4.7 Article

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

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THEORETICAL AND APPLIED GENETICS
卷 135, 期 2, 页码 605-622

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SPRINGER
DOI: 10.1007/s00122-021-03988-8

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资金

  1. Ekhagastiftelsen Award [2017-50]
  2. USDA- NPGS Award [58-5030-9-052]
  3. USDA-NIFA Award [2016-5118125400]

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The genetic control of market class in carrots is mainly additive but also highly polygenic. Advancements in digital image analysis have made high-throughput quantification of root size and shape attributes possible, enabling the study of genetic control of root morphology. Combining digital image analysis with GWAS and GEBVs has provided novel insights into the genetic control of market class traits in carrots.
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.

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