Use of simulation to optimize a sweet corn breeding program: implementing genomic selection and doubled haploid technology.

Genomic selection and doubled haploids hold significant potential to enhance genetic gains and shorten breeding cycles across various crops. Here, we utilized stochastic simulations to investigate the best strategies for optimize a sweet corn breeding program. We assessed the effects of incorporating varying proportions of old and new parents into the crossing block (3:1, 1:1, 1:3, and 0:1 ratio, representing different degrees of parental substitution), as well as the implementation of genomic selection in two distinct pipelines: one calibrated using the phenotypes of testcross parents (GSTC scenario) and another using F1 individuals (GSF1). Additionally, we examined scenarios with doubled haploids, both with (DH) and without (DHGS) genomic selection. Across 20 years of simulated breeding, we evaluated scenarios considering traits with varying heritabilities, the presence or absence of genotype-by-environment effects, and two program sizes (50 versus 200 crosses per generation). We also assessed parameters such as parental genetic mean, average genetic variance, hybrid mean, and implementation costs for each scenario. Results indicated that within a conventional selection program, a 1:3 parental substitution ratio (replacing 75% of parents each generation with new lines) yielded the highest performance. Furthermore, the GSTC model outperformed the GSF1 model in enhancing genetic gain. The DHGS model emerged as the most effective, reducing cycle time from five to four years and enhancing hybrid gains despite increased costs. In conclusion, our findings strongly advocate for the integration of genomic selection and doubled haploids into sweet corn breeding programs, offering accelerated genetic gains and efficiency improvements.

Utilizing genomic prediction to boost hybrid performance in a sweet corn breeding program.

Sweet corn breeding programs, like field corn, focus on the development of elite inbred lines to produce commercial hybrids. For this reason, genomic selection models can help the in silico prediction of hybrid crosses from the elite lines, which is hypothesized to improve the test cross scheme, leading to higher genetic gain in a breeding program. This study aimed to explore the potential of implementing genomic selection in a sweet corn breeding program through hybrid prediction in a within-site across-year and across-site framework. A total of 506 hybrids were evaluated in six environments (California, Florida, and Wisconsin, in the years 2020 and 2021). A total of 20 traits from three different groups were measured (plant-, ear-, and flavor-related traits) across the six environments. Eight statistical models were considered for prediction, as the combination of two genomic prediction models (GBLUP and RKHS) with two different kernels (additive and additive + dominance), and in a single- and multi-trait framework. Also, three different cross-validation schemes were tested (CV1, CV0, and CV00). The different models were then compared based on the correlation between the estimated breeding values/total genetic values and phenotypic measurements. Overall, heritabilities and correlations varied among the traits. The models implemented showed good accuracies for trait prediction. The GBLUP implementation outperformed RKHS in all cross-validation schemes and models. Models with additive plus dominance kernels presented a slight improvement over the models with only additive kernels for some of the models examined. In addition, models for within-site across-year and across-site performed better in the CV0 than the CV00 scheme, on average. Hence, GBLUP should be considered as a standard model for sweet corn hybrid prediction. In addition, we found that the implementation of genomic prediction in a sweet corn breeding program presented reliable results, which can improve the testcross stage by identifying the top candidates that will reach advanced field-testing stages.

Genome assembly and population genomic analysis provide insights into the evolution of modern sweet corn.

Sweet corn is one of the most important vegetables in the United States and Canada. Here, we present a de novo assembly of a sweet corn inbred line Ia453 with the mutated shrunken2-reference allele (Ia453-sh2). This mutation accumulates more sugar and is present in most commercial hybrids developed for the processing and fresh markets. The ten pseudochromosomes cover 92% of the total assembly and 99% of the estimated genome size, with a scaffold N50 of 222.2 Mb. This reference genome completely assembles the large structural variation that created the mutant sh2-R allele. Furthermore, comparative genomics analysis with six field corn genomes highlights differences in single-nucleotide polymorphisms, structural variations, and transposon composition. Phylogenetic analysis of 5,381 diverse maize and teosinte accessions reveals genetic relationships between sweet corn and other types of maize. Our results show evidence for a common origin in northern Mexico for modern sweet corn in the U.S. Finally, population genomic analysis identifies regions of the genome under selection and candidate genes associated with sweet corn traits, such as early flowering, endosperm composition, plant and tassel architecture, and kernel row number. Our study provides a high-quality reference-genome sequence to facilitate comparative genomics, functional studies, and genomic-assisted breeding for sweet corn.

Genetic Perturbation of the Starch Biosynthesis in Maize Endosperm Reveals Sugar-Responsive Gene Networks.

In maize, starch mutants have facilitated characterization of key genes involved in endosperm starch biosynthesis such as large subunit of AGPase Shrunken2 (Sh2) and isoamylase type DBE Sugary1 (Su1). While many starch biosynthesis enzymes have been characterized, the mechanisms of certain genes (including Sugary enhancer1) are yet undefined, and very little is understood about the regulation of starch biosynthesis. As a model, we utilize commercially important sweet corn mutations, sh2 and su1, to genetically perturb starch production in the endosperm. To characterize the transcriptomic response to starch mutations and identify potential regulators of this pathway, differential expression and coexpression network analysis was performed on near-isogenic lines (NILs) (wildtype, sh2, and su1) in six genetic backgrounds. Lines were grown in field conditions and kernels were sampled in consecutive developmental stages (blister stage at 14 days after pollination (DAP), milk stage at 21 DAP, and dent stage at 28 DAP). Kernels were dissected to separate embryo and pericarp from the endosperm tissue and 3' RNA-seq libraries were prepared. Mutation of the Su1 gene led to minimal changes in the endosperm transcriptome. Responses to loss of sh2 function include increased expression of sugar (SWEET) transporters and of genes for ABA signaling. Key regulators of starch biosynthesis and grain filling were identified. Notably, this includes Class II trehalose 6-phosphate synthases, Hexokinase1, and Apetala2 transcription factor-like (AP2/ERF) transcription factors. Additionally, our results provide insight into the mechanism of Sugary enhancer1, suggesting a potential role in regulating GA signaling via GRAS transcription factor Scarecrow-like1.

Sugar Transporters in Plants: New Insights and Discoveries.

Carbohydrate partitioning is the process of carbon assimilation and distribution from source tissues, such as leaves, to sink tissues, such as stems, roots and seeds. Sucrose, the primary carbohydrate transported long distance in many plant species, is loaded into the phloem and unloaded into distal sink tissues. However, many factors, both genetic and environmental, influence sucrose metabolism and transport. Therefore, understanding the function and regulation of sugar transporters and sucrose metabolic enzymes is key to improving agriculture. In this review, we highlight recent findings that (i) address the path of phloem loading of sucrose in rice and maize leaves; (ii) discuss the phloem unloading pathways in stems and roots and the sugar transporters putatively involved; (iii) describe how heat and drought stress impact carbohydrate partitioning and phloem transport; (iv) shed light on how plant pathogens hijack sugar transporters to obtain carbohydrates for pathogen survival, and how the plant employs sugar transporters to defend against pathogens; and (v) discuss novel roles for sugar transporters in plant biology. These exciting discoveries and insights provide valuable knowledge that will ultimately help mitigate the impending societal challenges due to global climate change and a growing population by improving crop yield and enhancing renewable energy production.

Sucrose transporter2 contributes to maize growth, development, and crop yield.

During daylight, plants produce excess photosynthates, including sucrose, which is temporarily stored in the vacuole. At night, plants remobilize sucrose to sustain metabolism and growth. Based on homology to other sucrose transporter (SUT) proteins, we hypothesized the maize (Zea mays) SUCROSE TRANSPORTER2 (ZmSUT2) protein functions as a sucrose/H+ symporter on the vacuolar membrane to export transiently stored sucrose. To understand the biological role of ZmSut2, we examined its spatial and temporal gene expression, determined the protein subcellular localization, and characterized loss-of-function mutations. ZmSut2 mRNA was ubiquitously expressed and exhibited diurnal cycling in transcript abundance. Expressing a translational fusion of ZmSUT2 fused to a red fluorescent protein in maize mesophyll cell protoplasts revealed that the protein localized to the tonoplast. Under field conditions, zmsut2 mutant plants grew slower, possessed smaller tassels and ears, and produced fewer kernels when compared to wild-type siblings. zmsut2 mutants also accumulated two-fold more sucrose, glucose, and fructose as well as starch in source leaves compared to wild type. These findings suggest (i) ZmSUT2 functions to remobilize sucrose out of the vacuole for subsequent use in growing tissues; and (ii) its function provides an important contribution to maize development and agronomic yield.

Sucrose Transporter ZmSut1 Expression and Localization Uncover New Insights into Sucrose Phloem Loading.

Sucrose transporters (SUTs) translocate sucrose (Suc) across cellular membranes, and in eudicots, multiple SUTs are known to function in Suc phloem loading in leaves. In maize (Zea mays), the Sucrose Transporter1 (ZmSut1) gene has been implicated in Suc phloem loading based upon RNA expression in leaves, electrophysiological experiments, and phenotypic analysis of zmsut1 mutant plants. However, no previous studies have examined the cellular expression of ZmSut1 RNA or the subcellular localization of the ZmSUT1 protein to assess the gene's hypothesized function in Suc phloem loading or to evaluate its potential roles, such as phloem unloading, in nonphotosynthetic tissues. To this end, we performed RNA in situ hybridization experiments, promoter-reporter gene analyses, and ZmSUT1 localization studies to elucidate the cellular expression pattern of the ZmSut1 transcript and protein. These data showed that ZmSut1 was expressed in multiple cell types throughout the plant and indicated that it functions in phloem companion cells to load Suc and also in other cell types to retrieve Suc from the apoplasm to prevent its accumulation and loss to the transpiration stream. Additionally, by comparing a phloem-mobile tracer with ZmSut1 expression, we determined that developing maize leaves dynamically switch from symplasmic to apoplasmic phloem unloading, reconciling previously conflicting reports, and suggest that ZmSut1 does not have an apparent function in either unloading process. A model for the dual roles for ZmSut1 function (phloem loading and apoplasmic recycling), Sut1 evolution, and its possible use to enhance Suc export from leaves in engineering C3 grasses for C4 photosynthesis is discussed.

Genomic DNA Isolation from Maize (Zea mays) Leaves Using a Simple, High-Throughput Protocol.

A simple, robust, inexpensive, high-throughput method for isolating genomic DNA from maize (Zea mays) leaf tissues is described. The DNA obtained using this extraction protocol is suitable for polymerase chain reaction (PCR) genotyping, which can be employed for the identification of alleles in diverse genetic and breeding approaches, such as marker-assisted selection, genetic fine mapping, and mutant introgression. This method utilizes 96-well plates for the collection of leaf tissue and the subsequent isolation of genomic DNA. The DNA isolation step is performed inexpensively within 3 hr and uses a urea-based extraction buffer that does not require an organic extraction step. Yields of genomic DNA are sufficient to perform ∼25 PCR-genotyping reactions per sample. These qualities, coupled with the protocol being robust and easy for inexperienced users to master, make this method ideal for new researchers. © 2016 by John Wiley & Sons, Inc.

Soluble Sugar and Starch Extraction and Quantification from Maize (Zea mays) Leaves.

An easy-to-perform protocol for isolating and quantifying soluble sugars (sucrose, glucose, and fructose) and starch from maize (Zea mays) leaf tissue is described. The method has been optimized to extract non-structural carbohydrates (NSC) from frozen, finely ground tissue in a methanol:chloroform:water solution. Three rounds of tissue extraction for 30 min each at 50°C provide quantitative recovery of soluble sugars. The use of alternative extraction solvents is discussed, as well as the advantages and disadvantages of these solvents. Additionally, we provide two support protocols. The first quantifies the isolated NSC via commercially available enzymatic kits that couple the amount of each specific sugar to the production of NADPH, which is detected using equipment readily available to most laboratories. The second describes the preparation of a purification column to remove strongly charged or hydrophobic molecules from the extracted sugar solution, which is required prior to quantification with high-pressure liquid chromatography or high-performance anion-exchange chromatography. The protocols are robust and easily adapted for use in measuring NSC extracted from other plant species or tissues, making them ideal for new users. © 2016 by John Wiley & Sons, Inc.

Direct and indirect plant defenses are not suppressed by endosymbionts of a specialist root herbivore.

Insect endosymbionts influence many important metabolic and developmental processes of their host. It has been speculated that they may also help to manipulate and suppress plant defenses to the benefit of herbivores. Recently, endosymbionts of the root herbivore Diabrotica virgifera virgifera have been reported to suppress the induction of defensive transcripts in maize roots, which may explain the finding of another study that once attacked plants become more susceptible to subsequent D. v. virgifera attack. To test this hypothesis, we cured D. v. virgifera from its major endosymbiont Wolbachia and tested whether endosymbiont-free individuals elicit different defense responses in maize roots. The presence of Wolbachia did not alter the induction of defense marker genes and resistance in a susceptible maize hybrid and a resistant line. Furthermore, attacked maize plants emitted the same amount of (E)-ß-caryophyllene, a volatile signal that serves as foraging cue for both entomopathogenic nematodes and D. v. virgifera. Finally, the effectiveness of the entomopathogenic nematode Heterorhabditis bacteriophora to infest D. v. virgifera was not changed by curing the larvae from their endosymbionts. These results show that the defense mechanisms of maize are not affected by Wolbachia. Consequently, D. v. virgifera does not seem to derive any plant-defense mediated benefits from its major endosymbiont.