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

Abstract

SummaryIn 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.

Natural genetic variation in photosynthesis: an untapped resource to increase crop yield potential?

“…In particular, high‐throughput phenotyping approaches can help detect important genomic regions for leaf and/or canopy photosynthetic traits in wheat and speed up the selection of desirable traits. Either large panels of wheat with unknown ancestry or bi and multiparental populations (for quantitative trait loci analysis) can be used for this approach, as already demonstrated in rice (Teng et al , ; Gu et al , ) and recently reviewed by van Bezouw et al (). In addition the development of single‐nucleotide polymorphism platforms in wheat (Wilkinson et al , ) and the recently annotated genome of bread wheat (Appels et al , ) will ensure a more comprehensive understanding of the genetic control of photosynthetic traits or other A ‐determining traits such as g s and stomatal dynamics.…”

From genome to phenome: genome‐wide association studies and other approaches that bridge the genotype to phenotype gap

“…Van Bezouw et al . () describe how the convergence of phenomic and genomic approaches offers great promise for studying natural variation in photosynthetic efficiency. They review early examples in this direction and propose a framework by which screening for easily scorable phenotypes can capture variance within a trait and provide strong arguments for the study of acclimation to fluctuation environments.…”

“…() and Van Bezouw et al . (), the impact that environmental conditions play in phenotypic plasticity represents a cornerstone of plant biology. Understanding how plants respond and adapt to environmental changes will be fundamental to addressing the societal problems generated due to crop losses driven by climate change.…”

Emerging Technologies in Algal Biotechnology: Toward the Establishment of a Sustainable, Algae-Based Bioeconomy

“…With a reference genome in hand, linking a phenotype to the relevant gene alleles traditionally relies on statistical analysis of the progeny after cross-breeding two individuals or populations with different phenotypes for example through Quantitative Trait Loci (QTL) mapping. With each successive generation, the genomic regions responsible for the phenotypes can be narrowed down until one has a testable list of candidate gene loci (van Bezouw et al, 2019). Given that many microalgae either do not breed at all or only under often unknown environmental conditions, novel approaches must be developed to fully utilize the power of phenomic mutant screens.…”