Sol CAP Solanaceae Coordinated Agricultural Project Dedicated to

Sol. CAP Solanaceae Coordinated Agricultural Project Dedicated to the Improvement of Potato and Tomato Executive Commitee : David Douches Walter De Jong Robin Buell David Francis Alexandra Stone Lukas Mueller Allen. Van Deynze Supported by the National Research Initiative Plant Genome Program of USDA’s Cooperative State Research , Education and Extension Service

Commercial Solanaceae Production US: $5. 38 billion product value (1. 6 million acres)

Solanaceae Breeding Bottlenecks & Challenges • Narrow genetic base • Inefficient early generation selection • Many pests • Multi trait evaluation – Quality – Resistance – Agronomy • Market differentiation • Lack of markers in elite germplasm • Small populations

In Solanaceae There is a Major Gap Between Genomic Information and Breeding • Tomato and potato breeding are based upon phenotypes, not genotypes, despite the fact that they are being sequenced • Sol Genomics Network (SGN) database is not being utilized by breeders • Similar genomes, few examples of orthologous gene discovery • Marker assisted breeding (MAB) is not practiced due to: – limited genetic diversity – lack of genetic markers linked to traits of interest

Sol. CAP Project Participants Lead Institution: Michigan State University New York Cornell University Maryland Oregon USDA/ARS Beltsville Oregon State University Cedar Lake Research and Consulting Idaho USDA/ARS University of Idaho California Minnesota UC Davis Campbells R&D Wisconsin University of Minnesota USDA/ARS University of Wisconsin Michigan State University Ohio State University West Virginia State University North Carolina State University Florida University of Florida

Principal Scientists • • David Douches (Michigan State, potato breeder) David Francis (Ohio State, tomato breeder) Walter De Jong (Cornell University, potato breeder) Allen Van Deynze (UC Davis, genotyping/sequencing) Robin Buell (Michigan State, sequencing/bioinformatics) Lukas Mueller (Boyce Thompson Inst. , bioinformatics) Alexandra Stone (Oregon State, e. Xtension)

Sol. CAP Research Objectives • CSREES (Two E’s focus of afternoon session) • Primary research objective: – To provide infrastructure to link allelic variation in genes to valuable traits within the two most important vegetable crops in the Solanaceae: potato and tomato • General objectives: – Increase the likelihood that breeding of crops in the Solanaceae will benefit from genotype based selection processes – Leverage genomic resources for the improvement of multiple crops that share taxonomic affinity and DNA homology first CAP that has a multiple species focus • Unique challenge because, despite having close genomic structure, the breeding systems are different – Expand beyond a single commodity to encompass multiple related species will create a broader vision for translational genomics in agricultural research.

Stakeholder defined Core Components – Traits • Carbohydrate and sugar metabolism (processing traits) – Germplasm • Elite germplasm, Breeder driven; Appropriate outgroups – Tools • Fund existing facilities to SNP genotype germplasm panels – Flexible funding • genotyping additional populations for validation or additional traits • marker conversion – Data mining and management • SGN, Sol. CAP websites – Extension • e. Xtension; partner with other CAPs – Education • Curriculum development; breeder workshops, graduate course

How will tomato and potato breeding benefit from Sol. CAP? • Develop molecular genetic tools and infrastructure so that applied breeders can begin to use marker assisted selection in elite germplasm. • Develop 1536 SNP (or more as platforms expand) markers that are polymorphic in elite potato and tomato germplasm. • SNP Genotype 480 potato clones and 480 tomato lines provided by North American breeders with these markers.

How will Tomato and potato breeding benefit from Sol. CAP? • Provide, as a service, genotyping of populations/ breeding clones in 2010, 2011 and 2012, submitted by the breeding community. • Develop a breeder portal for access to SGN (sgn. cornell. edu) to improve use by applied breeders. • Workshops for breeders, staff, and graduate students in bioinformatics, marker theory and practice. • Develop a distance education course in marker assisted breeding. • Generate and disseminate web accessible outreach materials for the public, through an e. Xtension community of practice.

Objectives • Summarize all research objectives here…

Germplasm Panels • Collect standardized phenotypic data across multiple environments for tomato and potato. – standardized database of phenotypes for key traits across germplasm panels for each commodity, accessible through the Sol. CAP and Solanaceae Genome Network (SGN) websites.

Germplasm Panels • Cooperative tests at least 2 locations for each crop under the supervision of experienced field breeders. • Through the “cooperators guide”, we will also promote a “genomics mentality” that emphasizes increased genotypic replication and the collection of standardized and objective phenotypic data that can be linked to ontologies.

High throughput analysis of carotenoids, sugars, and acids using IR Spectra (Luis Rodruiguez Saona, D. Francis, OSU) Absorbance, A 0. 08 0. 06 Red Tomato Yellow Tomato Green Tomato translycopene 0. 04 Lycopene 0. 02 0. 00 3600 3200 2800 2400 2000 1600 Wavenumber, cm-1 1200 800

Pred conc (mg/100 g) by ATR-IR Lycopene Quantification 12 R=0. 958 SEV = 0. 80 mg/100 g 8 4 0 0 5 10 Lycopene conc (mg/100 g sample) by HPLC

Germplasm Panel, e. g. Potato • A subset of the germplasm panel will be: – Lines chosen based upon CHO variation – Important varieties and advanced lines of value to the breeder – Solanum species and accessions introgressed into 4 x germplasm – 4 x mapping population from a russet x russet cross: primary CHO/ vitamin C mapping population for QTL analysis – 2 x mapping population will be used for mapping SNPs

Germplasm Panel, e. g. Potato • Field tested 2 years X 3 major environments for potato production (PNW northern irrigated desert/fall harvest, NC northern humid/ fall harvest and SE southern humid/spring or summer harvest) to collect samples for CHO, vitamin C analysis and other traits. – Evaluation of specific gravity, chip color, skin type, shape, vine maturity, tuber number, vitamin C, internal defects, bruising, anthocyanins and biotic resistances. – K. Haynes (USDA/ARS, MD) will provide experimental design, data management (combining genotypic and phenotypic data) and statistical analysis of the phenotypic data for potato.

Genotyping Platform • Develop extensive sequence data of expressed genes, and identify Single Nucleotide Polymorphism (SNP) markers associated with candidate genes for sugar, carbohydrate, and vitamin biosynthetic pathways. – Catalog allelic variation in structural and regulatory genes and subsequently explore correlation with corresponding traits.

c. DNA Libraries for Sequencing Using illumina Genome Analyzer (Solexa) Tomato • T 5(CA fresh market) • FL 7600(Florida fresh market) • NC 84173(North Carolina fresh market) • OH 9242(Ohio processing) • PI 114490(wild cherry tomato) • PI 128216(wild current tomato) • H 1706 (Midwest Processing; focus of Genome sequence) • TA 496 (CA Processing; focus of EST sequence) Potato • Snowden • Atlantic • Premier Russet Leaf Flower Callus Tuber Leaf Flower Callus Fruit

Sequencing and Marker Discovery • Transcript assemblies – Represent consensus sequences of all ESTs • alleles that are similar enough to be co assembled under the parameters used. – Represent the predominant allele in the underlying EST population • Identify SNPs via alignment to consensus transcript assemblies and reference genome sequence. – computationally identify all possible SNPs within a genotype

Add data from Robin’s e. SNP discovery and cross linking to validated SNPs … # in potato # in tomato Validation flags

High Throughput Genotyping illumina Genomic Analyzer

SNP Genotyping • Establish centralized facilities for genotyping a core set of SNPs in standard germplasm panels in tomato and potato. – a uniform database (>1. 47 M data points) of integrated mapped markers and genotypes for 480 accessions of each crop. – The genetic data will resolve population structure and facilitate association mapping in the core collections and designing further QTL mapping populations – (For e. g. see Matt Robbins, OSU, presentation)

Genotyping the core collections will impact strategies for translation. • Potential translational approaches: – 1) introgression from other populations (domesticated or wild) – 2) selection for coupling phase recombinants to establish linkage blocks of favorable alleles (e. g. disease resistance loci) – 3) population development designed to maximize variation w/in market classes – 4) association approaches – 5) whole genome approaches • Other translational strategies will emerge under other CAPs or through innovation in public research. • Currently traits and populations among the breeding communities for tomato and potato exist to implement each of the five approaches, but there are insufficient numbers of markers to do so.

Small Grants Program • Address regional, individual program and emerging needs within the Solanaceae community through a small grants program. • Six key areas we intend to allocate resources to are: – Genotyping mapping populations in the core facilities requested by the greater breeding community – Marker conversion – developing SNP markers linked to QTL into easily assayed (e. g. CAPs or d. CAPs) markers that end users can readily apply in their own research programs – QTL validation and MAS – Population development to address emerging needs – Extension or education special projects – New directions not envisioned at the time of proposal submission.

Databases and Resources • Create integrated, breeder focused resources for genotypic and phenotypic analysis by leveraging existing databases and resources at SGN and MSU. – Breeders, geneticists, and bioinformaticians will work to create integrated genomic and phenotypic databases that serve the entire potato and tomato breeding and genetics community

Developing “Breeder Friendly” Tools consider dropping from PAG • Current SGN interfaces are aimed at the molecular biologist, with searches designed to facilitate molecular discovery – Need a portal that is trait and germplasm centered • Ability to search by traits relevant to (and defined by) breeders • When a marker is identified, a protocol for use in breeding will be provided. • Search option that only yields polymorphic marker, phenotype, or QTL results from elite germplasm • Ability to search for known parents or offspring of any given genotype • Ability to generate a list of markers that are polymorphic between any two parents • Detailed tutorial/definitions of terms and traits utilized within the database

Outcomes for Breeding from Sol. CAP • A genome wide set of markers and bioinformatic tools accessible by breeders – Breeders will access germplasm for crossing based upon SNP polymorphism and linked QTL of interest – design crosses complementary for QTL and traits, and then use MAB in EGS.

Outcomes for Breeding from Sol. CAP • Better understanding of the allelic variation influencing CHOs – Design crosses to create improved sugar and starch levels and starch quality. – Crosses designed to manipulate and select variation within existing elite populations or introgress novel alleles from wild germplasm. – More predictable and directed breeding effort for processing and fresh market traits.

Outcomes for Breeding from Sol. CAP • The discovery of orthologous genes through improved bioinformatic databases

Outcomes for Breeding from Sol. CAP • Changes in breeding systems. Vegetable breeding has limitations not inherent in grain (cost of plot maintenance; narrow harvest window) Influence breeders to increase genotypic replication Make better use of breeding values through incorporation of information on population structure and kinship Use objective means to increase variation in breeding populations.

Sol. CAP Management Structure

http: //solcap. msu. edu