Genotypic and phenotypic characterization of a large, diverse population of maize near-isogenic lines.

Genome-wide association (GWA) studies can identify quantitative trait loci (QTL) putatively underlying traits of interest, and nested association mapping (NAM) can further assess allelic series. Near-isogenic lines (NILs) can be used to characterize, dissect and validate QTL, but the development of NILs is costly. Previous studies have utilized limited numbers of NILs and introgression donors. We characterized a panel of 1270 maize NILs derived from crosses between 18 diverse inbred lines and the recurrent inbred parent B73, referred to as the nested NILs (nNILs). The nNILs were phenotyped for flowering time, height and resistance to three foliar diseases, and genotyped with genotyping-by-sequencing. Across traits, broad-sense heritability (0.4-0.8) was relatively high. The 896 genotyped nNILs contain 2638 introgressions, which span the entire genome with substantial overlap within and among allele donors. GWA with the whole panel identified 29 QTL for height and disease resistance with allelic variation across donors. To date, this is the largest and most diverse publicly available panel of maize NILs to be phenotypically and genotypically characterized. The nNILs are a valuable resource for the maize community, providing an extensive collection of introgressions from the founders of the maize NAM population in a B73 background combined with data on six agronomically important traits and from genotyping-by-sequencing. We demonstrate that the nNILs can be used for QTL mapping and allelic testing. The majority of nNILs had four or fewer introgressions, and could readily be used for future fine mapping studies.

Fine mapping of a quantitative resistance gene for gray leaf spot of maize (Zea mays L.) derived from teosinte (Z. mays ssp. parviglumis).

KEY MESSAGE: In this study we mapped the QTL Qgls8 for gray leaf spot (GLS) resistance in maize to a ~130 kb region on chromosome 8 including five predicted genes. In previous work, using near isogenic line (NIL) populations in which segments of the teosinte (Zea mays ssp. parviglumis) genome had been introgressed into the background of the maize line B73, we had identified a QTL on chromosome 8, here called Qgls8, for gray leaf spot (GLS) resistance. We identified alternate teosinte alleles at this QTL, one conferring increased GLS resistance and one increased susceptibility relative to the B73 allele. Using segregating populations derived from NIL parents carrying these contrasting alleles, we were able to delimit the QTL region to a ~130 kb (based on the B73 genome) which encompassed five predicted genes.

Validation and Characterization of Maize Multiple Disease Resistance QTL.

Southern Leaf Blight, Northern Leaf Blight, and Gray Leaf Spot, caused by ascomycete fungi, are among the most important foliar diseases of maize worldwide. Previously, disease resistance quantitative trait loci (QTL) for all three diseases were identified in a connected set of chromosome segment substitution line (CSSL) populations designed for the identification of disease resistance QTL. Some QTL for different diseases co-localized, indicating the presence of multiple disease resistance (MDR) QTL. The goal of this study was to perform an independent test of several of the MDR QTL identified to confirm their existence and derive a more precise estimate of allele additive and dominance effects. Twelve F2:3 family populations were produced, in which selected QTL were segregating in an otherwise uniform genetic background. The populations were assessed for each of the three diseases in replicated trials and genotyped with markers previously associated with disease resistance. Pairwise phenotypic correlations across all the populations for resistance to the three diseases ranged from 0.2 to 0.3 and were all significant at the alpha level of 0.01. Of the 44 QTL tested, 16 were validated (identified at the same genomic location for the same disease or diseases) and several novel QTL/disease associations were found. Two MDR QTL were associated with resistance to all three diseases. This study identifies several potentially important MDR QTL and demonstrates the importance of independently evaluating QTL effects following their initial identification.

Using Maize Chromosome Segment Substitution Line Populations for the Identification of Loci Associated with Multiple Disease Resistance.

Southern Leaf Blight (SLB), Northern Leaf Blight (NLB), and Gray Leaf Spot (GLS) caused by Cochliobolus heterostrophus, Setosphaeria turcica, and Cercospora zeae-maydis respectively, are among the most important diseases of corn worldwide. Previously, moderately high and significantly positive genetic correlations between resistance levels to each of these diseases were identified in a panel of 253 diverse maize inbred lines. The goal of this study was to identify loci underlying disease resistance in some of the most multiple disease resistant (MDR) lines by the creation of chromosome segment substitution line (CSSL) populations in multiple disease susceptible (MDS) backgrounds. Four MDR lines (NC304, NC344, Ki3, NC262) were used as donor parents and two MDS lines (Oh7B, H100) were used as recurrent parents to produce eight BC3F4:5 CSSL populations comprising 1,611 lines in total. Each population was genotyped and assessed for each disease in replicated trials in two environments. Moderate to high heritabilities on an entry mean basis were observed (0.32 to 0.83). Several lines in each population were significantly more resistant than the MDS parental lines for each disease. Multiple quantitative trait loci (QTL) for disease resistance were detected for each disease in most of the populations. Seventeen QTL were associated with variation in resistance to more than one disease (SLB/NLB: 2; SLB/GLS: 7; NLB/GLS: 2 and 6 to all three diseases). For most populations and most disease combinations, significant correlations were observed between disease scores and also between marker effects for each disease. The number of lines that were resistant to more than one disease was significantly higher than would be expected by chance. Using the results from individual QTL analyses, a composite statistic based on Mahalanobis distance (Md) was used to identify joint marker associations with multiple diseases. Across all populations and diseases, 246 markers had significant Md values. However further analysis revealed that most of these associations were due to strong QTL effects on a single disease. Together, these findings reinforce our previous conclusions that loci associated with resistance to different diseases are clustered in the genome more often than would be expected by chance. Nevertheless true MDR loci which have significant effects on more than one disease are still much rarer than loci with single disease effects.