Polymorphism detection of DGAT1 and Lep genes in Anatolian water buffalo (Bubalus bubalis) populations in Turkey.

Acyl-CoA: diacylglycerol-acyltransferase 1 (DGAT1) enzyme plays a key role in controlling the synthesis rate triglyceride from diacylglycerol. Leptin (LP, OB, obese) is an important hormone that synthesizes mostly from adipose tissue and regulates glucose metabolism and homeostasis. DGAT1 and Lep genes are closely related to reproduction, growth, milk yield and composition in water buffalo breeds. This study aimed to identify genetic variation in the DGAT1 and Lep gene regions in 150 water buffalo individuals from five different provinces of Turkey using DNA sequencing. A total of 38 nucleotide variations and indels have identified 761 bp long partial intron 2 and exon 3 and 5 ' UTR regions of the Lep gene in Anatolian water buffalo populations; 422 bp long partial exon 7-9 and exon 8 regions of DGAT1 gene were amplified and two mutations were defined in the point of 155 and 275 nucleotide that is three genotypes for S allele and Y allele of DGAT1 gene in intron 7 in Anatolian buffalo populations, respectively. These SNPs may have an effect on reproduction, growth, milk yield and composition in water buffalo populations and may prove to be useful for water buffalo breeding.

Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPs.

BACKGROUND: With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and FST) to select the most informative SNPs for ancestry inference. RESULTS: Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% ± 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. CONCLUSIONS: The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees.

Genetic Characterization of Native Donkey (Equus asinus) Populations of Turkey Using Microsatellite Markers.

This study presents the first insights to the genetic diversity and structure of the Turkish donkey populations. The primary objectives were to detect the main structural features of Turkish donkeys by microsatellite markers. A panel of 17 microsatellite markers was applied for genotyping 314 donkeys from 16 locations of Turkey. One hundred and forty-two alleles were identified and the number of alleles per locus ranged from 4 to 12. The highest number of alleles was observed in AHT05 (12) and the lowest in ASB02 and HTG06 (4), while ASB17 was monomorphic. The mean HO in the Turkish donkey was estimated to be 0.677, while mean HE was 0.675. The polymorphic information content (PIC) was calculated for each locus and ranged from 0.36 (locus ASB02) to 0.98 (locus AHT05), which has the highest number of alleles per locus in the present study. The average PIC in our populations was 0.696. The average coefficient of gene differentiation (GST) over the 17 loci was 0.020 ± 0.037 (p < 0.01). The GST values for single loci ranged from -0.004 for LEX54 to 0.162 for COR082. Nei's gene diversity index (Ht) for loci ranged from 0.445 (ASB02) to 0.890 (AHT05), with an average of 0.696. A Bayesian clustering method, the Structure software, was used for clustering algorithms of multi-locus genotypes to identify the population structure and the pattern of admixture within the populations. When the number of ancestral populations varied from K = 1 to 20, the largest change in the log of the likelihood function (K) was when K = 2. The results for K = 2 indicate a clear separation between Clade I (KIR, CAT, KAR, MAR, SAN) and Clade II (MAL, MER, TOK, KAS, KUT, KON, ISP, ANT, MUG, AYD and KAH) populations.