Analysis of Global Gene Expression in Maize (Zea mays) Vegetative and Reproductive Tissues That Differ in Accumulation of Starch and Sucrose.

Carbon allocation between vegetative and reproductive tissues impacts cereal grain production. Despite great agricultural importance, sink-source relationships have not been fully characterized at the early reproductive stages in maize. Here, we quantify the accumulation of non-structural carbohydrates and patterns of gene expression in the top internode of the stem and the female inflorescence of maize at the onset of grain filling (reproductive stage R1). Top internode stem and female inflorescence tissues of the Puma maize inbred line were collected at reproductive stage R1 (without pollination) and non-structural carbohydrates were quantified by spectrophotometry. The female inflorescence accumulated starch at higher levels than the top internode of the stem. Global mRNA transcript levels were then evaluated in both tissues by RNA sequencing. Gene expression analysis identified 491 genes differentially expressed between the female inflorescence and the top stem internode. Gene ontology classification of differentially expressed genes showed enrichment for sucrose synthesis, the light-dependent reactions of photosynthesis, and transmembrane transporters. Our results suggest that sugar transporters play a key role in sugar partitioning in the maize stem and reveal previously uncharacterized differences between the female inflorescence and the top internode of the stem at early reproductive stages.

Estimation of physiological genomic estimated breeding values (PGEBV) combining full hyperspectral and marker data across environments for grain yield under combined heat and drought stress in tropical maize (Zea mays L.).

High throughput phenotyping technologies are lagging behind modern marker technology impairing the use of secondary traits to increase genetic gains in plant breeding. We aimed to assess whether the combined use of hyperspectral data with modern marker technology could be used to improve across location pre-harvest yield predictions using different statistical models. A maize bi-parental doubled haploid (DH) population derived from F1, which consisted of 97 lines was evaluated in testcross combination under heat stress as well as combined heat and drought stress during the 2014 and 2016 summer season in Ciudad Obregon, Sonora, Mexico (27°20" N, 109°54" W, 38 m asl). Full hyperspectral data, indicative of crop physiological processes at the canopy level, was repeatedly measured throughout the grain filling period and related to grain yield. Partial least squares regression (PLSR), random forest (RF), ridge regression (RR) and Bayesian ridge regression (BayesB) were used to assess prediction accuracies on grain yield within (two-fold cross-validation) and across environments (leave-one-environment-out-cross-validation) using molecular markers (M), hyperspectral data (H) and the combination of both (HM). Highest prediction accuracy for grain yield averaged across within and across location predictions (rGP) were obtained for BayesB followed by RR, RF and PLSR. The combined use of hyperspectral and molecular marker data as input factor on average had higher predictions for grain yield than hyperspectral data or molecular marker data alone. The highest prediction accuracy for grain yield across environments was measured for BayesB when molecular marker data and hyperspectral data were used as input factors, while the highest within environment prediction was obtained when BayesB was used in combination with hyperspectral data. It is discussed how the combined use of hyperspectral data with molecular marker technology could be used to introduce physiological genomic estimated breeding values (PGEBV) as a pre-harvest decision support tool to select genetically superior lines.

Genome-wide analysis of the invertase gene family from maize.

KEY MESSAGE: The recent release of the maize genome (AGPv4) contains annotation errors of invertase genes and therefore the enzymes are bestly curated manually at the protein level in a comprehensible fashion The synthesis, transport and degradation of sucrose are determining factors for biomass allocation and yield of crop plants. Invertase (INV) is a key enzyme of carbon metabolism in both source and sink tissues. Current releases of the maize genome correctly annotates only two vacuolar invertases (ivr1 and ivr2) and four cell wall invertases (incw1, incw2 (mn1), incw3, and incw4). Our comprehensive survey identified 21 INV isogenes for which we propose a standard nomenclature grouped phylogenetically by amino acid similarity: three vacuolar (INVVR), eight cell wall (INVCW), and ten alkaline/neutral (INVAN) isogenes which form separate dendogram branches due to distinct molecular features. The acidic enzymes were curated for the presence of the DPN tripeptide which is coded by one of the smallest exons reported in plants. Particular attention was placed on the molecular role of INV in vascular tissues such as the nodes, internodes, leaf sheath, husk leaves and roots. We report the expression profile of most members of the maize INV family in nine tissues in two developmental stages, R1 and R3. INVCW7, INVVR2, INVAN8, INVAN9, INVAN10, and INVAN3 displayed the highest absolute expressions in most tissues. INVVR3, INVCW5, INVCW8, and INVAN1 showed low mRNA levels. Expressions of most INVs were repressed from stage R1 to R3, except for INVCW7 which increased significantly in all tissues after flowering. The mRNA levels of INVCW7 in the vegetative stem correlated with a higher transport rate of assimilates from leaves to the cob which led to starch accumulation and growth of the female reproductive organs.

Genomic Selection Outperforms Marker Assisted Selection for Grain Yield and Physiological Traits in a Maize Doubled Haploid Population Across Water Treatments.

To increase genetic gain for tolerance to drought, we aimed to identify environmentally stable QTL in per se and testcross combination under well-watered (WW) and drought stressed (DS) conditions and evaluate the possible deployment of QTL using marker assisted and/or genomic selection (QTL/GS-MAS). A total of 169 doubled haploid lines derived from the cross between CML495 and LPSC7F64 and 190 testcrosses (tester CML494) were evaluated in a total of 11 treatment-by-population combinations under WW and DS conditions. In response to DS, grain yield (GY) and plant height (PHT) were reduced while time to anthesis and the anthesis silking interval (ASI) increased for both lines and hybrids. Forty-eight QTL were detected for a total of nine traits. The allele derived from CML495 generally increased trait values for anthesis, ASI, PHT, the normalized difference vegetative index (NDVI) and the green leaf area duration (GLAD; a composite trait of NDVI, PHT and senescence) while it reduced trait values for leaf rolling and senescence. The LOD scores for all detected QTL ranged from 2.0 to 7.2 explaining 4.4 to 19.4% of the observed phenotypic variance with R2 ranging from 0 (GY, DS, lines) to 37.3% (PHT, WW, lines). Prediction accuracy of the model used for genomic selection was generally higher than phenotypic variance explained by the sum of QTL for individual traits indicative of the polygenic control of traits evaluated here. We therefore propose to use QTL-MAS in forward breeding to enrich the allelic frequency for a few desired traits with strong additive QTL in early selection cycles while GS-MAS could be used in more mature breeding programs to additionally capture alleles with smaller additive effects.

A study of allelic diversity underlying flowering-time adaptation in maize landraces.

Landraces (traditional varieties) of domesticated species preserve useful genetic variation, yet they remain untapped due to the genetic linkage between the few useful alleles and hundreds of undesirable alleles. We integrated two approaches to characterize the diversity of 4,471 maize landraces. First, we mapped genomic regions controlling latitudinal and altitudinal adaptation and identified 1,498 genes. Second, we used F-one association mapping (FOAM) to map the genes that control flowering time, across 22 environments, and identified 1,005 genes. In total, we found that 61.4% of the single-nucleotide polymorphisms (SNPs) associated with altitude were also associated with flowering time. More than half of the SNPs associated with altitude were within large structural variants (inversions, centromeres and pericentromeric regions). The combined mapping results indicate that although floral regulatory network genes contribute substantially to field variation, over 90% of the contributing genes probably have indirect effects. Our dual strategy can be used to harness the landrace diversity of plants and animals.

Correction: Identification of QTL for Early Vigor and Stay-Green Conferring Tolerance to Drought in Two Connected Advanced Backcross Populations in Tropical Maize (Zea mays L.).

[This corrects the article DOI: 10.1371/journal.pone.0149636.].

Identification of QTL for Early Vigor and Stay-Green Conferring Tolerance to Drought in Two Connected Advanced Backcross Populations in Tropical Maize (Zea mays L.).

We aimed to identify quantitative trait loci (QTL) for secondary traits related to grain yield (GY) in two BC1F2:3 backcross populations (LPSpop and DTPpop) under well-watered (4 environments; WW) and drought stressed (6; DS) conditions to facilitate breeding efforts towards drought tolerant maize. GY reached 5.6 and 5.8 t/ha under WW in the LPSpop and the DTPpop, respectively. Under DS, grain yield was reduced by 65% (LPSpop) to 59% (DTPpop) relative to WW. GY was strongly associated with the normalized vegetative index (NDVI; r ranging from 0.61 to 0.96) across environmental conditions and with an early flowering under drought stressed conditions (r ranging from -0.18 to -0.25) indicative of the importance of early vigor and drought escape for GY. Out of the 105 detected QTL, 53 were overdominant indicative of strong heterosis. For 14 out of 18 detected vigor QTL, as well as for eight flowering time QTL the trait increasing allele was derived from CML491. Collocations of early vigor QTL with QTL for stay green (bin 2.02, WW, LPSpop; 2.07, DS, DTPpop), the number of ears per plant (bins 2.02, 2.05, WW, LPSpop; 5.02, DS, LPSpop) and GY (bin 2.07, WW, DTPpop; 5.04, WW, LPSpop), reinforce the importance of the observed correlations. LOD scores for early vigor QTL in these bins ranged from 2.2 to 11.25 explaining 4.6 (additivity: +0.28) to 19.9% (additivity: +0.49) of the observed phenotypic variance. A strong flowering QTL was detected in bin 2.06 across populations and environmental conditions explaining 26-31.3% of the observed phenotypic variation (LOD: 13-17; additivity: 0.1-0.6d). Improving drought tolerance while at the same time maintaining yield potential could be achieved by combining alleles conferring early vigor from the recurrent parent with alleles advancing flowering from the donor. Additionally bin 8.06 (DTPpop) harbored a QTL for GY under WW (additivity: 0.27 t/ha) and DS (additivity: 0.58 t/ha). R2 ranged from 0 (DTPpop, WW) to 26.54% (LPSpop, DS) for NDVI, 18.6 (LPSpop, WW) to 42.45% (LPSpop, DS) for anthesis and from 0 (DTPpop, DS) to 24.83% (LPSpop, WW) for GY. Lines out-yielding the best check by 32.5% (DTPpop, WW) to 60% (DTPpop, DS) for all population-by-irrigation treatment combination (except LPSpop, WW) identified are immediately available for the use by breeders.

Metabolic profiling of plant extracts using direct-injection electrospray ionization mass spectrometry allows for high-throughput phenotypic characterization according to genetic and environmental effects.

In comparison to the exponential increase of genotyping methods, phenotyping strategies are lagging behind in agricultural sciences. Genetic improvement depends upon the abundance of quantitative phenotypic data and the statistical partitioning of variance into environmental, genetic, and random effects. A metabolic phenotyping strategy was adapted to increase sample throughput while saving reagents, reducing cost, and simplifying data analysis. The chemical profiles of stem extracts from maize plants grown under low nitrogen (LN) or control trial (CT) were analyzed using optimized protocols for direct-injection electrospray ionization mass spectrometry (DIESI-MS). Specific ions significantly decreased or increased because of environmental (LN versus CT) or genotypic effects. Biochemical profiling with DIESI-MS had a superior cost-benefit compared to other standard analytical technologies (e.g., ultraviolet, near-infrared reflectance spectroscopy, high-performance liquid chromatography, and gas chromatography with flame ionization detection) routinely used for plant breeding. The method can be successfully applied in maize, strawberry, coffee, and other crop species.

Molecular mapping across three populations reveals a QTL hotspot region on chromosome 3 for secondary traits associated with drought tolerance in tropical maize.

Identifying quantitative trait loci (QTL) of sizeable effects that are expressed in diverse genetic backgrounds across contrasting water regimes particularly for secondary traits can significantly complement the conventional drought tolerance breeding efforts. We evaluated three tropical maize biparental populations under water-stressed and well-watered regimes for drought-related morpho-physiological traits, such as anthesis-silking interval (ASI), ears per plant (EPP), stay-green (SG) and plant-to-ear height ratio (PEH). In general, drought stress reduced the genetic variance of grain yield (GY), while that of morpho-physiological traits remained stable or even increased under drought conditions. We detected consistent genomic regions across different genetic backgrounds that could be target regions for marker-assisted introgression for drought tolerance in maize. A total of 203 QTL for ASI, EPP, SG and PEH were identified under both the water regimes. Meta-QTL analysis across the three populations identified six constitutive genomic regions with a minimum of two overlapping traits. Clusters of QTL were observed on chromosomes 1.06, 3.06, 4.09, 5.05, 7.03 and 10.04/06. Interestingly, a ~8-Mb region delimited in 3.06 harboured QTL for most of the morpho-physiological traits considered in the current study. This region contained two important candidate genes viz., zmm16 (MADS-domain transcription factor) and psbs1 (photosystem II unit) that are responsible for reproductive organ development and photosynthate accumulation, respectively. The genomic regions identified in this study partially explained the association of secondary traits with GY. Flanking single nucleotide polymorphism markers reported herein may be useful in marker-assisted introgression of drought tolerance in tropical maize.

Mapping of QTLs for lateral and axile root growth of tropical maize.

Maize genotypes may adapt to dry environments by avoiding desiccation by means of a deeper root system or by maintaining growth and water extraction at low water potentials. The aim of this study was to determine the quantitative genetic control of root growth and root morphology in a population of 236 recombinant inbred lines (RILs) from the cross between CML444 (high-yielding) x SC-Malawi (low-yielding), which segregates for the response to drought stress at flowering. The RILs and the parental lines were grown on blotting paper in growth pouches until the two-leaf stage under non-stressed conditions; the parents were additionally exposed to desiccation stress induced by polyethylene glycol with a molecular weight of 8000 Dalton (PEG-8000). The lengths of axile and lateral roots were measured non-destructively at 2, 5, 7 and 9 days after germination, by scanning with an A4 scanner followed by digital image analysis. CML444 had a lower rate constant of lateral root elongation (k(Lat)) than SC-Malawi, but the two genotypes did not differ in their response to desiccation. QTLs affecting root vigor, as depicted by increments in k(Lat), the elongation rate of axile roots (ER(Ax)) and the number of axile roots (No(Ax)) were identified in bins 2.04 and 2.05. QTLs for No(Ax) and ER(Ax) collocated with QTLs for yield parameters in bins 1.03-1.04 and 7.03-04. The correspondence of QTLs for axile root traits in bins 1.02-1.03 and 1.08 and QTLs for lateral roots traits in bins 2.04-2.07 in several mapping populations suggests the presence of genes controlling root growth in a wide range of genetic backgrounds.