Indian Red Jungle fowl reveals a genetic relationship with South East Asian Red Jungle fowl and Indian native chicken breeds as evidenced through whole mitochondrial genome sequences

Front Genet. 2023 Aug 9:14:1083976. doi: 10.3389/fgene.2023.1083976. eCollection 2023.

Abstract

Background: Native chickens are dispersed in a wide geographical range and have hereditary assets that are kept by farmers for various purposes. Mitochondrial DNA (mtDNA) is a widely utilized marker in molecular studies because of its quick advancement, matrilineal legacy, and simple molecular structure. Method and Results: We performed NGS sequencing to investigate mitochondrial genomes and to evaluate the hereditary connections, diversity, and measure of gene stream estimation in Indian native chicken breeds and Red Jungle fowl. The chicken breeds were genotyped using the D-loop region and 23 haplotypes were identified. When compared to Indian native breeds, more haplotypes were identified in the NADH dehydrogenase subunits, Cytochrome c oxidase, Cytochrome b, ATP synthase subunit 6, and Ribosomal RNA genes. The phylogenetic examination indicated that the analyzed chicken breeds were divided into six significant clades, namely A, B, C, D, E, and F, of which the F clade indicated the domestication of chicken breeds in India. Additionally, our work affirmed that the Indian Red Jungle Fowl is the origin for both reference Red Jungle Fowl as well as all Indian breeds, which is reflected in the dendrogram as well as network analysis based on the whole mtDNA and D-loop region. Indian Red Jungle Fowl is distributed as an outgroup, suggesting that this ancestry was reciprocally monophyletic. Conclusion: The mtDNA sequences of Indian native chickens provided novel insights into adaptation mechanisms and the significance of important mtDNA variations in understanding the maternal lineages of native birds.

Keywords: SNPs; chicken; mitochondrial DNA; molecular phylogeny; mutations and variants; next-generation sequencing.

Grants and funding

The work was funded by the Department of Science and Technology (SERB) (Project No. CRG/2018/002246), the Government of India.