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<p>The domestic water buffalo (<i>Bubalus bubalis</i>) plays a vital role in Indian agriculture, contributing significantly to milk production and draught power. Despite their economic importance, breed differentiation and clustering of Indian buffalo breeds remain underexplored. This study aimed to identify Ancestry Informative Markers (AIMs) and to compare their effectiveness against genome wide markers (GWMs) for breed differentiation task in six Indian buffalo using ddRAD sequencing approach.&#xa0;A total of 96 buffalo samples representing six Indian breeds (Murrah, Surti, Bhadawari, Pandharpuri, Mehsana, and Toda) were genotyped using ddRAD sequencing, generating 237,762 SNPs. Quality control filtering retained SNPs with &gt; 95% call rate and individuals with &lt; 10% missing genotypes, yielding 232,463 high-quality SNPs. AIMs were selected using combined criteria including Delta, F<sub>ST</sub>, and Informativeness of Assignment. Population structure was analyzed through Principal Component Analysis (PCA) and Admixture, with comparative performance evaluated using Bayesian hierarchical modeling with LOO cross-validation and WAIC scores. Selection signatures were detected using normalized haplotype-based iHS statistics implemented in Selscan software.&#xa0;Principal component analysis (PCA) and Admixture results indicated incomplete breed differentiation using GWMs. However, a subset of the top 2000 AIMs, effectively resolved breed-specific clusters, hence these AIMs can be designated as "Breed Informative Markers". Bayesian hierarchical modeling demonstrated that AIMs provided superior ancestry estimates compared to GWMs, as indicated by less negative leave-one-out (LOO) cross-validation and widely applicable information criterion (WAIC) scores. Haplotype-based selection signatures based on AIMs revealed breed-specific genomic regions under selection and we nomenclature them as "Ancestry Informative Selection Signatures (AISS)". Notably, the&#xa0;Carbonic Anhydrase II (<i>CA2</i>),&#xa0;Splicing Factor 3B Subunit 4 (<i>SF3B4</i>), and&#xa0;Fc Receptor Like 5 (<i>FCRL5</i>)&#xa0;genes in Murrah were linked to acid–base balance, pre-mRNA splicing, and innate immunity, respectively. The&#xa0;RNA-binding Raly-like protein (<i>RALYL</i>)&#xa0;gene in Mehsana was associated with disease resistance and thermoregulation, while the SET Domain Containing 3&#xa0;(<i>SETD3</i>)&#xa0;gene in Toda buffalo contributed to muscle development, enhancing its draught capabilities. This study represents the first comprehensive effort to develop AIM and AISS panel for buffalo breed differentiation, paving the way for cost-effective and precise genetic assessments.</p>

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Ancestry informative selection signature model enhanced breed discrimination in Indian Buffaloes

  • 期刊论文

  • 发表日期：

    2025年12月26日

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  • Rangasai Chandra Goli,
  • Kiyevi G. Chishi,
  • Oguru Sai Sruthi,
  • Karan Mahar,
  • Tanuj Gunturu,
  • Muralidhar Metta,
  • Amit Kumar,
  • Soumen Naskar,
  • Nidhi Sukhija,
  • Kanaka Krishnamurthy Kareningappa

摘要

The domestic water buffalo (Bubalus bubalis) plays a vital role in Indian agriculture, contributing significantly to milk production and draught power. Despite their economic importance, breed differentiation and clustering of Indian buffalo breeds remain underexplored. This study aimed to identify Ancestry Informative Markers (AIMs) and to compare their effectiveness against genome wide markers (GWMs) for breed differentiation task in six Indian buffalo using ddRAD sequencing approach. A total of 96 buffalo samples representing six Indian breeds (Murrah, Surti, Bhadawari, Pandharpuri, Mehsana, and Toda) were genotyped using ddRAD sequencing, generating 237,762 SNPs. Quality control filtering retained SNPs with > 95% call rate and individuals with < 10% missing genotypes, yielding 232,463 high-quality SNPs. AIMs were selected using combined criteria including Delta, FST, and Informativeness of Assignment. Population structure was analyzed through Principal Component Analysis (PCA) and Admixture, with comparative performance evaluated using Bayesian hierarchical modeling with LOO cross-validation and WAIC scores. Selection signatures were detected using normalized haplotype-based iHS statistics implemented in Selscan software. Principal component analysis (PCA) and Admixture results indicated incomplete breed differentiation using GWMs. However, a subset of the top 2000 AIMs, effectively resolved breed-specific clusters, hence these AIMs can be designated as "Breed Informative Markers". Bayesian hierarchical modeling demonstrated that AIMs provided superior ancestry estimates compared to GWMs, as indicated by less negative leave-one-out (LOO) cross-validation and widely applicable information criterion (WAIC) scores. Haplotype-based selection signatures based on AIMs revealed breed-specific genomic regions under selection and we nomenclature them as "Ancestry Informative Selection Signatures (AISS)". Notably, the Carbonic Anhydrase II (CA2), Splicing Factor 3B Subunit 4 (SF3B4), and Fc Receptor Like 5 (FCRL5) genes in Murrah were linked to acid–base balance, pre-mRNA splicing, and innate immunity, respectively. The RNA-binding Raly-like protein (RALYL) gene in Mehsana was associated with disease resistance and thermoregulation, while the SET Domain Containing 3 (SETD3) gene in Toda buffalo contributed to muscle development, enhancing its draught capabilities. This study represents the first comprehensive effort to develop AIM and AISS panel for buffalo breed differentiation, paving the way for cost-effective and precise genetic assessments.