Bayesian Multiple Quantitative Trait Loci Mapping for Recombinant Inbred Intercrosses

被引:6
|
作者
Yuan, Zhongshang [1 ,3 ]
Zou, Fei [1 ,2 ]
Liu, Yanyan [3 ]
机构
[1] Univ N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA
[2] Univ N Carolina, Carolina Ctr Genome Sci, Chapel Hill, NC 27599 USA
[3] Wuhan Univ, Sch Math & Stat, Wuhan 430072, Hubei, Peoples R China
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
CHAIN MONTE-CARLO; EXPERIMENTAL CROSSES; COLLABORATIVE CROSS; SYSTEMS GENETICS; ENTIRE GENOME; LINE CROSSES; MODEL; SELECTION; SHRINKAGE; RESOURCE;
D O I
10.1534/genetics.110.125542
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
The Collaborative Cross (CC) is a renewable mouse resource that mimics the genetic diversity in humans. The recombinant inbred intercrosses (RIX) generated from CC recombinant inbred (RI) lines share similar genetic structures to those of F(2) individuals. In contrast to F(2) mice, genotypes of RIX can be inferred from the genotypes of their RI parents and can be produced repeatedly. Also, RIX mice do not typically share the same degree of relatedness. This unbalanced genetic relatedness requires careful statistical modeling to avoid a large number of false positive findings. For complex traits, mapping multiple genes simultaneously is arguably more powerful than mapping one gene at a time. In this article, we describe how we have developed a Bayesian quantitative trait locus (QTL) mapping method that simultaneously deals with the special genetic architecture of RIX and maps multiple genes. The performance of the proposed method is evaluated by extensive simulations. In addition, for a given set of RI lines, there are numerous ways to generate RIX samples. To provide a general guideline on future RIX studies, we compare several RIX designs through simulations.
引用
收藏
页码:189 / U309
页数:11
相关论文
共 50 条
  • [1] Varying Coefficient Models for Mapping Quantitative Trait Loci Using Recombinant Inbred Intercrosses
    Gong, Yi
    Zou, Fei
    GENETICS, 2012, 190 (02) : 475 - U278
  • [2] Bayesian mapping of multiple quantitative trait loci from incomplete inbred line cross data
    Sillanpää, MJ
    Arjas, E
    GENETICS, 1998, 148 (03) : 1373 - 1388
  • [3] Bayesian quantitative trait loci mapping for multiple traits
    Banerjee, Samprit
    Yandell, Brian S.
    Yi, Nengjun
    GENETICS, 2008, 179 (04) : 2275 - 2289
  • [4] Mapping multiple quantitative trait loci by Bayesian classification
    Zhang, M
    Montooth, KL
    Wells, MT
    Clark, AG
    Zhang, DB
    GENETICS, 2005, 169 (04) : 2305 - 2318
  • [5] Multiple trait multiple interval mapping of quantitative trait loci from inbred line crosses
    Luciano Da Costa E Silva
    Shengchu Wang
    Zhao-Bang Zeng
    BMC Genetics, 13
  • [6] Multiple trait multiple interval mapping of quantitative trait loci from inbred line crosses
    Silva, Luciano Da Costa E.
    Wang, Shengchu
    Zeng, Zhao-Bang
    BMC GENETICS, 2012, 13
  • [7] Mapping quantitative trait loci using the experimental designs of recombinant inbred populations
    Kao, Chen-Hung
    GENETICS, 2006, 174 (03) : 1373 - 1386
  • [8] Mapping Quantitative Trait Loci for Yield Potential Traits in Wheat Recombinant Inbred Lines
    Kang, Chon-Sik
    Mo, Young-Jun
    Kim, Kyeong-Min
    Kim, Kyeong-Hoon
    Chun, Jae-Buhm
    Park, Chul-Soo
    Cho, Seong-Woo
    AGRONOMY-BASEL, 2021, 11 (01):
  • [9] Quantitative trait locus analysis using recombinant inbred intercrosses: Theoretical and empirical considerations
    Zou, F
    Gelfond, JAL
    Airey, DC
    Lu, L
    Manly, KF
    Williams, RW
    Threadgill, DW
    GENETICS, 2005, 170 (03) : 1299 - 1311
  • [10] Mapping quantitative trait loci for circadian behavioral rhythms in SMXA recombinant inbred strains
    Suzuki, T
    Ishikawa, A
    Nishimura, M
    Yoshimura, T
    Namikawa, T
    Ebihara, S
    BEHAVIOR GENETICS, 2000, 30 (06) : 447 - 453