Contributions of the VitisGen2 project to grapevine breeding and genetics

The VitisGen projects (2011-2022) have improved the tools available for breeding new grapevine cultivars with regional adaptation, high quality, and disease resistance. VitisGen2 (the second project in the series) was a multi-state collaboration (USDA-Geneva, New York; University of California, Davis; USDA-Parlier, California; Cornell University; Missouri State University; University of Minnesota; South Dakota State University; Washington State University; North Dakota State University; and E&J Gallo, California) to develop improved genetic mapping technology; to identify useful DNA marker-trait associations; and to incorporate marker-assisted selection (MAS) into breeding programs. A novel genetic mapping platform (rhAmpSeq) now provides 2000 + markers that are transferable across the Vitis genus. rhAmpSeq has been used in California, New York, Missouri, and South Dakota to identify new QTL for powdery and downy mildew resistance. In addition, fruit/flower traits that would normally take years to phenotype have been associated with predictive markers accessible from seedling DNA (e.g. malate metabolism, anthocyanin acylation, bloom phenology and flower sex). Since 2011, the project has used MAS to screen thousands of grape seedlings from public breeding programs in the United States and has produced “Ren- Stack” public domain lines to enable simultaneous access to 4 or 6 powdery mildew resistance loci from single source genotypes. High-throughput phenotyping for powdery and downy mildew resistance has been revolutionized with the Blackbird automated-imaging system powered by artificial intelligence for image analysis. Affordable DNA sequencing along with phenotyping innovations are transforming grapevine breeding

Next Generation Mapping of Enological Traits in an F2 Interspecific Grapevine Hybrid Family

In winegrapes (Vitis spp.), fruit quality traits such as berry color, total soluble solids content (SS), malic acid content (MA), and yeast assimilable nitrogen (YAN) affect fermentation or wine quality, and are important traits in selecting new hybrid winegrape cultivars. Given the high genetic diversity and heterozygosity of Vitis species and their tendency to exhibit inbreeding depression, linkage map construction and quantitative trait locus (QTL) mapping has relied on F1 families with the use of simple sequence repeat (SSR) and other markers. This study presents the construction of a genetic map by single nucleotide polymorphisms identified through genotyping-by-sequencing (GBS) technology in an F2 mapping family of 424 progeny derived from a cross between the wild species V. riparia Michx. and the interspecific hybrid winegrape cultivar, ‘Seyval’. The resulting map has 1449 markers spanning 2424 cM in genetic length across 19 linkage groups, covering 95% of the genome with an average distance between markers of 1.67 cM. Compared to an SSR map previously developed for this F2 family, these results represent an improved map covering a greater portion of the genome with higher marker density. The accuracy of the map was validated using the well-studied trait berry color. QTL affecting YAN, MA and SS related traits were detected. A joint MA and SS QTL spans a region with candidate genes involved in the malate metabolism pathway. We present an analytical pipeline for calling intercross GBS markers and a high-density linkage map for a large F2 family of the highly heterozygous Vitis genus. This study serves as a model for further genetic investigations of the molecular basis of additional unique characters of North American hybrid wine cultivars and to enhance the breeding process by marker-assisted selection. The GBS protocols for identifying intercross markers developed in this study can be adapted for other heterozygous species

The epiphytic microbiota of sour rot-affected grapes differs minimally from that of healthy grapes, indicating causal organisms are already present on healthy berries.

Sour rot is a disease complex produced by an interaction between grape berries and various species of yeast and acetic acid bacteria in the presence of Drosophila fruit flies. While yeast and bacteria are consistently found on healthy grape berries worldwide, we explored whether the composition of these epiphytic communities differed depending on the presence or absence of sour rot symptoms. Using high-throughput sequencing, we characterized the microbiome of sour rot-affected grapes from two geographical areas across two years. In 2015 and 2016, both healthy and sour rot-affected berries were collected from commercial and research vineyards in Geneva, NY and commercial vineyards in Tasmania, AUS. In this experiment, all associated organisms grouped together primarily by location, and not by presence/absence of symptoms or cultivar. The predominant difference between asymptomatic and symptomatic samples, regardless of location, was the abundance of Acetobacter species, which were significantly more plentiful in the symptomatic samples. Yeast genera such as Candida, Hanseniaspora, Pichia and Saccharomyces were abundant in both sets of samples, but varied by region. The consistent presence of yeast species and the increased abundance of acetic acid-generating bacteria is consistent with our understanding of their etiological role in sour rot development. In 2016, diseased grapes also were collected from vineyards in Fredonia, NY, and Modesto, CA. Consistent with our comparison study, all associated organisms again grouped together primarily by location. Yeast genera such as Candida, Hanseniaspora, Pichia and Saccharomyces were abundant in both sets of samples, but varied by region. The consistent presence of yeast species and the abundance of acetic acid-generating bacteria in both experiments is consistent with our understanding of their etiological role in sour rot development

QScout: A QGIS plugin tool suite for georeferencing and analysis of field‐scouted and remote sensing data

Abstract Field scouting is an important part of many research methodologies in plant pathology and plant phenomics. However, linking scouting data to field imagery is often hampered by the time‐consuming task of georeferencing with a GIS. Here, we present the QScout tool suite for integrating remote sensing imagery and raster data with field‐scouting data in QGIS, an open‐source GIS program. The central features of QScout are the Drop Pins and Locate Pins plugins, allowing the user to easily link scouted data to remote sensing imagery. QScout also includes the Value Grabber and Grid Aggregator plugins, which transfer raster data into pins and aggregate the data from the pins into a grid, respectively. The final tools, Drop, Grab, and Aggregate and Locate, Grab, and Aggregate, are plugins that combine subsets of the four core plugins. The interface allows GIS users to effectively make use of field‐scouted observations with remote imagery and can improve data organization, analysis, and identification of locations of interest for further scouting or targeted management. QScout is publicly available as a GitHub repository: (https://github.com/GoldLabGrapeSPEC/QScout)

Heterozygous Mapping Strategy (HetMappS) for High Resolution Genotyping-By-Sequencing Markers: A Case Study in Grapevine

<div><p>Genotyping by sequencing (GBS) provides opportunities to generate high-resolution genetic maps at a low genotyping cost, but for highly heterozygous species, missing data and heterozygote undercalling complicate the creation of GBS genetic maps. To overcome these issues, we developed a publicly available, modular approach called HetMappS, which functions independently of parental genotypes and corrects for genotyping errors associated with heterozygosity. For linkage group formation, HetMappS includes both a reference-guided synteny pipeline and a reference-independent <i>de novo</i> pipeline. The <i>de novo</i> pipeline can be utilized for under-characterized or high diversity families that lack an appropriate reference. We applied both HetMappS pipelines in five half-sib F₁ families involving genetically diverse <i>Vitis spp</i>. Starting with at least 116,466 putative SNPs per family, the HetMappS pipelines identified 10,440 to 17,267 phased pseudo-testcross (Pt) markers and generated high-confidence maps. Pt marker density exceeded crossover resolution in all cases; up to 5,560 non-redundant markers were used to generate parental maps ranging from 1,047 cM to 1,696 cM. The number of markers used was strongly correlated with family size in both <i>de novo</i> and synteny maps (r = 0.92 and 0.91, respectively). Comparisons between allele and tag frequencies suggested that many markers were in tandem repeats and mapped as single loci, while markers in regions of more than two repeats were removed during map curation. Both pipelines generated similar genetic maps, and genetic order was strongly correlated with the reference genome physical order in all cases. Independently created genetic maps from shared parents exhibited nearly identical results. Flower sex was mapped in three families and correctly localized to the known sex locus in all cases. The HetMappS pipeline could have wide application for genetic mapping in highly heterozygous species, and its modularity provides opportunities to adapt portions of the pipeline to other family types, genotyping technologies or applications.</p></div

Comparison of the distribution of minor tag frequency (MTF) and minor allele frequencies (MAF) in final and spurious SNPs.

<p>MTF (continuous line) and MAF (dotted line) distributions are shown for A) the final map (9,876 SNPs) and B) markers removed during curation (1,204 SNPs) in ‘Horizon’ x Illinois 547–1 <i>de novo</i> map.</p

Relatedness to parents and Mendelian errors in the F₁ family 'Horizon' x Illinois 547–1.

<p>A) Analysis of progeny relatedness to parents demonstrated that most progeny had expected relatedness values near (0,0), whereas 8 individuals were more related to ‘Horizon’ (emasculated hermaphrodite parent) and less related to Illinois547-1 (pollen parent) and were thus removed for downstream analysis. B) Mendelian error analysis indicated that 7 of these same individuals were enriched for male incompatible genotypes.</p

Separation of chromosomes into linkage groups (LGs) in the HetMappS synteny pipeline.

<p>This dendrogram was created from hierarchical clustering of a topological overlap matrix (as implemented by WGCNA) for markers on chromosome 2 in the F₁ family ‘Horizon’ x Illinois 547–1. LGs result from cutting the dendrogram with height 0.9 and minimum cluster size 30, creating one LG for each parent.</p

Linkage group (LG) formation in the HetMappS <i>de novo</i> pipeline.

<p>A representative dendrogram is shown for the F₁ family ‘Horizon’ x Illinois 547–1, created from hierarchical clustering of a topological overlap matrix (as implemented in WGCNA), and subsequent cutting of the dendrogram. A cut height of 0.925 and minimum LG size of 50 resulted in 91% of the initial markers (15,464) separating into 40 LGs. Two pairs of LGs were joined in subsequent steps to create 2 parental maps with 19 LGs each.</p

Overview of the HetMappS pipelines.

<p>(A) shared initial steps resulting in identification of pseudo-testcross markers, (B) linkage group creation and phasing steps, either (B1) synteny or (B2) <i>de novo</i>, and (C) genetic ordering and formatting for R/qtl.</p