Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement

Abstract

More accurate and precise phenotyping strategies are necessary to empower high-resolution linkage mapping and genome-wide association studies and for training genomic selection models in plant improvement. Within this framework, the objective of modern phenotyping is to increase the accuracy, precision and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration and experimental design. Much like the efforts to optimize genotyping during the 1980s and 1990s, designing effective phenotyping initiatives today requires multi-faceted collaborations between biologists, computer scientists, statisticians and engineers. Robust phenotyping systems are needed to characterize the full suite of genetic factors that contribute to quantitative phenotypic variation across cells, organs and tissues, developmental stages, years, environments, species and research programs. Next-generation phenotyping generates significantly more data than previously and requires novel data management, access and storage systems, increased use of ontologies to facilitate data integration, and new statistical tools for enhancing experimental design and extracting biologically meaningful signal from environmental and experimental noise. To ensure relevance, the implementation of efficient and informative phenotyping experiments also requires familiarity with diverse germplasm resources, population structures, and target populations of environments. Today, phenotyping is quickly emerging as the major operational bottleneck limiting the power of genetic analysis and genomic prediction. The challenge for the next generation of quantitative geneticists and plant breeders is not only to understand the genetic basis of complex trait variation, but also to use that knowledge to efficiently synthesize twenty-first century crop varieties.

Development of a field-based high-throughput mobile phenotyping platform

“…Continued development promises to make feasible the sequencing/resequencing of model plant and major crop species and parental and progeny lines of mapping populations, allowing plant breeders to link fragments of chromosome in the progeny line to the parent (Varshney et al 2009). These genomic advancements will improve the precision and efficiency of phenotype predictions from genotypes, consequently accelerating the development and improvement of modern crop cultivars (Cobb et al 2013).…”

“…New plant genotypes with intrinsic high yields and yield stability under drought and salinity stress, adaptable to future climate conditions must be developed (Furbank and Tester 2011). In order to quickly and efficiently achieve this, the genetic basis of complex plant traits, such as yield and drought stress tolerance, must be understood and methods for predicting these traits from genetic composition of lines or cultivars must be improved (Cobb et al 2013;White et al 2012). Understanding the genetic basis of complex plant traits requires linking genetic information with correspondingly observed phenotypic data (Montes, Melchinger, and Reif 2007b).…”

“…Genotyping methods have become highly mechanized, uniform across organisms, and relatively low in cost, with costs decreasing every year (Cobb et al 2013). However, little improvement of methods for collecting plaint trait data or phenotyping have occurred in the last 30 years, especially for collecting data for single plots or plants in field-based situations (White et al 2012).…”

“…However, little improvement of methods for collecting plaint trait data or phenotyping have occurred in the last 30 years, especially for collecting data for single plots or plants in field-based situations (White et al 2012). Availability of high-quality phenotypic and corresponding environmental data is becoming essential to understand the genotype-tophenotype relationship; due to lack of phenotypic data, phenotyping is currently considered the major operational bottleneck of genetic analysis (Cobb et al 2013;Furbank and Tester 2011).…”

Wheat in Kenya: Past and Twenty-First Century Breeding

“…The objective of modern phenotyping is to increase the accuracy, precision, and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration, and experimental design [32]. Hence robust phenotyping assays for the nation program with the objective of reducing inefficiencies in development and release of superior cultivars would immensely benefit from investments in infrastructure and human capacities in biometrics in plant breeding.…”