COS 159-6 - Identifying and quantifying genome-associated plant functional traits to improve plant selection for rangeland restoration

Abstract: Novel climate extremes and invasive species threaten the long-term productivity of Great Basin rangelands. By coupling genomic-based trait modeling with plant ecophysiological performance, we aim to develop and select native plant materials resilient to current and future conditions. In this study, we genotyped a population of ~1300 individuals of the native bluebunch wheatgrass (Pseudoroegneria spicata), including 6 crosses from 3 distinct source populations to investigate genome associations (i.e., QTLs), gene x environment interactions, trait correlations, and trait heritability. We also compared a suite of plant physiological and functional traits measured across two years with contrasting summer precipitation. We measured field-based traits, including plant height, stem number, seed size and yield, and seedling establishment in 2019 and 2020, and we surveyed these traits plus chlorophyll fluorescence during the 2022 field season. We also assessed relationships between each measured trait and seedling establishment, an early indicator of plant material performance.

Genome-wide analyses detected multiple chromosome loci with significant associations with leaf temperature photosystem II efficiency (φPSII), with an overall false-discovery rate (FDR) < 5 %. Total June precipitation was 3-fold higher in 2019 than 2020, and field-based traits varied significantly between years. Plants were, on average, 16 cm taller and produced seeds with 10 % greater seed area in 2019, while total seed yield per plant was 24 % greater in 2020 than 2019. Of these traits, we were only able to detect genome-associated SNPs for average number of seeds per head. Interestingly, two of the physiological traits (leaf temperature and φPSII) were also positively associated with percent establishment. In an ongoing study, we selected seeds from parent lines with contrasting heritable φPSII to investigate ecophysiological water-traits in a controlled growth chamber experiment to: 1) understand how maternal environment and seedling abiotic conditions (e.g. drought) impact plant performance, and 2) disentangle specific photochemical limitations driving observed differences in performance. By continuing to refine high-throughput genome trait-selection process coupled with robust ecophysiological and remote-sensing metrics, we expect to develop plant materials that better meet the challenging restoration needs of degraded sagebrush steppe rangelands.