Biology subjects

Daly, M. J.

Publications and source records attributed to Daly, M. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Autism genes converge on three functional programs organized by neuronal subclass, developmental timing, and cortical patterning

Our companion sequencing study uncovered 253 genes robustly associated with autism spectrum disorder (ASD), yet the biological programs they impact, and the cellular, developmental, and spatial contexts in which they converge, remain unresolved. Here we systematically contextualize genes associated with ASD across neurodevelopment and cortical areas, integrating developmental single-cell and spatial atlases with gene- and isoform co-expression, regulatory, proteomic, and synaptic networks. Genetic burden concentrates within temporally-resolved neuronal subclasses: newborn excitatory neurons, immature interneurons, and maturing intratelencephalic lineages. Genes associated with ASD converge on three functional programs--gene regulation, neuronal morphogenesis, and synaptic transmembrane signaling machinery--resolved from 28 ASD-associated networks, several of which are directly regulated by ASD genes including MEF2C, SOX11, and FOXP2. These programs are spatially patterned, with risk genes exhibiting an increasing anterior-to-posterior cortical expression gradient, anchored in the primary visual cortex and driven by excitatory neuron gene-regulatory programs. Finally, ASD risk genes associated with more severe developmental phenotypes show broader excitatory neuron enrichment and less interneuron involvement. Together, these findings anchor ASD genetic vulnerability to specific neurodevelopmental lineages, epochs, and molecular substrates, and delineate the features that distinguish ASD from comorbidities with broader developmental impacts.

genomics↗

bioRxiv2025

Blood donor biobank pipeline to collect genome-based samples for research

The integration of genome data with electronic health records, driven by large biobank studies, has advanced human genetics by allowing systematic exploration of genotype-phenotype links. Regular donation enables large, longitudinal sample cohorts. Because blood donors are generally healthy, disease treatments or progression do not disturb interpretations in functional studies. We describe here a pipeline on how to collect blood donors high quality plasma, serum, and living cell samples for multi-omics studies. Peripheral blood mononuclear cells (PBMC) were frozen and, after thawing, contained standard levels of immune cell subpopulations, responded to immune activation, and were of good quality starting material for multi-omics and cell imaging studies. We demonstrate that most genetic variants of interest to the major genomics study in Finland, FinnGen, could be found by random collection of samples during the standard blood donation without recall. Probing simple associations in the multi-omics data confirmed expected associations with e.g. age and sex, demonstrating good sample quality. As an example of interesting findings, we observed a significant association between frequent blood donation and lower levels of per- and polyfluoroalkyl substances (PFAS). The study demonstrates that regular blood donors are a suitable target population for high-quality, cost-effective sample collections.

molecular biology↗

bioRxiv2025

Genetics-to-structure multiscale analysis identifies disrupted calcium homeostasis as a mechanism of psychiatric disease

Neuropsychiatric disorders are highly heritable, but the molecular mechanisms linking risk variants to disease remain unclear1. Linking genetics to biological mechanisms requires integrating evidence across scales, from sequence variation to gene regulation to protein function. Here we integrate genetic, transcriptomic, and structural evidence to identify dysregulation of neuronal Ca2+ dynamics as a contributing mechanism. We analyzed single-nucleus neuronal RNA-seq data together with genome-wide association study (GWAS) heritability in a new way to identify gene expression programs enriched for psychiatric risk; genes encoding Ca2+ flux pathway genes were implicated by this analysis, a result that was then confirmed by concentrations of rare coding variants in these same genes in persons with psychiatric disorders. A critical gene in this biology, ATP2B2, encodes a Ca2+-extruding ATPase pump2 linked to neuropsychiatric disorders primarily through missense variants. To recognize specific molecular functions affected by these missense variants, we developed a 3D-neighborhood-based method that maps missense variants onto AlphaFold3-predicted protein structures and tests clustering of protein-altering variants in three-dimensional space. This approach revealed clustering of these missense changes in the Ca2+ pore and ATP:Mg2+ coordination site of ATP2B2. To validate the structural predictions arising from the genetic analysis, we determined the structure of human Ca2+-bound ATP2B2 at 2.64 [A] resolution by cryogenic electron microscopy. The structure replicated the 3D mutational hotspots identified by the genetic analysis, supporting the observation that neuropsychiatric variants cluster near specific catalytic sites of ATP2B2. In vitro experiments revealed that missense variants prioritized by the structural clustering analysis impaired ATP2B2-mediated Ca2+ extrusion in cellular and biochemical assays. Together, these findings suggest that precise regulation of Ca2+ dynamics is a contributing mechanism in neuropsychiatric disorders and establish a structure-based framework for predicting the mechanistic impact of missense variants.

genetics↗

bioRxiv2025

Sensitive Transcriptomics and Genotyping reveals function of genetic variants in immunity

Advancements in genomics have revolutionized human genetics by defining the genetic architecture of disease. However, identifying causal variants and their mechanisms of action remains a challenge in translating genetics into therapeutic interventions. Here, we developed Sensitive Transcriptomics And Genotyping by sequencing (STAG-seq), a high-throughput platform designed to define mechanistic genotype-phenotype relationships through simultaneous single-cell measurements of genomic DNA and RNA transcripts. Combined with base-editing, STAG-seq enables functionalization of variants in relevant cellular contexts. We demonstrate the applicability of this approach in several settings. First, we screened genetic perturbations to identify monoallelic and biallelic variant effects in primary human macrophages treated with innate immune stimuli. Next, we phenotyped clinically relevant missense variants associated with immunodeficiency and autoimmunity. Finally, we defined a noncoding variant in a pleiotropic autoimmunity locus that governs TNRC18 expression in primary T cells. STAG-seq thus enables variant phenotyping at scale to advance functional genomics and disease biology.

genomics↗

bioRxiv2024

The Ulcerative Colitis-Associated Gene NXPE1 Catalyzes Glycan Modifications on Colonic Mucin

Colonic mucus forms a first line of defense against bacterial invasion while providing nutrition to support coinhabiting microbes in the gut. Mucus is composed of polymeric networks of mucin proteins, which are heavily modified post-translationally. The full compendium of enzymes responsible for these modifications and their roles in health and disease remain incompletely understood. Herein we determine the biochemical function of NXPE1, a gene implicated in ulcerative colitis (UC), and demonstrate that it encodes an acetyltransferase that modifies mucin glycans. Specifically, NXPE1 utilizes acetyl-CoA to regioselectively modify the mucus sialic acid, 5-N-acetylneuraminic acid (Neu5Ac), at the 9-OH group to generate 9-O-acetylated Neu5Ac (Neu5,9Ac2). We further demonstrate that colonic organoids derived from donors harboring the missense variant NXPE1 G353R, which is protective against UC, exhibit severely impaired acetylation of Neu5Ac on mucins. Together, our findings support a model in which NXPE1 masks the alcohols of mucus sialoglycans via acetylation, which is important for modulating mucus barrier properties that limit interactions with commensal microbes.

immunology↗

bioRxiv2024

Early establishment and life course stability of sex biases in the human brain transcriptome

To elaborate on the origins of the established male-female differences in several brain-related phenotypes, we assessed the patterns of transcriptomic sex biases in the developing and adult human forebrain. We find an abundance of sex differences in expression (sex-DE) in the prenatal brain, driven by both hormonal and sex-chromosomal factors, and considerable consistency in the sex effects between the developing and adult brain, with little sex-DE exclusive to the adult forebrain. Sex-DE was not enriched in genes associated with brain disorder, consistent with systematic differences in the characteristics of these genes (e.g. constraint). Yet, the genes with persistent sex-DE across lifespan were overrepresented in disease gene co-regulation networks, pointing to their potential to mediate sex biases in brain phenotypes. Altogether, our work highlights the prenatal development as a crucial timepoint for the establishment of brain sex differences.

genomics↗

bioRxiv2024

Variant scoring performance across selection regimes depends on variant-to-gene and gene-to-disease components

Variant scoring methods (VSMs) aid in the interpretation of coding mutations and their potential impact on health, but their evaluation in the context of human genetics applications remains inconsistent. Here, we describe GeneticsGym, a systematic approach to evaluating the real-world impact of VSMs on human genetic analysis. We show that the relative performance of VSMs varies across regimes of natural selection, and that both variant-to-gene and gene-to-disease components contribute.

bioinformatics↗

bioRxiv2024

Genetic association data are broadly consistent with stabilizing selection shaping human common diseases and traits

Results from genome-wide association studies (GWAS) enable inferences about the balance of evolutionary forces maintaining genetic variation underlying common diseases and other genetically complex traits. Natural selection is a major force shaping variation, and understanding it is necessary to explain the genetic architecture and prevalence of heritable diseases. Here, we analyze data for 27 traits, including anthropometric traits, metabolic traits, and binary diseases--both early-onset and post-reproductive. We develop an inference framework to test existing population genetics models based on the joint distribution of allelic effect sizes and frequencies of trait-associated variants. A majority of traits have GWAS results that are inconsistent with neutral evolution or long-term directional selection (selection against a trait or against disease risk). Instead, we find that most traits show consistency with stabilizing selection, which acts to preserve an intermediate trait value or disease risk. Our observations also suggest that selection may reflect pleiotropy, with each variant influenced by associations with multiple selected traits.

genomics↗

bioRxiv2024

The landscape of regional missense mutational intolerance quantified from 125,748 exomes

Missense variants can have a range of functional impacts depending on factors such as the specific amino acid substitution and location within the gene. To interpret their deleteriousness, studies have sought to identify regions within genes that are specifically intolerant of missense variation. Here, we leverage the patterns of rare missense variation in 730,947 exome sequenced individuals in the Genome Aggregation Database (gnomAD v4.1.1) against a null mutational model to identify transcripts with regional differences in missense constraint. Missense-depleted regions are enriched for ClinVar pathogenic variants, de novo missense variants from individuals with neurodevelopmental disorders, and complex trait heritability. Following ClinGen calibration recommendations for the ACMG/AMP variant classification guidelines, we establish that variants within regions with <36% of their expected missense variation achieve moderate support for pathogenicity. We integrate this regional constraint measure into a missense deleteriousness metric (named MPC) that effectively stratifies rare and de novo missense variants in individuals with early-onset developmental conditions from controls. These results provide additional tools to aid in missense variant interpretation.

genomics↗

bioRxiv2023

CHARR efficiently estimates contamination from DNA sequencing data

DNA sample contamination is a major issue in clinical and research applications of whole genome and exome sequencing. Even modest levels of contamination can substantially affect the overall quality of variant calls and lead to widespread genotyping errors. Currently, popular tools for estimating the contamination level use short-read data (BAM/CRAM files), which are expensive to store and manipulate and often not retained or shared widely. We propose a new metric to estimate DNA sample contamination from variant-level whole genome and exome sequence data, CHARR, Contamination from Homozygous Alternate Reference Reads, which leverages the infiltration of reference reads within homozygous alternate variant calls. CHARR uses a small proportion of variant-level genotype information and thus can be computed from single-sample gVCFs or callsets in VCF or BCF formats, as well as efficiently stored variant calls in Hail VDS format. Our results demonstrate that CHARR accurately recapitulates results from existing tools with substantially reduced costs, improving the accuracy and efficiency of downstream analyses of ultra-large whole genome and exome sequencing datasets.

bioinformatics↗

bioRxiv2023

Understanding Complex Trait Susceptibilities and Ethnical Diversity in a Sample of 4,145 Russians Through Analysis of Clinical and Genetic Data

The population of Russia consists of more than 150 local ethnicities. The ethnic diversity and geographic origins, which extend from eastern Europe to Asia, make the population uniquely positioned to investigate the shared properties of inherited disease risks between European and Asian ethnicities. We present the analysis of genetic and phenotypic data from a cohort of 4,145 individuals collected in three metro areas in western Russia. We show the presence of multiple admixed ancestry clusters spanning from primarily European to Asian and high identity-by-descent sharing with the Finnish population. As a result, there was notable enrichment of Finnish-specific variants in Russia. We illustrate the utility of Russian-descent cohorts for discovery of novel population-specific genetic associations, as well as replication of previously identified associations that were thought to be population-specific in other cohorts. Finally, we provide access to a database of GWAS results for 465 unique phenotypes and allele frequencies.

genetics↗

bioRxiv2023

Inferring compound heterozygosity from large-scale exome sequencing data

Recessive diseases arise when both the maternal and the paternal copies of a gene are impacted by a damaging genetic variant in the affected individual. When a patient carries two different potentially causal variants in a gene for a given disorder, accurate diagnosis requires determining that these two variants occur on different copies of the chromosome (i.e., are in trans) rather than on the same copy (i.e. in cis). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. We developed a strategy for inferring phase for rare variant pairs within genes, leveraging genotypes observed in exome sequencing data from the Genome Aggregation Database (gnomAD v2, n=125,748). When applied to trio data where phase can be determined by transmission, our approach estimates phase with 95.7% accuracy and remains accurate even for very rare variants (allele frequency < 1x10-4). We also correctly phase 95.9% of variant pairs in a set of 293 patients with Mendelian conditions carrying presumed causal compound heterozygous variants. We provide a public resource of phasing estimates from gnomAD, including phasing estimates for coding variants across the genome and counts per gene of rare variants in trans, that can aid interpretation of rare co-occurring variants in the context of recessive disease.

genomics↗

bioRxiv2023

A harmonized public resource of deeply sequenced diverse human genomes

Underrepresented populations are often excluded from genomic studies due in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high quality set of 4,094 whole genomes from HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also demonstrate substantial added value from this dataset compared to the prior versions of the component resources, typically combined via liftover and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared to previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

genomics↗

bioRxiv2022

Secretoglobin family 1D member 2 (SCGB1D2) protein inhibits growth of Borrelia burgdorferi and affects susceptibility to Lyme disease

Lyme disease is a tick-borne disease caused by bacteria of the genus Borrelia. The disease can initially manifest as an erythema migrans rash and, if able to evade the host immune defenses, can progress into a secondary stage chronic disease with debilitating physical or neurological manifestations1,2. The host factors that modulate susceptibility for Lyme disease have remained mostly unknown. Here we show a novel host defense mechanism against Lyme disease in humans. Using epidemiological and genetic data from FinnGen, we identify a common missense variant at the gene encoding for Secretoglobin family 1D member 2 (SCGB1D2) protein that increases the susceptibility for Lyme disease. The genetic variant changes proline at position 53 to leucine and is predicted as deleterious. Consequently, we validate the dysfunction of this protein variant using live Borrelia burgdorferi (Bb). Recombinant reference SCGB1D2 protein inhibits the growth of Bb twice as effectively as the recombinant SCGB1D2 P53L deleterious missense variant. Together, these data suggest that SCGB1D2 is a host defense factor present in the skin, sweat, and other secretions which protects against Bb infection. This finding provides a novel therapeutic avenue for drug development to prevent and treat Lyme disease.

genetics↗

bioRxiv2022

Discordant genotype calls across technology platforms elucidate variants with systematic errors in next-generation sequencing

Large-scale next-generation sequencing datasets have been transformative for informing clinical variant interpretation and as reference panels for statistical and population genetic efforts. While such resources are often treated as ground truth, we find that in widely used reference datasets such as the Genome Aggregation Database (gnomAD), some variants pass gold standard filters yet are systematically different in their genotype calls across genotype discovery approaches. The inclusion of such discordant sites in study designs involving multiple genotype discovery strategies could bias results and lead to false-positive hits in association studies due to technological artifacts rather than a true relationship to the phenotype. Here, we describe this phenomenon of discordant genotype calls across genotype discovery approaches, characterize the error mode of wrong calls, provide a blacklist of discordant sites identified in gnomAD that should be treated with caution in analyses, and present a metric and machine learning classifier trained on gnomAD data to identify likely discordant variants in other datasets. We find that different genotype discovery approaches have different sets of variants at which this problem occurs but that there are characteristic variant features that can be used to predict discordant behavior. Discordant sites are largely shared across ancestry groups, though different populations are powered for discovery of different variants. We find that the most common error mode is that of a variant being heterozygous for one approach and homozygous for the other, with heterozygous in the genomes and homozygous reference in the exomes making up the majority of miscalls.

genomics↗

bioRxiv2021

Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa

African populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and comprehensive multigenerational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within the African continent, as well as how within-Africa variation can be informative for broader variant interpretation; many variants appearing rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity within Africa.

genomics↗

bioRxiv2020

An efficient and accurate frailty model approach for genome-wide survival association analysis controlling for population structure and relatedness in large-scale biobanks

With decades of electronic health records linked to genetic data, large biobanks provide unprecedented opportunities for systematically understanding the genetics of the natural history of complex diseases. Genome-wide survival association analysis can identify genetic variants associated with ages of onset, disease progression and lifespan. We developed an efficient and accurate frailty (random effects) model approach for genome-wide survival association analysis of censored time-to-event (TTE) phenotypes in large biobanks by accounting for both population structure and relatedness. Our method utilizes state-of-the-art optimization strategies to reduce the computational cost. The saddlepoint approximation is used to allow for analysis of heavily censored phenotypes (>90%) and low frequency variants (down to minor allele count 20). We demonstrated the performance of our method through extensive simulation studies and analysis of five TTE phenotypes, including lifespan, with heavy censoring rates (90.9% to 99.8%) on ~400,000 UK Biobank participants with white British ancestry and ~180,000 samples in FinnGen, respectively. We further performed genome-wide association analysis for 871 TTE phenotypes in UK Biobank and presented the genome-wide scale phenome-wide association (PheWAS) results with the PheWeb browser.

genomics↗

bioRxiv2020

Genome-wide maps of enhancer regulation connect risk variants to disease genes

Genome-wide association studies have now identified tens of thousands of noncoding loci associated with human diseases and complex traits, each of which could reveal insights into biological mechanisms of disease. Many of the underlying causal variants are thought to affect enhancers, but we have lacked genome-wide maps of enhancer-gene regulation to interpret such variants. We previously developed the Activity-by-Contact (ABC) Model to predict enhancer-gene connections and demonstrated that it can accurately predict the results of CRISPR perturbations across several cell types. Here, we apply this ABC Model to create enhancer-gene maps in 131 cell types and tissues, and use these maps to interpret the functions of fine-mapped GWAS variants. For inflammatory bowel disease (IBD), causal variants are >20-fold enriched in enhancers in particular cell types, and ABC outperforms other regulatory methods at connecting noncoding variants to target genes. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577 genes that appear to influence multiple phenotypes via variants in enhancers that act in different cell types. Guided by these variant-to-function maps, we show that an enhancer containing an IBD risk variant regulates the expression of PPIF to tune mitochondrial membrane potential. Together, our study reveals insights into principles of genome regulation, illuminates mechanisms that influence IBD, and demonstrates a generalizable strategy to connect common disease risk variants to their molecular and cellular functions.

genetics↗