If you are experiencing problems downloading PDF or HTML fulltext, our helpdesk recommend clearing your browser cache and trying again. If you need help in clearing your cache, please click here . Still need help? Email help@ingentaconnect.com

Emerging tools in quantitative trait loci detection

$61.74 plus tax (Refund Policy)

Buy Article:


In this work, I briefly describe some of the new tools that are emerging for quantitative trait loci (QTL) and causative mutation detection. First, I summarize what has been the current trend in QTL search. The type of DNA polymorphism and the statistical techniques used have varied over the last two decades. The initial emphasis on linkage analysis using microsatellites, random amplification of polymorphic DNA (RAPD), or amplified random-length polymorphism (AFLPs) and standard statistical techniques has been substituted by a recent focus in massive single-nucleotide polymorphism (SNP) association studies where coalescence theory has a preeminent role. Then, I focus on new statistical approaches that are being developed (or should be). In particular, a unified framework that combines coalescence and mixed-model theory is badly needed. I finally emphasize the relevance of modelling in emerging experiments like genetical genomics approaches.

Keywords: Genetical genomics; linkage disequilibrium; quantitative trait loci

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/09064700801959429

Affiliations: Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona, Bellaterra, Spain,Institut Català de Recerca i Estudis Avançats (ICREA), Barcelona, Spain

Publication date: December 1, 2007

More about this publication?
Related content

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more