Emerging tools in quantitative trait loci detection

被引:1
|
作者
Perez-Enciso, Miguel [1 ]
机构
[1] Univ Autonoma Barcelona, Dept Ciencia Anim & Aliments, Bellaterra 08193, Spain
[2] Inst Catala Recerca & Estudis Avancats ICREA, Barcelona, Spain
关键词
genetical genomics; linkage disequilibrium; quantitative trait loci;
D O I
10.1080/09064700801959429
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
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.
引用
收藏
页码:202 / 207
页数:6
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