Introduction and General

Training presentations





User presentations

Ranjana Bhattacharjee1, Asrat Amele1, Jessica B. Lyons2, Jessen Bredeson2, Paul D. Fraser3, Lukas Muller4, Agre Paterne1, P. Lava Kumar1, Michael Abberton1, Patrick Adebola1, Daniel Rokhsar1, and Robert Asiedu1. 1International Institute of Tropical Agriculture, PMB 5320, Ibadan, Nigeria. 2University of California – Berkeley, California, USA. 3Royal Holloway University of London, London, UK. 4Boyce Thompson Institute, Cornell University, Ithaca, USA.

                Advances in next-generation sequencing (NGS), genotyping technologies coupled with high-performance computation approaches, and partnerships with advanced research institutes have paved many possibilities to apply genomics tools to advance crop-breeding programs in several models and non-model plant species. This enabled the application of ‘genomics-assisted breeding’ or ‘whole genome selection. Breeding for yam improvement targets highly diverse biotic and abiotic constraints, whilst meeting complex end-user quality preferences to improve the livelihoods of beneficiaries in developing countries. Achieving breeding targets and increasing the rate of genetic gains in yam, with long breeding cycles, and genomes with high heterozygosity and different ploidy levels is challenging. However, a variety of genomic approaches has already been incorporated at various levels, including sequencing of draft genomes of some species, and application of NGS to genotype genetic resources (genebank accessions) and breeding lines for further exploitation using genomic approaches, such as genetic diversity, linkage mapping, and QTL (quantitative trait loci) analysis while pipelines are established to test GWAS (genome-wide association study) and GS (genomic selection). The use of GS will become more evident in yams as the tools become more efficient for polyploid genotypes, incorporating dominance and epistatic effects, as well as multi-location environmental effects, and progeny selection. This will need to be coupled with high-throughput phenotyping, knowledge from other -omics approaches (e.g., gene expression via transcriptomics, protein function via proteomics, and metabolic pathways via metabolomics), and a big data platform to allow the identification of molecular markers linked to complex traits, the dissection of genetic variability, identification of putative candidate genes, and their causative alleles for gene expression or gene function. The yam program can expand and benefit by bringing together a diverse range of disciplines and partners, and knowledge sharing from other root and tuber crops. The multi-species nature of the crop provides a huge platform to even learn from different species and expand.

Olivia Angelin-Bonnet1, Susan Thomson2, Patrick J. Biggs1, Matthieu Vignes1, and Samantha Baldwin2. 1Massey University, Palmerston North, NZ. 2Plant and Food Reserach, Lincoln, NZ. 

                Tuber bruising of tetraploid potato is an important quality trait as it affects the appearance and flavour of the tubers and thus impacts their fitness for sale. The development of potato lines that are more resistant to bruising is therefore a desirable objective for breeding programs, rendering the genetic analysis of this trait an important task. In this study, we investigated the biological mechanisms underlying tetraploid potato tuber bruising using multi-omics data. Genotype by sequencing using exon capture obtained from a breeding population of half-sibling families was used to uncover regions of interest for the bruising phenotype, as well as other agronomic traits of interest. In addition, we employed a Systems Biology approach to obtain a more holistic and comprehensive view of the molecular mechanisms involved in tuber bruising and bridge the gap between genetic variations and phenotype. To this end, RNA sequencing and metabolomics data were also obtained, and GWAS, differential expression analysis, and multi-omics data integration were leveraged in order to detect molecular features (i.e. genomic variants, genes, and metabolites) involved in tuber bruising. We demonstrate that even as capture sequencing only allows us to measure genetic variations in a subset of the genome, it is possible to uncover interesting and biologically meaningful genotype-phenotype associations, especially when combining the GWAS results with other omics datasets. Moreover, these associations were obtained with samples selected from a breeding program, demonstrating that available data from populations not specifically designed for association study can be used to uncover genomic regions potentially associated with a trait of interest.


Poster presentations

Ira A. Herniter and Nicholi Vorsa. Rutgers University, New Brunswick, NJ.

                  Blueberry (Vaccinium sect Cyanoccocus) is an increasingly important fruit crop native to North America. Collected from the wild for thousands of years, blueberry was only domesticated in the early twentieth century. While blueberry has long been a minor crop, recently interest in its health properties, including high levels of anthocyanins, has led to increased consumption and cultivation around the globe. However, quality genetic resources for blueberry have been lacking, greatly hampering the development of new varieties which can produce well under the constraints of changing climatic and pest regimes. We report the development of several populations being used for trait mapping. Four are diploid interspecific populations resulting from crosses between V. corymbosum, native to temperate climate, and V. darrowi, native to a subtropical climate, as well as a large germplasm collection consisting of released blueberry cultivars and wild relatives, including species from across North America, as well as species from Europe, Pacific Russia, and South America. The populations have great diversity in a range of traits, including leaf shape, berry size, fruit chemistry, flowering time, among others. The populations are an important resource for the development of new varieties and increasing understanding of blueberry physiology.

Beatriz Tome Gouveia1, Brian M. Schwartz2, Yangi Wu3, Kevin E. Kenworthy4, Ambika Chandra5, Paul L. Raymer2, Marta T. Pudzianowska6, Esdras M. Carbajal1, Manual R. Chavarria Sanchez4, Jing Zhang2, Bradley M. Batterhsell3, Pamela S. Rowe, Meghyn B. Meeks5, Tianyi Wang5, Chase N. McKeithen4, and Susan R. Milla-Lewis1. 1North Carolina State University, Raleigh, NC. 2University of Georgia, Tifton, GA. 3Oklahoma State University, Stillwater, OK. 4University of Florida, Gainesville, FL. 5Texas A&M University, Dallas, TX. 6University of California, Riverside, CA.

                  Zoysiagrass (Zoysia Willd. species, 2n = 4x = 40), a complex that encompasses 11 species, are primarily used for home lawns, public parks, and athletic fields, being the second most used warm-season turfgrass on golf courses in the US. Water limitations are currently one of the biggest challenges for the turfgrass industry. Starting in 2010, a Turfgrass Specialty Crop Research Initiative (SCRI) project, funded by USDA-NIFA, has focused on addressing the problems of limited availability and reduced quality of water for irrigating turfgrass areas by breeding warm-season turfgrass species for improved drought and salinity tolerances. The objective of this study was to evaluate the performance of zoysiagrass breeding lines from the breeding programs at University of Georgia – Tifton and Griffin, North Carolina State University, Texas A&M University and University of Florida under drought conditions. Field trials arranged as randomized complete-block designs with three replications were installed at research facilities at Citra, FL, and Stillwater, OK in the summer of 2020. The response variables evaluated were turfgrass quality under normal or non-drought conditions (TQND), and both percent green cover (PGC), evaluated using UAS, and turfgrass quality (NTEP ratings from 1 to 9) (TQD) under drought conditions. The genetic variance was significant and non-significant for all traits in the single-environment and multi-environment analysis, respectively. The genotype-by-environment interaction variance was significant for all traits. Heritability estimates were above 0.50 for all traits in all locations, except for TQD in Citra. A high positive correlation was observed between TQD and PGC in both locations, whereas these traits showed low correlation with TQND. Several breeding lines performed better than the checks for both TQD and PGC at both locations. Evaluation of these genotypes will continue through 2023. Results of this study will support the selection of drought-tolerant elite zoysiagrass genotypes with increased performance stability for the target regions.

Christopher Benson1, David Huff1, Shaun Bushman2, Peter Maughan3, Rick Jeelen3, and Matthew Robbins2. 1Pennsylvania State University, State College, PA. 2USDA-ARS, Logan, UT. 3Brigham Young University, Provo, UT. 

                  Poa annua (annual bluegrass, 2n=28, AABB) is an allotetraploid grass species that outperforms its diploid progenitors in both diversity of morphologies and geographic range. On golf course putting greens, Poa annua's ability to produce seed under 3mm mowing height has contributed to its discordant reputations as both a noxious weed and a valued commodity. Despite an estimated $40 billion U.S. turfgrass industry, there have been limited successful efforts directed at managing Poa annua, either for or against, primarily due to its complex genetic and epigenetic versatility. Here we present the pseudomolecule-level genome assemblies of Poa annua and its diploid progenitors, Poa infirma, and Poa supina. BRAKER2 annotations of these species with Iso-Seq RNA-evidence yielded 72,034, 37,207, and 35,698 high-confidence proteins, respectively. Both the assemblies and the annotations for all species contained >90% conserved orthologs, corroborating their quality. We demonstrate that the parental diploid genomes accurately represent the A and B subgenomes of Poa annua and characterize genetic exchange between and within the subgenomes of Poa annua. We show that the bifurcating ecological niches of the parents is mirrored by genomic and structural mutations in their diploid genomes. The subgenomes of Poa annua bear strong resemblance to its progenitors, confirming its status as a neo-allotetraploid. We speculate that Poa annua's global proliferation is conferred through the union of two parental genomes with wide genetic distance for hybridization and contrasting ecological ranges. We plan to incorporate genomic and transcriptomic resources to aid in better targeting of Poa annua in turfgrass beeding applications.

Neil O. Anderson1, Liesl Bower-Jernigan1, Rajmund Eperjesi1, Robert Suryani1, Steven Gullickson2, and Albert Radloff2. 1University of Minnesota, Minneapolis, MN. 2MGK, Minneapolis, MN. 

                  Many species in the Chrysanthemum complex and its alliance of satellite genera (e.g. Arctanthemum, Leucanthemum, Tanacetum) have been bred and selected since the 15th century BCE. Crops include a diversity of uses and forms from green pesticides (pyrethrum, C. cinerariifolium, C. coccineum; 2n=2x=16, 2n=3x=24), edible shoots (C. carinatum, C. coronarium, C. segetum; 2n=2x=16), salt tolerance (C. arcticum, subsp. arcticum, polaré; 2n=2x=16, 2n=4x=32), to ornamentals (cut flower, potted plant, garden types, C. xgrandiflorum, C. xhybridum; 2n=6x=54) also used for medicinal, herbal teas, and wine. The most widely cultivated crop, C. xgrandiflorum, is a complex perennial geophyte, an allohexaploid of >10 species (C. zawadskii, etc.), complicated by self incompatibility (3 S loci), pseudo-self compatibility (PSC), aneuploidy, sterility, inbreeding depression, and genetic load. Chrysanthemum populations in the University of Minnesota breeding program were analyzed for genetic structure within/among species and cultivar series to determine alliances within the ploidy complex. Genotypic analyses (GBS; DArTseqLD) was used to identify 389 low density, unique SNPs and determine genetic structure within and among wild (C. arcticum, subsp. arcticum, polaré; C. zawadskii) and cultivated (C. cinerariifolium, C. xgrandiflorum ‘Minn’ series, C. xhybridum ‘MammothTM’ series) species populations. Principal Coordinates Analysis (PCoA) of all species showed two clusters of C. arcticum/C. cinerariifolium and C. xgrandiflorum/C. xhybridum/C. zawadskii with 74.9% diversity for the principal component (PCoA1) and 8.1% for PCoA2. Surprisingly, the first subgroup had C. cinerariifolium in close dalliance with C.a. subsp. polaré (Nome, AK), followed by C.a. subsp. arcticum (Aleutian Islands), C. arcticum (Anchor Point, Kenai, Ninilchik, Valdez, AK) with C.a. subsp. polaré (Churchill, Manitoba, Canada). Chrysanthemum xgrandiflorum had the greatest level of genetic diversity, although it slightly overlapped with both C. zawadskii and C. xhybridum. The ‘Minn’ and ‘MammothTM’ series had low levels of genetic differentiation due to C. xhybridum being derived from C. xgrandiflorum and C. weyrichii (2n=6x=54). Future research will focus on phenotypic trait/SNP associations in a genome-wide association study (GWAS) to aid in marker-assisted selection.

Felipe Bitencourt Martins1, Aline Costa Lima Moraes1, Alexandre Hild Aono1, Rebecca Caroline Ulbricht Ferreira1, Lucimara Chiari2, Rosangela Maria Simeão2, Sanzio Carvalho Lima Barrios2, Mateus Figueiredo Santos2, Liana Jank2, Cacilda Borges do Valle2, Bianca Baccili Zanotto Vigna2, Anete Pereira de Souza1. 1University of Campinas, Sao Paulo, Brazil. 2Embrapa Gado de Corte, Mato Grosso do Sul, Brazil. 

         Artificial hybridization plays a fundamental role in plant breeding programs since it generates new genotypic combinations that can result in desirable phenotypes. Depending on the species and mode of reproduction, controlled crosses may be challenging, and contaminating individuals can be introduced accidentally. In this context, the identification of such contaminants is important to avoid compromising further selection cycles, as well as genetic and genomic studies. The main objective of this work was to propose an automated multivariate methodology for the detection and classification of putative contaminants, including apomictic clones, self-fertilized individuals, half-siblings and full contaminants, in biparental polyploid progenies of tropical forage grasses. We established a pipeline to identify contaminants in genotyping-by-sequencing (GBS) data encoded as allele dosages of single nucleotide polymorphism (SNP) markers by integrating principal component analysis (PCA), genotypic analysis (GA) measures based on Mendelian segregation and clustering analysis (CA). The combination of these methods allowed the correct identification of all contaminants in all simulated progenies (n=200) with more than 690 markers and the detection of putative contaminants in three real progenies of tropical forage grasses, providing an easy and promising methodology for the identification of contaminants in biparental progenies of tetraploid and hexaploid forages or other species. The proposed pipeline was made available through the polyCID Shiny app, which was developed in R language with a user-friendly interface designed to facilitate its use by plant breeders. Furthermore, it can be easily coupled with traditional genetic approaches, such as linkage map construction and other SNP based techniques, thereby increasing the efficiency of breeding programs.