4.7 Article

Mapping of epistatic quantitative trait loci in four-way crosses

Journal

THEORETICAL AND APPLIED GENETICS
Volume 122, Issue 1, Pages 33-48

Publisher

SPRINGER
DOI: 10.1007/s00122-010-1420-8

Keywords

-

Funding

  1. National Basic Research Program of China [2006CB101708]
  2. National Natural Science Foundation of China [30900842, 30971848, 30471114]
  3. Jiangsu Natural Science Foundation [BK2008335]
  4. NCET [NCET-05-0489]
  5. 111 Project [B08025]
  6. NAU [KJ08001]

Ask authors/readers for more resources

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available