Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)

Abstract

In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High-throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis-related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio-engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype-to-gene identification pipeline.

Original languageEnglish
Pages (from-to)112-133
JournalThe Plant Journal
Volume97
Issue number1
DOIs
Publication statusPublished - 12 Dec 2018

Fingerprint

Photosynthesis
Genomics
Plant Development
genomics
phenotype
photosynthesis
Plant Physiological Phenomena
Phenotype
plant development
Bioengineering
Acclimatization
Optical Imaging
Chlorophyll
bioengineering
Genes
genetic traits
Breeding
plant physiology
food crops
quantitative traits

Keywords

  • genome-wide association study
  • genomics
  • high-throughput phenotyping
  • phenomics
  • photosynthesis
  • trait discovery

Cite this

@article{a14dd6842cda4cb4995bea05eafedf21,
title = "Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency",
abstract = "In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High-throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis-related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio-engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype-to-gene identification pipeline.",
keywords = "genome-wide association study, genomics, high-throughput phenotyping, phenomics, photosynthesis, trait discovery",
author = "{van Bezouw}, {Roel F.H.M.} and Keurentjes, {Joost J.B.} and Jeremy Harbinson and Aarts, {Mark G.M.}",
year = "2018",
month = "12",
day = "12",
doi = "10.1111/tpj.14190",
language = "English",
volume = "97",
pages = "112--133",
journal = "The Plant Journal",
issn = "0960-7412",
publisher = "Wiley",
number = "1",

}

TY - JOUR

T1 - Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency

AU - van Bezouw, Roel F.H.M.

AU - Keurentjes, Joost J.B.

AU - Harbinson, Jeremy

AU - Aarts, Mark G.M.

PY - 2018/12/12

Y1 - 2018/12/12

N2 - In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High-throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis-related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio-engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype-to-gene identification pipeline.

AB - In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High-throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis-related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio-engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype-to-gene identification pipeline.

KW - genome-wide association study

KW - genomics

KW - high-throughput phenotyping

KW - phenomics

KW - photosynthesis

KW - trait discovery

U2 - 10.1111/tpj.14190

DO - 10.1111/tpj.14190

M3 - Article

VL - 97

SP - 112

EP - 133

JO - The Plant Journal

JF - The Plant Journal

SN - 0960-7412

IS - 1

ER -