Root-ABA1 QTL affects root lodging, grain yield, and other agronomic traits in maize grown under well-watered and water-stressed conditions

A major QTL affecting root traits and leaf ABA concentration was identified in maize (Zea mays L.) and named root-ABA1. For this QTL, back-cross-derived lines (BDLs) homozygous either for the (+) or for the (-) allele increasing or decreasing, respectively, root size and leaf ABA concentration, were developed. This study was conducted to evaluate the QTL effects in various genetic backgrounds and at different water regimes. The (+/+) and (-/-) BDLs were crossed with five or 13 inbred tester lines of different origin, thus producing two sets of test-crosses that were evaluated in Italy and China, respectively. Testing was conducted under both well-watered and water-stressed conditions. In Italy, the test-crosses derived from (+/+) BDLs, as compared with those derived from (-/-) BDLs, showed, across both water regimes, higher leaf ABA concentration (on average 384 versus 351 ng g(-1) DW) and lower root lodging (28.0 versus 52.5%), and lower grain yield under water-stressed conditions (4.88 versus 6.27 Mg ha(-1)). In China, where root lodging did not occur, the test-crosses derived from (+/+) BDLs were less productive at both water regimes (on average, 6.83 versus 7.49 Mg ha(-1)). The lower grain yield of the test-crosses derived from (+/+) BDLs was due to a lower number of ears per plant and to lower kernel weight. The results indicate that the (+) root-ABA1 allele confers not only a consistently lower susceptibility to root lodging but also a lower grain yield, especially when root lodging does not occur.     

Validation and characterization of a major QTL affecting leaf ABA concentration in maize

A previous study conducted on a maize (Zea mays L.) mapping population derived from Os420 × IABO78 identified a quantitative trait locus (QTL) for leaf-abscisic acid concentration (L-ABA) on chromosome 2 (bin 2.04). In order to validate this QTL, we analyzed with RFLP markers 16 F₄ lines obtained by divergent selection for L-ABA from the same source. Three RFLPs mapping near bin 2.04 showed skewed allelic frequencies; the L-ABA increasing allele (+) was more frequent within the eight lines selected for high L-ABA, while the decreasing allele (–) was more frequent within the eight lines selected for low L-ABA. To characterize more accurately the direct and associated effects of this QTL, near-isogenic lines were developed by molecular marker-assisted back-crossing; four backcross-derived lines were homozygous (+/+) at the QTL and four were (–/–). A pair of near-isogenic hybrids (+/+) and (–/–) at the QTL were also produced. These materials were field tested under water-stressed and well-watered conditions. Across water regimes, the four (+/+) lines averaged a significantly higher mean value than the four (–/–) lines for L-ABA (494 vs. 396 ng ABA g^–1 DW) and a significantly lower mean value for relative water content (90.6 vs. 92.0%). The (+/+) hybrid exceeded the (–/–) for L-ABA (476 vs. 325 ng g^–1 DW) and was less affected by root lodging (44.6 vs. 66.1%). Our results validate the presence of a major QTL for L-ABA on bin 2.04 and indicate that the QTL also affects root traits and relative water content.     

QTL analysis of drought-related traits and grain yield in relation to genetic variation for leaf abscisic acid concentration in field-grown maize

Abscisic acid (ABA) concentration is a quantitatively inherited trait which plays a pivotal role in the response of plants to drought stress. A recent study identified 17 quantitative trait loci (QTLs) controlling bulk-leaf ABA concentration (L-ABA) in a maize (Zea mays L.) population of 80 F4 random families tested for two years under droughted field conditions. Sixteen of the QTL regions influencing L-ABA also harboured QTLs for one or more of the following traits: stomatal conductance, a drought sensitivity index, leaf temperature, leaf relative water content, anthesis-silking interval, and grain yield. The analysis of the effects of each QTL region on the investigated traits indicated that L-ABA mainly represented an indicator of the level of drought stress experienced by the plant at the time of sampling because an increase in L-ABA was most commonly associated with a decrease in both stomatal conductance and grain yield as well as an increase in leaf temperature. Opposite results were observed at one QTL region on chromosome 7 near the RFLP locus asg8. A model is presented to interpret these contrasting results in terms of pleiotropic effects.Key words: Abscisic acid, ABA, drought stress, quantitative trait locus (QTL), molecular markers, Zea mays.      

QTL mapping and epistasis analysis of brace root traits in maize

Root architecture is a major factor influencing root lodging, which limits greater yield stability at high planting density. Total brace root tier number (TBRTN) and effective brace root tier number (EBRTN) are the two most important root architecture traits influencing root lodging. However, the genetic mechanisms that underlie these traits remain poorly understood. In this study, quantitative trait loci (QTL) for TBRTN and EBRTN were mapped using a set of 201 recombinant inbred lines (RILs) and 278 immortalized F2 (IF2) populations derived from these RILs, which were evaluated in three environments. Ten QTL in the RILs and 15 QTL in the IF2 population were detected. In the two populations, we identified two coincident major QTL for TBRTN and a single identical major QTL for EBRTN. The QTL for TBRTN showed the largest additive effect, accounting for 16.36 and 17.88% of the phenotypic variance in the RILs and IF2 population, respectively. Additional epistatic effects were identified for all the maize chromosomes, except for chromosome 4. Most epistatic effects involved pairs of loci that were on different chromosomes. At the same time, we found loci that interacted simultaneously with several other loci to affect expression of the traits, which was particularly evident in the IF2 population. For example, qTAR1-2 interacted simultaneously with qTAR2-1, qTAR3-1, qTAR5-1, and qITAR8-2 to affect the expression of TBRTN. Therefore, a complex network controlling the traits was found in maize. These results provide useful information for understanding the molecular mechanisms controlling root architecture.     

Genetic dissection of maize seedling root system architecture traits using an ultra-high density bin-map and a recombinant inbred line population

Maize(Zea mays) root system architecture(RSA)mediates the key functions of plant anchorage and acquisition of nutrients and water. In this study,a set of 204 recombinant inbred lines(RILs) was derived from the widely adapted Chinese hybrid ZD958(Zheng58 Chang7-2),genotyped by sequencing(GBS) and evaluated as seedlings for 24 RSA related traits divided into primary,seminal and total root classes. Signi ficant differences between the means of the parental phenotypes were detected for 18 traits,and extensive transgressive segregation in the RIL population was observed for all traits. Moderate to strong relationships among the traits were discovered. A total of 62 quantitative trait loci(QTL) were identi fied that individually explained from1.6% to 11.6%(total root dry weight/total seedling shoot dry weight) of the phenotypic variation. Eighteen,24 and 20 QTL were identi fied for primary,seminal and total root classes of traits,respectively. We found hotspots of 5,3,4 and 12 QTL in maize chromosome bins 2.06,3.02-03,9.02-04,and 9.05-06,respectively,implicating the presence of root gene clusters or pleiotropic effects. These results characterized the phenotypic variation and genetic architecture of seedling RSA in a population derived from a successful maize hybrid.     

Dynamic QTL and epistasis analysis on seedling root traits in upland cotton

Roots are involved in acquisition of water and nutrients, as well as in providing structural support to plant. The root system provides a dynamic model for developmental analysis. Here, we investigated quantitative trait loci (QTL), dynamic conditional QTL and epistatic interactions for seedling root traits using an upland cotton F₂ population and a constructed genetic map. Totally, 37 QTLs for root traits, 35 dynamic conditional QTLs based on the net increased amount of root traits (root tips, forks, length, surface area and volume) (i) after transplanting 10 days compared to 5 days, and (ii) after transplanting 15 days to 10 days were detected. Obvious dynamic characteristic of QTL and dynamic conditional QTL existed at different developmental stages of root because QTL and dynamic conditional QTL had not been detected simultaneously. We further confirmed that additive and dominance effects of QTL qRSA-chr1-1 in interval time 5 to 10 DAT (days after transplant) offset the effects in 10 to 15 DAT. Lots of two-locus interactions for root traits were identified unconditionally or dynamically, and a few epistatic interactions were only detected simultaneously in interval time of 5–10 DAT and 10–15 DAT, suggesting different interactive genetic mechanisms on root development at different stages. Dynamic conditional QTL and epistasis effects provide new attempts to understand the dynamics of roots and provide clues for root architecture selection in upland cotton.     

Quantitative trait loci for rooting pattern traits of common beans grown under drought stress versus non-stress conditions

Drought is the major abiotic constraint contributing to yield reduction in common bean (Phaseolus vulgaris L.) worldwide. An increasing scarcity of water in the future will make improving adaptation to drought stress a major objective of most crop breeding efforts. Drought avoidance by increased extraction of soil moisture from greater depth under drought conditions is an adaptive mechanism of common bean. A recombinant inbred line population of DOR364?×?BAT477 was evaluated for rooting pattern traits in soil cylinder tubes under soil drying (progressive water stress) and non-stress (well-watered with 80% of field capacity) treatments in a greenhouse. One of the parents, BAT 477, is a deep-rooting genotype while the other parent, DOR 364, is a commercial cultivar in Central America. The recombinant inbred line population expressed quantitative variation and transgressive segregation for ten rooting pattern traits as well as five shoot traits of 48-day-old plants. A mixed model quantitative trait locus (QTL) mapping analysis was carried out using a genetic map constructed with 165 genetic markers that covered 11 linkage groups of the common bean genome. Genotype estimates were calculated from best design and spatial effects model for each trait. A total of 15 putative QTL were identified for seven rooting pattern traits and four shoot traits. The QTL detected were scattered over five of the 11 linkage groups. The QTL detected for all the root traits except total root length and fine root length were main effect QTL and did not interact with the level of water supply. The total root length and fine root length QTL with significant QTL?×?environment interaction only differed in magnitude of effect, and interaction was of a non-crossover type. Other QTL for total root length, fine roots, thick roots, root volume and root biomass were co-localized and also explained relatively more genetic variance. This suggests that the QTL affecting root traits in common beans are based on constitutive expression of genes and that drought avoidance based on deep rooting, longer root length, thicker roots, increasing root length distribution with depth, root volume and root biomass can be used in molecular breeding. The positive alleles for most of the QTL detected in this study were derived from the paternal parent BAT477. The results from the present analyses highlighted the feasibility of marker-aided selection as an alternative to conventional labor-intensive, phenotypic screening of drought avoidance root traits.     

QTL for root angle and number in a population developed from bread wheats (Triticum aestivum) with contrasting adaptation to water-limited environments

Root architecture traits in wheat are important in deep soil moisture acquisition and may be used to improve adaptation to water-limited environments. The genetic architecture of two root traits, seminal root angle and seminal root number, were investigated using a doubled haploid population derived from SeriM82 and Hartog. Multiple novel quantitative trait loci (QTL) were identified, each one having a modest effect. For seminal root angle, four QTL (?log₁₀(P) >3) were identified on 2A, 3D, 6A and 6B, and two suggestive QTL (?log₁₀(P) >2) on 5D and 6B. For root number, two QTL were identified on 4A and 6A with four suggestive QTL on 1B, 3A, 3B and 4A. QTL for root angle and root number did not co-locate. Transgressive segregation was found for both traits. Known major height and phenology loci appear to have little effect on root angle and number. Presence or absence of the T1BL.1RS translocation did not significantly influence root angle. Broad sense heritability (h ²) was estimated as 50 % for root angle and 31 % for root number. Root angle QTL were found to be segregating between wheat cultivars adapted to the target production region indicating potential to select for root angle in breeding programs.     

Mapping and validation of quantitative trait loci for resistance to Cercospora zeae-maydis infection in tropical maize (Zea mays L.)

Breeding for resistance to gray leaf spot, caused by Cercospora zeae-maydis (Cz) is paramount for many maize environments, in particular under warm and humid growing conditions. In this study, we mapped and characterized quantitative trait loci (QTL) involved in the resistance of maize against Cz. We confirmed the impact of the QTL on disease severity using near-isogenic lines (NILs), and estimated their effects on three major agronomic traits using their respective near isogenic hybrids (NIHs), which we obtained by crossing the NILs with an inbred from a complementary heterotic pool. We further validated three of the four QTL that were mapped using the Multiple Interval Mapping approach and showed LOD values >2.5. NILs genotype included all combinations between favorable alleles of the two QTL located in chromosome 1 (Q ₁ in bin 1.05 and Q ₂ in bin 1.07), and the allele in chromosome 3 (Q ₃ in bin 3.07). Each of the three QTL separately significantly reduced the severity of Cz. However, we found an unfavorable epistatic interaction between Q ₁ and Q ₂: presence of the favorable allele at one of the QTL allele effectively nullified the effect of the favorable allele at the other. In contrast, the interaction between Q ₂ and Q ₃ was additive, promoting the reduction of the severity to a greater extent than the sum of their individual effects. When evaluating the NIH we found significant individual effects for Q ₁ and Q ₃ on gray leaf spot severity, for Q ₂ on stalk lodging and grain yield, and for Q ₃ on grain moisture and stalk lodging. We detected significant epitasis between Q ₁ and Q ₂ for grain moisture and between Q ₁ and Q ₃ for stalk lodging. These results suggest that the combination of QTL impacts the effectiveness of marker-assisted selection procedures in commercial product development programs.     

Identification of QTLs associated with agronomic performance under nitrogen-deficient conditions using chromosome segment substitution lines of a wild rice relative, <Emphasis Type="Italic">Oryza rufipogon</Emphasis>

Improved root system architecture can enhance agronomic performance by increasing water and nitrogen (N) acquisition efficiency. However, little is known about interaction between root system architecture and agronomic performance under field environments. To gain a better understanding about the genetic basis of these relationships, we evaluated a set of chromosome segment substitution lines (CSSLs) derived from crosses between a tropical japonica rice cultivar ‘Curinga’ and a wild species Oryza rufipogon accession IRGC105491. Root system architectural traits were investigated using the CSSLs at 40 days old seedlings using the root basket method under hydroponic conditions, and agronomic performances were also tested under field conditions with different N treatments. Agronomic performances were computed as the ratio of a trait value under low to high N treatments, including grain yield and biomass yield as nitrogen-deficiency tolerance (NDT) traits. Root architecture and NDT trait QTLs were mapped using 238 SNP marker loci. A total of 13 QTLs for root system architectural, NDT and morpho-physiological traits were identified on chromosomes 1, 3, 4, 5, 7, 8, 9, 10 and 12. Interestingly, a QTL for deeper root number was identified the region of SNP markers between id1012330 and id1021697 on chromosome 1 under hydroponic conditions overlapped with a QTL for NDT trait of relative grain yield (qRGY1). These results suggest that deeper root trait is helpful to maintain grain yield under nitrogen-deficient conditions. The QTL associated root architecture could potentially be used in future rice-breeding efforts to increase agronomic performance under nitrogen-deficient conditions.     

Combining QTL and candidate gene analysis with phenotypic model to unravel the relationship between lodging and related traits in soybean

Lodging is one of the major influencing factors of yield and quality in soybean [Glycine max (L.) Merr.] and other crops. To dissect the genetic basis of lodging in soybean, a recombinant inbred line population consisting of 165 lines was used to evaluate lodging percentage and eight related traits (branch number, internode length, number of nodes, plant height, stem diameter, stem strength, root length, and root weight) in three environments. Regression analysis indicated that plant height and root weight, which explain more than 55% of the variation in lodging percentage, might be the key factors influencing lodging in soybean. Nine consensus quantitative trait locus (QTLs) of lodging percentage were detected in one to three environments. Of which, eight consensus QTLs were colocated with 16 consensus QTLs of lodging-related traits by meta-analysis. In addition, seven candidate genes with the biological functions of shoot branching, root development, internode elongation, and lignin biosynthesis were identified on four pleiotropic QTL regions (oq.13-1, oq.13-2, oq.19-2, and oq.19-3) for lodging percentage and related traits. These findings showed that the consensus QTLs of lodging percentage might result from the pleiotropic QTLs affecting the lodging-related traits. Soybean lodging is determined by the cumulative effect of many traits/processes of growth and development. The combination of MAS, statistical model, and phenotypic selection will provide a powerful breeding strategy for lodging resistance in soybean.     

Genetic basis of phenotypic correlations among growth traits in hybrid willow (Salix dasycladosxS. viminalis) grown under two water regimes

Phenotypic correlations and quantitative trait loci (QTL) for important growth traits and a surrogate of intrinsic water-use efficiency (leaf delta(13)C) were analysed in a willow pedigree of 92 full-sibling clones grown under two water regimes. The major objective was to examine the genetic basis of the phenotypic correlations. Cuttings of Salix were glasshouse-grown during one growing season. The relative growth rate (RGR) and underlying traits were assessed. QTL analysis was conducted based on an available linkage map for Salix. Leaf area productivity and leaf nitrogen productivity were more important in determining RGR than leaf area ratio and specific leaf area. However, phenotypic correlations among growth traits partly varied between the two environments. QTL were detected for most growth traits, among them many common QTL for different traits. The QTL pattern reflected the phenotypic correlation pattern. None of the QTL for the complex traits was consistent across the different environments. The results demonstrate a genetic basis for phenotypic correlations among growth traits in Salix, and provide evidence for the existence of 'master switches' regulating some of the traits.     

Assessing the importance of genotype x environment interaction for root traits in rice using a mapping population. I: a soil-filled box screen

Altering root system architecture is considered a method of improving crop water and soil nutrient capture. The analysis of quantitative trait loci (QTLs) for root traits has revealed inconsistency in the same population evaluated in different environments. It must be clarified if this is due to genotype × environment interaction or considerations of statistics if the value of QTLs for marker-assisted breeding is to be estimated. A modified split-plot design was used where a main plot corresponded to a separate experiment. The main plot factor had four treatments (environments), which were completely randomized among eight trials, so that each treatment was replicated twice. The sub-plot factor consisted of 168 recombinant inbreed lines of the Bala × Azucena rice mapping population, randomly allocated to the seven soil-filled boxes. The aim of the trial was to quantify QTL × environment interaction. The treatments were chosen to alter partitioning to roots; consisting of a control treatment (high-soil nitrogen, high light and high-water content) and further treatments where light, soil nitrogen or soil water was reduced singly. After 4 weeks growth, maximum root length (MRL), maximum root thickness, root mass below 50 cm, total plant dry mass (%), root mass and shoot length were measured. The treatments affected plant growth as predicted; low nitrogen and drought increased relative root partitioning, low-light decreased it. The parental varieties Bala and Azucena differed significantly for all traits. Broad-sense heritability of most traits was high (57–86%). Variation due to treatment was the most important influence on the variance, while genotype was next. Genotype × environment interaction was detected for all traits except MRL, although the proportion of variation due to this interaction was generally small. It is concluded that genotype × environment interaction is present but less important than genotypic variation. A companion paper presents QTL × environment analysis of data.     

Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat

A high-resolution chromosome arm-specific mapping population was used in an attempt to locate/detect gene(s)/QTL for different root traits on the short arm of rye chromosome 1 (1RS) in bread wheat. This population consisted of induced homoeologous recombinants of 1RS with 1BS, each originating from a different crossover event and distinct from all other recombinants in the proportions of rye and wheat chromatin present. It provides a simple and powerful approach to detect even small QTL effects using fewer progeny. A promising empirical Bayes method was applied to estimate additive and epistatic effects for all possible marker pairs simultaneously in a single model. This method has an advantage for QTL analysis in minimizing the error variance and detecting interaction effects between loci with no main effect. A total of 15 QTL effects, 6 additive and 9 epistatic, were detected for different traits of root length and root weight in 1RS wheat. Epistatic interactions were further partitioned into inter-genomic (wheat and rye alleles) and intra-genomic (rye–rye or wheat–wheat alleles) interactions affecting various root traits. Four common regions were identified involving all the QTL for root traits. Two regions carried QTL for almost all the root traits and were responsible for all the epistatic interactions. Evidence for inter-genomic interactions is provided. Comparison of mean values supported the QTL detection.     

RFLP mapping of quantitative trait loci controlling abscisic acid concentration in leaves of drought-stressed maize (Zea mays L.)

 Abscisic acid (ABA) concentration in leaves of drought-stressed plants is a quantitatively inherited trait. In order to identify quantitative trait loci (QTLs) controlling leaf ABA concentration (L-ABA) in maize, leaf samples were collected from 80 F_3:4 families of the cross Os420 (high L-ABA)×IABO78 (low L-ABA) tested under drought conditions in field trials conducted over 2 years. In each year, leaf samples were collected at stem elongation and near anthesis. The genetic map obtained with 106 restriction fragment length polymorphism (RFLP) loci covered 1370 cM, which represented approximately 85% of the UMC maize map. Sixteen different QTLs with a LOD>2.0 were revealed in at least one sampling. Across samplings, only four QTLs significantly influenced L-ABA, accounting for 66% of the phenotypic variation and 76% of the genetic variation among families. At these QTLs, the alleles which increased L-ABA were contributed by Os420. The two most important QTLs were mapped on chromosome 2 near csu133 and csu109a. The effects associated with the QTL near csu133 were more pronounced near anthesis. The support intervals of the four primary QTLs for L-ABA did not overlap the presumed map position of mutants impaired in ABA biosynthesis. Received: 27 January 1998 / Accepted: 22 April 1998     

Paths to selection on life history loci in different natural environments across the native range of Arabidopsis thaliana

Selection on quantitative trait loci (QTL) may vary among natural environments due to differences in the genetic architecture of traits, environment‐specific allelic effects or changes in the direction and magnitude of selection on specific traits. To dissect the environmental differences in selection on life history QTL across climatic regions, we grew a panel of interconnected recombinant inbred lines (RILs) of Arabidopsis thaliana in four field sites across its native European range. For each environment, we mapped QTL for growth, reproductive timing and development. Several QTL were pleiotropic across environments, three colocalizing with known functional polymorphisms in flowering time genes (CRY2, FRI and MAF2‐5), but major QTL differed across field sites, showing conditional neutrality. We used structural equation models to trace selection paths from QTL to lifetime fitness in each environment. Only three QTL directly affected fruit number, measuring fitness. Most QTL had an indirect effect on fitness through their effect on bolting time or leaf length. Influence of life history traits on fitness differed dramatically across sites, resulting in different patterns of selection on reproductive timing and underlying QTL. In two oceanic field sites with high prereproductive mortality, QTL alleles contributing to early reproduction resulted in greater fruit production, conferring selective advantage, whereas alleles contributing to later reproduction resulted in larger size and higher fitness in a continental site. This demonstrates how environmental variation leads to change in both QTL effect sizes and direction of selection on traits, justifying the persistence of allelic polymorphism at life history QTL across the species range.     

Quantitative trait loci affecting survival and fertility-related traits in Caenorhabditis elegans show genotype-environment interactions, pleiotropy and epistasis.

We have identified, using composite interval mapping, quantitative trait loci (QTL) affecting a variety of life history traits (LHTs) in the nematode Caenorhabditis elegans. Using recombinant inbred strains assayed on the surface of agar plates, we found QTL for survival, early fertility, age of onset of sexual maturity, and population growth rate. There was no overall correlation between survival on solid media and previous measures of survival in liquid media. Of the four survival QTL found in these two environments, two have genotype-environment interactions (GEIs). Epistatic interactions between markers were detected for four traits. A multiple regression approach was used to determine which single markers and epistatic interactions best explained the phenotypic variance for each trait. The amount of phenotypic variance accounted for by genetic effects ranged from 13% (for internal hatching) to 46% (for population growth). Epistatic effects accounted for 9-11% of the phenotypic variance for three traits. Two regions containing QTL that affected more than one fertility-related trait were found. This study serves as an example of the power of QTL mapping for dissecting the genetic architecture of a suite of LHTs and indicates the potential importance of environment and GEIs in the evolution of this architecture.     

QTL Mapping of Agronomic Waterlogging Tolerance Using Recombinant Inbred Lines Derived from Tropical Maize (Zea mays L) Germplasm

Waterlogging is an important abiotic stress constraint that causes significant yield losses in maize grown throughout south and south-east Asia due to erratic rainfall patterns. The most economic option to offset the damage caused by waterlogging is to genetically incorporate tolerance in cultivars that are grown widely in the target agro-ecologies. We assessed the genetic variation in a population of recombinant inbred lines (RILs) derived from crossing a waterlogging tolerant line (CAWL-46-3-1) to an elite but sensitive line (CML311-2-1-3) and observed significant range of variation for grain yield (GY) under waterlogging stress along with a number of other secondary traits such as brace roots (BR), chlorophyll content (SPAD), % stem and root lodging (S&RL) among the RILs. Significant positive correlation of GY with BR and SPAD and negative correlation with S&RL indicated the potential use of these secondary traits in selection indices under waterlogged conditions. RILs were genotyped with 331 polymorphic single nucleotide polymorphism (SNP) markers using KASP (Kompetitive Allele Specific PCR) Platform. QTL mapping revealed five QTL on chromosomes 1, 3, 5, 7 and 10, which together explained approximately 30% of phenotypic variance for GY based on evaluation of RIL families under waterlogged conditions, with effects ranging from 520 to 640 kg/ha for individual genomic regions. 13 QTL were identified for various secondary traits associated with waterlogging tolerance, each individually explaining from 3 to 14% of phenotypic variance. Of the 22 candidate genes with known functional domains identified within the physical intervals delimited by the flanking markers of the QTL influencing GY and other secondary traits, six have previously been demonstrated to be associated with anaerobic responses in either maize or other model species. A pair of flanking SNP markers has been identified for each of the QTL and high throughput marker assays were developed to facilitate rapid introgression of waterlogging tolerance in tropical maize breeding programs.