Biology subjects

Cabrera, A. A.

Publications and source records attributed to Cabrera, A. A..

9 recordsLinked to original sources

bioRxiv2025

Tracing the drivers of range-wide bowhead whale genomic structure and diversity

Understanding how past environmental and anthropogenic factors shaped contemporary genetic patterns is essential for assessing the vulnerability of species in the face of ongoing climate change. The bowhead whale (Balaena mysticetus) - the only baleen whale found in the Arctic year-round - has a strong association with sea ice, long history of human exploitation, and a circumpolar distribution, making it a valuable model for investigating how these factors have shaped population structure in the marine Arctic. We analysed both nuclear and mitochondrial genomes from bowhead whale individuals sampled across the species circumpolar range, encompassing all four recognized management stocks. Our results reveal three not four genetically differentiated populations: the Sea of Okhotsk stock; the East Greenland-Svalbard-Barents Sea stock; and a combined population containing the Bering-Chukchi-Beaufort Seas and East Canada-West Greenland stocks. We utilised ecological niche modeling and bowhead whale telemetry data to model stock connectivity over the past 11,700 years, and identify past habitat connectivity as a key driver of current population structure. Despite centuries of intensive commercial whaling, the three bowhead whale populations exhibit little-to-no evidence of recent inbreeding and retain high genetic diversity relative to other mammalian species. The lowest genetic diversity, most inbreeding, and highest realised genetic load being in the Sea of Okhotsk population. Collectively, our findings shed light on the recent population history and dynamics of bowhead whales, and offer valuable baseline data on present-day genetic structure and diversity to support effective conservation and management strategies.

evolutionary biology↗

bioRxiv2025

Small molecule bioactivity benchmarks are often well-predicted by counting cells

Phenotypic profiling methods, such as Cell Painting and gene expression, have been widely used to predict compound bioactivity, often showing improvement over predictive models based on chemical structures alone. We discovered that a large subset of assays in widely-used benchmark datasets either directly relate to cell health and cytotoxicity or are assays intending to capture a more specific phenotype but whose active compounds impact cell count, while inactives do not. As a result, counting cells can achieve similar predictive performance as Cell Painting or gene expression data. Filtering benchmarks to include only assays relating to protein targets reveals that Cell Painting can capture information that cannot be predicted by mere cell counting. We re-evaluated three benchmark datasets used with Cell Painting data and observed that, in many cases, cell count models produced an AUC comparable to models using the full Cell Painting profiles. However, in protein-target-specific benchmarks across 17 distinct protein targets, Cell Painting features demonstrated unique predictive power, outperforming mean balanced accuracy from cell count models with a relative improvement of 19.6%. We propose five practical recommendations for benchmarking machine learning models for predicting bioactivity, including using cell count as a baseline feature. Although multi-class classification applications (such as matching samples based on their morphological profile) are less likely to be predictable by cell count than bioactivity benchmarks, these recommendations are broadly applicable to machine learning for drug discovery.

bioinformatics↗

bioRxiv2025

Cell Painting for cytotoxicity and mode-of-action analysis in primary human hepatocytes

High-throughput, human-relevant approaches for predicting chemical toxicity are urgently needed for better decision-making in human health. Here, we apply image-based profiling (the Cell Painting assay) and two cytotoxicity assays (metabolic and membrane damage readouts) to primary human hepatocytes after exposure to eight concentrations of 1085 compounds that include pharmaceuticals, pesticides, and industrial chemicals with known liver toxicity-related outcomes. Three computational methods (CellProfiler, a Cell Painting-specific convolutional neural network, and a pretrained vision transformer) were compared to extract morphology features from single cells or entire images. We used these morphology features to predict activity in the measured cytotoxicity assays, as well as in 412 curated ToxCast assays that span cytotoxicity, cell-based, and cell-free categories. We found that the morphological profiles detect compound bioactivity at lower concentrations than standard cytotoxicity assays. In supervised analyses, they predict cytotoxicity and targeted cell-based assay readouts, but not cell-free assay readouts. We also found that the various feature extraction methods performed relatively similarly and that filtering out non-bioactive or cytotoxic concentrations did not boost supervised assay prediction performance for any assay endpoint category, although it did have a large influence on unsupervised cluster analysis. We envision that image-based profiling could serve as a key component of modern safety assessment.

pharmacology and toxicology↗

bioRxiv2024

Four centuries of commercial whaling eroded 11,000 years of population stability in bowhead whales

The bowhead whale, an Arctic endemic, was heavily overexploited during commercial whaling between the 16th-20th centuries1. Current climate warming, with Arctic amplification of average global temperatures, poses a new threat to the species2. Assessing the vulnerability of bowhead whales to near-future predictions of climate change remains challenging, due to lacking data on population dynamics prior to commercial whaling and responses to past climatic change. Here, we integrate palaeogenomics and stable isotope ({delta}13C and{delta} 15N) analysis of 201 bowhead whale fossils from the Atlantic Arctic with palaeoclimate and ecological modelling based on 823 radiocarbon dated fossils, 151 of which are new to this study. We find long-term resilience of bowhead whales to Holocene environmental perturbations, with no obvious changes in genetic diversity or population structure, despite large environmental shifts and centuries of whaling by Indigenous peoples prior to commercial harvests. Leveraging our empirical data, we simulated a time-series model to quantify population losses associated with commercial whaling. Our results indicate that commercial exploitation induced population subdivision and losses of genetic diversity that are yet to be fully realised; declines in genetic diversity will continue, even without future population size reductions, compromising the species resilience to near-future predictions of Arctic warming.

evolutionary biology↗

bioRxiv2022

Impact of Holocene environmental change on the evolutionary ecology of an Arctic top predator

The Arctic is among the most climatically sensitive environments on Earth, and the disappearance of multiyear sea-ice in the Arctic Ocean is predicted within decades. As apex predators, polar bears are sentinel species for addressing the impact of environmental variability on Arctic marine ecosystems. By integrating genomics, isotopic analysis, morphometrics, and ecological modelling, we investigate how Holocene environmental changes affected the evolutionary ecology of polar bears around Greenland. We show that throughout the last [~]11,000 years, Greenlandic polar bears have been heavily influenced by changes in sea-surface temperature (SST) and sea-ice cover. Most notable are major reductions in effective population size at the beginning of the Holocene and during the Holocene Thermal Maximum [~]6 kya, which coincide with increases in annual mean SST, reduction in sea-ice covers, declines in suitable habitat, and shifts in suitable habitat northwards. Furthermore, we show how individuals sampled from west and east Greenland are genetically, morphologically, and ecologically distinct. We find bears sampled in west Greenland to be larger, more genetically diverse and have diets dominated by ringed seals, whereas bears from east Greenland are smaller and less diverse with more varied diets, putatively driven by regional biotic differences. Taken together, we provide novel insights into the vulnerability of polar bears to environmental change, and how the Arctic marine ecosystem plays a vital role in shaping the evolutionary and ecological trajectories of its inhabitants. TeaserMultivariate investigations of the environments role in the evolutionary ecology of Greenlandic polar bears.

evolutionary biology↗

bioRxiv2021

How low can you go: sex identification from sequencing data of species lacking assembled sex chromosomes

Accurate sex identification is crucial for elucidating the biology of a species. In the absence of directly observable sexual characteristics, sex identification of wild fauna can be challenging, if not impossible. Molecular sexing offers a powerful alternative to morphological sexing approaches. Here, we present SeXY, a novel sex-identification pipeline, for very low-coverage shotgun sequencing data from a single individual. SeXY was designed to utilise low-effort screening data for sex identification and does not require a conspecific sex-chromosome assembly as reference. We assess the accuracy of our pipeline to data quantity by downsampling sequencing data from 100,000 to 1,000 mapped reads, and to reference genome selection by mapping to a variety of reference genomes of various qualities and phylogenetic distance. We show that our method is 100% accurate when mapping to a high-quality (highly contiguous N50 > 30 Mb) conspecific genome, even down to 1,000 mapped reads. For lower-quality reference assemblies (N50 < 30 Mb), our method is 100% accurate with 50,000 mapped reads, regardless of reference assembly quality or phylogenetic distance. The SeXY pipeline provides several advantages over previously implemented methods; SeXY (i) requires sequencing data from only a single individual, (ii) does not require assembled conspecific sex-chromosomes, or even a conspecific reference assembly, (iii) takes into account variation in coverage across the genome, and (iv) is accurate with only 1,000 mapped reads in many cases.

genomics↗

bioRxiv2020

Speciation in the face of gene flow within the toothed whale superfamily Delphinoidea

AO_SCPLOWBSTRACTC_SCPLOWThe importance of post-divergence gene flow in speciation has been documented across a range of taxa in recent years, and may have been especially widespread in highly mobile, wide-ranging marine species, such as cetaceans. Here, we studied individual genomes from nine species across the three families of the toothed whale superfamily Delphinoidea (Delphinidae, Phocoenidae, Monodontidae). To investigate the role of post-divergence gene flow in the speciation process, we used a multifaceted approach, including: (i) phylogenomics, (ii) the distribution of shared derived alleles, and (iii) demographic inference. We found the divergence of lineages within Delphinoidea did not follow a process of pure bifurcation, but was much more complex. Sliding-window phylogenomics reveal a high prevalence of discordant topologies within the superfamily, with further analyses indicating these discordances arose due to both incomplete lineage sorting and gene flow. D-statistics, D-foil, and f-branch analyses supported gene flow between members of Delphinoidea, with the vast majority of gene flow occurring as ancient interfamilial events. Demographic analyses provided evidence that introgressive gene flow has likely ceased between all species pairs tested, despite reports of contemporary interspecific hybrids. Our study provides the first steps towards resolving the large complexity of speciation within Delphinoidea; we reveal the prevalence of ancient interfamilial gene flow events prior to the diversification of each family, and suggests that contemporary hybridisation events may be disadvantageous, as hybrid individuals do not appear to contribute to the parental species gene pools.

evolutionary biology↗

bioRxiv2018

Strong and lasting impacts of past global warming on baleen whale and prey abundance

AbstractThe demography of baleen whales and their prey during the past 30 thousand years was assessed to understand the effects of past rapid global warming on marine ecosystems. Mitochondrial and genome-wide DNA sequence variation in eight baleen whale and seven prey species revealed strong, ocean-wide demographic changes that were correlated with changes in global temperatures and regional oceanographic conditions. In the Southern Ocean baleen whale and prey abundance increased exponentially and in apparent synchrony, whereas changes in abundance varied among species in the more heterogeneous North Atlantic Ocean. The estimated changes in whale abundance correlated with increases in the abundance of prey likely driven by reductions in sea-ice cover and an overall increase in primary production. However, the specific regional oceanographic environment, trophic interactions and species ecology also appeared to play an important role. Somewhat surprisingly the abundance of baleen whales and prey continued to increase for several thousand years after global temperatures stabilized. These findings warn of the potential for dramatic, long-term effects of current climate changes on the marine ecosystem.\n\nOne Sentence SummaryThe effects of past global warming on marine ecosystems were drastic, system-wide and long-lasting.

evolutionary biology↗

bioRxiv2018

Fin whale (Balaenoptera physalus) mitogenomics: A cautionary tale of defining sub-species from mitochondrial sequence monophyly

HighlightsO_LIMitochondrial monophyly is commonly employed to define evolutionary significant units.\nC_LIO_LIMonophyly may be caused by insufficient sampling or a recent common ancestor.\nC_LIO_LIMitogenomic studies are generally based on few samples and prone to sampling issues.\nC_LIO_LIExpanded mitogenome sampling negates previous monophyly in fin whales.\nC_LI\n\nAbstractThe advent of massive parallel sequencing technologies has resulted in an increase of studies based upon complete mitochondrial genome DNA sequences that revisit the taxonomic status within and among species. Spatially distinct monophyly in mitogenomic genealogies, i.e., the sharing of a recent common ancestor among con-specific samples collected in the same region has been viewed as evidence for subspecies. Several recent studies in cetaceans have employed this criterion to suggest subsequent intraspecific taxonomic revisions. We reason that employing intra-specific, spatially distinct monophyly at non-recombining, clonally inherited genomes is an unsatisfactory criterion for defining subspecies based upon theoretical (genetic drift) and practical (sampling effort) arguments. This point is illustrated by a re-analysis of a global mitogenomic assessment of fin whales, Balaenoptera physalus spp., published by Archer et al. (2013) which proposed to further subdivide the Northern Hemisphere fin whale subspecies, B. p. physalus. The proposed revision was based upon the detection of spatially distinct monophyly among North Atlantic and North Pacific fin whales in a genealogy based upon complete mitochondrial genome DNA sequences. The extended analysis conducted in this study (1,676 mitochondrial control region, 162 complete mitochondrial genome DNA sequences and 20 microsatellite loci genotyped in 358 samples) revealed that the apparent monophyly among North Atlantic fin whales reported by Archer et al. (2013) to be due to low sample sizes. In conclusion, defining sub-species from monophyly (i.e., the absence of para-or polyphyly) can lead to erroneous conclusions due to relatively \"trivial\" aspects, such as sampling. Basic population genetic processes (i.e., genetic drift and migration) also affect the time to most recent common ancestor and hence the probability that individuals in a sample are monophyletic.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=195 SRC=\"FIGDIR/small/488130v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (28K):\norg.highwire.dtl.DTLVardef@1e38e54org.highwire.dtl.DTLVardef@9533eborg.highwire.dtl.DTLVardef@183b5b5org.highwire.dtl.DTLVardef@eae09_HPS_FORMAT_FIGEXP M_FIG C_FIG

evolutionary biology↗