Biology subjects

O'Connell, J.

Publications and source records attributed to O'Connell, J..

13 recordsLinked to original sources

bioRxiv2025

cellSTAAR: Incorporating single-cell-sequencing-based functional data to boost power in rare variant association testing of non-coding regions

Whole genome sequencing (WGS) studies have identified hundreds of millions of rare variants (RVs) and have enabled RV association tests (RVATs) of these variants with complex traits and diseases. Analysis of non-coding variants is challenged by the considerable variability in regulatory function which candidate Cis-Regulatory Elements (cCREs) exhibit across cell types. We propose cellSTAAR, which integrates WGS data with single-cell ATAC-seq data to capture variability in chromatin accessibility across cell types via the construction of cell-type-specific functional annotations and variant sets. To reflect the uncertainty in cCRE-gene linking, cellSTAAR also links cCREs to their target genes using an omnibus framework which aggregates results from a variety of popular linking approaches. We applied cellSTAAR on Freeze 8 (N = 60,000) of the NHLBI Trans-Omics for Precision Medicine (TOPMed) consortium data to four lipids phenotypes: LDL cholesterol, a binary variable corresponding to high LDL cholesterol, HDL cholesterol, and triglycerides. We also provide replication results for all four phenotypes using UK Biobank (N = 190,000). Evidence from simulation studies and our real data analysis demonstrates that cellSTAAR boosts power and improves interpretation of RVATs of cCREs.

genetics↗

bioRxiv2024

Phasing millions of samples achieves near perfect accuracy, enabling parent-of-origin classification of variants

Haplotype phasing, the process of determining which genetic variants are physically located on the same chromosome, is crucial for various genetic analyses. In this study, we first benchmark SHAPEIT and Beagle, two state-of-the-art phasing methods, on two large datasets: > 8 million diverse, research-consented 23andMe, Inc. customers and the UK Biobank (UKB). We find that both perform exceptionally well. Beagles median switch error rate (SER) (after excluding single SNP switches) in white British trios from UKB is 0.026% compared to 0.00% for European ancestry 23andMe research participants; 55.6% of European ancestry 23andMe research participants have zero non-single SNP switches, compared to 42.4% of white British trios. South Asian ancestry 23andMe research participants have the highest median SER amongst the 23andMe populations, but it is still remarkably low at 0.46%. We also investigate the relationship between identity-by-descent (IBD) and SER, finding that switch errors tend to occur in regions of little or no IBD segment coverage. SHAPEIT and Beagle excel at intra-chromosomal phasing, but lack the ability to phase across chromosomes, motivating us to develop an inter-chromosomal phasing method, called HAPTIC (HAPlotype TIling and Clustering), that assigns paternal and maternal variants discretely genome-wide. Our approach uses identity-by-descent (IBD) segments to phase blocks of variants on different chromosomes. HAPTIC represents the segments a focal individual shares with their relatives as nodes in a signed graph and performs bipartite clustering on the signed graph using spectral clustering. We test HAPTIC on 1022 UKB trios, yielding a median phase error of 0.08% in regions covered by IBD segments (33.5% of sites). We also ran HAPTIC in the 23andMe database and found a median phase error rate (the rate of mismatching alleles between the inferred and true phase) of 0.92% in Europeans (93.8% of sites) and 0.09% in admixed Africans (92.7% of sites). HAPTICs precision depends heavily on data from relatives, so will increase as datasets grow larger and more diverse. HAPTIC enables analyses that require the parent-of-origin of variants, such as association studies and ancestry inference of untyped parents.

bioinformatics↗

bioRxiv2024

A Comprehensive Model of Blood Flow Restriction in the Post-surgical Rat

Blood flow restriction (BFR) with low-load exercise (BFR-exercise) is an increasingly popular tool used to increase muscle strength and attenuate muscle atrophy, especially after injury or surgery. However, the mechanisms underlying BFR-mediated muscle growth are not well understood. Likely contributing to the mechanistic knowledge gap, rodent models of BFR-exercise have not been well described. In this methods paper, we demonstrate a comprehensive, clinically relevant protocol to establish BFR-exercise in awake rats. This protocol includes generating a muscle loss state via bilateral ACL-R, determining targeted blood flow occlusion pressures, and performing weighted hind-limb knee extension exercises with BFR. These methods can be used for further application in mechanistic and physiologic studies of BFR-exercise.

animal behavior and cognition↗

bioRxiv2023

Scaling between cell cycle duration and wing growth is regulated by Fat-Dachsous signaling in Drosophila

The atypical cadherins Fat and Dachsous (Ds) signal through the Hippo pathway to regulate growth of numerous organs, including the Drosophila wing. Here, we find that Ds-Fat signaling tunes a unique feature of cell proliferation found to control the rate of wing growth during the third instar larval phase. The duration of the cell cycle increases in direct proportion to the size of the wing, leading to linear-like growth during the third instar. Ds-Fat signaling enhances the rate at which the cell cycle lengthens with wing size, thus diminishing the rate of wing growth. We show that this results in a complex but stereotyped relative scaling of wing growth with body growth in Drosophila. Finally, we examine the dynamics of Fat and Ds protein distribution in the wing, observing graded distributions that change during growth. However, the significance of these dynamics is unclear since perturbations in expression have negligible impact on wing growth.

developmental biology↗

bioRxiv2023

ME-Bayes SL: Enhanced Bayesian Polygenic Risk Prediction Leveraging Information across Multiple Ancestry Groups

Polygenic risk scores (PRS) are now showing promising predictive performance on a wide variety of complex traits and diseases, but there exists a substantial performance gap across different populations. We propose MUSSEL, a method for ancestry-specific polygenic prediction that borrows information in the summary statistics from genome-wide association studies (GWAS) across multiple ancestry groups. MUSSEL conducts Bayesian hierarchical modeling under a MUltivariate Spike-and-Slab model for effect-size distribution and incorporates an Ensemble Learning step using super learner to combine information across different tuning parameter settings and ancestry groups. In our simulation studies and data analyses of 16 traits across four distinct studies, totaling 5.7 million participants with a substantial ancestral diversity, MUSSEL shows promising performance compared to alternatives. The method, for example, has an average gain in prediction R2 across 11 continuous traits of 40.2% and 49.3% compared to PRS-CSx and CT-SLEB, respectively, in the African Ancestry population. The best-performing method, however, varies by GWAS sample size, target ancestry, underlying trait architecture, and the choice of reference samples for LD estimation, and thus ultimately, a combination of methods may be needed to generate the most robust PRS across diverse populations.

genetics↗

bioRxiv2022

Large library docking for novel SARS-CoV-2 main protease non-covalent and covalent inhibitors

Antiviral therapeutics to treat SARS-CoV-2 are much desired for the on-going pandemic. A well-precedented viral enzyme is the main protease (MPro), which is now targeted by an approved drug and by several investigational drugs. With the inevitable liabilities of these new drugs, and facing viral resistance, there remains a call for new chemical scaffolds against MPro. We virtually docked 1.2 billion non-covalent and a new library of 6.5 million electrophilic molecules against the enzyme structure. From these, 29 non-covalent and 11 covalent inhibitors were identified in 37 series, the most potent having an IC50 of 29 M and 20 M, respectively. Several series were optimized, resulting in inhibitors active in the low micromolar range. Subsequent crystallography confirmed the docking predicted binding modes and may template further optimization. Together, these compounds reveal new chemotypes to aid in further discovery of MPro inhibitors for SARS-CoV-2 and other future coronaviruses.

biophysics↗

bioRxiv2022

Novel Methods for Multi-ancestry Polygenic Prediction and their Evaluations in 3.7 Million Individuals of Diverse Ancestry

Polygenic risk scores (PRS) increasingly predict complex traits, however, suboptimal performance in non-European populations raise concerns about clinical applications and health inequities. We developed CT-SLEB, a powerful and scalable method to calculate PRS using ancestry-specific GWAS summary statistics from multi-ancestry training samples, integrating clumping and thresholding, empirical Bayes and super learning. We evaluate CT-SLEB and nine-alternatives methods with large-scale simulated GWAS ([~]19 million common variants) and datasets from 23andMe Inc., the Global Lipids Genetics Consortium, All of Us and UK Biobank involving 5.1 million individuals of diverse ancestry, with 1.18 million individuals from four non-European populations across thirteen complex traits. Results demonstrate that CT-SLEB significantly improves PRS performance in non-European populations compared to simple alternatives, with comparable or superior performance to a recent, computationally intensive method. Moreover, our simulation studies offer insights into sample size requirements and SNP density effects on multi-ancestry risk prediction.

genetics↗

bioRxiv2021

Influence of viral transport media and freeze-thaw cycling on the sensitivity of qRT-PCR detection of SARS-CoV-2 nucleic acids

The events of the last year have highlighted the complexity of implementing large-scale molecular diagnostic testing for novel pathogens. The purpose of this study was to determine the chemical influences of sample collection media and storage on the stability and detection of viral nucleic acids by qRT-PCR. We studied the mechanism(s) through which viral transport media (VTM) and number of freeze-thaw cycles influenced the analytical sensitivity of qRT-PCR detection of SARS-CoV-2. Our goal is to reinforce testing capabilities and identify weaknesses that could arise in resource-limited environments that do not have well-controlled cold chains. The sensitivity of qRT-PCR analysis was studied in four VTM for synthetic single-stranded RNA (ssRNA) and double-stranded DNA (dsDNA) simulants of the SARS-CoV-2 genome. The sensitivity and reproducibility of qRT-PCR for the synthetic ssRNA and dsDNA were found to be highly sensitive to VTM with the best results observed for ssRNA in HBSS and PBS-G. Surprisingly, the presence of epithelial cellular material with the ssRNA increased the sensitivity of the qRT-PCR assay. Repeated freeze-thaw cycling decreased the sensitivity of the qRT-PCR with two noted exceptions. The choice of VTM is critically important to defining the sensitivity of COVID-19 molecular diagnostics assays and this study suggests they can impact upon the stability of the SARS-CoV-2 viral genome. This becomes increasingly important if the virus structure is destabilised before analysis, which can occur due to poor storage conditions. This study suggests that COVID-19 testing performed with glycerol-containing PBS will produce a high level of stability and sensitivity. These results are in agreement with clinical studies reported for patient-derived samples.

molecular biology↗

bioRxiv2020

Improved Monoisotopic Mass Estimation for Deeper Proteome Coverage

Accurate assignment of monoisotopic peaks is essential for the identification of peptides in bottom-up proteomics. Misassignment or inaccurate attribution of peptidic ions leads to lower sensitivity and fewer total peptide identifications. In the present work we present a performant, open-source, cross-platform algorithm, Monocle, for the rapid reassignment of instrument assigned precursor peaks to monoisotopic peptide assignments. We demonstrate that the present algorithm can be integrated into many common proteomics pipelines and provides rapid conversion from multiple data source types. Finally, we show that our monoisotopic peak assignment results in up to a two-fold increase in total peptide identifications compared to analyses lacking monoisotopic correction and a 44% improvement over previous monoisotopic peak correction algorithms.

bioinformatics↗

bioRxiv2020

Rare variant enriched identity-by-descent enables the detection of distant relatedness and older divergence between populations

MotivationThe global human population has experienced an explosive growth from a few million to roughly 7 billion people in the last 10,000 years. Accompanying this growth has been the accumulation of rare variants that can inform our understanding of human evolutionary history. Common variants have primarily been used to infer the structure of the human population and relatedness between two individuals. However, with the increasing abundance of rare variants observed in large-scale projects, such as Trans-Omics for Precision Medicine (TOPMed), the use of rare variants to decipher cryptic relatedness and fine-scale population structure can be beneficial to the study of population demographics and association studies. Identity-by-descent (IBD) is an important framework used for identifying these relationships. IBD segments are broken down by recombination over time, such that longer shared haplotypes give strong evidence of recent relatedness while shorter shared haplotypes are indicative of more distant relationships. Current methods to identify IBD accurately detect only long segments (> 2cM) found in related individuals. AlgorithmWe describe a metric that leverages rare-variants shared between individuals to improve the detection of short IBD segments. We computed IBD segments using existing methods implemented in Refined IBD where we enrich the signal using our metric that facilitates the detection of short IBD segments (<2cM) by explicitly incorporating rare variants. ResultsTo test our new metric, we simulated datasets involving populations with varying divergent time-scales. We show that rare-variant IBD identifies shorter segments with greater confidence and enables the detection of older divergence between populations. As an example, we applied our metric to the Old-Order Amish cohort with known genealogies dating 14 generations back to validate its ability to detect genetic relatedness between distant relatives. This analysis shows that our method increases the accuracy of identifying shorter segments that in turn capture distant relationships. ConclusionsWe describe a method to enrich the detection of short IBD segments using rare-variant sharing within IBD segments. Leveraging rare-variant sharing improves the information content of short IBD segments better than common variants alone. We validated the method in both simulated and empirical datasets. This method can benefit association analyses, IBD mapping analyses, and demographic inferences.

genomics↗

bioRxiv2020

The deubiquitylase USP9X controls ribosomal stalling

When a ribosome stalls during translation, it runs the risk of collision with a trailing ribosome. Such an encounter leads to the formation of a stable di-ribosome complex, which needs to be resolved by a dedicated machinery. The initial stalling and the subsequent resolution of di-ribosomal complexes requires activity of Makorin and ZNF598 ubiquitin E3 ligases respectively, through ubiquitylation of the eS10 and uS10 sub-units of the ribosome. It is common for the stability of RING E3 ligases to be regulated by an interacting deubiquitylase (DUB), which often opposes auto-ubiquitylation of the E3. Here, we show that the DUB USP9X directly interacts with ZNF598 and regulates its abundance through the control of protein stability in human cells. We have developed a highly specific small molecule inhibitor of USP9X. Proteomics analysis, following inhibitor treatment of HCT116 cells, confirms previous reports linking USP9X with centrosome associated protein stability and reveals loss of ZNF598 and Makorin 2. In the absence of USP9X or following chemical inhibition of its catalytic activity, steady state levels of Makorins and ZNF598 are diminished and the ribosomal quality control pathway is impaired.

cell biology↗

bioRxiv2019

Tracking human population structure through time from whole genome sequences

The genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a populations history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyse the population separation history. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago.\n\nAuthor SummaryHuman demographic history is reflected in specific patterns of shared mutations between the genomes from different populations. Here we aim to unravel this pattern to infer population structure through time with a new approach, called MSMC-IM. Based on estimates of coalescence rates within and across populations, MSMC-IM fits a time-dependent migration model to the pairwise rate of coalescences. We implemented this approach as an extension to existing software (MSMC2), and tested it with simulations exhibiting different histories of admixture and gene flow. We then applied it to the genomes from 15 worldwide populations to reveal their pairwise separation history ranging from a few thousand up to several million years ago. Among other results, we find evidence for remarkably deep population structure in some African population pairs, suggesting that deep ancestry dating to one million years ago and older is still present in human populations in small amounts today.

evolutionary biology↗

bioRxiv2017

Genome-wide genetic data on ~500,000 UK Biobank participants

The UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment. A rich variety of phenotypic and health-related information is available on each participant, making the resource unprecedented in its size and scope. Here we describe the genome-wide genotype data (~805,000 markers) collected on all individuals in the cohort and its quality control procedures. Genotype data on this scale offers novel opportunities for assessing quality issues, although the wide range of ancestries of the individuals in the cohort also creates particular challenges. We also conducted a set of analyses that reveal properties of the genetic data - such as population structure and relatedness - that can be important for downstream analyses. In addition, we phased and imputed genotypes into the dataset, using computationally efficient methods combined with the Haplotype Reference Consortium (HRC) and UK10K haplotype resource. This increases the number of testable variants by over 100-fold to ~96 million variants. We also imputed classical allelic variation at 11 human leukocyte antigen (HLA) genes, and as a quality control check of this imputation, we replicate signals of known associations between HLA alleles and many common diseases. We describe tools that allow efficient genome-wide association studies (GWAS) of multiple traits and fast phenome-wide association studies (PheWAS), which work together with a new compressed file format that has been used to distribute the dataset. As a further check of the genotyped and imputed datasets, we performed a test-case genome-wide association scan on a well-studied human trait, standing height.

genetics↗