Biology subjects

LaPolice, T. M.

Publications and source records attributed to LaPolice, T. M..

5 recordsLinked to original sources

bioRxiv2026

Simulations reveal hybridization in Caribbean Acropora restoration poses low risk of genetic swamping but limited potential for adaptive introgression

Severe global declines in coral populations have driven growing demand for human intervention and restoration. One goal of restoration is to repopulate reef ecosystems through outplanting, which requires detailed understanding of target systems. However, long term ecological and reproductive data from interventions remain scarce. An exception to this are the critically endangered Caribbean corals, Acropora palmata and A. cervicornis, which have been central to restoration efforts in the region. These species serve as a unique case study due to the abundance of published data spanning ecology, and reproductive biology. In the wild, these species can cross to form an F1 hybrid, A. prolifera, though it is rarely used in restoration. It remains unclear whether A. prolifera is an evolutionary dead-end competing with its parents, or a potential bridge enabling genetic exchange via backcrossing. To evaluate benefits and risks of restoration among Caribbean Acropora, we developed a two-dimensional agent-based simulation using reproductive and ecological data to model realistic reef dynamics. Our model suggests the hybrid can facilitate introgression between parentals without outcompeting them. Yet, such introgression is too limited for large-scale or beneficial ancestry transfer except under ecologically unrealistic conditions or timescales significantly longer than those relevant for management. Thus, our model suggests that the risks of genetic swamping may be overstated, whereas hopes for adaptive introgression are also low, underscoring the value of simulations for generating long-term ecological and evolutionary insights relevant to coral restoration.

bioinformatics↗

bioRxiv2024

The European Neolithic Expansion: A Model Revealing Intense Assortative Mating and Restricted Cultural Transmission

The Neolithic revolution initiated a pivotal change in human society, marking the shift from foraging to farming. The underlying mechanisms of agricultural expansion are debated, primarily between cultural diffusion (knowledge and practices transfer) and demic diffusion, or people migration and replacement. Ancient DNA analyses reveal significant ancestry changes during Europes Neolithic transition, suggesting primarily demic expansion. However, the presence of 10-15% hunter-gatherer ancestry in modern Europeans indicates cultural transmission and non-assortative mating were additional contributing factors. We integrate mathematical models, agent-based simulations, and ancient DNA analysis to dissect and quantify the roles of cultural diffusion and assortative mating in farmings expansion. Our findings indicate limited cultural transmission and predominantly within-group mating. Additionally, we challenge the assumption that demic spread always leads to ancestry turnover. This underscores the need to reassess prehistoric cultural expansions and offers new insights into early agricultural society through the integration of ancient DNA with archaeological models.

genomics↗

bioRxiv2023

The Complete Sequence and Comparative Analysis of Ape Sex Chromosomes

Apes possess two sex chromosomes--the male-specific Y and the X shared by males and females. The Y chromosome is crucial for male reproduction, with deletions linked to infertility1. The X chromosome carries genes vital for reproduction and cognition2. Variation in mating patterns and brain function among great apes suggests corresponding differences in their sex chromosomes. However, due to their highly repetitive nature and incomplete reference assemblies, ape sex chromosomes have been challenging to study. Here, using the methodology developed for the telomere-to-telomere (T2T) human genome, we produced gapless assemblies of the X and Y chromosomes for five great apes (chimpanzee, bonobo, gorilla, Bornean and Sumatran orangutans) and a lesser ape, the siamang gibbon. These assemblies allowed us to untangle the intricacies of ape sex chromosome evolution. We found that, compared to the Xs, the ape Ys vary greatly in size and have low alignability and high levels of structural rearrangements. This divergence on the Y arises from the accumulation of lineage-specific ampliconic regions, palindromes, transposable elements, and satellites. Our analysis of Y chromosome genes revealed expansions of multi-copy gene families and signatures of purifying selection. Thus, the Y exhibits dynamic evolution, while the X is more stable. Mapping short-read sequencing data to these assemblies revealed diversity and selection patterns on sex chromosomes of >100 great ape individuals. These reference assemblies are expected to inform human evolution and conservation genetics of nonhuman apes, all of which are endangered species.

genomics↗

bioRxiv2021

A deep learning framework for predicting human essential genes from population and functional genomic data

Being able to predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve our ability to identify genes associated with genetic disorders. Numerous computational methods have recently been developed to predict human essential genes from population genomic data; however, the existing methods have limited power in pinpointing short essential genes due to the sparsity of polymorphisms in the human genome. Here we present an evolution-based deep learning model, DeepLOF, which integrates population and functional genomic data to improve gene essentiality prediction. Compared to previous methods, DeepLOF shows unmatched performance in predicting ClinGen haploinsufficient genes, mouse essential genes, and essential genes in human cell lines. Furthermore, DeepLOF discovers 109 potentially essential genes that are too short to be identified by previous methods. Altogether, DeepLOF is a powerful computational method to aid in the discovery of essential genes.

bioinformatics↗

bioRxiv2020

Signal, bias, and the role of transcriptome assembly quality in phylogenomic inference

The empirical details of whole transcriptome sequencing and assembly have been thoroughly evaluated, but few studies have addressed how user-defined aspects of the assembly process may influence performance in phylogenomic analyses. Errors in transcriptome assembly could affect ortholog prediction, alignment quality, and phylogenetic signal. Here we investigate the impacts of transcriptome assembly quality in phylogenomic studies by constructing phylogenomic data matrices from alternative transcriptome assemblies representing high-quality and intentionally low-quality assembly outcomes. We leveraged a well-resolved topology for craniates to apply a topological constraint to our analyses, providing a way to quantify phylogenetic signal. Craniates are amply represented in publicly available raw RNA-seq repositories, allowing us to control for transcriptome tissue type as well. By studying the performance of phylogenomic datasets derived from these alternative high- and low-quality inputs in a controlled experiment, we show that high-quality transcriptomes produce richer phylogenomic datasets with partitions that have lower alignment ambiguity, less compositional bias, and stronger phylogenetic signal than low-quality transcriptome assemblies. Our findings demonstrate the importance of transcriptome assembly in phylogenomic analyses and suggest that a portion of the uncertainty observed in phylogenomic studies could be alleviated at the assembly stage.

systems biology↗