Mean, variance and heritability estimates for parental lines and RIL families based on evaluation under waterlogging conditions.

<p>WLT—Waterlogging tolerant parent (CML311-2-1-3); WST—Waterlogging sensitive parent (CAWL-46-3-1); H—Heritability (Broad sense) estimate.</p><p>Mean, variance and heritability estimates for parental lines and RIL families based on evaluation under waterlogging conditions.</p

Linkage groups along with QTL identified for traits associated with waterlogging tolerance using RIL and TC phenotypes (R_: Identified using RIL dataset, T_: Identified using TC data set, Traits: GY—Grain yield, RL—Root lodging, SL—Stem lodging, BR—Brace roots, M—Plant Mortality %, CC—Chlorophyll content, ASI—Anthesis-Silking interval).

<p>Linkage groups along with QTL identified for traits associated with waterlogging tolerance using RIL and TC phenotypes (R_: Identified using RIL dataset, T_: Identified using TC data set, Traits: GY—Grain yield, RL—Root lodging, SL—Stem lodging, BR—Brace roots, M—Plant Mortality %, CC—Chlorophyll content, ASI—Anthesis-Silking interval).</p

QTL identified for waterlogging tolerance using RIL phenotypes.

<p>QTL identified for waterlogging tolerance using RIL phenotypes.</p

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

<div><p>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.</p></div

QTL identified for waterlogging tolerance using RIL test cross phenotypes.

<p>QTL identified for waterlogging tolerance using RIL test cross phenotypes.</p

Grain yield (GY) for the best lines and best check (CML312/CML444) measured in the LPSpop (LPS) and DTPpop (DTP) under well-watered and drought stressed conditions.

<p>Grain yield (GY) for the best lines and best check (CML312/CML444) measured in the LPSpop (LPS) and DTPpop (DTP) under well-watered and drought stressed conditions.</p

Summary table of all non-overdominant QTL measured in the DTPpop (DTP) and LPSpop (LPS) population under well-watered (WW) and drought stressed (DS) conditions showing position (Pos), bin, flanking markers, LOD scores, phenotypic variance explained by a QTL (PVE), additive and dominance effects.

<p>Traits measured are senescence measured 4 (SEN4) and 6 (SEN6) weeks after flowering, NDVI, grain yield (GY), ears per plants (EPP), anthesis, the anthesis silking interval (ASI) and plant height (PHT).</p

Most important QTL for vigor, flowering and grain yield identified in well-watered (blue font) and drought stressed conditions (red font) in bins 2.02, 2.05, 2.06, 2.07, 5.02, 5.04 and 8.06 in the LPSpop and DTPpop, collocations with QTL for related traits in other studies and underlying candidate genes.

<p>Most important QTL for vigor, flowering and grain yield identified in well-watered (blue font) and drought stressed conditions (red font) in bins 2.02, 2.05, 2.06, 2.07, 5.02, 5.04 and 8.06 in the LPSpop and DTPpop, collocations with QTL for related traits in other studies and underlying candidate genes.</p

Phenotypic (Pheno) and genotypic (Geno) correlations between grain yield and senescence measured 4 (SEN4) and 6 (SEN6) weeks after flowering, the numbers of ears per plant (EPP), NDVI4, the anthesis silking interval (ASI), plant height (PHT) and anthesis.

<p>Phenotypic (Pheno) and genotypic (Geno) correlations between grain yield and senescence measured 4 (SEN4) and 6 (SEN6) weeks after flowering, the numbers of ears per plant (EPP), NDVI4, the anthesis silking interval (ASI), plant height (PHT) and anthesis.</p

Summary table of all overdominant QTL measured in the DTPpop (DTP) and LPSpop (LPS) under well-watered (WW) and drought stressed (DS) conditions showing position (Pos), bin, flanking markers, LOD scores, phenotypic variance explained by a QTL (PVE), additive and dominance effects.

<p>Traits measured are senescence 4 (SEN4) and 6 (SEN6) weeks after flowering, NDVI, grain yield (GY), ears per plants (EPP), anthesis, the anthesis silking interval (ASI) and plant height (PHT).</p