Identification and diversity of Y-chromosome haplotypes in Qinghai yak populations.

The aim of the present study was to perform a preliminary analysis of the characterization and diversity of Y-chromosome haplotypes/haplogroups in yak of Qinghai Province, China. A total of 322 male yaks from nine populations belonging to three officially recognized breeds (Gaoyuan, Huanhu and Datong) were sampled. Animals were genotyped using six previously reported Y-SNPs present in the SRY, USP9Y, UTY, AMELY and OFD1Y genes and four new Y-SNPs in the OFD1Y gene (g.569A>C, g.578A>C, g.608G>T and g.653G>C) identified in this study. Seven Y-chromosome haplotypes (H1-H7) were identified according to the combination of the 10 Y-SNPs. H1, H2 and H6 were the most common and shared haplotypes across all yak populations/breeds. Private haplotypes H3 and H7 were detected in the Datong breed; H4 in Guoleimude, Qumalai, Qilian, Tianjun and Ganglong populations; and H5 in Qumalai of Gaoyuan breed. Haplotype clustering and network analyses inferred two haplogroups, Y1 and Y2, indicating two divergent lineages of paternal origins of Qinghai yak. The analysis of molecular variance showed a significant difference among individuals (P < 0.0001) with more than 93% of the total genetic variation present within populations, suggesting a weak genetic structure among Qinghai yak populations. The overall Y-haplotype diversity was 0.538 ± 0.028, showing a relatively high diversity in Qinghai yak. The Gaoyuan and Datong breeds had similar haplotype diversities (0.547 ± 0.030 and 0.553 ± 0.083, respectively), which were higher than that of the Huanhu breed (0.441 ± 0.098). Our results support the conservation and sustainable use of unique yak genetic resources in Qinghai.

[Statistical parametric mapping analysis of 18F-FDG PET in Parkinson's disease with mild cognitive impairment].

Objective: To investigate the characteristics of cerebral metabolism associated with mild cognitive impairment (MCI) Parkinson's disease (PD), cognitive normal PD and normal control to find a PET biomarker for the diagnose and estimate of PD-MCI. Methods: Forty-seven patients diagnosed with PD (included 15 with mild cognitive impairment) and 20 control subjects were enrolled. All the subjects were evaluated with FDG-PET and clinical scale. The statistical parametric mapping (SPM) were analyzed to determine metabolic patterns that may be useful in differentiating between the three groups. Results: SPM analysis showed that significant hypometabolism were observed in both side of front lobe, parietal lobe, left temporal lobe and left occipital lobe; in the contrast, the relative hypermetabolism had been observed in the cerebellum, vermis, hippocampus and supplement motor area (SMA) in patients with PD-MCI. PD without MCI showed hypometabolism in both side of front lob, caudate and putamen. PD-MCI showed that the significant hypermetabolism were in the insular and cerebellum while hypometabolism were in the both side of occipital compared to PD without MCI. Conclusion: A voxel-by-voxel based SPM method i. e. SPM8 analysis by PET scan is an effective way to analysis the FDG uptake pattern of PD patients. The hypermetabolism in the insula and cerebellum and hypometabolism in the both side of occipital may be a biomarker for make a diagnosis of PD-MCI.