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Whalley, C.

Publications and source records attributed to Whalley, C..

3 recordsLinked to original sources

The miR-430 locus with extreme promoter density is a transcription body organizer, which facilitates long range regulation in zygotic genome activation

In anamniote embryos the major wave of zygotic genome activation (ZGA) starts during the mid-blastula transition. This major wave of ZGA is facilitated by several mechanisms, including dilution of repressive maternal factors and accumulation of activating transcription factors during the fast cell division cycles preceding the mid-blastula transition. However, a set of genes escape global genome repression and are activated substantially earlier, during what is called, the minor wave of genome activation. While the mechanisms underlying the major wave of genome activation have been studied extensively, the minor wave of genome activation is little understood. In zebrafish the earliest expressed RNA polymerase II (Pol II) transcribed genes are activated in a pair of large transcription bodies depleted of chromatin, abundant in elongating Pol II and nascent RNAs (Hadzhiev et al., 2019; Hilbert et al., 2021). This transcription body includes the miR-430 gene cluster required for maternal mRNA clearance. Here we explored the genomic, chromatin organisation and cis-regulatory mechanisms of the minor wave of genome activation occurring in the transcription body. By long read genome sequencing we identified a remarkable cluster of miR-430 genes with over 300 promoters and spanning 0.6 Mb, which represent the highest promoter density of the genome. We demonstrate that the miR-430 gene cluster is required for the formation of the transcription body and acts as a transcription organiser for minor wave activation of a set of zinc finger genes scattered on the same chromosome arm, which share promoter features with the miR-430 cluster. These promoter features are shared among minor wave genes overall and include the TATA-box and sharp transcription start site profile. Single copy miR-430 promoter transgene reporter experiments indicate the importance of promoter-autonomous mechanisms regulating escape from global repression of the early embryo. These results together suggest that formation of the transcription body in the early embryo is the result of high promoter density coupled to a minor wave-specific core promoter code for transcribing key minor wave ZGA genes, which are required for the overhaul of the transcriptome during early embryonic development.

developmental biology↗

Germline loss-of-function variants in the base-excision repair gene MBD4 cause a Mendelian recessive syndrome of adenomatous colorectal polyposis and acute myeloid leukaemia

Inherited defects in base-excision repair (BER) predispose to adenomatous polyposis and colorectal cancer (CRC), yet our understanding of this important DNA repair pathway remains incomplete. By combining detailed clinical, histological and molecular profiling, we reveal biallelic germline loss-of-function (LOF) variants in the BER gene MBD4 to predispose to adenomatous polyposis and -uniquely amongst CRC predisposition syndromes- to myeloid neoplasms. Neoplasms from MBD4-deficient patients almost exclusively accumulate somatic CpG>TpG mutations, resembling mutational signature SBS1. MBD4-deficient adenomas harbour mutations in known CRC driver genes, although AMER1 mutations were more common and KRAS mutations less frequent. We did not find an increased risk for colorectal tumours in individuals with a monoallelic MBD4 LOF variant. We suggest that this condition should be termed MBD4-associated neoplasia syndrome (MANS) and that MBD4 is included in testing for the genetic diagnosis of polyposis and/or early-onset AML.

genetics↗

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↗