of coupling linkage between neighboring nonsynonymous alleles: directional selection on introgressed alleles or selection that maintains distinct haplotypes in the presence of recombination. Our results establish a framework for identifying patterns of selection in fine-scale haplotype structure that indicate specific ecological processes in species that recombine with distantly related lineages or possess coexisting adaptive haplotypes.

evolutionary biology↗

bioRxiv2018

Signals of polygenic adaptation on height have been overestimated due to uncorrected population structure in genome-wide association studies

Genetic predictions of height differ among human populations and these differences are too large to be explained by genetic drift. This observation has been interpreted as evidence of polygenic adaptation. Differences across populations were detected using SNPs genome-wide significantly associated with height, and many studies also found that the signals grew stronger when large numbers of subsignificant SNPs were analyzed. This has led to excitement about the prospect of analyzing large fractions of the genome to detect subtle signals of selection and claims of polygenic adaptation for multiple traits. Polygenic adaptation studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the height analyses in the UK Biobank, a much more homogeneously designed study. Our results show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population structure.

evolutionary biology↗