Biology subjects

Wilson, M. W.

Publications and source records attributed to Wilson, M. W..

5 recordsLinked to original sources

bioRxiv2025

Estimating how Site-Level Differences in Acoustic Environments Affect Species Detection by Machine Learning Models

O_LIMachine learning models are vital in species detection from acoustic data, due to the large amount of recordings produced, especially in passive acoustic monitoring studies. However, the acoustic environment of a site can significantly impact the detectability of species using such models, potentially leading to biased estimates of species abundance and distribution. This impact is poorly understood, and current manual validation methods for assessing acoustic detectability are intractable when working with many species, across multiple locations and datasets, due to the intensive time requirements to manually identify false negatives. C_LIO_LIWe introduce a new method, Noise-Augmented Detectability Estimation (NADE), to estimate the impact of site-specific environmental noise on the acoustic detectability of different species. We use vocalisations augmented with noise from the sites themselves to alleviate the need for manual validation of detectability. Our approach produces site- and species-specific estimates of the complex relationship between background noise, vocalisation amplitude, and acoustic detectability when using a machine learning detection model. We evaluate this method using BirdNET on six bird species, in the UK, demonstrating its potential for broader application in acoustic ecology. C_LIO_LIOur results show that there are large differences in the ability of a machine learning model to detect and classify vocalisations across different sites and species. For example: the detectability of loud vocalisations can be 90% at one site and 10% at another; the detectability at a site can be halved during the course of a survey; and that the amplitude of the background noise alone is insufficient to correctly estimate the detectability of a vocalisation. Detectability at a site can also vary considerably by species: a site can have the relatively high detectability for one species but poorer detectability for another. C_LIO_LIBy providing a quantitative measure of how site-specific background noise affects acoustic detectability, NADE could be used to improve the accuracy of species abundance estimates derived from passive acoustic monitoring, helping to identify sites and times where the detectability is likely to be lower. This approach provides a significant step towards making acoustic detectability estimation more feasible, allowing more robust estimates of species abundance and distribution from acoustic data. C_LI

ecology↗

bioRxiv2024

Exploring penetrance of clinically relevant variants in over 800,000 humans from the Genome Aggregation Database

Incomplete penetrance, or absence of disease phenotype in an individual with a disease-associated variant, is a major challenge in variant interpretation. Studying individuals with apparent incomplete penetrance can shed light on underlying drivers of altered phenotype penetrance. Here, we investigate clinically relevant variants from ClinVar in 807,162 individuals from the Genome Aggregation Database (gnomAD), demonstrating improved representation in gnomAD version 4. We then conduct a comprehensive case-by-case assessment of 734 predicted loss of function variants (pLoF) in 77 genes associated with severe, early-onset, highly penetrant haploinsufficient disease. We identified explanations for the presumed lack of disease manifestation in 701 of the variants (95%). Individuals with unexplained lack of disease manifestation in this set of disorders rarely occur, underscoring the need and power of deep case-by-case assessment presented here to minimize false assignments of disease risk, particularly in unaffected individuals with higher rates of secondary properties that result in rescue.

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

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↗

bioRxiv2021

AC2P20 selectively kills M. tuberculosis at acidic pH by depleting free thiols

Mycobacterium tuberculosis (Mtb) senses and adapts to host immune cues as part of its pathogenesis. One environmental cue sensed by Mtb is the acidic pH of its host niche in the macrophage phagosome. Disrupting the ability of Mtb to sense and adapt to acidic pH has the potential to reduce survival of Mtb in macrophages. Previously, a high throughput screen of a [~]220,000 compound small molecule library was conducted to discover chemical probes that inhibit Mtb growth at acidic pH. The screen discovered chemical probes that kill Mtb at pH 5.7 but are inactive at pH 7.0. In this study, AC2P20 was prioritized for continued study to test the hypothesis that it was targeting Mtb pathways associated with pH-driven adaptation. RNAseq transcriptional profiling studies showed AC2P20 modulates expression of genes associated with redox homeostasis. Gene enrichment analysis revealed that the AC2P20 transcriptional profile had significant overlap with a previously characterized pH-selective inhibitor, AC2P36. Like AC2P36, we show that AC2P20 kills Mtb by selectively depleting free thiols at acidic pH. Mass spectrometry studies show the formation of a disulfide bond between AC2P20 and reduced glutathione, supporting a mechanism where AC2P20 is able to deplete intracellular thiols and dysregulate redox homeostasis. The observation of two independent molecules targeting free thiols to kill Mtb at acidic pH further supports that Mtb has restricted redox homeostasis and sensitivity to thiol-oxidative stress at acidic pH.

microbiology↗