Genomic Regions Associated with Root Traits under Drought Stress in Tropical Maize (Zea mays L.)

Abstract

An association mapping panel, named as CIMMYT Asia association mapping (CAAM) panel, involving 396 diverse tropical maize lines were phenotyped for various structural and functional traits of roots under drought and well-watered conditions. The experiment was conducted during Kharif (summer-rainy) season of 2012 and 2013 in root phenotyping facility at CIMMYT-Hyderabad, India. The CAAM panel was genotyped to generate 955, 690 SNPs through GBS v2.7 using Illumina Hi-seq 2000/2500 at Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA. GWAS analysis was carried out using 331,390 SNPs filtered from the entire set of SNPs revealed a total of 50 and 67 SNPs significantly associated for root functional (transpiration efficiency, flowering period water use) and structural traits (rooting depth, root dry weight, root length, root volume, root surface area and root length density), respectively. In addition to this, 37 SNPs were identified for grain yield and shoot biomass under well-watered and drought stress. Though many SNPs were found to have significant association with the traits under study, SNPs that were common for more than one trait were discussed in detail. A total 18 SNPs were found to have common association with more than one trait, out of which 12 SNPs were found within or near the various gene functional regions. In this study we attempted to identify the trait specific maize lines based on the presence of favorable alleles for the SNPs associated with multiple traits. Two SNPs S3_128533512 and S7_151238865 were associated with transpiration efficiency, shoot biomass and grain yield under well-watered condition. Based on favorable allele for these SNPs seven inbred lines were identified. Similarly, four lines were identified for transpiration efficiency and shoot biomass under drought stress based on the presence of favorable allele for the common SNPs S1_211520521, S2_20017716, S3_57210184 and S7_130878458 and three lines were identified for flowering period water-use, transpiration efficiency, root dry weight and root volume based on the presence of favorable allele for the common SNPs S3_162065732 and S3_225760139.

Genome‐wide association studies of fruit quality traits in jujube germplasm collections using genotyping‐by‐sequencing

“…In the present study of jujube, a cross‐pollinated species, the average extent of LD decay for the entire jujube genome was estimated to be 10 kb at r 2 < 0.1. In general, a faster LD decay rate and a smaller LD block results in higher mapping resolution (Zaidi et al., 2016). The LD values observed in the current study are similar to our previous findings for a core collection of 150 accessions in which r 2 declined from an initial value of 0.483 to 0.104 over 9.77 kb (Chen et al., 2017b), which is similar to results reported for sesame (Morris et al., 2013).…”

Genetic analysis of seedling root traits reveals the association of root trait with other agronomic traits in maize

“…The root system, which plays an important role in crop growth and stress responses, anchors the shoots, absorbs water and nutrients from the soil, and is the biosynthetic site of phytohormones required for plant development [ 1 ]. As the site of plant-soil interactions, the roots also play a key role in plant responses to environmental changes and influence agronomically important traits, such as drought or flood tolerance [ 2 – 4 ], root-lodging resistance [ 5 , 6 ], and the efficiency of nutrient use under suboptimal growth conditions [ 7 – 10 ]. The effectiveness of root function depends on the characteristics and architecture of the root system.…”

Genomics-Enabled Next-Generation Breeding Approaches for Developing System-Specific Drought Tolerant Hybrids in Maize

“…Identification and utilization of SNPs through GBS have been performed in maize for various purposes. More than 100 SNPs were identified for root traits under drought stress condition from 955,690 SNPs generated though GBS (Zaidi et al, 2016 ). Genomic prediction of SNPs developed through GBS was studied from a diverse panel of 296 maize inbreds and 504 DH lines (Crossa et al, 2013 ) by phenotyping in controlled water-stress condition.…”