Biology subjects

Yen, K.

Publications and source records attributed to Yen, K..

3 recordsLinked to original sources

bioRxiv2026

Nuclear Mitochondrial Interaction Test Reveals Sex-Dependent Mitochondrial SNPs Interacting with Klotho Variants on Diabetes Risk

ContextThe environmental or other genetic factors might influence the effect of Klotho (KL) on glucose metabolism. ObjectiveWe investigated mitochondrial genetic variants that interact with KL single nucleotide polymorphisms (SNPs) to modulate diabetes risk. MethodsWe used the data from 7,047 non-Hispanic white participants of the Health and Retirement Study, a prospective observational study including adults aged 50 years and older from the United States. First, we performed single gene-wide association scans to identify KL SNPs associated with diabetes. Next, we performed a nuclear-by-mitochondrial interaction test (NuMIT) in which we use an identified KL SNP from the gene-wide scan to evaluate potential interactions with 85 mitochondrial SNPs in relation to diabetes. ResultsWe failed to identify a significant association between diabetes and the KL SNP in our single gene-wide association test. However, we identified a novel variant (KL rs9563121) which showed a trend of increasing klotho mRNA levels with each additional minor allele. A NuMIT analysis identified mitochondrial SNPs, which showed significant interactions with rs9563121 in relation to diabetes risk. MitoG15929A showed significant interactions with rs9563121 in both men and women. MitoG15929A diminished the potential beneficial effect of KL rs9563121 on diabetes risk in women. Among men with the MitoG15929A variant, KL rs9563121 was associated with higher prevalence of diabetes. ConclusionThe NuMIT approach revealed significant interactions between mitochondrial and nuclear DNA variants of KL. Furthermore, MitoG15929A may have a role in the interaction between diabetes and KL in a sex-dependent manner.

genetics↗

bioRxiv2023

SEM: sized-based expectation maximization for characterizing nucleosome positions and subtypes

Genome-wide nucleosome profiles are predominantly characterized using MNase-seq, which involves extensive MNase digestion and size selection to enrich for mono-nucleosome-sized fragments. Most available MNase-seq analysis packages assume that nucleosomes uniformly protect 147bp DNA fragments. However, some nucleosomes with atypical histone or chemical compositions protect shorter lengths of DNA. The rigid assumptions imposed by current nucleosome analysis packages ignore variation in nucleosome lengths, potentially blinding investigators to regulatory roles played by atypical nucleosomes. To enable the characterization of different nucleosome types from MNase-seq data, we introduce the Size-based Expectation Maximization (SEM) nucleosome calling package. SEM employs a hierarchical Gaussian mixture model to estimate the positions and subtype identity of nucleosomes from MNase-seq fragments. Nucleosome subtypes are automatically identified based on the distribution of protected DNA fragment lengths at nucleosome positions. Benchmark analysis indicates that SEM is on par with existing packages in terms of standard nucleosome-calling accuracy metrics, while uniquely providing the ability to characterize nucleosome subtype identities. Using SEM on a low-dose MNase H2B MNase-ChIP-seq dataset from mouse embryonic stem cells, we identified three nucleosome types: short-fragment nucleosomes, canonical nucleosomes, and dinucleosomes. The short-fragment nucleosomes can be divided further into two subtypes based on their chromatin accessibility. Interestingly, the subset of short-fragment nucleosomes in accessible regions exhibit high MNase sensitivity and display distribution patterns around transcription start sites (TSSs) and CTCF peaks, similar to the previously reported "fragile nucleosomes". These SEM-defined accessible short-fragment nucleosomes are found not just in promoters, but also in enhancers and other regulatory regions. Additional investigations reveal their co-localization with the chromatin remodelers Chd6, Chd8, and Ep400. In summary, SEM provides an effective platform for distinguishing various nucleosome subtypes, paving the way for future exploration of non-standard nucleosomes.

bioinformatics↗

bioRxiv2019

A Pro-Diabetogenic mtDNA Polymorphism in the Mitochondrial-Derived Peptide, MOTS-c

Type 2 Diabetes (T2D) is an emerging public health problem in Asia. An Asian mitochondrial DNA variation m.1382A>C (rs111033358) leads to a K14Q amino acid replacement in MOTS-c, an insulin sensitizing mitochondrial-derived peptide. Meta-analysis of three cohorts (n=27,527, J-MICC, MEC, and TMM) showed that males but not females with the C-allele exhibit a higher prevalence of T2D. Furthermore, in J-MICC, only males with the C-allele in the lowest tertile of physical activity increased their prevalence of T2D, demonstrating a kinesio-genomic interaction. High-fat fed, male mice injected with MOTS-c showed reduced weight and improved glucose tolerance, but not K14Q-MOTS-c treated mice. Like the human data, female mice were unaffected. Mechanistically, K14Q-MOTS-c leads to diminished insulin-sensitization in vitro. Thus, the m.1382A>C polymorphism is associated with susceptibility to T2D in men, possibly interacting with exercise, and contributing to the risk of T2D in sedentary males by reducing the activity of MOTS-c.

genetics↗