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Updated: Jul 3, 2025

Genotyping Single Nucleotide Polymorphisms in the Mitochondrial Genome by Pyrosequencing
Published on: February 10, 2023
Mitochondrial DNA D-Loop Polymorphisms among the Galla Goats Reveals Multiple Maternal Origins with Implication on
Ednah M Masila1,2, Stephen O Ogada1, Irene N Ogali2
1Institute for Biotechnology Research, Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000-00200, Juja, Kenya.
Abstract:
Despite much attention given to the history of goat evolution in Kenya, information on the origin, demographic history, dispersal route, and genetic diversity of Galla goats remains unclear. Here, we examined the genetic background, diversity, demographic history, and population genetic variation of Galla goats using mtDNA D-loop and HSP70 single-nucleotide polymorphism markers. The results revealed 90 segregating sites and 68 haplotypes in a 600-bp mtDNA D-loop sequence. The overall mean mitochondrial haplotype diversity was 0.993. The haplotype diversities ranged between 0.8939 ± 0.0777 and 1.0000 ± 0.0221 in all populations supporting high genetic diversity. Mitochondrial phylogenetic analysis revealed three Galla goat haplogroups (A, G, and D), supporting multiple maternal ancestries, of which haplogroup A was the most predominant. Analysis of molecular variance (AMOVA) showed considerable variation within populations at 94.39%, evidence of high genetic diversity. Bimodal mismatch distribution patterns were observed while most populations recorded negative results for Tajima and Fu's Fs neutrality tests supporting population expansion. Genetic variation among populations was also confirmed using HSP70 gene fragment sequences, where six polymorphic sites which defined 21 haplotypes were discovered. Analysis of molecular variance revealed a significant FST index value of 0.134 and a high FIS index value of 0.746, an indication of inbreeding. This information will pave the way for conservation strategies and informed breeding to improve Galla or other goat breeds for climate-smart agriculture.
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