scholarly journals Genetic architecture of flowering time differentiation between locally adapted populations ofArabidopsis thaliana

2013 ◽  
Vol 197 (4) ◽  
pp. 1321-1331 ◽  
Author(s):  
Michael A. Grillo ◽  
Changbao Li ◽  
Mark Hammond ◽  
Lijuan Wang ◽  
Douglas W. Schemske
Keyword(s):  
Flowering Time ◽  
Genetic Architecture ◽  
Ofarabidopsis Thaliana

scholarly journals Genetic architecture and adaptation of flowering time among environments

2021 ◽  
Author(s):  
Wenjie Yan ◽  
Baosheng Wang ◽  
Emily Chan ◽  
Thomas Mitchell‐Olds
Keyword(s):  
Flowering Time ◽  
Genetic Architecture

scholarly journals The genetic architecture of leaf number and its genetic relationship to flowering time in maize

2015 ◽  
Vol 210 (1) ◽  
pp. 256-268 ◽  
Author(s):  
Dan Li ◽  
Xufeng Wang ◽  
Xiangbo Zhang ◽  
Qiuyue Chen ◽  
Guanghui Xu ◽  
...  
Keyword(s):  
Flowering Time ◽  
Genetic Relationship ◽  
Genetic Architecture ◽  
Leaf Number

The Genetic Architecture of Flowering Time and Photoperiod Sensitivity in Maize as Revealed by QTL Review and Meta Analysis

2012 ◽  
Vol 54 (6) ◽  
pp. 358-373 ◽  
Author(s):  
Jie Xu ◽  
Yaxi Liu ◽  
Jian Liu ◽  
Moju Cao ◽  
Jing Wang ◽  
...  
Keyword(s):  
Flowering Time ◽  
Genetic Architecture ◽  
Meta Analysis ◽  
Photoperiod Sensitivity

The Genetic Architecture of Maize Flowering Time

Science ◽  
2009 ◽  
Vol 325 (5941) ◽  
pp. 714-718 ◽  
Author(s):  
E. S. Buckler ◽  
J. B. Holland ◽  
P. J. Bradbury ◽  
C. B. Acharya ◽  
P. J. Brown ◽  
...  
Keyword(s):  
Flowering Time ◽  
Genetic Architecture

scholarly journals Genome-wide association study reveals the genetic architecture of flowering time in rapeseed (Brassica napus L.)

DNA Research ◽  
2015 ◽  
pp. dsv035 ◽  
Author(s):  
Liping Xu ◽  
Kaining Hu ◽  
Zhenqian Zhang ◽  
Chunyun Guan ◽  
Song Chen ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Association Study ◽  
Flowering Time ◽  
Genetic Architecture ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Brassica Napus L ◽  
Genome Wide

scholarly journals Genome-wide association analyses reveal complex genetic architecture underlying natural variation for flowering time in canola

2016 ◽  
Vol 39 (6) ◽  
pp. 1228-1239 ◽  
Author(s):  
H. Raman ◽  
R. Raman ◽  
N. Coombes ◽  
J. Song ◽  
R. Prangnell ◽  
...  
Keyword(s):  
Flowering Time ◽  
Genetic Architecture ◽  
Natural Variation ◽  
Genome Wide Association ◽  
Association Analyses ◽  
Genome Wide

scholarly journals Adaptive divergence in flowering time among natural populations ofArabidopsis thaliana: Estimates of selection and QTL mapping

Evolution ◽  
2016 ◽  
Vol 71 (3) ◽  
pp. 550-564 ◽  
Author(s):  
Jon Ågren ◽  
Christopher G. Oakley ◽  
Sverre Lundemo ◽  
Douglas W. Schemske
Keyword(s):  
Qtl Mapping ◽  
Flowering Time ◽  
Natural Populations ◽  
Adaptive Divergence ◽  
Ofarabidopsis Thaliana

scholarly journals Epistasis detection and modeling for genomic selection in cowpea (Vigna unguiculata. L. Walp.)

2019 ◽  
Author(s):  
Marcus O. Olatoye ◽  
Zhenbin Hu ◽  
Peter O. Aikpokpodion
Keyword(s):  
Genomic Selection ◽  
Flowering Time ◽  
Marker Assisted Selection ◽  
Fixed Effects ◽  
Genetic Architecture ◽  
Phytochrome A ◽  
Epistatic Interactions ◽  
Moderate Effect ◽  
Advanced Generation ◽  
Non Parametric

AbstractGenetic architecture reflects the pattern of effects and interaction of genes underling phenotypic variation. Most mapping and breeding approaches generally consider the additive part of variation but offer limited knowledge on the benefits of epistasis which explains in part the variation observed in traits. In this study, the cowpea multiparent advanced generation inter-cross (MAGIC) population was used to characterize the epistatic genetic architecture of flowering time, maturity, and seed size. In addition, considerations for epistatic genetic architecture in genomic-enabled breeding (GEB) was investigated using parametric, semi-parametric, and non-parametric genomic selection (GS) models. Our results showed that large and moderate effect sized two-way epistatic interactions underlie the traits examined. Flowering time QTL colocalized with cowpea putative orthologs of Arabidopsis thaliana and Glycine max genes like PHYTOCLOCK1 (PCL1 [Vigun11g157600]) and PHYTOCHROME A (PHY A [Vigun01g205500]). Flowering time adaptation to long and short photoperiod was found to be controlled by distinct and common main and epistatic loci. Parametric and semi-parametric GS models outperformed non-parametric GS model. Using known QTL as fixed effects in GS models improved prediction accuracy when traits were controlled by both large and moderate effect QTL. In general, our study demonstrated that prior understanding the genetic architecture of a trait can help make informed decisions in GEB. This is the first report to characterize epistasis and provide insights into the underpinnings of GS versus marker assisted selection in cowpea.

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