Association Mapping of Total Carotenoids in Diverse Soybean Genotypes Based on Leaf Extracts and High-Throughput Canopy Spectral Reflectance Measurements

作者：Dhanapal Arun Prabhu; Ray Jeffery D; Singh Shardendu K; Hoyos Villegas Valerio; Smith James R; Purcell Larry C; King C Andy; Fritschi Felix B^*

来源：PLos One, 2015, 10(9): e0137213.

DOI：10.1371/journal.pone.0137213

Carotenoids are organic pigments that are produced predominantly by photosynthetic organisms and provide antioxidant activity to a wide variety of plants, animals, bacteria, and fungi. The carotenoid biosynthetic pathway is highly conserved in plants and occurs mostly in chromoplasts and chloroplasts. Leaf carotenoids play important photoprotective roles and targeted selection for leaf carotenoids may offer avenues to improve abiotic stress tolerance. A collection of 332 soybean [Glycine max (L.) Merr.] genotypes was grown in two years and total leaf carotenoid content was determined using three different methods. The first method was based on extraction and spectrophotometric determination of carotenoid content (eCaro) in leaf tissue, whereas the other two methods were derived from high-throughput canopy spectral reflectance measurements using wavelet transformed reflectance spectra (tCaro) and a spectral reflectance index (iCaro). An association mapping approach was employed using 31,253 single nucleotide polymorphisms (SNPs) to identify SNPs associated with total carotenoid content using a mixed linear model based on data from two growing seasons. A total of 28 SNPs showed a significant association with total carotenoid content in at least one of the three approaches. These 28 SNPs likely tagged 14 putative loci for carotenoid content. Six putative loci were identified using eCaro, five loci with tCaro, and nine loci with iCaro. Three of these putative loci were detected by all three carotenoid determination methods. All but four putative loci were located near a known carotenoid-related gene. These results showed that carotenoid markers can be identified in soybean using extract-based as well as by high-throughput canopy spectral reflectance-based approaches, demonstrating the utility of field-based canopy spectral reflectance phenotypes for association mapping.

• 出版日期2015-9-14