Samuel Trachsel

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.

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.

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.

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.

Effects of planting density and nitrogen fertilization level on grain yield and harvest index in seven modern tropical maize hybrids (Zea mays L.)

To support tropical maize ( Zea mays L.) breeding efforts, the current work aimed to assess harvest index (HI) in modern hybrids and determine the effect of different planting densities on grain yield and HI under well-fertilized (HN) and nitrogen (N) deficient conditions. Harvest index and grain yield of 34 hybrids on average reached 0·42 and 7·06 t/ha (five environments), indicating a large potential for improvement in HI relative to temperate hybrids. Ear weight ( r = 0·88), HI ( r = 0·78) and shoot dry weight ( r = 0·68) were strongly associated with grain yield. In the second experiment, seven hybrids were evaluated at planting densities of 5, 7, 9 and 11 plants/m 2 under HN (six environments) and N deficient (LN) conditions (four environments) to assess the effect of planting density on grain yield and HI. Grain yield increased by 40·4 and 21·8% under HN and LN conditions when planting density was increased relative to the lowest planting density. Harvest index increased from 0·42 at 5 plants/m 2 to 0·45 at 11 plants/m 2 under HN conditions and decreased from 0·44 at 5 plants/m 2 to 0·42 at 9 plants/m 2 under LN conditions. Harvest index was maximized at planting densities of 8·33 plants/m 2 and 5·30 plants/m 2 under HN and LN conditions, respectively, while grain yield was maximized at 9·93 plants/m 2 and 7·89/m 2 . Optimal planting density maximizing both HI and grain yield were higher than planting densities currently used in tropical germplasm. It can be concluded that productivity in tropical maize could be increased both under intensive (+40·4%) and lower-input management (+21·8%) by increasing planting densities above those currently used in smallholder agriculture in Latin America and Sub-Saharan Africa, in environments targeted by the International Maize and Wheat Improvement Center.

Using an Airborne Platform to Measure Canopy Temperature and NDVI under Heat Stress in Maize

In light of anticipated climate change, we assessed the possibility to use an airborne platform to measure canopy temperature (CT) and the normalized differential vegetation index (NDVI) as well as the suitability of both traits for their use in breeding for tolerance to heat stress. We evaluated 71 subtropical maize (Zea mays L.) hybrids under heat stress and combined heat and drought stress in an environment with average temperatures of 29.8°C during the growing season and 31.2°C during the flowering period. Grain yield (GY) ranged from 0.33 to 4.19 Mg ha−1 under heat stress and from 0 to 1.37 Mg ha−1 under combined heat and drought stress, going along with increases in CT from 42.5°C to 49.5°C and decreases in NDVI from 0.54 to 0.48. The NDVI explained differences between and within treatments, while CT explained differences in GY among treatments and genotypes within the heat and drought stress treatment, as indicated by genetic correlations with GY. A principal component analysis was used to identify combinations of physiological characteristics associated with genotypic variation in GY. Results showed that selection gains for GY could be improved by 0.486 Mg ha−1 and 0.015 Mg ha−1 under heat and combined heat and drought stress, respectively, if selection is simultaneously carried out for GY, NDVI, and lower CT and shorter anthesis silking interval. We postulate that the use of selection indices, including CT and NDVI in conjunction with GY, will improve selection gains and increase cost efficiency of breeding programs.

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

Nat. Genet.; 10.1038/ng.3784; corrected online 20 February 2017 In the version of this article initially published online, the name of author Martha Willcox was misspelled as Martha Wilcox. The error has been corrected in the print, PDF and HTML versions of this article.

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.

Genome-wide analysis of the invertase gene family from maize

Key messageThe 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 fashionAbstractThe 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.

Stay-green and associated vegetative indices to breed maize adapted to heat and combined Heat-Drought Stresses

The objective of this study was to assess the importance of stay-green on grain yield under heat and combined heat and drought stress and to identify the associated vegetative indices allowing higher throughput in order to facilitate the identification of climate resilient germplasm. Hybrids of tropical and subtropical adaptation were evaluated under heat and combined heat and drought stress in 2014 and 2015. Five weekly measurements with an airplane mounted multispectral camera starting at anthesis were used to estimate the area under the curve (AUC) for vegetation indices during that period; the indices were compared to the AUC (AUCSEN) for three visual senescence scores taken two, four, and six weeks after flowering and a novel stay-green trait (AUC for stay-green; AUCSG) derived from AUCSEN by correcting for the flowering date. Heat and combined heat and drought stress reduced grain yield by 53% and 82% (relative to non-stress trials reported elsewhere) for trials carried out in 2014 and 2015, respectively, going along with lower AUCSG in 2014. The AUCSG was consistently correlated with grain yield across trials and years, reaching correlation coefficients of 0.55 and 0.56 for 2014 and 2015, respectively. The AUC for different vegetative indices, AUCNDVI (rgGY = 0.62; rgAUCSG = 0.72), AUCHBSI (rgGY = 0.64; rgAUCSG = 0.71), AUCGRE (rgGY = 0.57; rgAUCSG = 0.61), and AUCCWMI (rgGY = 0.63; rgAUCSG = 0.75), were associated with grain yield and stay-green across experiments and years. Due to its good correlation with grain yield and stay-green across environments, we propose AUCNDVI for use as an indicator for stay-green and a long grain filling. The trait AUCNDVI can be used in addition to grain yield to identify climate-resilient germplasm in tropical and subtropical regions to increase food security in a changing climate.