Leveraging the genomics revolution with high-throughput phenotyping for crop improvement of abiotic stresses

Abstract

A major challenge for 21st century plant geneticists is to predict plant performance based on genetic information. This is a daunting challenge, especially when there are thousands of genes that control complex traits as well as the extreme variation that results from the environment where plants are grown. Rapid advances in technology are assisting in overcoming the obstacle of connecting the genotype to phenotype. Next generation sequencing has provided a wealth of genomic information resulting in numerous completely sequenced genomes and the ability to quickly genotype thousands of individuals. The ability to pair the dense genotypic data with phenotypic data, the observed plant performance, will culminate in successfully predicting cultivar performance. While genomics has advanced rapidly, phenomics, the science and ability to measure plant phenotypes, has slowly progressed, resulting in an imbalance of genotypic to phenotypic data. The disproportion of high-throughput phenotyping (HTP) data is a bottleneck to many genetic and association mapping studies as well as genomic selection (GS). To alleviate the phenomics bottleneck, an affordable and portable phenotyping platform, Phenocart, was developed and evaluated. The Phenocart was capable of taking multiple types of georeferenced measurements including normalized difference vegetation index and canopy temperature, throughout the growing season. The Phenocart performed as well as existing manual measurements while increasing the amount of data exponentially. The deluge of phenotypic data offered opportunities to evaluate lines at specific time points, as well as combining data throughout the season to assess for genotypic differences. Finally in an effort to predict crop performance, the phenotypic data was used in GS models. The models combined molecular marker data from genotyping-by-sequencing with high-throughput phenotyping for plant phenotypic characterization. Utilizing HTP data, rather than just the often measured yield, increased the accuracy of GS models. Achieving the goal of connecting genotype to phenotype has direct impact on plant breeding by allowing selection of higher yielding crops as well as selecting crops that are adapted to local environments. This will allow for a faster rate of improvement in crops, which is imperative to meet the growing global population demand for plant products.