The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).

If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.

Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

Fullscreen Fullscreen Off


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.
User
Notifications
Font Size