Browsing by Subject "Animal Genetics and Genomics"

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    Open Access
    Fat mass and obesity associated (FTO) gene influences skeletal muscle phenotypes in non-resistance trained males and elite rugby playing position
    (2017) Heffernan, S M; Stebbings, G K; Kilduff, L P; Erskine, R M; Day, S H; Morse, C I; McPhee, J S; Cook, C J; Vance, B; Ribbans, W J; Raleigh, S M; Roberts, C; Bennett, M A; Wang, G; Collins, M; Pitsiladis, Y P; Williams, A G
    Abstract Background FTO gene variants have been associated with obesity phenotypes in sedentary and obese populations, but rarely with skeletal muscle and elite athlete phenotypes. Methods In 1089 participants, comprising 530 elite rugby athletes and 559 non-athletes, DNA was collected and genotyped for the FTO rs9939609 variant using real-time PCR. In a subgroup of non-resistance trained individuals (NT; n = 120), we also assessed structural and functional skeletal muscle phenotypes using dual energy x-ray absorptiometry, ultrasound and isokinetic dynamometry. In a subgroup of rugby athletes (n = 77), we assessed muscle power during a countermovement jump. Results In NT, TT genotype and T allele carriers had greater total body (4.8% and 4.1%) and total appendicular lean mass (LM; 3.0% and 2.1%) compared to AA genotype, with greater arm LM (0.8%) in T allele carriers and leg LM (2.1%) for TT, compared to AA genotype. Furthermore, the T allele was more common (94%) in selected elite rugby union athletes (back three and centre players) who are most reliant on LM rather than total body mass for success, compared to other rugby athletes (82%; P = 0.01, OR = 3.34) and controls (84%; P = 0.03, OR = 2.88). Accordingly, these athletes had greater peak power relative to body mass than other rugby athletes (14%; P = 2 x 10 -6 ). Conclusion Collectively, these results suggest that the T allele is associated with increased LM and elite athletic success. This has implications for athletic populations, as well as conditions characterised by low LM such as sarcopenia and cachexia.
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    Open Access
    The within-host population dynamics of Mycobacterium tuberculosis vary with treatment efficacy
    (2017) Trauner, Andrej; Liu, Qingyun; Via, Laura E; Liu, Xin; Ruan, Xianglin; Liang, Lili; Shi, Huimin; Chen, Ying; Wang, Ziling; Liang, Ruixia; Zhang, Wei; Wei, Wang; Gao, Jingcai; Sun, Gang; Brites, Daniela; England, Kathleen; Zhang, Guolong; Gagneux, Sébastien; Barry, Clifton E; Gao, Qian
    BACKGROUND: Combination therapy is one of the most effective tools for limiting the emergence of drug resistance in pathogens. Despite the widespread adoption of combination therapy across diseases, drug resistance rates continue to rise, leading to failing treatment regimens. The mechanisms underlying treatment failure are well studied, but the processes governing successful combination therapy are poorly understood. We address this question by studying the population dynamics of Mycobacterium tuberculosis within tuberculosis patients undergoing treatment with different combinations of antibiotics. RESULTS: By combining very deep whole genome sequencing (~1000-fold genome-wide coverage) with sequential sputum sampling, we were able to detect transient genetic diversity driven by the apparently continuous turnover of minor alleles, which could serve as the source of drug-resistant bacteria. However, we report that treatment efficacy has a clear impact on the population dynamics: sufficient drug pressure bears a clear signature of purifying selection leading to apparent genetic stability. In contrast, M. tuberculosis populations subject to less drug pressure show markedly different dynamics, including cases of acquisition of additional drug resistance. CONCLUSIONS: Our findings show that for a pathogen like M. tuberculosis, which is well adapted to the human host, purifying selection constrains the evolutionary trajectory to resistance in effectively treated individuals. Nonetheless, we also report a continuous turnover of minor variants, which could give rise to the emergence of drug resistance in cases of drug pressure weakening. Monitoring bacterial population dynamics could therefore provide an informative metric for assessing the efficacy of novel drug combinations.