Two strongly linked blocks within the KIF16B gene significantly influence wool length and greasy yield in fine wool sheep (Ovis aries)

BACKGROUND A previous genome-wide association study (GWAS) identified the kinesin family member 16B (KIF16B) as a candidate gene related to sheep wool production. In this work, DNA pool sequencing and SNPscanTM high-throughput genotyping methods were used to detect single-nucleotide polymor phisms (SNPs) in the sheep KIF16B gene. The correlations between the SNPs and wool length and greasy wool yield were systematically assessed. RESULTS Forty-five SNPs were identified and 37 of them were genotyped, including 10 exon mutations, 26 intron mutations, and 1 promoter region mutation. Most of the SNPs were of medium genetic diversity and at Hardy-Weinberg equilibrium (HWE). Among them, 10 SNPs were associated with greasy wool yield and 28 SNPs impact the wool length. Five specific SNPs were found to exert significant effects on the wool length in all body parts analyzed in this study. Furthermore, linkage disequilibrium (LD) analysis was conducted among SNP loci and they were found to be significantly associated with economically important traits. Two strongly linked SNP blocks were identified within these SNPs and they might exert significant impacts on the greasy wool yield and wool length. CONCLUSIONS The identified SNPs exert significant effects on wool production and could be considered as potential DNA markers for selecting the individuals with superior phenotypes

Plasma Targeted Metabolomics Analysis for Amino Acids and Acylcarnitines in Patients with Prediabetes, Type 2 Diabetes Mellitus, and Diabetic Vascular Complications

Background@#We hypothesized that specific amino acids or acylcarnitines would have benefits for the differential diagnosis of diabetes. Thus, a targeted metabolomics for amino acids and acylcarnitines in patients with diabetes and its complications was carried out. @*Methods@#A cohort of 54 normal individuals and 156 patients with type 2 diabetes mellitus and/or diabetic complications enrolled from the First Affiliated Hospital of Jinzhou Medical University was studied. The subjects were divided into five main groups: normal individuals, impaired fasting glucose, overt diabetes, diabetic microvascular complications, and diabetic peripheral vascular disease. The technique of tandem mass spectrometry was applied to obtain the plasma metabolite profiles. Metabolomics multivariate statistics were applied for the metabolic data analysis and the differential metabolites determination. @*Results@#A total of 10 cross-comparisons within diabetes and its complications were designed to explore the differential metabolites. The results demonstrated that eight comparisons existed and yielded significant metabolic differences. A total number of 24 differential metabolites were determined from six selected comparisons, including up-regulated amino acids, down-regulated medium-chain and long-chain acylcarnitines. Altered differential metabolites provided six panels of biomarkers, which were helpful in distinguishing diabetic patients. @*Conclusion@#Our results demonstrated that the biomarker panels consisted of specific amino acids and acylcarnitines which could reflect the metabolic variations among the different stages of diabetes and might be useful for the differential diagnosis of prediabetes, overt diabetes and diabetic complications.

Plasma Targeted Metabolomics Analysis for Amino Acids and Acylcarnitines in Patients with Prediabetes, Type 2 Diabetes Mellitus, and Diabetic Vascular Complications

Background@#We hypothesized that specific amino acids or acylcarnitines would have benefits for the differential diagnosis of diabetes. Thus, a targeted metabolomics for amino acids and acylcarnitines in patients with diabetes and its complications was carried out. @*Methods@#A cohort of 54 normal individuals and 156 patients with type 2 diabetes mellitus and/or diabetic complications enrolled from the First Affiliated Hospital of Jinzhou Medical University was studied. The subjects were divided into five main groups: normal individuals, impaired fasting glucose, overt diabetes, diabetic microvascular complications, and diabetic peripheral vascular disease. The technique of tandem mass spectrometry was applied to obtain the plasma metabolite profiles. Metabolomics multivariate statistics were applied for the metabolic data analysis and the differential metabolites determination. @*Results@#A total of 10 cross-comparisons within diabetes and its complications were designed to explore the differential metabolites. The results demonstrated that eight comparisons existed and yielded significant metabolic differences. A total number of 24 differential metabolites were determined from six selected comparisons, including up-regulated amino acids, down-regulated medium-chain and long-chain acylcarnitines. Altered differential metabolites provided six panels of biomarkers, which were helpful in distinguishing diabetic patients. @*Conclusion@#Our results demonstrated that the biomarker panels consisted of specific amino acids and acylcarnitines which could reflect the metabolic variations among the different stages of diabetes and might be useful for the differential diagnosis of prediabetes, overt diabetes and diabetic complications.