Literature DB >> 28724075

A Comprehensive Image-based Phenomic Analysis Reveals the Complex Genetic Architecture of Shoot Growth Dynamics in Rice (Oryza sativa).

Malachy T Campbell, Qian Du, Kan Liu, Chris J Brien, Bettina Berger, Chi Zhang, Harkamal Walia.   

Abstract

Early vigor is an important trait for many rice ( L.)-growing environments. However, genetic characterization and improvement for early vigor is hindered by the temporal nature of the trait and strong genotype × environment effects. We explored the genetic architecture of shoot growth dynamics during the early and active tillering stages by applying a functional modeling and genomewide association (GWAS) mapping approach on a diversity panel of ∼360 rice accessions. Multiple loci with small effects on shoot growth trajectory were identified, indicating a complex polygenic architecture. Natural variation for shoot growth dynamics was assessed in a subset of 31 accessions using RNA sequencing and hormone quantification. These analyses yielded a gibberellic acid (GA) catabolic gene, , which could influence GA levels to regulate vigor in the early tillering stage. Given the complex genetic architecture of shoot growth dynamics, the potential of genomic selection (GS) for improving early vigor was explored using all 36,901 single-nucleotide polymorphisms (SNPs) as well as several subsets of the most significant SNPs from GWAS. Shoot growth trajectories could be predicted with reasonable accuracy using the 50 most significant SNPs from GWAS (0.37-0.53); however, the accuracy of prediction was improved by including more markers, which indicates that GS may be an effective strategy for improving shoot growth dynamics during the vegetative growth stage. This study provides insights into the complex genetic architecture and molecular mechanisms underlying early shoot growth dynamics and provides a foundation for improving this complex trait in rice.
Copyright © 2017 Crop Science Society of America.

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Year:  2017        PMID: 28724075     DOI: 10.3835/plantgenome2016.07.0064

Source DB:  PubMed          Journal:  Plant Genome        ISSN: 1940-3372            Impact factor:   4.089


  13 in total

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Review 3.  Integrating High-Throughput Phenotyping and Statistical Genomic Methods to Genetically Improve Longitudinal Traits in Crops.

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Review 4.  Salt stress under the scalpel - dissecting the genetics of salt tolerance.

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Journal:  Plant J       Date:  2019-01       Impact factor: 6.417

5.  Automated phenotyping for early vigour of field pea seedlings in controlled environment by colour imaging technology.

Authors:  Giao N Nguyen; Sally L Norton; Garry M Rosewarne; Laura E James; Anthony T Slater
Journal:  PLoS One       Date:  2018-11-19       Impact factor: 3.240

6.  Deciphering the Genetic Architecture of Cooked Rice Texture.

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Journal:  Front Plant Sci       Date:  2018-10-02       Impact factor: 5.753

7.  Utilizing trait networks and structural equation models as tools to interpret multi-trait genome-wide association studies.

Authors:  Mehdi Momen; Malachy T Campbell; Harkamal Walia; Gota Morota
Journal:  Plant Methods       Date:  2019-09-18       Impact factor: 4.993

8.  Functional QTL mapping and genomic prediction of canopy height in wheat measured using a robotic field phenotyping platform.

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9.  Unoccupied aerial system enabled functional modeling of maize height reveals dynamic expression of loci.

Authors:  Steven L Anderson; Seth C Murray; Yuanyuan Chen; Lonesome Malambo; Anjin Chang; Sorin Popescu; Dale Cope; Jinha Jung
Journal:  Plant Direct       Date:  2020-05-10

10.  High-throughput 3D modelling to dissect the genetic control of leaf elongation in barley (Hordeum vulgare).

Authors:  Ben Ward; Chris Brien; Helena Oakey; Allison Pearson; Sónia Negrão; Rhiannon K Schilling; Julian Taylor; David Jarvis; Andy Timmins; Stuart J Roy; Mark Tester; Bettina Berger; Anton van den Hengel
Journal:  Plant J       Date:  2019-02-22       Impact factor: 6.417

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