Location Of Genomic Regions Research Articles

Characterization of genomic regions escaping epigenetic reprogramming in sheep.

The mammalian genome undergoes two global epigenetic reprogramming events during the establishment of primordial germ cells and in the pre-implantation embryo after fertilization. These events involve the erasure and re-establishment of DNA methylation marks. However, imprinted genes and transposable elements (TEs) maintain their DNA methylation signatures to ensure normal embryonic development and genome stability. Despite extensive research in mice and humans, there is limited knowledge regarding environmentally induced epigenetic marks that escape epigenetic reprogramming in other species. Therefore, the objective of this study was to examine the characteristics and locations of genomic regions that evade epigenetic reprogramming in sheep, as well as to explore the biological functions of the genes within these regions. In a previous study, we identified 107 transgenerationally inherited differentially methylated cytosines (DMCs) in the F1 and F2 generations in response to a paternal methionine-supplemented diet. These DMCs were found in TEs, non-repetitive regions, and imprinted and non-imprinted genes. Our findings suggest that genomic regions, rather than TEs and imprinted genes, have the propensity to escape reprogramming and serve as potential candidates for transgenerational epigenetic inheritance. Notably, 34 transgenerational methylated genes influenced by paternal nutrition escaped reprogramming, impacting growth, development, male fertility, cardiac disorders, and neurodevelopment. Intriguingly, among these genes, 21 have been associated with neural development and brain disorders, such as autism, schizophrenia, bipolar disease, and intellectual disability. This suggests a potential genetic overlap between brain and infertility disorders. Overall, our study supports the concept of transgenerational epigenetic inheritance of environmentally induced marks in mammals.

Effects of Temperature on the Meiotic Recombination Landscape of the Yeast Saccharomyces cerevisiae.

ABSTRACTAlthough meiosis in warm-blooded organisms takes place in a narrow temperature range, meiosis in many organisms occurs over a wide variety of temperatures. We analyzed the properties of meiosis in the yeast Saccharomyces cerevisiae in cells sporulated at 14°C, 30°C, or 37°C. Using comparative-genomic-hybridization microarrays, we examined the distribution of Spo11-generated meiosis-specific double-stranded DNA breaks throughout the genome. Although there were between 300 and 400 regions of the genome with high levels of recombination (hot spots) observed at each temperature, only about 20% of these hot spots were found to have occurred independently of the temperature. In S. cerevisiae, regions near the telomeres and centromeres tend to have low levels of meiotic recombination. This tendency was observed in cells sporulated at 14°C and 30°C, but not at 37°C. Thus, the temperature of sporulation in yeast affects some global property of chromosome structure relevant to meiotic recombination. Using single-nucleotide polymorphism (SNP)-specific whole-genome microarrays, we also examined crossovers and their associated gene conversion events as well as gene conversion events that were unassociated with crossovers in all four spores of tetrads obtained by sporulation of diploids at 14°C, 30°C, or 37°C. Although tetrads from cells sporulated at 30°C had slightly (20%) more crossovers than those derived from cells sporulated at the other two temperatures, spore viability was good at all three temperatures. Thus, despite temperature-induced variation in the genetic maps, yeast cells produce viable haploid products at a wide variety of sporulation temperatures.

Detection and localization of a single binary trait locus in experimental populations.

The advancements made in molecular technology coupled with statistical methodology have led to the successful detection and location of genomic regions (quantitative trait loci; QTL) associated with quantitative traits. Binary traits (e.g. susceptibility/resistance), while not quantitative in nature, are equally important for the purpose of detecting and locating significant associations with genomic regions. Existing interval regression methods used in binary trait analysis are adapted from quantitative trait analysis and the tests for regression coefficients are tests of effect, not detection. Additionally, estimates of recombination that fail to take into account varying penetrance perform poorly when penetrance is incomplete. In this work a complete probability model for binary trait data is developed allowing for unbiased estimation of both penetrance and recombination between a genetic marker locus and a binary trait locus for backcross and F2 experimental designs. The regression model is reparameterized allowing for tests of detection. Extensive simulations were conducted to assess the performance of estimation and testing in the proposed parameterization. The proposed parameterization was compared with interval regression via simulation. The results indicate that our parameterization shows equivalent estimation capabilities, requires less computational effort and works well with only a single marker.