Biology subjects

Makova, K.

Publications and source records attributed to Makova, K..

3 recordsLinked to original sources

bioRxiv2017

Infant Weight Gain Trajectories Linked To Oral Microbiome Composition

Gut and oral microbiome perturbations have been observed in obese adults and adolescents. Less is known about how weight gain in early childhood is influenced by gut, and particularly oral, microbiomes. Here we analyze the relationships among weight gain and gut and oral microbiomes in 226 two-year-olds who were followed during the first two years of life, as part of a larger study, with weight and length measured at seven time points. We used these data to identify children with rapid weight gain (a strong risk factor for childhood obesity), and to derive growth curves with novel Functional Data Analysis (FDA) techniques. The childrens oral and gut microbiomes were sampled at the end of the two-year period, and surveyed with 16S sequencing. First, we show that growth curves are associated negatively with diversity and positively with Firmicutes-to-Bacteroidetes ratio of the oral microbiome - a relationship that is also observed in children with rapid (vs. non-rapid) weight gain. We also demonstrate an association between the gut microbiome and child growth, but only when considering the effect of diet on the microbiome. Lastly, we identify several bacterial genera that are associated with child growth patterns. These results suggest that by the age of two, the oral microbiome may have already begun to establish patterns often seen in older obese individuals. They also suggest that the gut microbiome, while strongly influenced by diet, at age two does not harbor obesity signatures many researchers identified in later life stages.

genomics↗

bioRxiv2017

A population phylogenetic view of mitochondrial heteroplasmy

The mitochondrion has recently emerged as an active player in a myriad of cellular processes. Additionally, it was recently shown that more than 200 diseases are known to be linked to variants in mitochondrial DNA or in nuclear genes interacting with mitochondria. This has reinvigorated interest in its biology and population genetics. Mitochondrial heteroplasmy, or genotypic variation of mitochondria within an individual, is now understood to be common in humans and important in human health. However, it is still not possible to make quantitative predictions about the inheritance of heteroplasmy and its proliferation within the body, partly due to the lack of an appropriate model. Here, we present a population-genetic framework for modeling mitochondrial heteroplasmy as a process that occurs on an ontogenetic phylogeny, with genetic drift and mutation changing heteroplasmy frequencies during the various developmental processes represented in the phylogeny. Using this framework, we develop a Bayesian inference method for inferring rates of mitochondrial genetic drift and mutation at different stages of human life. Applying the method to previously published heteroplasmy frequency data, we demonstrate a severe effective germline bottleneck comprised of the cumulative genetic drift occurring between the divergence of germline and somatic cells in the mother and the separation of germ layers in the offspring. Additionally, we find that the two somatic tissues we analyze here undergo tissue-specific bottlenecks during embryogenesis, less severe than the effective germline bottleneck, and that these somatic tissues experience little additional genetic drift during adulthood. We conclude with a discussion of possible extensions of the ontogenetic phylogeny framework and its possible applications to other ontogenetic processes in addition to mitochondrial heteroplasmy.

genomics↗

bioRxiv2017

RecoverY : K-mer based read classification for Y-chromosome specific sequencing and assembly

MotivationThe haploid mammalian Y chromosome is usually under-represented in genome assemblies due to high repeat content and low depth due to its haploid nature. One strategy to ameliorate the low coverage of Y sequences is to experimentally enrich Y-specific material before assembly. Since the enrichment process is imperfect, algorithms are needed to identify putative Y-specific reads prior to downstream assembly. A strategy that uses k-mer abundances to identify such reads was used to assemble the gorilla Y (Tomaszkiewicz et al 2016). However, the strategy required the manual setting of key parameters, a time-consuming process leading to sub-optimal assemblies.\n\nResultsWe develop a method, RecoverY, that selects Y-specific reads by automatically choosing the abundance level at which a k-mer is deemed to originate from the Y. This algorithm uses prior knowledge about the Y chromosome of a related species or known Y transcript sequences. We evaluate RecoverY on both simulated and real data, for human and gorilla, and investigate its robustness to important parameters. We show that RecoverY leads to a vastly superior assembly compared to alternate strategies of filtering the reads or contigs. Compared to the preliminary strategy used in Tomaszkiewicz et al (2016), we achieve a 33% improvement in assembly size and a 20% improvement in the NG50, demonstrating the power of automatic parameter selection.\n\nAvailabilityOur tool RecoverY is freely available at https://github.com/makovalab-psu/RecoverY\n\nContactkmakova@bx.psu.edu, pashadag@cse.psu.edu\n\nSupplementary informationAttached as an additional file.

bioinformatics↗