Search

With a changing climate and a growing population, the world increasingly needs more-productive and resilient crops. But improving them requires a knowledge of what actually works in the field. [ABSTRACT FROM AUTHOR]

Key message: A novel locus was discovered on chromosome 7 associated with a lesion mimic in maize; this lesion mimic had a quantitative and heritable phenotype and was predicted better via subset genomic markers than whole genome markers across diverse environments. Lesion mimics are a phenotype of leaf micro-spotting in maize (Zea mays L.), which can be early signs of biotic or abiotic stresses. Dissecting its inheritance is helpful to understand how these loci behave across different genetic backgrounds. Here, 538 maize recombinant inbred lines (RILs) segregating for a novel lesion mimic were quantitatively phenotyped in Georgia, Texas, and Wisconsin. These RILs were derived from three bi-parental crosses using a tropical pollinator (Tx773) as the common parent crossed with three inbreds (LH195, LH82, and PB80). While this lesion mimic was heritable across three environments based on phenotypic ( H p = 0.68) and genomic ( H g = 0.91) data, transgressive segregation was observed. A genome-wide association study identified a single novel locus on chromosome 7 (at 70.6 Mb) also covered by a quantitative trait locus interval (69.3–71.0 Mb), explaining 11–15% of the variation, depending on the environment. One candidate gene identified in this region, Zm00001eb308070, is related to the abscisic acid pathway involving in cell death. Genomic predictions were applied to genome-wide markers (39,611 markers) contrasted with a marker subset (51 markers). Population structure explained more variation than environment in genomic prediction, but other substantial genetic background effects were additionally detected. Subset markers explained substantially less genetic variation (24.9%) for the lesion mimic than whole genome markers (55.4%) in the model, yet predicted the lesion mimic better (0.56–0.66 vs. 0.26–0.29). These results indicate this lesion mimic phenotype was less affected by environment than by epistasis and genetic background effects, which explain its transgressive segregation. [ABSTRACT FROM AUTHOR]

Key message: Significant introgression-by-environment interactions are observed for traits throughout development from small introgressed segments of the genome. Relatively small genomic introgressions containing quantitative trait loci can have significant impacts on the phenotype of an individual plant. However, the magnitude of phenotypic effects for the same introgression can vary quite substantially in different environments due to introgression-by-environment interactions. To study potential patterns of introgression-by-environment interactions, fifteen near-isogenic lines (NILs) with > 90% B73 genetic background and multiple Mo17 introgressions were grown in 16 different environments. These environments included five geographical locations with multiple planting dates and multiple planting densities. The phenotypic impact of the introgressions was evaluated for up to 26 traits that span different growth stages in each environment to assess introgression-by-environment interactions. Results from this study showed that small portions of the genome can drive significant genotype-by-environment interaction across a wide range of vegetative and reproductive traits, and the magnitude of the introgression-by-environment interaction varies across traits. Some introgressed segments were more prone to introgression-by-environment interaction than others when evaluating the interaction on a whole plant basis throughout developmental time, indicating variation in phenotypic plasticity throughout the genome. Understanding the profile of introgression-by-environment interaction in NILs is useful in consideration of how small introgressions of QTL or transgene containing regions might be expected to impact traits in diverse environments. [ABSTRACT FROM AUTHOR]

White spot is an important maize disease, prevalent in most high production tropical regions with a severe negative impact in grain yield. Breeding for white spot resistance is the most effective mechanism to control the disease. The objectives of this research include identifying and mapping chromosomal regions and putative genes associated to the maize response to white spot. We performed an association mapping with phenotypic data collected in two environments located at South region of Brazil, and by using a set of 355,972 high-quality single nucleotide polymorphism markers in a panel composed by 183 tropical field corn and popcorn inbred lines. Nine SNPs were significantly associated with white spot, five of them co-localized on previously reported quantitative trait loci regions, while remaining regions are novel. The total phenotypic variance explained (r2) by the nine SNPs associated with white spot severity was 64.3%, while the variance explained by each SNP ranged from 0.72 to 25.54%. The identified putative gene models are promising candidates associated with white spot resistance. Once these SNPs were validated, they can be useful for selecting superior genotypes. [ABSTRACT FROM AUTHOR]

Key message : Capitalizing upon the genomic characteristics of long-term random mating populations, sampling from pre-selected landraces is a promising approach for broadening the genetic base of elite germplasm for quantitative traits. Abstract: Genome-enabled strategies for harnessing untapped allelic variation of landraces are currently evolving. The success of such approaches depends on the choice of source material. Thus, the analysis of different strategies for sampling allelic variation from landraces and their impact on population diversity and linkage disequilibrium (LD) is required to ensure the efficient utilization of diversity. We investigated the impact of different sampling strategies on diversity parameters and LD based on high-density genotypic data of 35 European maize landraces each represented by more than 20 individuals. On average, five landraces already captured ~95% of the molecular diversity of the entire dataset. Within landraces, absence of pronounced population structure, consistency of linkage phases and moderate to low LD levels were found. When combining data of up to 10 landraces, LD decay distances decreased to a few kilobases. Genotyping 24 individuals per landrace with 5k SNPs was sufficient for obtaining representative estimates of diversity and LD levels to allow an informed pre-selection of landraces. Integrating results from European with Central and South American landraces revealed that European landraces represent a unique and diverse spectrum of allelic variation. Sampling strategies for harnessing allelic variation from landraces depend on the study objectives. If the focus lies on the improvement of elite germplasm for quantitative traits, we recommend sampling from pre-selected landraces, as it yields a wide range of diversity, allows optimal marker imputation, control for population structure and avoids the confounding effects of strong adaptive alleles. [ABSTRACT FROM AUTHOR]

In this work, we explore the ability of several characterization approaches for phenotyping to extract information about plant cell wall properties in diverse maize genotypes with the goal of identifying approaches that could be used to predict the plant's response to deconstruction in a biomass-to-biofuel process. Specifically, a maize diversity panel was subjected to two high-throughput biomass characterization approaches, pyrolysis molecular beam mass spectrometry (py-MBMS) and near-infrared (NIR) spectroscopy, and chemometric models to predict a number of plant cell wall properties as well as enzymatic hydrolysis yields of glucose following either no pretreatment or with mild alkaline pretreatment. These were compared to multiple linear regression (MLR) models developed from quantified properties. We were able to demonstrate that direct correlations to specific mass spectrometry ions from pyrolysis as well as characteristic regions of the second derivative of the NIR spectrum regions were comparable in their predictive capability to partial least squares (PLS) models for p-coumarate content, while the direct correlation to the spectral data was superior to the PLS for Klason lignin content and guaiacyl monomer release by thioacidolysis as assessed by cross-validation. The PLS models for prediction of hydrolysis yields using either py-MBMS or NIR spectra were superior to MLR models based on quantified properties for unpretreated biomass. However, the PLS models using the two high-throughput characterization approaches could not predict hydrolysis following alkaline pretreatment while MLR models based on quantified properties could. This is likely a consequence of quantified properties including some assessments of pretreated biomass, while the py-MBMS and NIR only utilized untreated biomass. [ABSTRACT FROM AUTHOR]

Key message: Natural variation for the timing of vegetative phase change in maize is controlled by several large effect loci, one corresponding to Glossy15 , a gene known for regulating juvenile tissue traits. Abstract: Vegetative phase change is an intrinsic component of developmental programs in plants. Juvenile and adult vegetative tissues in grasses differ dramatically in their anatomical and biochemical composition affecting the utility of specific genotypes as animal feed and biofuel feedstock. The molecular network controlling the process of developmental transition is incompletely characterized. In this study, we used scoring for juvenile and adult epicuticular wax as an entry point to discover quantitative trait loci (QTL) controlling phenotypic variation for the developmental timing of juvenile to adult transition in maize. We scored the last leaf with juvenile wax on 25 recombinant inbred line families of the B73 reference Nested Association Mapping (NAM) population and the intermated B73×Mo17 (IBM) population across multiple seasons. A total of 13 unique QTL were identified through genome-wide association analysis across the NAM populations, three of which have large effects. A QTL located on chromosome nine had the most significant SNPs within Glossy15, a gene controlling expression of juvenile leaf traits. The second large effect QTL is located on chromosome two. The most significant SNP in this QTL is located adjacent to a homolog of the Arabidopsis transcription factor, enhanced downy mildew- 2, which has been shown to promote the transition from juvenile to adult vegetative phase. Overall, these results show that several major QTL and potential candidate genes underlie the extensive natural variation for this developmental trait. [ABSTRACT FROM AUTHOR]

Expected future cellulosic ethanol production increases the demand for biomass in the US Corn Belt. With low nutritious value, low nitrogen content, and compact biomass, maize cobs can provide a significant amount of cellulosic materials. The value of maize cobs depends on cob architecture, chemical composition, and their relation to grain yield as primary trait. Eight traits including cob volume, fractional diameters, length, weight, tissue density, and grain yield have been analyzed in this quantitative trait locus (QTL) mapping experiment to evaluate their inheritance and inter-relations. One hundred eighty-four recombinant inbred lines of the intermated B73 × Mo17 (IBM) Syn 4 population were evaluated from an experiment carried out at three locations and analyzed using genotypic information of 1,339 public SNP markers. QTL detection was performed using (1) comparison-wise thresholds with reselection of cofactors ( α = 0.001) and (2) empirical logarithm of odds score thresholds ( P = 0.05). Several QTL with small genetic effects ( R = 2.9-13.4 %) were found, suggesting a complex quantitative inheritance of all traits. Increased cob tissue density was found to add value to the residual without a commensurate negative impact on grain yield and therefore enables for simultaneous selection for cob biomass and grain yield. [ABSTRACT FROM AUTHOR]

Whereas breeders have exploited diversity in maize for yield improvements, there has been limited progress in using beneficial alleles in undomesticated varieties. Characterizing standing variation in this complex genome has been challenging, with only a small fraction of it described to date. Using a population genetics scoring model, we identified 55 million SNPs in 103 lines across pre-domestication and domesticated Zea mays varieties, including a representative from the sister genus Tripsacum. We find that structural variations are pervasive in the Z. mays genome and are enriched at loci associated with important traits. By investigating the drivers of genome size variation, we find that the larger Tripsacum genome can be explained by transposable element abundance rather than an allopolyploid origin. In contrast, intraspecies genome size variation seems to be controlled by chromosomal knob content. There is tremendous overlap in key gene content in maize and Tripsacum, suggesting that adaptations from Tripsacum (for example, perennialism and frost and drought tolerance) can likely be integrated into maize. [ABSTRACT FROM AUTHOR]

Correction to: Characterizing introgression-by-environment interactions using maize near isogenic lines Graph: Supplementary file1 (XLSX 9869 KB) Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s00122-021-03959-z. [Extracted from the article]