Biology subjects

Buckley, M.

Publications and source records attributed to Buckley, M..

3 recordsLinked to original sources

bioRxiv2018

Intact extrastriate visual network without primary visual cortex in a Rhesus macaque with naturally occurring Blindsight

Lesions of primate primary visual cortex (V1) lead to loss of conscious visual perception, and are often devastating to those affected. Understanding the neural consequences of such damage may aid the development of rehabilitation methods. In this rare case of a Rhesus macaque (monkey S), likely born without V1, we investigated the brain structures underlying residual visual abilities using multimodal magnetic resonance imaging. In-group behaviour was unremarkable. Compared to controls, visual structures outside of monkey Ss lesion appeared normal. Visual stimulation under anaesthesia with checkerboards activated lateral geniculate nucleus of monkey S, but not the pulvinar, while full-field moving dots activated the pulvinar. Functional connectivity analysis revealed a network of bilateral dorsal visual areas temporally correlated with V5/MT, consistent across lesion and control animals. Overall, we found an intact network of visual cortical areas even without V1, but little evidence for strengthened subcortical input to V5/MT supporting residual visual function.

neuroscience↗

bioRxiv2018

Cryptic Promoter Activation Drives POU5F1 (OCT4) Expression in Renal Cell Carcinoma

Transcriptional dysregulation drives cancer formation but the underlying mechanisms are still poorly understood. As a model system, we used renal cell carcinoma (RCC), the most common malignant kidney tumor which canonically activates the hypoxia-inducible transcription factor (HIF) pathway. We performed genome-wide chromatin accessibility and transcriptome profiling on paired tumor/normal samples and found that numerous transcription factors with a RCC-selective expression pattern also demonstrated evidence of HIF binding in the vicinity of their gene body. Some of these transcription factors influenced the tumors regulatory landscape, notably the stem cell transcription factor POU5F1 (OCT4). Unexpectedly, we discovered a HIF-pathway-responsive cryptic promoter embedded within a human-specific retroviral repeat element that drives POU5F1 expression in RCC via a novel transcript. Elevat POU5F1 expression levels were correlated with advanced tumor stage and poorer overall survival in RCC patients. Thus, integrated transcriptomic and epigenomic analysis of even a small number of primary patient samples revealed remarkably convergent shared regulatory landscapes and a novel mechanism for dysregulated expression of POU5F1 in RCC.

cancer biology↗

bioRxiv2017

An Integrative Framework For Detecting Structural Variations In Cancer Genomes

Structural variants can contribute to oncogenesis through a variety of mechanisms, yet, despite their importance, the identification of structural variants in cancer genomes remains challenging. Here, we present an integrative framework for comprehensively identifying structural variation in cancer genomes. For the first time, we apply next-generation optical mapping, high-throughput chromosome conformation capture (Hi-C), and whole genome sequencing to systematically detect SVs in a variety of cancer cells.\n\nUsing this approach, we identify and characterize structural variants in up to 29 commonly used normal and cancer cell lines. We find that each method has unique strengths in identifying different classes of structural variants and at different scales, suggesting that integrative approaches are likely the only way to comprehensively identify structural variants in the genome. Studying the impact of the structural variants in cancer cell lines, we identify widespread structural variation events affecting the functions of non-coding sequences in the genome, including the deletion of distal regulatory sequences, alteration of DNA replication timing, and the creation of novel 3D chromatin structural domains.\n\nThese results underscore the importance of comprehensive structural variant identification and indicate that non-coding structural variation may be an underappreciated mutational process in cancer genomes.

genomics↗