Here are the abstracts of the oral and poster presentations from the 2023 Tools for Polyploids Workshop. The recordings of each presentation will be available on this page after the workshop. Poster presentations can be downloaded by clicking on the title.
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User Presentations
Development of a Mid-Density Genotyping Platform for Alfalfa and its Application in a Drought Tolerance Breeding Program
Alexander M Sandercock, Manoj Sapkota, Cesar Augusto Medina, Zhanyou Xu, Long-Xi Yu, Dongyan Zhao, Katherine Mejia-Guerra, Marcelo Mollinari, Deborah A Samac, Brian M Irish, Kasia Heller-Uszynska, Craig T Beil, Moira J Sheehan. Breeding Insight, Cornell University, University of Minnesota, Plant Germplasm Introduction and Testing Research Unit, Sarepta Therapeutics, North Carolina University, Diversity Arrays Technology, Plant Science Research Unit, USDA-ARS.
Molecular breeding techniques have revolutionized breeding decisions in major crops like tomato and maize, yet many crop species lack accessible genetic resources. The development of genetic resources, such as openly accessible marker panels, can improve breeding programs through lowering costs and time necessary to make selection decisions. Alfalfa (Medicago sativa L.) is a globally important perennial forage crop that is pivotal in beef and dairy production, yet breeding is still largely relying on “breeders’ eyes”. To improve breeding and assist breeders in adopting modern molecular techniques, Breeding Insight (BI) developed a 3K DArTag marker panel from whole-genome skim sequencing of 40 elite alfalfa lines used in North America. DArTag markers were selected for their genome-wide distribution and location within genic regions. The marker panel was then tested through the genotyping of an F1 and a backcross population – leading to the creation of a combined genetic map of 1,792 markers. Finally, we performed DArTag sequencing for 436 alfalfa genotypes within a breeding population to identify genomic regions associated with drought tolerance. Using GWASpoly and trait data for 16 harvest yields (May-August, 2020-2023), we discovered 24 quantitative trait loci (QTL) associated with drought tolerance. Genomic prediction was tested using RRBLUP, GBLUP, and WGBLUP models. RRBLUP and GBLUP provided moderate and comparable predictive abilities through ten-fold cross-validation. WGBLUP integrated SNPs allocated within the above-mentioned 24 QTL regions and provided increased predictive abilities. Thus, the open accessibility of this genetic resource marks a significant contribution to existing alfalfa breeding programs and is suited to benefit the global alfalfa breeding community.
Construction of a SNP-based genetic linkage map in alfalfa (Medicago sativa L.) using three different reference genomes
Harpreet Kaur1, Melinda Dornbusch2, Laura M. Shannon1, Deborah A. Samac2. 1Department of Horticultural Science, University of Minnesota. 2Plant Science Research Unit, United States Department of Agriculture
Alfalfa (Medicago sativa L.) is an important perennial forage legume grown worldwide. It is an outcrossing, highly heterozygous autotetraploid species (2n=4x=32) with genome size of approximately 800 MB. The objective of this study was to compare high-density genetic maps developed using GBS-based SNP markers called using three different reference genomes: 1) the ZhongmuNo.1 monoploid genome assembly, 2) the first homolog of allele-aware XinJiangDaYe genome assembly, and 3) the stable FASTA format of a graph-based pangenome developed using ZhongmuNo.1 as reference with four additional assemblies. A biparental F1 population of 166 plants was made by crossing RegenSY27x and UMN3988 genotype 5. After trimming low quality bases and removing low quality reads from raw GBS data, 1.4 billion single-end 100 bp size reads were used to develop three SNP marker datasets. The percent heterozygosity and missing data in each individual were similar for all three SNP datasets. We called genotypes and imputed missing data using ‘updog’. The final SNP datasets consisted of 10,652, 12,392 and 9,809 SNP markers in 164 individuals for the three reference genomes, respectively, which were used to produce three linkage maps. To reduce the inflation in map distance, gaps between markers, and increase the marker density mappoly was run again after removing SNPs with more than a 10 cM gap between them. The final phased linkage map with four haplotypes consisted of 2,482, 2,635, and 2,618 SNP markers spanning 1743.66, 2576.59, and 2701.13 cM in 8 linkage groups for ZhongmuNo.1, XinJiangDaYe, and the graph-based pangenome, respectively. The number and order of SNP markers in pangenome, with only 277 additional SNPs included from four other genomes, has significantly increased the linkage map length and average gap size, in comparison with monoploid ZhongmuNo.1 reference genome. However, the proportion of SNP markers mapped to the total number of markers used for linkage mapping was improved in pangenome (0.27) as compared to the ZhongmuNo.1 (0.23) and XinJiangDaYe (0.21) assemblies. These results demonstrated that high within-species genomic variability is present in alfalfa and SNP calling using reference genomes of different cultivars can produce different genetic maps in a population. These results increase the available molecular marker resources and will be used for scaffolding the reference genome sequences for U.S. alfalfa germplasm.
The effect of allele frequency estimates on genomic relatedness following VanRaden method one
Timothy Millar. The New Zealand Institute for Plant and Food Research Limited.
Estimation of the genomic relationship matrix (GRM) is a core operation in statistical and quantitative genetics. The first method of VanRaden (2008) is one of the most commonly applied GRM estimators in both diploid and autopolyploid breeding programs. An often-overlooked aspect of this estimator is its reliance on allele frequencies of the “unselected base population”. Indeed, many implementations of VanRaden’s first method use allele frequencies of the sample-population instead of those of the base population. This practice represents an implicit assumption that sample-population allele frequencies are a reasonable estimate of those of the base population. We explore the effects of this assumption in highly inbred pedigrees, and introduce the method of McPeek, Wu and Ober (2004) for estimating base population allele frequencies from the sample population.
David Gerard1, Mira Thakkar1, Luis Felipe Ventorim Ferrão2. 1American University. 2University of Florida.
In experiments with F1 populations, as a quality control measure, researchers often test whether genotype frequencies conform to those expected under Mendelian segregation. However, classical segregation patterns can be distorted in tetraploids due to the meiotic processes of double reduction and preferential pairing, which can alter gamete frequencies. Currently, there is no method to test for segregation distortion while accounting for these two processes in tetraploid F1 populations. Furthermore, current methods do not account for genotype uncertainty. To address this gap, we propose a Bayesian approach that incorporates both preferential pairing and double reduction in a new model for offspring genotypes in tetraploid F1 populations, optionally accounting for genotype uncertainty. We demonstrate the efficacy of our approach through simulations and on a real dataset of tetraploid blueberries.
Genetic diversity and population structure in the developing of regionally adapted alfalfa germplasm pools
Cesar A. Medina, Meng Lin, Dongyan Zhao, Craig T Beil, Moira J Sheehan, Brian Irish, LongXi Yu, Hari Poudel, Annie Claessens, Virginia Moore, Jamie Crawford, Kevin P Smith, Mike Peel, Heathcliffe Riday, E. Charles Brummer, Zhanyou Xu. Plant Science Research Unit, USDA-ARS. Breeding Insight, Cornell University. Plant Germplasm Introduction and Testing Research Unit, USDA-ARS. Lethbridge Research and Development Center, Agriculture and Agri-Food Canada. Quebec Research and Development Centre, Agriculture and Agri-Food Canada. School of Integrative Plant Science, Plant Breeding and Genetics Section, Cornell University. Agronomy and Plant Genetics, University of Minnesota. Forage and Range Research Lab, USDA-ARS. US Dairy Forage Research Center, USDA-ARS. Department of Plant Sciences, University of California Davis.
Alfalfa is a perennial, allogamous, and seed-propagated species with high genetic complexity at individual and population levels. To generate locally adapted alfalfa pools, it is necessary to have desirable parents keeping good diversity, maximal recombination, and weak selection. In this work, we tested the genetic diversity and genetic differentiation in 28 populations used to develop locally adapted germplasm pools: four base populations (C0) from different geographical origins (CASIA, EURO, OTTM, SYBR), 20 cycle 1 populations (C1), generated from four base populations selected in five locations, and four commercial varieties (checks). A panel of 3,000 DArT markers was used to quantify the genetic diversity and population structure in 28 alfalfa populations. PCA and DAPC analysis identified a significant structured population among alfalfa populations according to the geographical origin and plot checks in a central cluster. Inbreeding coefficients (FIS) range from -0.06 to 0.04, and 23 out of 28 populations have negative FIS values, indicating that most populations have an excess of heterozygous, a symptom of random mating in the populations. Genetic differentiation was calculated using FST and Rho parameters with similar but highest values with Rho. Pairwise Rho values between populations ranged from 0.0071 to 0.3019: populations SIBR-NY and SIBR-BASE were more similar (0.0071) and population OTTM-AB and variety 55H94 were more different (0.3019). All base populations have the lowest Rho values compared to C1 populations and check varieties. Analysis of molecular variance found high variance among individuals within populations and low variance between populations which is common in panmictic populations. Variation among population was highest among check varieties and lowest in base populations with 14.6% and 8.6%, respectively. This information allows to know the state of population structure and genetic variation in alfalfa germplasm pools. This work shows that base populations have extensive recombination, weak selection, and minimal inbreeding which is required for base-broadening selection.
Advances in Marker Assisted and Genomic Selection in the North Carolina State University Sweetpotato Breeding Program
Simon Fraher1, Bonny Oloka1, Gabriel de Siqueira Gesteira1, Marcelo Mollinari1, Adrienne Gorny1, G. Craig Yencho1, Guilherme da Silva Pereira2. 1North Carolina State University, Raleigh, NC. 2University of Vicosa, Vicosa, Minas Gerais, BR.
Sweetpotato (L.) Lam. (2n=6x=90) is the most valuable horticultural crop in North Carolina, where approximately 70% of US production occurs. The NC industry is threatened by the quarantined guava root-knot nematode, Meloidogyne enterolobii. Unfortunately, nearly all resistant genotypes are poorly adapted to the Southeast growing region. Yield, shape, skin color, and resistance to other pathogens are of utmost concern. One such pathogen is Fusarium oxysporum f.sp. batatas, which was once the number one disease facing the NC industry prior to resistance breeding. Most M. enterolobii resistant sweetpotato germplasm is susceptible to Fusarium wilt. Last year, we reported a major QTL for M. enterolobii resistance in the biparental mapping population ‘Tanzania’ x ‘Beauregard’. Another major QTL has been detected for Fusarium wilt resistance in a second population, DM04-0001 x ‘Covington’. Development of KASP markers for these two critically important resistance traits may be the first applications of marker-assisted selection in this crop. Nevertheless, most horticultural traits are likely to be quantitative in nature and not amenable to KASP genotyping. To address quantitative traits, we phenotyped a genomic selection training population of approximately 600 individuals between 2019-2023 in augmented row-column field trial designs. Phenotyping strategies included and will include visual selection based on CIP descriptors, optical grading, drone phenotyping, and a tractor-mounted camera for image analysis. Using DArT genotyping (approximately 2,800 SNP markers), it is our goal to identify genome regions associated with traits like yield, shape, and skin and flesh color in addition to disease resistance in order to support the use of genomic selection in this globally important vegetable crop.
Genetic basis of Stem-End Chip Defects and Strategies for Implementation of Genomic Selection in Potatoes
Jeewan Pandey1, Douglas C. Scheuring1, Jeffrey W. Koym2, Maria Isabel Vales1. 1Department of Horticultural Sciences, Texas A&M University. 2Texas A&M University, AgriLife Research and Extension Center.
Potato chips are the most popular snack food in the world. Quality standards for potato chips are very high: Tubers should have high starch content, fry light, and contain few internal defects that result in browning. A major quality issue is the stem-end chip defect, identified by dark coloration near the stem end of the fried chips. The stem-end chip defect can be caused by environmental stress or diseases. The genetics of the stem-end chip defect were previously studied in a biparental mapping population, and several QTLs were identified. However, studies must be expanded to diverse panels and guide breeding efforts. This study aimed to identify genomic regions associated with the stem-end chip defect incidence, severity, and index (incidence*severity) using a diverse panel of chipping clones; to obtain genomic-estimated breeding values; and to examine the effect of marker density on genomic prediction accuracy. Chipping clones (384) from public breeding programs in the USA were evaluated for several years in Dalhart, Texas. After harvesting, the tubers were chipped and inspected for stem-end-related traits. Genome-wide association studies (GWAS) were performed using GWASpoly using the Infinium Illumina SNP Array. Genomic selection was performed using StageWise. The effect of marker density was assessed using sets containing 4K, 10K, and 15K SNP markers. QTLs associated with stem-end chip index were identified on chromosomes 6 and 8. The accuracy of genomic selection for stem-end was similar when comparing the three SNP genotypic sets used, suggesting that moderate marker-density arrays should be useful for estimating genomic-estimated breeding values and ranking clones cost-effective for breeding programs to adopt genomic selection. This study has improved our understanding of the genetic basis of the stem-end defect and guides future genomic selection efforts.
Improving genomic prediction of quality traits with image-based analysis in potato (Solanum tuberosum)
Muyideen Yusuf, Michael Miller, Thomas R. Stefaniak, Laura M. Shannon. University of Minnesota, St. Paul, MN.
Potato is the most grown vegetable in the world. Both consumers and processors evaluate potatoes based on quality traits such as shape and skin color, making these traits important targets for breeders. Achieving and evaluating genetic gain is facilitated by precise and accurate trait measures. Historically, quality traits have been measured using visual rating scales which are subject to human error and necessarily lump individuals with distinct traits into categories. Image analysis offers a method of generating quantitative measures of quality traits. In this study, we use TubAR, an image-analysis R package, to generate quantitative measures of shape and skin color traits for use in genomic prediction. We developed and compared two genomic covariance structures for mixed model analysis based on additive (G) and additive plus dominance (G + D) for two aspects of skin color, redness, and lightness, and two aspects of shape, roundness, and length-to-width ratio, for fresh market red and yellow potatoes grown in Minnesota between 2019 and 2022. Similarly, we used the much larger chipping potato population grown at the same time to develop a multi-trait selection index for roundness, specific gravity, and yield. Traits ranged in heritability with shape traits falling between 0.23 and 0.85, and color traits falling between 0.34 and 0.91. Genetic effects were primarily additive with color traits showing the strongest effect (0.47) while shape traits varied with market class and based on model fit and prediction ability, the G model was superior to the G + D model. The combination of image analysis and genomic prediction presents a promising avenue for improving potato quality traits.
Development and validation of a mid-density genotyping platform for cranberry (Vaccinium macrocarpon)
Shufen Chen1, Meng Lin1, Xuemei Tang1, Nahla Bassil2, Jenyne Loarca3, Jeffrey Neyhart4, Juan Zalapa3, Craig Beil1, Moira Sheehan1. 1Cornell University, Ithaca, NY. 2National Clonal Germplasm Repository, USDA-ARS. 3Vegetable Crops Research Unit, USDA-ARS, Department of Plant and Agroecosystem Sciences, University of Wisconsin-Madison. 4Genetic Improvement for Fruits and Vegetables Laboratory, USDA-ARS.
Cranberry (Vaccinium macrocarpon) is a native fruit crop of North America, gaining global popularity in both production and consumption due to its distinct flavor and potential health advantages. The United States, followed by Canada, is the largest cranberry-producing country worldwide. Breeding cranberry cultivars primarily via phenotypic selection can be a labor-intensive and time-consuming endeavor. The integration of genomic-based techniques can significantly expedite the breeding process. In that light, Breeding Insight developed a 3K DArTag panel from 505K single nucleotide polymorphisms (SNPs) generated from resequencing data of 53 diverse cultivated cranberry breeding founders. DArTag markers were selected based on even genomic distribution, prioritizing those in genic regions, maximal genetic diversity among the North American breeding germplasm, and markers associated with previously mapped quantitative trait loci. The 3K DArTag panel also included 54 markers targeting conserved genomic regions between blueberry and cranberry and partially overlapped with the SNP set from the Vaccinium Coordinated Agricultural Project (VacCAP). Collectively, the cranberry 3K DArTag panel generated 6,118 microhaplotypes for a testing panel of a diverse collection of 201 diploid cranberries, 13 autotetraploid accessions, 27 hybrids from blueberry x cranberry crosses, and two F1 populations with a shared parent. Principal component analysis using read counts showed clear clustering of different populations of the testing materials. Autotetraploid cranberry exhibited slightly elevated heterozygosity and missing data rates than diploid samples. The 54 cranberry/blueberry conservative markers were either non-amplified, or as in tetraploids, or as in diploids had similar amplification patterns among the diploid, tetraploid, and in blueberry x cranberry hybrid samples. Linkage maps were constructed for each of the two F1 populations using 692 and 810 markers and resulted in linkage groups with total lengths of 1224.37 cM and 1222.01 cM, respectively. These two maps can be potentially combined to increase mapping resolution. This 3K DArTag panel is available to the scientific community and can be a great resource for genomic studies in cranberry.
A public mid-density genotyping platform for Blueberry (Vaccinium corymbosum L.)
Manoj Sapkota1, Dongyan Zhao1, Nahla Bassil2, Ebrahiem M. Babiker3, Kasia Heller-Uszynska4, Marcelo Mollinari5, Craig T. Beil1, Moira J. Sheehan1. 1 Breeding Insight, Cornell University, Ithaca, NY, USA. 2 National Clonal Germplasm Repository, USDA-ARS, Corvallis, OR, USA. 3 Southern Horticultural Research Unit, USDA-ARS, Poplarville, MS, USA. 4 Diversity Arrays Technology, ACT 2617, Bruce, Australia. 5 North Carolina State University, Raleigh, NC, USA.
Specialty crop breeding programs, e.g., blueberry, often face challenges in adopting technology, particularly in developing and utilizing genetic marker panels for genomic-based decision-making in selection. To improve breeding efficiency, Breeding Insight (BI) generated a 3K DArTag (Diversity Array Technology) marker panel for blueberry (Vaccinium corymbosum L.), a valuable North American native crop. The panel, comprising 3,000 loci, was specifically designed to address the unique complexities of blueberry biology, which includes its autotetraploid nature and high heterozygosity. The 3K panel was established through whole-genome sequencing of 31 diverse cultivated blueberry accessions, representing various types used in North American breeding programs. Of these 3,000 loci, 97% (2,924) are situated in genic regions, with only 3% (76) in non-genic regions. To validate the utility of this genotyping panel, a wide array of materials was tested, including cultivated V. corymbosum blueberries (n = 168), interspecific hybrids and wild Vaccinium species (n = 47) from the Vaccinium subgenus, and a small selection of cultivated cranberry varieties (n = 5) from the Oxycoccus subgenus. The choice of materials aimed to determine the panel's usability across species (mostly cultivated V. corymbosum and V. virgatum) germplasm and its adaptability to wild Vaccinium and related species. Notably, missing marker data rates were lowest among cultivated blueberry accessions, higher among wild Vaccinium species, and highest among cranberry samples. Furthermore, we conducted additional validation of the genotyping panel using a blueberry bi-parental F1 population (n = 175) resulting from the cross between Draper and Jewel (V. corymbosum) parents. Employing the MAPpoly package in R, we successfully generated 12 linkage groups. Linkage group lengths ranged from 125.66 cM to 190.60 cM, with an average of 154.22 cM. This panel is suitable for marker-assisted selection, whole-genome association mapping, reconstruction of recombination patterns, allele dosage estimation, and parental confirmation in cultivated blueberry, with some limited application in other Vaccinium species. Importantly, this genotyping panel is publicly accessible along with the associated data, offering the blueberry breeding community a valuable resource in molecular breeding and enabling genetic datasets generated using the marker panel to be shared and compared across projects, institutions, and even countries. The development of this marker panel has the power to make routine genotyping a reality because of its cost-effectiveness, rapid genotyping capabilities, and reduced computational overhead to both public and private breeding programs.
Development of mid-density genotyping platforms and microhaplotype database for specialty crops and animals in North America
Dongyan Zhao. Breeding Insight, Cornell University, Ithaca, NY.
The development of high-throughput genotyping platforms has made SNP genotyping highly cost-effective and accessible in breeding programs. Aside from the popular array-based and genotyping-by-sequencing platforms, targeted amplicon sequencing techniques have been successfully used for many important crop and animal species, enabling efficient genotyping for marker-assisted selection and genomic prediction/selection. With reads produced from targeted sequencing, not only can one detect SNPs, but also new microhaplotypes because the reads often contain novel variants beyond the targeted SNPs. Microhaplotypes (here referring to sequences of 50-500 bp) have intrinsic advantages over SNPs in that they contain higher information content, increased genetic diversity, reduced allelic ambiguity and ascertainment bias, and adaptability to different populations. The use of microhaplotypes in breeding is especially beneficial for polyploid species due to their multiple copies of chromosomes and often highly heterozygous and complex genomic composition. To take full advantage of microhaplotype data, Breeding Insight (BI) has developed targeted genotyping panels using DArTag technology (www.diversityarrays.com) for several specialty crops and animals, including alfalfa, blueberry, sweetpotato, North America Atlantic salmon, pecan, etc. These panels are publicly available to all interested parties (for a full list, https://breedinginsight.org/breeding-solutions/open-source-dartag-marker-panels). To make microhaplotypes more accessible and comparable among different projects and breeding programs, BI is building microhaplotype databases (microHap DB) by storing genotype data from thousands of samples and assigning unique microhaplotype IDs for all microhaplotypes detected. For example, the alfalfa microHap DB (v22) contains 24,853 microhaplotypes discovered from the genotyping of ~12,000 cultivated tetraploid alfalfa and wild Medicago species using the alfalfa 3K DArTag panel. It is worth noting that the increment of the alfalfa microHap DB has reached a plateau, with fewer new microhaplotypes being added with subsequent genotyping projects. The next step is to extensively annotate the database because it is known that homeologous and paralogous sequences may be amplified besides the targeted regions in targeted sequencing platforms. BI has been testing the usage of microhaplotype segregation ratios in structured populations and read alignments to the full set of reference chromosomes to distinguish target microhaplotypes from paralogous sequences. The annotated database will be provided to DArT to assist their genotype calling process and will also be available to the public to look for available genetic variants that they are interested in but are not present in their germplasm. We envision that the DArTag panels and their associated microHap DBs will greatly improve breeding and research for all breeders in the community.
Poster Presentations
MagicImpute: Imputation and Error Detection for Sequence Data In Connected Multiparental Populations
Chaozhi Zheng1, Eligio Bossolini2, Antje Rohde2, Martin Boer1, Fred van Eeuwijk1. 1Wageningen University and Research. 2BASF Innovation Center Gent.
Multiparental populations have been produced for quantitative trait loci (QTL) mapping in many crops, where next-generation sequencing has become a cost-effective tool for genotyping. Previously, we have developed a hidden Markov framework MagicImpute (Zheng et al. 2018) for genotype imputation in a multiparental population, however, its computational time increases quickly with the number of parents. In this work, we extend MagicImpute with increasing computational efficiency and robustness to various types of errors. Particularly, it has the following novel features: (1) allow for multiple multiparental populations that may be connected by sharing parents, (2) allow for many missing parents that are not available for sequencing, (3) account for possible allelic bias and overdispersion in the sequence data model, and (4) infer marker-specific error rates and filter for high quality markers. It currently works for diploids and is extendable to polyploids. Beside extensive simulation studies, we evaluate MagicImpute by three real datasets: the rice F2 population (Furuta et al. 2017) with sequence coverage being low, the apple F1 population (Gardner et al. 2014) with parents being outbred, and the sorghum multi-parent advanced generation intercross (MAGIC) population (Ongom and Ejeta 2018) with 10 male sterile lines (out of 29 parents) being completely missing.
Understanding the Genetics of the Flower Color Transition Phenotype in Autotetraploid Roses
Haramrit Gill, Jeekin Lau, Shuyang Zhen, David Byrne, Oscar Riera-Lizarazu. Texas A&M University, College Station, TX.
Flower color is one of the most promising traits in ornamental plants and plays a significant role in roses' aesthetic and economic value. The rose industry thrives on producing novel flower colors and pigmentation patterns. Thus, it is important to understand flower pigmentation patterns. We observed an interesting phenotype that we call ‘flower color transition’ in two tetraploid garden rose populations [Stormy Weather (SW) X Brite Eyes (BE) and My Girl (MG) X Brite Eyes (BE)]. The roses exhibiting this phenotype have flowers that transition from a light yellow to a dark pink/red color as the flower ages, leading to bushes peppered with multiple colors. Here, we present studies to identify the type of pigment accumulated and the candidate genes controlling the accumulation of these pigments by determining quantitative trait loci (QTL) regions, and transcriptomic analysis. The main objective of this research was to gain a better understanding of the genetics and biochemistry of this trait. In the plants that show the ‘flower color transition’ trait, pigment analysis shows a gradual increase in anthocyanin accumulation over different stages of development. In contrast, stably pigmented, non-transitioning roses show either constant, elevated levels of anthocyanins or constant low levels throughout all stages of flower development. In addition, light treatments showed that the ‘flower color transition’ trait is induced by UV-B radiation. Thus, the ‘flower color transition’ trait is UV-B sensitive. The QTL analysis suggests the presence of QTL on linkage groups (LGs) 2, 3, 4, and 6 in the SWXBE population and on LGs 6 and 7 in the MGXBE population. The locations of QTL coincided with the locations of genes involved in the flavonoid biosynthetic pathway. Further, the transcriptomic analysis revealed that the ABC transporters, RhGT1, 3GT, MYB1/PAP1, and SPL9 are some of the main genes involved in the flower color transition phenomenon.
Tessa Hochhaus, Jeekin Lau, Cristiane H. Taniguti, David H. Byrne, and Oscar Riera-Lizarazu. Texas A&M University, College Station, TX.
Rose rosette disease (RRD) is one of the most threatening diseases to roses (Rosa sp.). RRD is caused by the rose rosette emaravirus and spread by an eriophid mite, Phyllocoptes fructiphilus Keifer. The disease symptoms include elongated and excessive branching of shoots, leaf distortion, red or yellow leaves, proliferation of prickles, and increased susceptibility to other stresses or diseases. Past studies have found quantitative trait loci (QTL) for reduced susceptibility to RRD on linkage groups (LGs) 1, 3, 5, and 6 in diploid populations, and LGs 1, 5, 6, and 7 in tetraploid populations. Recently, we utilized a meta-analysis approach to better understand the relationship between QTL identified in diploid and tetraploid populations. Through this meta-analysis, we were able to narrow the QTL regions. A meta-QTL on LG 5, MetaRRD5.2, and one on LG 6, MetaRRD6.1 were of particular interest due to the large proportion of phenotypic variance explained and the extent of colocalization of QTL. Meta-QTL intervals guided our search for genes related to antiviral mechanisms, R genes, and general plant defenses within the reference Rosa chinensis genome assembly. Since Rosa wichurana Basye’s Thornless is in the parentage of diploid populations used in this study and a genome assembly is now available, we performed a candidate gene search in the MetaRRD5.2 and MetaRRD6.1 intervals. With this, we hope to better define the gene content related to RRD resistance in these meta-QTL.
Kathleen Rhoades1. Amy Iezzoni2. 1The Savannah Institute. 2Michigan State University.
Sour cherry (Prunus cerasus L.) is an allotetraploid (2n = 4x =32) fruit tree derived from an interspecific hybridization between the diploid sweet cherry (P. avium L.)(2n =2x =16) and the tetraploid ground cherry (P. fruticosa Pall.)(2n = 2x = 32). Previous work in the sour cherry cultivar ‘Montmorency’ indicates that this hybridization is relatively recent, as the progenitor genomes diverged less than 1.61 million years ago. Sour cherry is known to exhibit irregular pairing at meiosis as well as disomic and tetrasomic inheritance patterns, which raises the question of the extent of homoeologous exchange in sour cherry and how much variation in subgenome dosage exists within the species. Accession-specific changes in homoeolog dosage are relevant to sour cherry breeders targeting specific loci. We examined a diverse panel of six sour cherry accessions and found evidence of 26 homoeologous exchange events and five whole-homoeolog replacements in three of the six accessions. We illustrate the consequences of this homoeolog dosage variation for four previously-characterized expansin genes associated with fruit ripening processes. The remaining three accessions, all of which are landraces, show no evidence of homoeologous exchange, raising questions about their history and origins.
Genome-wide association analyses reveal candidate genes associated with health components in blueberry
Estefania Tavares Flores, Gonzalo Casorzo, Paul Adunola, Mary Ann Lila, Mary Grace, Camila F. Azevedo, Luis Felipe Ferrao, Patricio Munoz. University of Florida, North Carolina State University, Universidade Federal de Vicosa.
Blueberry fruits (Vaccinium spp.) are depicted worldwide for their high content of antioxidants and phenolic compounds compared to other fresh fruits and vegetables. Anthocyanins have been described as the primary source of antioxidants in these berries. While demands for high-nutrient blueberries have increased significantly during the last two decades, a better understanding of how to genetically improve this trait is still required. We carried out a genome-wide association study toward this goal by gathering genomic and metabolic data from a southern highbush blueberry (SHB) breeding population of 369 genotypes. These were genotyped using a sequence capture methodology, including 50k SNP markers spanning all blueberry chromosomes. Target traits were phenotyped using high-performance liquid chromatography (HPLC), including total anthocyanin content, 20 anthocyanin types, and 40 phenolic and flavonoid non-anthocyanin compounds. A univariate linear mixed model was used for estimating SNP effects per trait after correcting for population structure. We found significant SNPs associated with health-component characteristics that can be further tested for marker-assisted selection, thus avoiding the cost and time required for phenotyping these traits. Findings from our analyses revealed consistent hits across Chr. 1, 2, 4, and 8 for anthocyanin-related traits – supporting previous studies in blueberry. Additional new hits were detected in Chr. 3, 5, 7, 10, 11, and 12 for both anthocyanin types and flavonoid-related traits. Notably, we detected an association in Chr. 9 related to total anthocyanin content, which seems to be the first time reported for this trait. Interestingly, several transcription factors have been annotated around this spanning region of the genome, including a bHLH type. bHLH transcription factors have been described before for playing a pivotal role in modulating expression of both flavonoid and anthocyanin late biosynthesis genes in plants, which makes this finding a good candidate for further validation. Altogether, identifying genomic regions potentially involved in anthocyanin and flavonoids is a meaningful advancement for understanding health component traits in blueberries, which can be further functionally validated and used for molecular breeding purposes.
Assessing Potato Heat Tolerance Using Leaf Membrane Integrity
Amaka Ifeduba, Shuyang Zhen, Jeewan Pandey, M. Isabel Vales. Texas A&M University, College Station, TX.
Rising global temperatures are having an increasingly detrimental impact on agricultural food production, and potato, typically a cool-season crop, is no exception. Heat stress during the potato growing season leads to significant losses in tuber yield and quality. Since high-temperature episodes are difficult to predict and control, planting heat-tolerant varieties is recommended as an assurance to prevent reductions in yield and quality. In order to develop new heat-tolerant varieties suitable for different geographic areas and market preferences, breeders need to understand the distinctive mechanisms employed by heat-tolerant varieties and devise effective screening techniques to swiftly distinguish between heat-tolerant and heat-sensitive varieties. We are exploring membrane integrity in connection to heat tolerance. As a starting point, we compared the membrane integrity of five potato genotypes (‘Vanguard Russet’, ‘Reveille Russet’, ‘Sierra Gold’, ‘Russet Burbank’, and ‘Atlantic’) across a temperature range of 30 - 70 °C in 5 °C increments, each for 30 minutes, while measuring the electrolyte leakage at each temperature setpoint. The results revealed significant differences in relative electrolyte leakage among the genotypes, with the more heat-tolerant genotypes (Vanguard Russet and Reveille Russet) exhibiting significantly lower electrolyte leakage than the heat-sensitive Russet Burbank and Atlantic. We extended this investigation to a diverse panel of 217 clones from the Texas A&M potato breeding program. The clones were genotyped using the Infinium 22K V3 Potato Array and phenotyped to evaluate electrolyte leakage at 50 °C. Genome-wide association studies were carried out to identify the genomic regions linked to membrane integrity using the GWASpoly package. Genomic estimated breeding values were computed using Stagewise. Our study aims to provide greater insight into the genetic foundation of leaf membrane integrity and connection with heat tolerance, ultimately developing a rapid heat-tolerance selection tool to speed up breeding efforts toward the development of heat-tolerant potato varieties.
Justin Conover, David Gerard, Ryan Gutenkunst, Micahel Barker. University of Arizona. American University.
A fundamental first step in population genomic analyses is choosing a reference genome to map sequencing data against for variant discovery. When considering an analysis of divergent populations or species, the population that is more distantly related to the reference genome will typically have less accurate variant discovery than the more closely related population, a phenomenon known as “reference bias”. Allotetraploid genomes present a unique bioinformatic challenge. These polyploid genomes are composed of two complete chromosomal complements from two divergent progenitor species. Hence, using either diploid progenitor’s genome as the reference will necessarily lead to a reference bias for variants in the subgenome from the other parental species. Additionally, recombination between duplicated homologous chromosomes (homoeologous exchange) can alter the dosage expectation of a given chromosomal region, further complicating variant discovery in allotetraploids. Here, we explore reference biases in a population of allotetraploid Brassica napus and its diploid progenitors, B. rapa and B. oleracea. We find that although reference biases abound when mapping to the reference genome of either diploid reference, these biases are largely ameliorated by creating and mapping reads to a variation graph pangenome composed of both diploid reference genomes. We also find that the method used to construct the variation graph pangenome, and the variant discovery pipeline, have significant effects on the accuracy of variant discovery.
Genetic Control of Primocane Fruiting in Tetraploid Blackberry
Alexander Silva, Lacy Nelson, Carmen Johns, Ellen Thompson, Michael Hardigan, John Clark, Margaret Worthington. University of Arkansas, Hortifrut, USDA-ARS Corvallis.
Blackberry (Rubus spp.) is a specialty crop of increasing economic significance due to rising consumption, expanded marketing, and advancements in cultivar development. Only in the United States alone, blackberry production for the fresh market represents over $664 million. Blackberries, characterized by a perennial root system and biennial canes, have traditionally been categorized into floricane-fruiting (FF) cultivars, producing fruits exclusively in second-year canes, and the most recently improved primocane-fruiting (PF) cultivars, which can also produce fruits in first-year canes; a characteristic discovered in the diploid blackberry genotype ‘Hillquist’ (R. argutus). PF cultivars offer the potential for dual cropping in a single year, extending the production season, and exhibiting adaptability to tropical regions. Despite the economic importance of PF cultivars, the genetic basis of this trait has not been well elucidated. It has been proposed that PF is controlled by one major recessive locus, but its location in the blackberry genome is unclear. Here we used a set of more than 350 tetraploid blackberry genotypes to identify genomic regions associated with PF through a genome-wide association study (GWAS). A region located at 33 Mbp on chromosome Ra03 was highly associated with primo/floricane-fruiting variation. Within this genomic region, several annotated genes related to flowering, including an AP2-like gene and a Gibberellin 20 oxidase coding gene, were identified. To discover functional genomic variants linked to PF and identify candidate genes responsible for primocane-fruiting, we have been doing allele mining and transcriptome analysis. For allele mining, a set of 5 PF and 11 FF genotypes were resequenced and aligned to the R. argutus reference genome. We identified 365 SNPs that discriminated between PF and FF genotypes within a 5 Mbp window around the GWAS peak. From this group, eleven SNPs were selected to design KASP markers and used to genotype a diverse panel of 650 tetraploid blackberry genotypes from the University of Arkansas System Division of Agriculture (UADA), Hortifrut Genetics, and USDA Horticultural Crops Research Unit breeding programs. Two markers differentiated between PF and FF genotypes with an error rate lower than 5%. For transcriptome analysis, the youngest leaves and shoot apical meristems (SAM) from one FF and two PF blackberry genotypes were collected before and after the transition to the reproductive stage for RNA sequencing. This revealed a suite of differentially expressed flowering genes distributed across the entire genome, enlightening the potential molecular mechanisms influencing the flowering pattern between floricane and primocane-fruiting genotypes.
Paula Espitita Buitrago1, Camilla Ryan2, Claudia Perea1, Jose de Vega2, Rosa Jauregui1. 1Alliance Bioversity-CIAT, 2Earlham Institute.
Improvement on resistance to spittlebugs (Hemiptera: Cercopidae) has been achieved in the Interspecific Urochloa hybrid program at high rates the Alliance Bioversity-CIAT using phenotyping selection to assess antibiosis and tolerance to nymphal attack at high accuracy. However, it takes 75 days and requires mass-rearing colonies and synchronising the insects’ life cycle with the trials. the trials. Consequently, it is challenging to evaluate ~800 plants, corresponding to 150 genotypes, in the second stage of the breeding scheme. We aim to integrate molecular techniques to accelerate the Interspecific Urochloa breeding programme .
The development of markers for selection is challenging due to the allotetraploid and apomictic nature of the materials in the U. ruziziensis/U. brizantha/U. decumbens agamic complex used in the programme. To overcome these challenges, we developed a bioinformatics pipeline using new resources, such as a tetraploid reference of Urochloa decumbens and R based software for polyploids, to identify QTL associated with resistance and tolerance to the nymphal stage of the spittlebug Aeneolamia varia in a multiparental mapping population. A total of 320 half-sib hybrids of four biparental families were sequenced using RADseq to a read depth of ~10X per haplotype. Then, these reads were preprocessed and aligned to two Urochloa references: a haploid reference of the diploid U. ruziziensis(n =9); and the haplotype-resolved tetraploid U. decumbens (n=9, 4n=36). Both sets of aligned reads were used for SNP calling using GATK’s “germline short variant discovery” pipeline setting the ploidy as 4 to obtain dosages. We also used allelic depth from GATK for dosage calling in the updog package comparing the models for preferential pairing (f1pp) and normal distribution (norm). We obtained more SNP loci and higher mean read depth when aligning to the haploid U. ruziziensis reference (9 chrs) compared to the haplotype resolved (36 chrs). Genotype plots for both datasets show that high read depth is crucial for accurate genotype calling, and often markers do not follow the expected segregation pattern of the models . This suggests unaccounted variation on the preferential pairing during meiosis in some chromosomes. The next steps involve using Tools for Polyploids R packages for genetic mapping to elucidate meiotic behavior (mappoly); for haplotype reconstruction of the multiparental population (polyHaplotyper or polyOrigin); and finally, for identification of QTL related to spittlebug resistance (polyqtlR).
QTL mapping of fruit quality traits in tetraploid kiwiberry (Actinidia arguta)
Ran Wang1, Xiujuan Qi2, Jinbao Fang2, Peter Bourke1, Richard G.F. Visser1, Chris Maliepaard1. 1Wageningen University and Research, 2Zhengzhou Fruit Research Institute.
Fruit quality traits play an important role in consumer preferences and consumption of kiwiberry (Actinidia arguta). The genetic basis of fruit quality traits in this woody, perennial and dioecious fruit crop so far remains largely unknown. This study aimed to identify the underlying genetic basis of fruit quality traits in A. arguta, using a single nucleotide polymorphism (SNP) genetic linkage map previously developed in a tetraploid F1 population of ‘Ruby-3’ x ‘KuiLv-M’. The F1 population was phenotyped over three years (2020–2022) for fruit quality traits, including skin colour, flesh colour, weight, diameter, total soluble solids, longitudinal diameter and fruit shape index. A total of nine QTLs were detected for five traits in this study, explaining between 10 - 32% of the trait variation. For fruit colour, the support interval of a major QTL on LG9 contained an MYB transcription factor MYB110, which was previously demonstrated to control colour regulation in kiwifruit, thus suggesting that the transcription factor MYB110 is the candidate gene for fruit colour in kiwiberry. The linked marker for fruit colour was validated in an F1 population and 24 kiwiberry cultivars. In conclusion, the knowledge obtained through the QTL mapping is applicable to improve the efficiency and cost-effectiveness in kiwiberry breeding.
Mapping high specific gravity trait in potato using Genotyping by sequencing.
Nima Samadi, Vidyasagar Sathuvalli Rajakalyan, Solomon Yima. Oregon State University, Corvallis, OR.
Potato varieties that combine high yields and biotic and abiotic stress tolerance with a high percentage of solids are needed by the potato processing industry. The dry matter content of tubers, as measured by specific gravity, is an important measure of quality used by processors to assess the suitability of potatoes for the production of French fries, chips, and dehydrated products. There are many factors that affect the specific gravity of tubers: variety, growing season, planting time, seed quality, planting density, nutrition, irrigation, pests, diseases, and soil type. However, the selection of suitable varieties is the most efficient way to produce potato crops with desired tuber specific gravity. In this study, we aim to identify the genomic regions associated with high specific gravity from a diploid hybrid population of Solanum phureja – S. stenotomum comprising 150 diploid individuals. The population was evaluated for its specific gravity for two years (2018 and 2019) across three distinct locations in Oregon. We employed Genotyping by Sequencing (GBS) to genotype the population, resulting in a total of 47,232 SNPs. Following data imputation and filtering, we identified 3,698 high-quality SNPs for use in the Genome-Wide Association Study and QTL mapping analyses. GWAS and QTL mapping analyses are currently underway. The genomic regions identified from this study will be used to identify candidate genes and to develop molecular markers for marker-assisted breeding for high specific gravity trait.