Biology subjects

Blake, A.

Publications and source records attributed to Blake, A..

5 recordsLinked to original sources

bioRxiv2023

Scaling use of the rust fungus Puccinia punctiformis for biological control of Canada thistle (Cirsium arvense (L.) Scop.): First report on a U.S. statewide effort

Canada thistle (Cirsium arvense (L.) Scop., CT) is one of the worst weeds threatening temperate regions of the world. A host-specific rust fungus, Puccinia punctiformis (F. Strauss) Rohl., is known to cause systemic disease of CT, ultimately killing individuals and reducing stand densities. In 2013, it was demonstrated that fall inoculation of rosettes with coarsely ground leaves bearing P. punctiformis telia can successfully initiate epiphytotics. In the same year, a cooperative project between the Colorado Department of Agriculture and United States Department of Agriculture was initiated, in which CT patches across the state of Colorado (USA) were inoculated and tracked over subsequent years for changes in stem density. Here, we report our findings from 8 years (2014-2021) of monitoring effort. At most sites (N = 87), CT stem densities declined, from a mean ({+/-} SE) of 87.9 ({+/-} 6.5) stems to 44.7 ({+/-} 4.2). These declines however were spatially-autocorrelated, and likely attributable to local growing conditions, as mean annual daily maximum temperature and standard deviation of elevation, as well as climatic conditions around the times of both treatment and monitoring, were found to be important predictors of CT decline. Further, we observed that the amount of inoculum deployed, timing since last release, and method in which it was spread locally at a site were also associated with the magnitude of CT stem decline. These results are indicative of the value of P. punctiformis as a CT biological control agent. The name Cirsium arvense dieback (CADB) is proposed herein to describe the agriculturally important decline in CT stem densities attributable to this previously un-named systemic disease.

pathology↗

bioRxiv2022

Copepod life history evolution under high and low food regimes

Copepods play a critical role in the carbon cycle of the planet - they mediate the sequestration of carbon into the deep ocean, and are the trophic link between phytoplankton and marine foodwebs. Global change stressors that decrease copepod productivity create the potential for catastrophic positive feedback loops. Accordingly, a growing list of studies examine the evolutionary capacity of copepods to adapt to the two primary stressors associated with global change: warmer temperatures and lower pH. But the evolutionary capacity of copepods to adapt to changing food regimes, the third major stressor associated with global change, remains unknown. We used experimental evolution to explore how a 10-fold difference in food availability affects life history evolution in the copepod, Tisbe sp. over two years, and spanning 30+ generations. Different food regimes evoked evolutionary responses across the entire copepod life history: we observed evolution in body size, size-fecundity relationships and offspring investment strategies. Our results suggest that changes to food regimes reshape life histories and that cryptic evolution in traits such as body size is likely. We demonstrate that evolution in response to changes in ocean productivity will alter consumer life histories, and may distort trophic links in marine foodchains. Evolution in response to changing phytoplankton productivity may alter the efficacy of the global carbon pump in ways that have not been anticipated until now.1

evolutionary biology↗

bioRxiv2022

Integrative single-cell characterization of hypothalamus sex-differential and obesity-associated genes and regulatory elements

Over 500 noncoding genomic loci are associated with obesity. The majority of these loci reside near genes that are expressed in the hypothalamus in specific neuronal subpopulations that regulate food intake, hindering the ability to identify and functionally characterize them. Here, we carried out integrative single-cell analysis (RNA/ATAC-seq) on both mouse and human male and female hypothalamus to characterize genes and regulatory elements in specific cell subpopulations. Utilizing both transcriptome and regulome data, we identify over 30 different neuronal and non-neuronal cell subpopulations and a shared core of transcription factors that regulate cell cluster-specific genes between mice and humans. We characterize several sex-specific differentially expressed genes and the regulatory elements that control them in specific cell subpopulations. Overlapping cell-specific scATAC peaks with obesity-associated GWAS variants, identifies potential obesity-associated regulatory elements. Using reporter assays and CRISPR editing, we show that many of these sequences, including the top obesity-associated loci (FTO and MC4R), are functional enhancers whose activity is altered due to the obesity-associated variant and regulate known obesity genes. Combined, our work provides a catalog of genes and regulatory elements in hypothalamus cell subpopulations and uses obesity to showcase how integrative single-cell sequencing can identify functional variants associated with hypothalamus-related phenotypes.

neuroscience↗

bioRxiv2020

TET2 drives 5hmc marking of GATA6 and epigenetically defines pancreatic ductal adenocarcinoma transcriptional subtypes

Background and AimsPancreatic ductal adenocarcinoma (PDAC) is characterised by advanced disease stage at presentation, aggressive disease biology and resistance to therapy resulting in extremely poor five-year survival <10%. PDAC is classified into transcriptional subtypes with distinct survival characteristics, although how these arise is not known. Epigenetic deregulation, rather than genetics, has been proposed to underpin progression but exactly why is unclear and hindered by analysis of clinical samples. MethodsGenome-wide epigenetic mapping of DNA modifications 5-hydroxymethylcytosine (5mc) and 5-hydroxymethylcytosine (5hmc) using oxidative bisulphite sequencing (oxBS). Bioinformatics using iCluster and mutational profiling to identify overlap with transcriptional signatures in FFPE from resected patients and confirmation in vivo. ResultsWe find that more aggressive squamous-like PDAC subtypes result from epigenetic inactivation of loci including GATA6 that promote differentiated classical-pancreatic subtypes. We show that squamous-like PDAC transcriptional subtypes are associated with greater loss of 5hmc due to reduced expression of the 5mc-hydroxylase TET2. Furthermore, we find that SMAD4 directly supports TET2 levels in the pancreas and classical-pancreatic tumors and loss of SMAD4 expression is associated reduced 5hmc, GATA6 and squamous-like tumors. Importantly, enhancing TET2 stability using Metformin and VitaminC/ascorbic acid (AA) restores 5hmc and GATA6 levels, reverting squamous-like tumor phenotypes and WNT-dependence in vitro and in vivo. ConclusionsWe identify epigenetic deregulation of pancreatic differentiation as an underpinning event behind the emergence of transcriptomic subtypes in PDAC. Our data shows that restoring epigenetic control increases biomarkers of classical-pancreatic tumors and raises the possibility that combination of Vitamin C and Metformin may prolong survival in patients with squamous-like pancreatic cancer.

cancer biology↗

bioRxiv2019

Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning

Image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data. Here we predict consensus molecular subtypes (CMS) of colorectal cancer (CRC) from standard H&E sections using deep learning. Domain adversarial training of a neural classification network was performed using 1,553 tissue sections with comprehensive multi- omic data from three independent datasets. Image-based consensus molecular subtyping (imCMS) accurately classified CRC whole-slide images and preoperative biopsies, spatially resolved intratumoural heterogeneity and provided accurate secondary calls with higher discriminatory power than bioinformatic prediction. In all three cohorts imCMS established sensible classification in CMS unclassified samples, reproduced expected correlations with (epi)genomic alterations and effectively stratified patients into prognostic subgroups. Leveraging artificial intelligence for the development of novel biomarkers extracted from histological slides with molecular and biological interpretability has remarkable potential for clinical translation.

cancer biology↗