|Title||Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency|
|Author(s)||Bezouw, Roel F.H.M. van; Keurentjes, Joost J.B.; Harbinson, Jeremy; Aarts, Mark G.M.|
|Source||The Plant Journal 97 (2018)1. - ISSN 0960-7412 - p. 112 - 133.|
Laboratory of Genetics
Horticulture & Product Physiology
|Publication type||Refereed Article in a scientific journal|
|Keyword(s)||genome-wide association study - genomics - high-throughput phenotyping - phenomics - photosynthesis - trait discovery|
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.