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Identification of cis- and trans-expression quantitative trait loci using Bayesian framework


Affiliations
1 ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
 

The detection and identification of expression quantitative trait loci (eQTLs) for biological characteristics like gene expression is an important focus of genomics. The existence of cis- and trans-eQTLs is crucial for esta­blishing their cumulative significance to the desired traits. A crucial aspect of genomics is identifying the cis- and trans-eQTLs that capture substantial changes in the expression of distant genes. The goal of the present study was to use an integrated hierarchical Bayesian model to identify the cis- and trans-eQTLS. Molecular approaches are utilized to categorize just the candidate genes when quantitative trait loci or eQTLs are identified. Variations inside or near the gene are hypothesized to determine the genetic varian­ces that reflect transcript levels. The identification of eQTLs has helped us better understand gene regulation and complex trait analysis. The present study focused on barley crops, and only cis-eQTLs were identified; no additional eQTL hotspots were determined. Mouse gene expressions were used to study trans-eQTLs and substantial cis- and trans-eQTLs, as well as four eQTL hotspots were identified

Keywords

Barley, gene expression, hotspots, integrated hierarchical model, quantitative trait loci.
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  • Identification of cis- and trans-expression quantitative trait loci using Bayesian framework

Abstract Views: 390  |  PDF Views: 143

Authors

Himadri Shekhar Roy
ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
Amrit Kumar Paul
ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
Ranjit Kumar Paul
ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India

Abstract


The detection and identification of expression quantitative trait loci (eQTLs) for biological characteristics like gene expression is an important focus of genomics. The existence of cis- and trans-eQTLs is crucial for esta­blishing their cumulative significance to the desired traits. A crucial aspect of genomics is identifying the cis- and trans-eQTLs that capture substantial changes in the expression of distant genes. The goal of the present study was to use an integrated hierarchical Bayesian model to identify the cis- and trans-eQTLS. Molecular approaches are utilized to categorize just the candidate genes when quantitative trait loci or eQTLs are identified. Variations inside or near the gene are hypothesized to determine the genetic varian­ces that reflect transcript levels. The identification of eQTLs has helped us better understand gene regulation and complex trait analysis. The present study focused on barley crops, and only cis-eQTLs were identified; no additional eQTL hotspots were determined. Mouse gene expressions were used to study trans-eQTLs and substantial cis- and trans-eQTLs, as well as four eQTL hotspots were identified

Keywords


Barley, gene expression, hotspots, integrated hierarchical model, quantitative trait loci.

References





DOI: https://doi.org/10.18520/cs%2Fv122%2Fi10%2F1214-1219