Biology subjects

Garretson, A. C.

Publications and source records attributed to Garretson, A. C..

5 recordsLinked to original sources

bioRxiv2025

Benchmarking Genomic Variant Calling Tools in Inbred Mouse Strains: Recommendations and Considerations

With the growing affordability of whole genome sequencing, variant identification has become an increasingly common task, but there are many challenges due to both technical and biological factors. In recent years, the number of software packages available for variant calling has rapidly increased. Understanding the benefits and drawbacks of different tools is important in setting leading practices and highlighting limitations. These considerations are crucial in model organism research, as many variant calling programs assume outbred genomes and implicit heterozygosity, which may not apply to inbred laboratory models. Here, we present an analysis of variant calling tools and their performance in the simulated genomes of the C57BL/6J inbred laboratory mouse and nine non-reference laboratory strains. Our findings reveal a tradeoff between the recall and precision of tools. Balancing these considerations, we show that an optimal call set is obtained by using an ensemble approach, but specific variant calling recommendations vary by strain and analytical goals. Further, we highlight filters improving the performance of different variant calling tools, both for the discovery of rare variants and in the discovery of strain polymorphisms. In summary, our work provides best practices for calling and filtering genomic variants in inbred organisms, particularly laboratory mice. Article SummaryIdentifying mutations and rare genetic variants is a central task for modern genomics. Many computational tools exist for variant detection, but their performance varies across diverse applications. Further, few variant calling tools have been benchmarked against inbred genomes, which are commonly used for research. To address this, we evaluated five variant calling tools using simulated data from ten diverse inbred mouse strains. We show that variant detection, recall, and precision vary across tools and mouse strains, and that an ensemble approach improves confidence in detected mutations. Our findings offer a set of best practices for variant calling in inbred organisms across diverse analytical applications.

bioinformatics↗

bioRxiv2024

An atlas of conserved transcription factor binding sites reveals the cell type-resolved gene regulatory landscape of flowering plants

Transcription factors (TFs) are proteins that bind DNA to control where and when genes are expressed. In plants, dozens of TF families interact with distinct sets of binding sites (TFBSs) that reflect each TFs role in organismal function and species-specific adaptations. However, defining these roles and understanding broader patterns of regulatory evolution remains challenging, as predicted TFBSs may lack a clear impact on transcription, and experimentally-derived TF binding maps to date are modest in scale or restricted to model organisms. Here, we present a scalable TFBS assay that we leveraged to create an atlas of nearly 3,000 genome-wide binding site maps for 360 TFs in 10 species spanning 150 million years of flowering plant evolution. We find that TF orthologs from distant species retain nearly identical binding preferences, suggesting that regulatory evolution primarily arises from gain and loss of TFBSs. Within lineages however, conserved TFBSs are over-represented and found in regions harboring signatures of functional regulatory elements. Moreover, genes with conserved TFBSs showed a striking enrichment for cell type-specific expression in single-nuclei RNA atlases, providing a robust marker of each TFs activity and developmental role. Finally, we compare distant lineages, illustrating how ancient regulatory modules were recruited and rewired to enable adaptations underlying the evolutionary success of grasses.

genomics↗

bioRxiv2024

Mapping the Global Distribution of Mus musculus: Implications for Evolutionary Genetics

House mice (Mus musculus) are a key biomedical research model and important vectors for disease transmission. In the wild, house mice are also an ecologically disruptive invasive species, and their activity is associated with significant economic and agricultural damage and cost. Despite the importance of house mice across these different contexts, the extent of their geographic distribution is not well understood. House mice are human commensals but are nonetheless sensitive to their prevailing environment, indicating that the range of human settlement cannot be used as a reliable proxy. Existing range maps for Mus musculus are based on minimum convex hulls informed by potentially biased sampling and do not 1) fully integrate large, digitized data documenting species occurrences, 2) provide insight into the likely species distribution in under-sampled regions, and 3) delineate internal structures of the range, including barriers to dispersal or unsuitable internal habitat. Consequently, we know little about the bioclimatic tolerance and environmental envelope occupied by this species. To address these unknowns, we leverage publicly available mouse sampling and biodiversity data to provide an updated range map of Mus musculus and define the environmental limits of the house mouse distribution. Using genetic data from public archives, we also model the genetic diversity of house mice across our newly updated range. Using these data, we visualize global genetic diversity trends and confirm the ancestral origins of Mus musculus to the region of the Indian subcontinent occupied by modern-day Pakistan and northwestern India. Taken together, our efforts highlight areas where house mice are predicted to be at their environmental tolerance limit, including regions where future sampling efforts may uncover mice with unique adaptive traits.

evolutionary biology↗

bioRxiv2023

Fitness effects of breeding strategy: implications for life history trait evolution and mouse husbandry

Reproductive tactics can profoundly influence population reproductive success, but paradoxically, breeding strategy and female reproductive care often vary across a population. The causes and fitness impacts of this variation are not well understood. Using breeding records from the Collaborative Cross mouse population, we evaluate the effects of breeding configuration on reproductive output. Overall, we find that communal breeding in trios leads to higher output and that both trio-breeding and overlapping litters are associated with increased neonatal survival. However, we find significant strain-level variation in optimal breeding strategy and show that the tradeoff between strategies is weakly heritable. We further find that strain reproductive condition influences the ability to support multiple litters and alters the related evolutionary tradeoffs of communal breeding. Together, these findings underscore the role of genetics in regulating alternative reproductive tactics in house mice and emphasize the need to adopt animal husbandry practices tailored to strain backgrounds.

evolutionary biology↗

bioRxiv2022

Networks of Phenological Synchrony Reveal a Highly Interconnected Ecosystem and Potential Vulnerability to Climate-Driven Mismatches

As anthropogenic climate change alters species phenology, phenological shifts may cascade to disrupt species interactions to impact ecosystem functioning. We present a 108-year phenology dataset of 8,840 event dates for 251 phenophases for seven amphibian species, 58 birds, 14 insects, and 163 plant species, including 52 species introduced to New York. The dataset was collected at a single location in the Northeastern United States, providing continuity in monitoring since the early 1900s. We show that linear phenology analyses can underestimate the magnitude of phenological shift relative to circular methods, particularly for species experiencing extreme advancements. However, species phenologies are generally advancing, with faster advancements of insects and amphibians compared to birds and plants. Additionally, in our dataset, species with event dates later in the year are advancing more rapidly than species earlier in the year, and this relationship is stronger for animals than for plants. We present a novel, network-based approach for visualizing community and ecosystem-scale phenological synchrony. Using this approach, we find a high degree of synchrony between the monitored species, and this approach reveals that plants are more central in the phenological network, as well as species with phenological events earlier in the year. While many synchronous species are shifting at relatively similar rates and display similar temperature sensitivities, we highlight two species interactions potentially vulnerable to changing climate: Eastern Tent Caterpillars and Monarchs. Our results illustrate the utility of long-term ecological monitoring for investigating ecosystem responses to climate change and identifying potentially vulnerable phenological networks. Significance StatementThe purpose of this study is to understand how climate change has affected the phenology of an ecological community for over 100+ years. We present a novel approach to analyzing and visualizing community-level phenological data. We find that plants are central to phenological networks, as are species that flower, fruit, or undergo other phenological events earlier in the year. This is important because understanding which species are most central to an ecosystem, as well as which species are vulnerable to climate-driven mismatches (e.g., a butterfly emerges before the flowers that it feeds on bloom) that could cascade through an ecosystem.

ecology↗