Biology subjects

Menzies, A.

Publications and source records attributed to Menzies, A..

3 recordsLinked to original sources

bioRxiv2020

The mutational landscape of human somatic and germline cells

During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

genomics↗

bioRxiv2020

Phylogenetic reconstruction of myeloproliferative neoplasm reveals very early origins and lifelong evolution

Mutations in cancer-associated genes drive tumour outgrowth. However, the timing of driver mutations and dynamics of clonal expansion that lead to human cancers are largely unknown. We used 448,553 somatic mutations from whole-genome sequencing of 843 clonal haematopoietic colonies to reconstruct the phylogeny of haematopoiesis, from embryogenesis to clinical disease, in 10 patients with myeloproliferative neoplasms which are blood cancers more common in older age. JAK2V617F, the pathognomonic mutation in these cancers, was acquired in utero or childhood, with upper estimates of age of acquisition ranging between 4.1 months and 11.4 years across 5 patients. DNMT3A mutations, which are associated with age-related clonal haematopoiesis, were also acquired in utero or childhood, by 7.9 weeks of gestation to 7.8 years across 4 patients. Subsequent driver mutation acquisition was separated by decades. The mean latency between JAK2V617F acquisition and clinical presentation was 31 years (range 12-54 years). Rates of clonal expansion varied substantially (<10% to >200% expansion/year), were affected by additional driver mutations, and predicted latency to clinical presentation. Driver mutations and rates of expansion would have been detectable in blood one to four decades before clinical presentation. This study reveals how driver mutation acquisition very early in life with life-long growth and evolution drive adult blood cancer, providing opportunities for early detection and intervention, and a new paradigm for cancer development.

cancer biology↗

bioRxiv2017

bcGST - an interactive bias-correction method to identify over-represented gene-sets in boutique arrays

Motivation: Gene annotation and pathway databases such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes are important tools in Gene Set Test (GST) that describe gene biological functions and associated pathways. GST aims to establish an association relationship between a gene set of interest and an annotation. Importantly, GST tests for over-representation of genes in an annotation term. One implicit assumption of GST is that the gene expression platform captures the complete or a very large proportion of the genome. However, this assumption is neither satisfied for the increasingly popular boutique array nor the custom designed gene expression profiling platform. Specifically, conventional GST is no longer appropriate due to the gene set selection bias induced during the construction of these platforms.\n\nResults: We propose bcGST, a bias-corrected Gene Set Test by introducing bias correction terms in the contingency table needed for calculating the Fishers Exact Test (FET). The adjustment method works by estimating the proportion of genes captured on the array with respect to the genome in order to assist filtration of annotation terms that would otherwise be falsely included or excluded. We illustrate the practicality of bcGST and its stability through multiple differential gene expression analyses in melanoma and TCGA cancer studies.\n\nAvailability: The bcGST method is made available as a Shiny web application at http://shiny.maths.usyd.edu.au/bcGST/\n\nContact: kevin.wang@sydney.edu.au

bioinformatics↗