Biology subjects

Wray, J.

Publications and source records attributed to Wray, J..

5 recordsLinked to original sources

bioRxiv2026

Dynamics of the B-Cell gene regulatory network in differentiation determine evolutionary trajectories of childhood leukaemogenesis

B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) is the most frequent paediatric malignancy. Despite extensive molecular and cellular characterization a mechanistic model of leukaemogenesis has not yet been developed. Here we present a multi-valued logical model of B-cell differentiation, centred on a core pentad of transcription factors whose dysregulation results in the developmental arrest characteristic of BCP-ALL. Whilst B-cell maturation follows a fixed and sequential differentiation process, leukaemic transformation is driven by stochastic genetic insults. Integrating BCR-ABL1 as the initiating event, we model alternative evolutionary trajectories by introducing secondary mutations at different time points within synchronous simulations. We demonstrate that the combination, order and timing of secondary mutations dictate maturation arrest points and fitness, explaining how different patterns of mutations seen in patients may arise and in turn influence disease severity. This platform provides a generalisable framework to model driver mutations in their developmental context to predict evolutionary trajectories in cancer.

cancer biology↗

bioRxiv2026

Breath to genome: Whole genome sequencing of large whales from blow sampling

Preserving biodiversity requires the genetic monitoring of wild populations, but traditional invasive sampling techniques can impact animal welfare. For cetaceans, a promising non-invasive approach is the collection of exhaled respiratory vapour, or blow, to generate individual genetic profiles. Here, we demonstrate the feasibility of generating whole genomes from the blow of humpback whales with data of sufficient quality for population genomics. A total of 58 blow samples from 26 Northeast Pacific humpback whales (Megaptera novaeangliae) were collected in Gitgaat First Nation territory using a commercially available drone. The high endogenous content at 84% on average allowed us to generate low-coverage nuclear genomes (mean 2.3x, range 0.2x-3.5x) and high coverage mitochondrial genomes (mean 94x, range 7.7x-151.3x) for inference of population structure, diversity and phylogenomics. The reliability of the blow-derived genomes was demonstrated by direct comparison between replicate blow samples, as well as paired tissue samples from a subset of individuals.

genomics↗

bioRxiv2024

The diffusion of cooperative and solo bubble net feeding in Canadian Pacific humpback whales

Cooperative foraging, a mutualistic resource acquisition behaviour observed across diverse taxa, can drive social network structure, as it typically involves high rates of interactions between individuals. Understanding the mechanisms and distribution of such behaviours is important to elucidate the drivers of social organisation. Bubble net feeding ( bubble netting) is a specialised foraging technique practised by certain humpback whale (Megaptera novaeangliae) populations globally. Over 20 years of study in the northern Canadian Pacific, we observed the diffusion of two morphs of this behaviour: social cooperative and independent, or solo, bubble netting. Network-based diffusion analyses - a tool developed to test for social learning - find strong evidence for the social learning of bubble netting when a static social network is used, even after accounting for individual-level traits such as site fidelity and sex (10.6 x103 to 35.4x103 times more support for social versus asocial learning; p < 0.0001). However, we could not completely exclude homophily due to the inherent sociality of this cooperative foraging behaviour. Nonetheless, it is clear that the rapid diffusion of bubble netting throughout this population has significant consequences for its social structure, which should be information considered by those planning the conservation of this threatened population.

animal behavior and cognition↗

bioRxiv2020

Social survival: humpback whales (Megaptera novaeangliae) use social structure to partition ecological niches within proposed critical habitat

Animal culture and social bonds are relevant to wildlife conservation because they influence patterns of geography, behavior, and strategies of survival. Numerous examples of socially-driven habitat partitioning and ecological-niche specialization can be found among vertebrates, including toothed whales. But such social-ecological dynamics, described here as social niche partitioning, are not known among baleen whales, whose societies -- particularly on foraging grounds -- are largely perceived as unstructured and incidental to matters of habitat use and conservation. However, through 16 years of behavioral and photo-identification observations of humpback whales (Megaptera novaeangliae) feeding within a fjord system in British Columbia, Canada, we have documented long-term pair bonds (lasting up to 12 years) as well as a complex societal structure, which corresponds closely to persistent patterns in feeding strategy, long-term site fidelity (extended seasonal occupancy and annual rate of return up to 75%), specific geographic preferences within the fjord system, and other forms of habitat use. Randomization tests of network congruency and clustering algorithms were used to test for overlap in patterns of social structure and habitat use, which confirmed the occurrence of social niche partitioning on the feeding grounds of this baleen whale. In addition, we document the extensive practice of group bubble net feeding in Pacific Canada. This coordinated feeding behavior was found to strongly mediate the social structure and habitat use within this humpback whale society. Additionally, during our 2004 - 2019 study, we observed a shift in social network structure in 2010 - 2012, which corresponded with environmental and demographic shifts including a sudden decline in the populations calving rate. Our findings indicate that the social lives of humpback whales, and perhaps baleen whales generally, are more complex than previously supposed and should be a primary consideration in the assessment of potential impacts to important habitat.

animal behavior and cognition↗

bioRxiv2018

Measuring rank robustness in scored protein interaction networks

BackgroundProtein interaction databases often provide confidence scores for each recorded interaction based on the available experimental evidence. Protein interaction networks (PINs) are then built by thresholding on these scores, so that only interactions of sufficiently high quality are included. These networks are used to identify biologically relevant motifs or nodes using metrics such as degree or betweenness centrality. This type of analysis can be sensitive to the choice of threshold. If a node metric is to be useful for extracting biological signal, it should induce similar node rankings across PINs obtained at different reasonable confidence score thresholds.\n\nResultsWe propose three measures--rank continuity, identifiability, and instability--to evaluate how robust a node metric is to changes in the score threshold. We apply our measures to twenty-five metrics and identify four as the most robust: the number of edges in the step-1 ego network, as well as the leave-one-out differences in average redundancy, average number of edges in the step-1 ego network, and natural connectivity. Our measures show good agreement across PINs from different species and data sources. Analysis of synthetically generated scored networks shows that robustness results are context-specific, and depend both on network topology and on how scores are placed across network edges.\n\nConclusionDue to the uncertainty associated with protein interaction detection, and therefore network structure, for PIN analysis to be reproducible, it should yield similar results across different confidence score thresholds. We demonstrate that while certain node metrics are robust with respect to threshold choice, this is not always the case. Promisingly, our results suggest that there are some metrics that are robust across networks constructed from different databases, and different scoring procedures.

bioinformatics↗