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McLean, E.

Publications and source records attributed to McLean, E..

2 recordsLinked to original sources

Genome-wide analysis of somatic non-coding mutation patterns and mitochondrial heteroplasmy in type B1 and B2 thymomas

IntroductionType B1 and B2 thymomas are lymphocyte-rich malignant tumors with few somatic mutations in protein-coding regions of the nuclear genome; nonetheless, non-coding regions remain uncharacterized. Here, we developed a rigorous tumor isolation method from lymphocyte-rich thymoma tissues and identified somatic mutations in non-coding and mitochondrial DNA. MethodsCD205+CD45- pure tumor cells were isolated from fresh-frozen tissues using DEPArray system. Deep whole-genome sequencing was performed, and recurrent somatic alterations in coding, non-coding, and mitochondria regions were systemically identified by computational framework. The mutations were classified according to gene function, cis-regulatory element, and mutational signature. ResultsThe total number of somatic mutations was approximately 80 times higher in non-coding regions than in coding regions in type B1-2 thymomas (1,671.3 vs. 21.1 per case). Coding mutations were identified in epigenetic regulators, DNA repair genes, and some other genes. Nevertheless, 40% of cases exhibited fewer than four mutations in coding regions. A systematic non-coding analysis identified a total of 405.0 mutations per case on cis-regulatory elements, and detected six recurrent mutations: one interferon regulatory factor (IRF8), two E3 ubiquitin ligases (UBR2 and RNF213), and three intergenic regions. Mitochondrial heteroplasmy was observed in 90% of cases, with a significant proportion of mutations located in D-loop region. The single-base substitution pattern was signature 12. ConclusionsNumerous non-coding mutations and mitochondrial heteroplasmy were detected in type B1 and B2 thymomas. Given the paucity of coding mutations observed in this disease entity, disruption of the non-coding landscape and mitochondrial heteroplasmic shift may be the primary cause of thymoma.

genomics↗

Comparing proportional and ordinal dominance ranks reveals multiple competitive landscapes in an animal society

Across group-living animals, linear dominance hierarchies lead to disparities in access to resources, health outcomes, and reproductive performance. Studies of how dominance rank affects these outcomes typically employ one of several dominance rank metrics without examining the assumptions each metric makes about its underlying competitive processes. Here we compare the ability of two dominance rank metrics--ordinal rank and proportional or standardized rank--to predict 20 distinct traits in a well-studied wild baboon population in Amboseli, Kenya. We propose that ordinal rank best predicts outcomes when competition is density-dependent, while proportional rank best predicts outcomes when competition is density-independent. We found that for 75% (15/20) of the traits, one of the two rank metrics performed better than the other. Strikingly, all male traits were better predicted by ordinal than by proportional rank, while female traits were evenly split between being better predicted by proportional or ordinal rank. Hence, male and female traits are shaped by different competitive regimes: males competitive environments are largely driven by density-dependent resource access (e.g., access to estrus females), while females competitive environments are shaped by both density-independent resource access (e.g. distributed food resources) and density-dependent resource access. However, traits related to competition for social and mating partners are an exception to this sex-biased pattern: these traits were better predicted by ordinal rank than by proportional rank for both sexes. We argue that this method of comparing how different rank metrics predict traits of interest can be used as a way to distinguish between different competitive processes operating in animal societies.

animal behavior and cognition↗