Genetic Mapping by Bulk Segregant Analysis in Drosophila: Experimental Design and Simulation-Based Inference.
Genetic Mapping by Bulk Segregant Analysis in Drosophila: Experimental Design and Simulation-Based Inference.
复制标题
DOI:
10.1534/genetics.116.192484
复制
发表时间:
2016-11
期刊:
影响因子:
3.3
通讯作者:
Pool JE
中科院分区:
文献类型:
--
作者:
Pool JE
Identifying the genomic regions that underlie complex phenotypic variation is a key challenge in modern biology. Many approaches to quantitative trait locus mapping in animal and plant species suffer from limited power and genomic resolution. Here, I investigate whether bulk segregant analysis (BSA), which has been successfully applied for yeast, may have utility in the genomic era for trait mapping in Drosophila (and other organisms that can be experimentally bred in similar numbers). I perform simulations to investigate the statistical signal of a quantitative trait locus (QTL) in a wide range of BSA and introgression mapping (IM) experiments. BSA consistently provides more accurate mapping signals than IM (in addition to allowing the mapping of multiple traits from the same experimental population). The performance of BSA and IM is maximized by having multiple independent crosses, more generations of interbreeding, larger numbers of breeding individuals, and greater genotyping effort, but is less affected by the proportion of individuals selected for phenotypic extreme pools. I also introduce a prototype analysis method for simulation-based inference for BSA mapping (SIBSAM). This method identifies significant QTL and estimates their genomic confidence intervals and relative effect sizes. Importantly, it also tests whether overlapping peaks should be considered as two distinct QTL. This approach will facilitate improved trait mapping in Drosophila and other species for which hundreds or thousands of offspring (but not millions) can be studied.
登录
查看更多内容
影响因子:
3.7
作者:
Baird NA;Etter PD;Atwood TS;Currey MC;Shiver AL;Lewis ZA;Selker EU;Cresko WA;Johnson EA
通讯作者:
Johnson EA
DOI:
10.1534/g3.115.017665
发表时间:
2015-06-01
期刊:
G3 (Bethesda, Md.)
影响因子:
--
作者:
Haase NJ;Beissinger T;Hirsch CN;Vaillancourt B;Deshpande S;Barry K;Buell CR;Kaeppler SM;de Leon N
通讯作者:
de Leon N
影响因子:
3.3
作者:
Bastide H;Lange JD;Lack JB;Yassin A;Pool JE
通讯作者:
Pool JE
影响因子:
3.3
作者:
King, Elizabeth G.;Macdonald, Stuart J.;Long, Anthony D.
通讯作者:
Long, Anthony D.
影响因子:
48
作者:
Lai, Chao-Qiang;Leips, Jeff;Mackay, Trudy F. C.
通讯作者:
Mackay, Trudy F. C.