scholarly journals Comparison of statistical models for nested association mapping in rapeseed (Brassica napus L.) through computer simulations

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Jinquan Li ◽  
Anja Bus ◽  
Viola Spamer ◽  
Benjamin Stich
2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Jordan Ubbens ◽  
Mikolaj Cieslak ◽  
Przemyslaw Prusinkiewicz ◽  
Isobel Parkin ◽  
Jana Ebersbach ◽  
...  

Association mapping studies have enabled researchers to identify candidate loci for many important environmental tolerance factors, including agronomically relevant tolerance traits in plants. However, traditional genome-by-environment studies such as these require a phenotyping pipeline which is capable of accurately measuring stress responses, typically in an automated high-throughput context using image processing. In this work, we present Latent Space Phenotyping (LSP), a novel phenotyping method which is able to automatically detect and quantify response-to-treatment directly from images. We demonstrate example applications using data from an interspecific cross of the model C4 grass Setaria, a diversity panel of sorghum (S. bicolor), and the founder panel for a nested association mapping population of canola (Brassica napus L.). Using two synthetically generated image datasets, we then show that LSP is able to successfully recover the simulated QTL in both simple and complex synthetic imagery. We propose LSP as an alternative to traditional image analysis methods for phenotyping, enabling the phenotyping of arbitrary and potentially complex response traits without the need for engineering-complicated image-processing pipelines.


Genes ◽  
2015 ◽  
Vol 6 (4) ◽  
pp. 1215-1229 ◽  
Author(s):  
Cun-Min Qu ◽  
Shi-Meng Li ◽  
Xiu-Jian Duan ◽  
Jin-Hua Fan ◽  
Le-Dong Jia ◽  
...  

2018 ◽  
Vol 155 ◽  
pp. 420-428 ◽  
Author(s):  
Fugui Zhang ◽  
Xin Xiao ◽  
Guixin Yan ◽  
Jihong Hu ◽  
Xi Cheng ◽  
...  

2020 ◽  
Author(s):  
tengyue wang ◽  
Lijuan Wei ◽  
Jia wang ◽  
Ling Xie ◽  
Yangyang Li ◽  
...  

Abstract Background: Brassica napus is one of the most important oilseed crops, and also an important biofuel plant due to its low air pollution and renewability. Growth period are important traits that affect yield and are crucial for its adaptation to different environments in B. napus.Results: To elucidate the genetic basis of growth period traits, genome-wide association analysis (GWAS) and linkage mapping were employed to detect the quantitative trait loci (QTL) for days to initial flowering (DIF), days to final flowering (DFF), days from initial flowering to final flowering (FP), days from final flowering to maturity (MT), and whole growth period (GP). A total of 146 SNPs were identified by association mapping, and 83 QTLs were identified by linkage mapping using the RIL population. Among these QTLs, 19 were pleiotropic SNPs related to multiple traits, and six (q18DFF.A03-2, q18MT.A03-2, q17DFF.A05-1, q18FP.C04, q17DIF.C05 and q17GP.C09) were consistently detected using both mapping methods. Additionally, we performed RNA sequencing to analyze the differential expression of gene (DEG) transcripts between early- and late-flowering lines selected from the RIL population, and the DEGs were integrated with association mapping and linkage analysis to confirm their roles in the growth period. Consequently, twelve candidate genes associated with growth period traits were identified in B. napus. Among these genes, seven have polymorphic sites in the coding sequence and the upstream 2-kb sequence based on the resequencing data. The haplotype BnaSOC1.A05-Haplb and BnaLNK2.C06-Hapla showed more favorable phenotypic traits. Conclusions: The candidate genes identified in this study will contribute to our genetic understanding of growth period traits and can be used as targets for target mutations or marker assisted breeding for rapeseed adapted to different environments.


2010 ◽  
Vol 27 (3) ◽  
pp. 271-287 ◽  
Author(s):  
C. Jestin ◽  
M. Lodé ◽  
P. Vallée ◽  
C. Domin ◽  
C. Falentin ◽  
...  

2015 ◽  
Vol 35 (6) ◽  
Author(s):  
Humberto A. Gajardo ◽  
Benjamin Wittkop ◽  
Braulio Soto-Cerda ◽  
Erin E. Higgins ◽  
Isobel A. P. Parkin ◽  
...  

2013 ◽  
Vol 127 (1) ◽  
pp. 85-96 ◽  
Author(s):  
Dongfang Cai ◽  
Yingjie Xiao ◽  
Wei Yang ◽  
Wei Ye ◽  
Bo Wang ◽  
...  

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