Genetic characterization of carrot root shape and size using genome-wide association analysis and genomic-estimated breeding values.

Resource Type: 
Publication
Publication Type: 
Journal Article
Title: 
Genetic characterization of carrot root shape and size using genome-wide association analysis and genomic-estimated breeding values.
Authors: 
Brainard SH, Ellison SL, Simon PW, Dawson JC, Goldman IL
Series Name: 
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Journal Abbreviation: 
Theor Appl Genet
Publication Year: 
2021
Publication Date: 
2021 Nov 15
DOI: 
10.1007/s00122-021-03988-8
ISSN: 
1432-2242
EISSN: 
1432-2242
Citation: 
Brainard SH, Ellison SL, Simon PW, Dawson JC, Goldman IL. Genetic characterization of carrot root shape and size using genome-wide association analysis and genomic-estimated breeding values.. TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik. 2021 Nov 15.
Abstract: 

KEY MESSAGE
The principal phenotypic determinants of market class in carrot-the size and shape of the root-are under primarily additive, but also highly polygenic, genetic control. The size and shape of carrot roots are the primary determinants not only of yield, but also market class. These quantitative phenotypes have historically been challenging to objectively evaluate, and thus subjective visual assessment of market class remains the primary method by which selection for these traits is performed. However, advancements in digital image analysis have recently made possible the high-throughput quantification of size and shape attributes. It is therefore now feasible to utilize modern methods of genetic analysis to investigate the genetic control of root morphology. To this end, this study utilized both genome wide association analysis (GWAS) and genomic-estimated breeding values (GEBVs) and demonstrated that the components of market class are highly polygenic traits, likely under the influence of many small effect QTL. Relatively large proportions of additive genetic variance for many of the component phenotypes support high predictive ability of GEBVs; average prediction ability across underlying market class traits was 0.67. GWAS identified multiple QTL for four of the phenotypes which compose market class: length, aspect ratio, maximum width, and root fill, a previously uncharacterized trait which represents the size-independent portion of carrot root shape. By combining digital image analysis with GWAS and GEBVs, this study represents a novel advance in our understanding of the genetic control of market class in carrot. The immediate practical utility and viability of genomic selection for carrot market class is also described, and concrete guidelines for the design of training populations are provided.

Publication Model: 
Print-Electronic
Language: 
English
Language Abbr: 
eng
Journal Country: 
Germany