Biology subjects

Zaidi, A. A.

Publications and source records attributed to Zaidi, A. A..

11 recordsLinked to original sources

bioRxiv2026

Beyond copy number: The regulatory architecture of mitochondrial DNA gene expression

Mitochondrial DNA (mtDNA) copy number is widely used as a biomarker for mitochondrial function and disease risk, yet its relationship to mtDNA gene expression - one important functional output - remains poorly understood. Prior studies examining this relationship have largely relied on heterogeneous tissue samples, where confounding by cell-type composition obscures the underlying biology. We rigorously tested this relationship in lymphoblastoid cell lines (LCLs), where we find no correlation between mtDNA copy number and gene expression across 731 individuals, and minimal association across 49 GTEx tissues except whole blood. Using population genetic modeling of heteroplasmy drift between DNA and RNA, we estimate that effectively {approx}50 out of 813 mtDNA templates are transcriptionally active in LCLs, indicating low mtDNA accessibility. This confirms, using an independent method and a different cell type, previous observations in HeLa cells, where mtDNA is largely compacted into nucleoids. Together, our results demonstrate that mtDNA copy number and expression are largely decoupled, and that above a certain rate-limiting threshold, mtDNA accessibility -- rather than absolute copy number -- is the more relevant quantity for explaining inter-individual differences in gene expression. This challenges the interpretation of mtDNA copy number as a proxy for mitochondrial transcriptional output and highlights the need for a more mechanistic understanding of mtDNA copy number associations with disease-relevant traits. Cis- and trans-eQTL mapping further reveals that genetic regulation of mtDNA gene expression operates primarily through post-transcriptional mechanisms rather than transcription initiation, yet despite the high inter-individual variance in mtDNA gene expression, genetic variation underlying mtDNA regulation appears to be under strong selective constraint.

genomics↗

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↗

bioRxiv2023

Interpreting SNP heritability in admixed populations

SNP heritability [Formula] is defined as the proportion of phenotypic variance explained by genotyped SNPs and is believed to be a lower bound of heritability (h2), being equal to it if all causal variants are genotyped. Despite the simple intuition behind [Formula], its interpretation and equivalence to h2 is unclear, particularly in the presence of admixture and assortative mating. Here we use analytical theory and simulations to describe the behavior of h2 and three widely used random-effect estimators of [Formula] Genome-wide restricted maximum likelihood (GREML), Haseman-Elston (HE) regression, and LD score regression (LDSC) - in admixed populations. We show that [Formula] estimates can be biased in admixed populations, even if all causal variants are genotyped and in the absence of confounding due to shared environment. This is largely because admixture generates directional LD, which contributes to the genetic variance, and therefore to heritability. Random-effect estimators of [Formula], because they assume that SNP effects are independent, do not capture the contribution, which can be positive or negative depending on the genetic architecture, leading to under- or over-estimates of [Formula] relative to h2. For the same reason, estimates of local ancestry heritability [Formula] are also biased in the presence of directional LD. We describe this bias in [Formula] and [Formula] as a function of admixture history and the genetic architecture of the trait, clarifying their interpretation and implication for genome-wide association studies and polygenic prediction in admixed populations.

genetics↗

bioRxiv2021

Long runs of homozygosity are correlated with marriage preferences across global population samples

Children of consanguineous unions carry long runs of homozygosity (ROH) in their genomes, due to their parents recent shared ancestry. This increases the burden of recessive disease in populations with high levels of consanguinity and has been heavily studied in some groups. However, there has been little investigation of the broader effect of consanguinity on patterns of genetic variation on a global scale. Here, we collect published genetic data and information about marriage practices from 396 worldwide populations and show that preference for cousin marriage has a detectable effect on the distribution of long ROH in these samples, increasing the expected number of ROH longer than 10Mb by a factor of 1.5 (P=2.3 x 10-4). Variation in marriage practice and consequent rates of consanguinity is therefore an important aspect of demographic history for the purposes of modeling human genetic variation. However, marriage practices explain a relatively small proportion of the variation in ROH distribution and consequently the ability to predict marriage practices from population genetic samples (for example of ancient populations) is limited.

genetics↗

bioRxiv2020

High-throughput phenotyping methods for quantifying hair fiber morphology

Quantifying the continuous variation in human scalp hair morphology is of interest to anthropologists, geneticists, dermatologists and forensic scientists, but existing methods for studying hair form are time-consuming and not widely used. Here, we present a high-throughput sample preparation protocol for the imaging of both longitudinal (curvature) and cross-sectional scalp hair morphology. Additionally, we describe and validate a new Python package designed to process longitudinal and cross-sectional hair images, segment them, and provide measurements of interest. Lastly, we apply our methods to an admixed African-European sample (n=140), demonstrating the benefit of quantifying hair morphology over qualitative classification or racial categories, and providing evidence against the long-held belief that cross-sectional morphology predicts curvature.

bioinformatics↗

bioRxiv2020

Demographic history impacts stratification in polygenic scores

Large genome-wide association studies (GWAS) have identified many loci exhibiting small but statistically significant associations with complex traits and disease risk. However, control of population stratification continues to be a limiting factor, particularly when calculating polygenic scores where subtle biases can cumulatively lead to large errors. We simulated GWAS under realistic models of demographic history to study the effect of residual stratification in large GWAS. We show that when population structure is recent, it cannot be fully corrected using principal components based on common variants--the standard approach--because common variants are uninformative about recent demographic history. Consequently, polygenic scores calculated from such GWAS results are biased in that they recapitulate non-genetic environmental structure. Principal components calculated from rare variants or identity-by-descent segments largely correct for this structure if environmental effects are smooth. However, even these corrections are not effective for local or batch effects. While sibling-based association tests are immune to stratification, the hybrid approach of ascertaining variants in a standard GWAS and then re-estimating effect sizes in siblings reduces but does not eliminate bias. Finally, we show that rare variant burden tests are relatively robust to stratification. Our results demonstrate that the effect of population stratification on GWAS and polygenic scores depends not only on the frequencies of tested variants and the distribution of environmental effects but also on the demographic history of the population.

genetics↗

bioRxiv2019

Robust Genome-Wide Ancestry Inference for Heterogeneous Datasets and Ancestry Facial Imaging based on the 1000 Genomes Project

Accurate inference of genomic ancestry is critically important in human genetics, epidemiology, and related fields. Geneticists today have access to multiple heterogeneous population-based datasets from studies collected under different protocols. Therefore, joint analyses of these datasets require robust and consistent inference of ancestry, where a common strategy is to yield an ancestry space generated by a reference dataset. However, such a strategy is sensitive to batch artefacts introduced by different protocols. In this work, we propose a novel robust genome-wide ancestry inference method; referred to as SUGIBS, based on an unnormalized genomic (UG) relationship matrix whose spectral (S) decomposition is generalized by an Identity-by-State (IBS) similarity degree matrix. SUGIBS robustly constructs an ancestry space from a single reference dataset, and provides a robust projection of new samples, from different studies. In experiments and simulations, we show that, SUGIBS is robust against individual outliers and batch artifacts introduced by different genotyping protocols. The performance of SUGIBS is equivalent to the widely used principal component analysis (PCA) on normalized genotype data in revealing the underlying structure of an admixed population and in adjusting for false positive findings in a case-control admixed GWAS. We applied SUGIBS on the 1000 Genome project, as a reference, in combination with a large heterogeneous dataset containing auxiliary 3D facial images, to predict population stratified average or ancestry faces. In addition, we projected eight ancient DNA profiles into the 1000 Genome ancestry space and reconstructed their ancestry face. Based on the visually strong and recognizable human facial phenotype, comprehensive facial illustrations of the populations embedded in the 1000 Genome project are provided. Furthermore, ancestry facial imaging has important applications in personalized and precision medicine along with forensic and archeological DNA phenotyping. Author SummaryEstimates of individual-level genomic ancestry are routinely used in human genetics, epidemiology, and related fields. The analysis of population structure and genomic ancestry can yield significant insights in terms of modern and ancient population dynamics, allowing us to address questions regarding the timing of the admixture events, and the numbers and identities of the parental source populations. Unrecognized or cryptic population structure is also an important confounder to correct for in genome-wide association studies (GWAS). However, to date, it remains challenging to work with heterogeneous datasets from multiple studies collected by different laboratories with diverse genotyping and imputation protocols. This work presents a new approach and an accompanying open-source software toolbox that facilitates a robust integrative analysis for population structure and genomic ancestry estimates for heterogeneous datasets. Given that visually evident and easily recognizable patterns of human facial characteristics covary with genomic ancestry, we can generate predicted ancestry faces on both the population and individual levels as we illustrate for the 26 1000 Genome populations and for eight eminent ancient-DNA profiles, respectively.

genetics↗

bioRxiv2019

MeshMonk: Open-source large-scale intensive 3D phenotyping

In the post-genomics era, an emphasis has been placed on disentangling genotype-phenotype connections so that the biological basis of complex phenotypes can be understood. However, our ability to efficiently and comprehensively characterize phenotypes lags behind our ability to characterize genomes. Here, we report a toolbox for fast and reproducible high-throughput dense phenotyping of 3D images. Given a target image, a rigid registration is first used to orient a template to the target surface, then the template is transformed further to fit the specific shape of the target using a non-rigid transformation model. As validation, we used N = 41 3D facial images registered with MeshMonk and manually landmarked at 19 locations. We demonstrate that the MeshMonk registration is accurate, with 0.62 mm as the average root mean squared error between the manual and automatic placements and no variation in landmark position or centroid size significantly attributable to landmarking method used. Though validated using 19 landmarks for comparison with traditional methods, MeshMonk allows for automatic dense phenotyping, thus facilitating more comprehensive investigations of 3D shape variation. This expansion opens up an exciting avenue of study in assessing genomic and phenomic data to better understand the genetic contributions to complex morphological traits.

evolutionary biology↗

bioRxiv2018

Mito-nuclear effects uncovered in admixed populations

To function properly, mitochondria utilize products of 37 and >1,000 genes encoded by the mitochondrial and nuclear genomes, respectively, which should be compatible with each other. Discordance between mitochondrial and nuclear genetic ancestry could contribute to phenotypic variation in admixed populations. Here we explored potential mito-nuclear incompatibility in six admixed human populations from the Americas: African Americans, African Caribbeans, Colombians, Mexicans, Peruvians, and Puerto Ricans. For individuals in these populations, we determined nuclear genome proportions derived from Africans, Europeans, and Native Americans, the geographic origins of the mitochondrial DNA (mtDNA), as well as mtDNA copy number in lymphoblastoid cell lines. By comparing nuclear vs. mitochondrial ancestry in admixed populations, we show that, first, mtDNA copy number decreases with increasing discordance between nuclear and mitochondrial DNA ancestry, in agreement with mito-nuclear incompatibility. The direction of this effect is consistent across mtDNA haplogroups of different geographic origins. This observation suggests suboptimal regulation of mtDNA replication when its components are encoded by nuclear and mtDNA genes with different ancestry. Second, while most populations analyzed exhibit no such trend, in Puerto Ricans and African Americans we find a significant enrichment of ancestry at nuclear-encoded mitochondrial genes towards the source populations contributing the most prevalent mtDNA haplogroups (Native American and African, respectively). This likely reflects compensatory effects of selection in recovering mito-nuclear interactions optimized in the source populations. Our results provide the first evidence of mito-nuclear effects in human admixed populations and we discuss its implications for human health and disease.

genetics↗

bioRxiv2018

Facial masculinity does not appear to be a condition-dependent male ornament in humans and does not reflect MHC heterozygosity

Facial masculinity is thought to be a condition-dependent male ornament, reflecting immunocompetence in humans. To test this hypothesis, we calculated an objective measure of facial masculinity/femininity using three-dimensional images in a large sample (N = 1,233) of people of European ancestry. We show that facial masculinity is positively correlated with adult height in both males and females. This suggests that variation in growth contributes, at least in part, to variation in facial masculinity, which is characteristic of condition-dependent traits. However, facial masculinity scales with growth similarly in males and females, suggesting that facial masculinity is not specifically a male ornament. Additionally, we measured immunocompetence via heterozygosity at the major histocompatibility complex (MHC), a well known genetic marker of immunity. We show that while height is positively correlated with MHC heterozygosity, facial masculinity is not. Thus, facial masculinity does not reflect immunocompetence measured by MHC heterozygosity in humans as thought previously. Overall, we find no support for the idea that facial masculinity is a condition-dependent male ornament that has evolved to indicate immunocompetence.

evolutionary biology↗

bioRxiv2017

Copy number variation of ampliconic genes across major human Y haplogroups

Due to its highly repetitive nature, the human male-specific Y chromosome remains understudied. It is important to investigate variation on the Y chromosome to understand its evolution and contribution to phenotypic variation, including infertility. Approximately 20% of the human Y chromosome consists of ampliconic regions which include nine multi-copy gene families. These gene families are expressed exclusively in testes and usually implicated in spermatogenesis. Here, to gain a better understanding of the role of the Y chromosome in human evolution and in determining sexually dimorphic traits, we studied ampliconic gene copy number variation in 100 males representing ten major Y haplogroups world-wide. Copy number was estimated with droplet digital PCR. In contrast to low nucleotide diversity observed on the Y in previous studies, here we show that ampliconic gene copy number diversity is very high. A total of 98 copy-number-based haplotypes were observed among 100 individuals, and haplotypes were sometimes shared by males from very different haplogroups, suggesting homoplasies. The resulting haplotypes did not cluster according to major Y haplogroups. Overall, only three gene families (DATZ, RBMY, TSPY) showed significant differences in copy number among major Y haplogroups, and the haplogroup of an individual could not be predicted based on his ampliconic gene copy numbers. Finally, we found a significant correlation between copy number variation and individuals height (for three gene families), but not between the former and facial masculinity/femininity. Our results suggest rapid evolution of ampliconic gene copy numbers on the human Y, and we discuss its causes.

evolutionary biology↗