Evidence map›Paper›PMID 40033180›Full record

ArticleBMC genomics2025

Dissecting genomes of multiple yak populations: unveiling ancestry and high-altitude adaptation through whole-genome resequencing analysis.

Sheikh Firdous Ahmad, Munish Gangwar, Amit Kumar, Amod Kumar, Mahesh Shivanand Dige, Girish Kumar Jha, Gyanendra Kumar Gaur, Triveni Dutt

Abstract read
In one paragraph

Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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  8. Whole-genome sequencing of Tahe red deer (Frontiers in veterinary science · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sheikh Firdous Ahmad *ICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243 122, India. firdousa61@gmail.com.
Munish Gangwar *ICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243 122, India.
Amit KumarICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243 122, India. vetamitchandan07@gmail.com.
Amod KumarICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana, 132 001, India.
Mahesh Shivanand DigeICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana, 132 001, India.
Girish Kumar JhaICAR-Indian Agricultural Statistics Research Institute, Pusa, New Delhi, 110 012, India.
Gyanendra Kumar GaurICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243 122, India.
Triveni DuttICAR-Indian Veterinary Research Institute, Uttar Pradesh, Izatnagar, Bareilly, 243 122, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study was undertaken to elucidate the population structure and differentiation of Indian yak from Chinese and wild cohorts on genome-wide scale by identifying the selection sweeps and genomic basis of their adaptation across different comparisons while analyzing whole genome sequencing (WGS) data using latest bioinformatics tools. The study included 105 individuals from three distinct yak populations i.e., Indian yak (n = 29); Chinese yak (n = 61) and wild yak (n = 15), hypothesized to be related along the evolutionary timescale. Efficient variant calling and quality control in GATK and PLINK programs resulted in around 1 million (1,002,970) high-quality (LD-independent) SNPs with an average genotyping rate of 96.55%. The PCA, ADMIXTURE and TREEMIX analysis revealed stratification of the yak groups into three distinct clusters. The empirical distribution pattern of minor allele frequency (MAF) of SNPs on genome-wide scale was also elucidated for three yak cohorts revealing unique distribution across five different bins. The selection signature analysis revealed candidate genes that are important for the adaptation of Indian yak against harsh environmental conditions in their habitats. Under iHS analysis, several genes were identified to be under selection pressure in Indian yak including ABCA12, EXOC1, JUNB, KLF1, PRDX2, NANOS3, RFX1, RFX2, and CACNG7. On the other hand, across population analysis revealed the genes like NR2F2, OSBPL10, CIDEC, WFIKKN2, ADCY, THSD7A, ADGRB3, TRPC1, VASH2, and ABHD5 to be part of selective sweeps under these comparisons. A total of 53 genes were found common between intra- and inter-population selection signature analysis of Indian yak. Notably, the genes harbouring the SNPs under selection pressure were significant for adaptation traits including lipidogenesis, energy metabolism, thermogenesis, hair follicle formation, oxidation-reduction reactions, hypoxia and reproduction. These genes may be evaluated as candidate genes for livestock adaptation to harsh environmental conditions and to further the research and application in the present era of climate change.

Indexed as

Adaptation, PhysiologicalAltitudeWhole Genome SequencingAnimalsCattleGene FrequencyGenetics, PopulationGenomeGenomicsPolymorphism, Single NucleotideSelection, GeneticAdaptationMAFPopulation structureSelection signatureWGSYak

Identifiers

PMID40033180
PMCPMC11877770

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.