Recipient Organization
CORNELL UNIVERSITY
(N/A)
ITHACA,NY 14853
Performing Department
Plant Breeding
Non Technical Summary
Sweet corn--the third most consumed vegetable in the U.S.--does not provide adequate daily levels of provitamin A (carotenoids), vitamin E (tocochromanols), zinc and iron, which are essential for optimal human health. Processed foods are routinely fortified with vitamins and minerals in the US, but this is not possible for fresh sweet corn. While the vitamin A requirement in the US is largely met by fortification, large segments of the US still do not obtain the daily recommended dietary amount of zinc, iron, vitamin E and the two non-provitamin A carotenoids, lutein and zeaxanthin, that delay age-related macular degeneration. Carotenoids and tocochromanols are also antioxidants that provide additional health benefits related to heart disease and specific cancers. This new program focuses on the development of novel breeding methods that unite speed breeding and genomic selection for the accelerated production of nutrient-dense sweet corn germplasm with enhanced carotenoid, tocochromanol, zinc, and iron levels. Even though there is an immediate need to increase the nutritional value of crops for the US (and developing nations), this work is not performed in commercial seed companies due to their primary focus on more economically important traits such as yield. Therefore, support of this proposed novel nutritional work by public funds is needed. The generated sweet corn germplasm, breeding methods, and information will benefit seed companies, growers, and consumers. Ultimately, this work is intended to serve and benefit the health and nutrition of people in NY and beyond.
Animal Health Component
70%
Research Effort Categories
Basic
30%
Applied
70%
Developmental
(N/A)
Goals / Objectives
Sweet corn breeders, growers, and consumers in New York State (NYS) and beyond will benefit tremendously from locally adapted, nutrient dense (vitamin E, provitamin E, zinc, and iron) sweet corn germplasm. The three major objectives of this research are to (i) develop a speed breeding method for sweet corn (year 1); (ii) develop genetic markers to target loci associated with increased nutritional levels in fresh sweet corn kernels (years 1 and 2); and (iii) implement speed breeding combined with genomic selection to accelerate development of germplasm enhanced for nutritional quality (years 2 to 3).
Project Methods
(i) develop a speed breeding method for sweet corn (year 1)The growth habit and generation time of sweet corn creates a bottleneck that limits the number of attainable breeding cycles per year. This decreases the rate at which sweet corn varieties can be developed. Therefore, we propose to develop a speed breeding (SB) procedure following that of Ghosh et al. (2018) and Watson et al. (2018) with modification for the controlled environment of a greenhouse to accelerate sweet corn plant development to rapidly cycle from seed-to-seed. SB is preferred to double-haploid technology because SB has lower cost, more opportunities for recombination, and less of a need for specialists. Our developed SB method will be tailored to sweet corn by optimizing the light type, photoperiod, temperature, humidity, soil, nutrients, and planting density with the flexibility to enable multiple mating designs in a greenhouse environment. Aimee Schulz and Travis Rooney, Ph.D. students in collaborator Edward Buckler's lab at Cornell, have developed a speed breeding approach for maize in a Guterman greenhouse, with early results suggesting 3 to 4 generations per year (unpublished data). Therefore, we hypothesize that this protocol can be further optimized for sweet corn genotypes varying in phenology.Our efforts to develop a SB protocol for sweet corn will be focused on the nine parents of the five breeding populations constructed in the prior Hatch grant (2017-18-141): 34f, Fa56A, P39M96, Wh03031, Wh08091, Wh10035R, Wh10049R, Wh92047, and Wh93006. The controlled environment will consist of a Guterman greenhouse at Cornell with 30°C/27°C day/night temperatures. We will assess two lighting treatments for the existence of photoperiod sensitivity: 20 h light with 4 h dark and 12 h light with 12 h dark in a 24-h diurnal cycle. Sweet corn plants will be treated with varying levels of GA inhibitor at different growth stages to slow shoot growth. Given that the amount of space in the greenhouse is restricted, we will also test the density to which sweet corn can tolerate in the greenhouse, which will provide insights into the scale at which single-seed descent can be conducted. In initial tests conducted by Aimee Schulz this past spring with the nine sweet corn lines under SB conditions, tasseling and silking were observed for some lines, but due to the COVID-19 pandemic the experiment was halted prior to completion. Regardless, the preliminary data are promising, suggesting that with further testing of conditions it should be possible to develop an effective SB protocol for sweet corn.(ii) develop genetic markers to target loci associated with increased nutritional levels in fresh sweet corn kernels (years 1 and 2)We have constructed five breeding populations now at the F2 generation that are expected to segregate for large-effect loci associated with vitamin E, provitamin A, zinc, iron, or cadmium content. Custom PCR-based allele-specific genetic marker assays will be designed to provide us with the ability to determine whether putative causal loci are fixed or segregating in advanced generation SB progeny. To identify the most favorable haplotypes at these loci for designing molecular markers, we will construct haplotypes at the genomic regions of the large-effect genes (lycE, crtRB1, vte1, vte4, hggt1, nas5, and hma3) found to associate with carotenoids, tocochromanols, or trace elements. We will use target (Genotyping-by-sequencing; Baseggio et al., 2019) and reference (HapMapv3; Bukowski et al., 2017) SNP genotype sets in B73 RefGen_v4 coordinates (B73 v4) to increase the marker density of the sweet corn association panel with an approach similar to Ramstein et al. (2020) in collaboration with Robin Buell at Michigan State University. Haplotype patterns will be assessed in Haploview (Barrett et al., 2005), haplotype blocks defined with the confidence interval method (Gabriel et al., 2002). The association of haplotype blocks and phenotypes will be tested following the method of Gonzalez-Jorge et al. (2013) with a mixed linear model that accounts for population structure and unequal relatedness (Yu et al., 2006), followed by the identification of the most favorable haplotype of each haplotype block with the Tukey-Kramer test. Haplotype tagging (Johnson et al., 2001) will be used to identify SNPs that distinguish the favorable haplotype at each of the seven loci. The selected SNPs will be genotyped via amplicon sequencing (AmpSeq) (Fresnedo-Ramírez et al., 2019). We will also explore other low-cost approaches for genome-wide amplicon sequencing (Zou et al., 2020) connected with the construction of a practical haplotype graph (PHG) by skim-sequencing the nine parents of the sweet corn breeding populations (Jensen et al., 2020). The samples for DNA sequencing and genotyping will be submitted to the BRC at Cornell. The DNA sequence and genotypic analyses will be conducted by the Gore lab at Cornell with existing and custom programs using PC workstations and local (Gore Lab and Cornell) high performance computing systems.(iii) implement speed breeding combined with genomic selection to accelerate development of germplasm enhanced for nutritional quality (years 2 to 3)We will use DNA marker-based selection combined with the validated SB protocol for advancement of the most promising selection candidates from the five biparental sweet corn populations. We will SNP genotype 200-300 F2 plants at the seven candidate causal gene loci (Fresnedo-Ramírez et al., 2019) to select those that have the highest frequency of favorable haplotypes (~5-10 lines/population), followed by SSD for several generations (derive at the F5 generation) via SB and concomitant DNA-marker based selection to fix favorable haplotypes in a Guterman greenhouse at Cornell. We hypothesize that it will be possible to generate sufficient quantitates of F5 seed for replicated field evaluation by the end of year 2 with the inclusion of a winter nursery in Chile if needed for bulk seed increase. If we are able to develop low-cost genome-wide markers in combination with the haplotype-targeted markers, then whole-genome prediction models will be developed that integrate both marker datasets by training models on the sweet corn association population and predicting phenotypes for individuals from the five biparental populations (Ben Hassen et al., 2018). In the SB process, standard agronomic traits will be scored on plants at each cycle including but not limited to germination rate, flowering time, plant height, grain yield and its components.Seed of the final selected lines will be increased and used for testing in replicated field trials. Standard management and statistical methods for field trials will be used to evaluate replicated plots of the newly developed lines for agronomic and nutritional traits including parental and check lines at Cornell's Musgrave Research Farm. We will also have a second replicated field site in WI with collaborator Bill Tracy. Evaluated agronomic traits will include yield, maturity, height, disease, lodging, and seedling establishment. The measured nutritional traits on fresh kernels harvested at the fresh eating stage will be kernel color, carotenoids, tocochromanols, and trace elements (Baseggio et al., 2019, Baseggio et al., 2020, Ziegler et al., 2017). The metabolite profiling will be performed in the lab of collaborator Dean DellaPenna, and the elemental analysis conducted in the lab of collaborator Ivan Baxter. Standard statistical tests will be performed to compare the genetic gain of the selected phenotypes to those of the parental and check lines. The statistical analyses will be performed on PC workstations in the Gore lab.