Hahn, J. | bioRxiv Science

bioRxiv2020

Sperm migration in the genital tract - in silico experiments identify key factors for reproductive success

Sperm migration in the female genital tract controls sperm selection and, therefore, reproductive success as male gametes are conditioned for fertilization while their number is dramatically reduced. Mechanisms underlying sperm migration are mostly unknown, since in vivo investigations are mostly unfeasible for ethical or practical reasons. By presenting a spatio-temporal model of the mammalian female genital tract combined with agent-based description of sperm motion and interaction as well as parameterizing it with bovine data, we offer an alternative possibility for studying sperm migration in silico. The model incorporates genital tract geometry as well as biophysical principles of sperm motion observed in vitro such as positive rheotaxis and thigmotaxis. This model for sperm migration from vagina to oviducts was successfully tested against in vivo data from literature. We found that physical sperm characteristics such as velocity and directional stability as well as sperm-fluid interactions and wall alignment are critical for success, i.e. sperms reaching the oviducts. Therefore, we propose that these identified sperm parameters should be considered in detail for conditioning sperm in artificial selection procedures since the natural processes are normally bypassed in reproductive in vitro technologies. The tremendous impact of mucus flow to support sperm accumulation in the oviduct highlights the importance of a species-specific optimum time window for artificial insemination regarding ovulation. Predictions from our extendable in silico experimental system will improve assisted reproduction in humans, endangered species, and livestock.

biophysics↗

bioRxiv2020

Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

BackgroundGenome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To better understand etiological pathways that might lead to discovery of new treatments or prevention strategies, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome while also exploring associations with common variants. Methods and ResultsUsing samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR=1.80, 95% confidence interval: 1.43, 2.27; P=7.12 x 10-7). Three common variants, rs9349379 in PHACTR1, and rs1333048 and rs4977574 in the 9p21 region, were significantly associated with prevalent CHD. Four common variants (rs4977574, rs10757278, rs1333049, and rs1333048) within the 9p21 locus were significantly associated with incident MI. We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) [≥] 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. ConclusionThis study confirmed previously reported loci influencing heart disease risk, and one single variant and three genes associated with MI and CHD were newly identified and warrant future investigation.

genetics↗