Genetic Diversity and Phyletic Evolution of Eleven Chinese Indigenous and Three Commercial Chicken Breeds by mtDNA Sequences
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ABSTRACT Chinese indigenous chicken breeds are geographically widespread, and a total of 116 indigenous chicken breeds are listed as Chinese national genetic resources. However, these indigenous chicken breeds are facing serious challenges as declining population and germplasm degeneration because lots of commercial chicken breeds had been introduced. In this study, the genetic variations of eleven Chinese indigenous chicken breeds of Sichuan province and three commercial chicken breeds were investigated based on the partial mitochondrial DNA D-loop of 487bp in length. 147 individuals from 14 breeds were examined and 34 haplotypes were observed. Genetic diversity analysis showed that the highest haplotype diversity level was found in Dahen Chicken (DH) population, while the Arbor Acres Chicken (WF) and Roman layer (RM) showed lower genetic diversity levels. The long-term artificial selection may lead to reduced nucleotide diversity. Genetic population differentiation analysis indicated that most of the variation (80.80%) was attributed to variations among breeds. Phylogenetic analysis revealed that these individuals were divided into four distinct genetic clades, including cluster A, B, C and D. Eighteen haplotypes were classified as cluster A, eight haplotypes were classified as cluster B, five haplotypes were classified as cluster C and three haplotypes were classified as cluster D. There was no breed-specific clade. Our study firstly identified the population’s genetic structure of Chinese indigenous chickens and the most important commercial breeds in Sichuan province, though the genetic diversity of indigenous breeds did not suffer obvious decrease, but could be helpful for efficient artificial breeding selection and genetic resources conservation.
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Publication Details
DOI
Publisher
SciELO journals
Subfield
Animal Science and Zoology
Field
Agricultural and Biological Sciences
Domain
Life Sciences
Confidence Score
99%
Source
Open Alex