Population structure and selection signal analysis of indigenous sheep from the southern edge of the Taklamakan Desert.

Analyzing the genetic diversity and selection characteristics of sheep (Ovis aries) holds significant value in understanding their environmental adaptability, enhancing breeding efficiency, and achieving effective conservation and rational utilization of genetic resources. In this study, we utilized Illumina Ovine SNP 50 K BeadChip data from four indigenous sheep breeds from the southern margin of the Taklamakan Desert (Duolang sheep: n = 36, Hetian sheep: n = 74, Kunlun sheep: n = 27, Qira black sheep: n = 178) and three foreign meat sheep breeds (Poll Dorset sheep: n = 105, Suffolk sheep: n = 153, Texel sheep: n = 150) to investigate the population structure, genetic diversity, and genomic signals of positive selection within the indigenous sheep. According to the Principal component analysis (PCA), the Neighbor-Joining tree (NJ tree), and Admixture, we revealed distinct clustering patterns of these seven sheep breeds based on their geographical distribution. Then used Cross Population Extended Haplotype Homozygosity (XP-EHH), Fixation Index (FST), and Integrated Haplotype Score (iHS), we identified a collective set of 32 overlapping genes under positive selection across four indigenous sheep breeds. These genes are associated with wool follicle development and wool traits, desert environmental adaptability, disease resistance, reproduction, and high-altitude adaptability. This study reveals the population structure and genomic selection characteristics in the extreme desert environments of native sheep breeds from the southern edge of the Taklimakan Desert, providing new insights into the conservation and sustainable use of indigenous sheep genetic resources in extreme environments. Additionally, these findings offer valuable genetic resources for sheep and other mammals to adapt to global climate change.

Skin characterization of diabetes mellitus revealed by polarization-sensitive optical coherence tomography imaging.

Significance: Diabetes can lead to the glycation of proteins and dysfunction of skin collagen. Skin lesions are a prevalent clinical symptom of diabetes mellitus (DM). Early diagnosis and assessing the efficacy of treatment for DM are crucial for patient health management. However, performing a non-invasive skin assessment in the early stages of DM is challenging. Aim: By using the polarization-sensitive optical coherent tomography (PS-OCT) imaging technique, it is possible to noninvasively assess the skin changes caused by diabetes. Approach: The PS-OCT was used to monitor the polarization characteristics of mouse skin at different stages of diabetes. Results: Based on a multi-layered adhesive tape model, we found that the polarization characteristics (retardation, optic axis, and polarization uniformity) were sensitive to the microstructure changes in the samples. Through this method, we observed significant changes in the polarization states of the skin as diabetes progressed. This was in line with the detected microstructure changes in skin collagen fibers using scanning electron microscopy. Conclusions: This study presents a highly useful approach for non-invasive skin assessment of diabetes.