Dataset Information

Evaluation of Genetic Diversity and Structure of Turkish Water Buffalo Population by Using 20 Microsatellite Markers.

ABSTRACT: The present study was aimed to investigate the genetic diversity among 17 Turkish water buffalo populations. A total of 837 individuals from 17 provincial populations were genotyped, using 20 microsatellites markers. The microsatellite markers analyzed were highly polymorphic with a mean number of alleles of (7.28) ranging from 6 (ILSTS005) to 17 (ETH003). The mean observed and expected heterozygosity values across all polymorphic loci in all studied buffalo populations were 0.61 and 0.70, respectively. Observed heterozygosity varied from 0.55 (Bursa (BUR)) to 0.70 (Muş (MUS)). It was lower than expected heterozygosity in most of the populations indicating a deviation from Hardy-Weinberg equilibrium. The overall value for the polymorphic information content of noted microsatellite loci was 0.655, indicating their suitability for genetic diversity analysis in buffalo. The mean F_IS value was 0.091 and all loci were observed significantly deviated from Hardy-Weinberg Equilibrium (HWE), most likely based on non-random breeding. The 17 buffalo populations were genetically less diverse as indicated by a small mean F_ST value (0.032 ± 0.018). The analysis of molecular variance (AMOVA) analysis indicated that about 2% of the total genetic diversity was clarified by population distinctions and 88 percent corresponded to differences among individuals. The information produced by this study can be used to establish a base of national conservation and breeding strategy of water buffalo population in Turkey.

SUBMITTER: Unal EO

PROVIDER: S-EPMC8070036 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundIn Ethiopia, livestock contributes 45% of agricultural GDP. Despite the economic role played by the sector, there have been little efforts to genetically improve the indigenous cattle. Morphological characterization of selected Ethiopian indigenous cattle has been made for (Bonga, Jimma, and Kerayu) cattle types. But, the selected indigenous cattle were not characterized at molecular level (genetic diversity information). Hence, this work was initiated to detect and determine the genetic diversity and population structure of selected Ethiopian indigenous cattle ecotypes using microsatellite markers.ResultsDifferent alleles were identified (131) and thirty-three of these alleles were unique to specific ecotypes. All loci used were informative with PIC values ranging from 0.5 (TGLA126) to 0.84 (ETH10) with a mean of 0.70 per locus. The Shannon information index ranged from (I = 1.02) ILST006 to (I = 1.63) ETH10 with an average of 1.28 revealing there is genetic diversity. Moreover, analysis of molecular variance (AMOVA) revealed 84% genetic variation within a population and 13% variation among populations. The value of F-statistics (Fst) (0.129 = 13%) indicated that there was moderate genetic differentiation among ecotypes. The (UPGMA) revealed, Bonga and Jimma clustered together while Kerayu cattle were relatively distinct, Principal coordinates analysis (PCOA) and structure analysis grouped the individual into different clusters confirming the presence of ecotype admixture due to geographical origins and uncontrolled mating.ConclusionIn general, this study has successfully characterized the genetic diversity and population structure of Bonga, Jimma, and Kerayu cattle ecotypes using high polymorphic/informative microsatellite markers. According to this study, Kerayu cattle have high AR and PA when compared to Bonga and Jimma cattle populations. So, the Kerayu population is more diverse than others and it is the hotspot for genetic diversity study. The generated information is very relevant for breeder and genetic conservation.

Dataset Information

Evaluation of Genetic Diversity and Structure of Turkish Water Buffalo Population by Using 20 Microsatellite Markers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets