Overview for Breeders Jing Yu, Sook Jung, Chun-Huai Chung, Taein Lee, Ping Zheng, Jodi Humann, Deah McGaughey, Morgan Frank, Kirsten Scott, Heidi Hough,

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Presentation transcript:

Overview for Breeders Jing Yu, Sook Jung, Chun-Huai Chung, Taein Lee, Ping Zheng, Jodi Humann, Deah McGaughey, Morgan Frank, Kirsten Scott, Heidi Hough, Todd Campbell, Josh Udall*, Don Jones, Dorrie Main Cotton Breeders Tour 2017 Chandler, Arizona It is pleasure to present a little information on CottonGen – a community database for cotton research. One of the primary intentions of cottongen is to serve cotton breeders as the improve and release cotton varieties. CottonGen is a community effort. The authors listed here have made direct contributions to its functionality.

Like every other science, cotton breeding is changing with the digital age. We are collecting more phenotype data than ever before. We are collecting more DNA sequence data than ever before. More isn’t always better. This amount of data is only useful if we can connect the dots and make proper scientific interpretations.

Community Databases Increasingly Important CottonGen’s primary mission is to support research by connecting datasets How can CottonGen be useful to you??? BIMS for cotton breeding Identify genetic markers to track traits Compare results of previous work with your own (e.g. QTLs) DNA sequence analysis (BLAST, PATHWAYS, sequence retrieval) Recent publications Individual scientists now routinely Sequence and genotype genomes from populations, families, individuals of interest Pursue large-scale gene expression studies Create highly saturated genetic maps Identify genome wide loci influencing traits of interest Conduct large-scale standardized phenotyping – challenging! CottonGen is a community database. Just a reminder that these type of databases are increasingly important in the era of big data generation and usage in crop science research. Where before big data was generated only in big programs, nowadays because of the reduction in cost and time associated with technological and computation advances, individual investigators and routinely generating these type of data. For example they are: Read the list …….

Integrated Data & Tools Integrated Data Facilitates Discovery and Application Genetics Breeding Germplasm Diversity Genomics Integrated Data & Tools Basic Science Translational Science Trait discovery Marker development Genetic mapping Breeding values Structure and evolution of genomes Gene function Genetic variability Mechanism underlying traits Just a reminder to ourselves of how integrating research data facilitates discovery and application. Then just click through and read the points under each section. 1. to send us the map and QTL data in excel format once the paper published. 2. to use the names giving in the Cotton Trait Ontology. Applied Science Utilization of DNA information in breeding decisions 4

About CottonGen Hosts the ICGI website within it and serves as a communication portal for cotton GGB science It is funded by a partnership between the cotton industry and federal programs

Data Available on CottonGen Genomics Data Annotated genome sequences (A2, D5, AD1, and AD2) Annotated RNA Seq reference transcriptomes (A2, D5, AD1, and AD2) Annotated Gossypium EST unigene CottonCyc metabolic pathways (D5 and AD1) Synteny (D5 and AD1) Genetics and Breeding Data 103 genetic maps 404K genetic markers 1026 QTLs 16K germplasm from GRIN, NCGC, China, Uzbekistan, etc. collections 12K digital images of 2K germplasm from USDA-ARS NCGC 492K trait scores from evaluations of US NCGC, GRIN, China and Uzbekistan 60K trait scores for 20 fiber traits from 14 years of RBTN trials (newly added) Just to give you an overview of the types of public data we have in CottonGen, which we have categorized here as genomics or genetics and breeding data. Just highlight some you these Josh.

3 Takehome points of CottonGen As reviewers and editors, please require data submission to CottonGen. Receive a CottonGen ID number. As you design and publish your experiments, use common descriptors and methods Use CottonGen! It is your resource. It is excellent.

Tools Available on CottonGen Implemented Tools Sequence BLAST Search Genome Browsers Pathway Cyc Map Comparison Sequence Retrieval Query search pages for Gene and transcripts Germplasm Marker publication QTL Phenotype data On this next slide we have an overview of the various tools and search pages we have in CottonGen

http://www.cottongen.org From the home page in cottongen you should be able to readily find access to the tools or data you are interested in. <Click> We have a major species quick start and as you can we have 4 species listed here. Clicking on them will take you to the data and tools available for that species (which I will show you shortly). <click> We also have a Tools Quick Start that provides links to some of the most used links in Cottongen, sorted by the type of user. <click> then at the top we have the navigation bar, that is available in all pages ypou subsequently visit

Species Dropdown: Links to Species Data and Tools Clicking on the species dropdown, you will see the individual species links for major ones. Selecting hirsutum in this case takes you to the species page for it, where you can see links <click> all the data types and tools <click> available for that particular species.

Data Dropdown: Cotton TO & NCGC Std. rating scales Clicking on the Data dropdown, you will see the links to specific data information (such as community project, Cotton Trait Ontology, etc.) and links to general data information (overview, download, submission) Selecting Cotton Trait Ontology in this case takes you to the Cotton TO for it, where you can see detailed information of cotton TO <click> all CottonGen standardized QTL names are formed by adding a lower-case “q” in front of each abbreviations, for example, trait 2.5 span length’s QTLs named as qSL2.5, fiber length QTLs named as qFL, etc. <click> from the page you also get the link to the Standardized rating scales that used in NCGC.

Data Dropdown: Cotton TO & NCGC Std. rating scales Here is the Standardized rating scales used in NCGC. All font green descriptors indicates the descriptor have panel image available, <click> such as selecting panel color <click> you see the panel image of petal color

Query Examples

Marker Search Select “Marker search” from the Search dropdown list, you will see a list of options of marker search and brief description of each option. such as to click here <click> for searching all marker loci that are within a specified distance of specific QTL on any map

Search Marker on Nearby QTLs This slide shows the interface of “search markers on nearby qtl” <click> To fill in qMIC* indicates to search all markers that nearby QTL “micronaire” (the trait abv is MIC, as listed on cotton trait ontology page), the wild card (*) is needed here is because that mapped QTL names will be followed by map related information (mapping pop, linkage group, etc.) <click> to fill in 5 means to set up the nearby distance within 5 cM away from the QTL Then we click on the green button “Search” <click> here is the search result

Find QTL(s) of SI that mapped on Chrom 23 The next query example is about QTL search. Assume that we want to find all “seed index” QTLs that mapped on chromosome 23. So we select “Search QTLs” from the Search dropdown list Search Dropdown → Search QTLs

Find QTL(s) of SI that mapped on Chrom 23 In the Search QTLs window, fill in trait name “seed index” <click> and QTL label has “ch23” <click>, then click on the green button “Search” <click> the search results will appear. <click> here to allow you to save the search results onto your own computer.

Further exploration on germplasm ‘7263 NLLY’

Find all germplasm with okra leave shape This example shows how to find all germplasm with okra shape leaves. From “search” dropdown list to “search trait evaluation” to “search qualitative traits” Search Dropdown → Trait Evaluation → Search Qualitative Traits

Find all germplasm with okra leave shape From dropdown list of trait to find “leaf shape”, there are several different evaluation datasets (UZ, CN, NCGC, etc.), <click> if we choose the dataset from NCGC, <click>the value will list all different shapes in this trait, Select “okra” from the value list, then “search” Trait Evaluation Search → select trait=leaf shape (NCGC) & value=okra → Search

Find all germplasm with okra leave shape We have the result here. <click> from NCGC germplasm evaluation, there are 1346 records has leave shape scored as “okra” <click> you can save the search result onto your own computer <click> click on germplasm name you can find more information about the specific germplasm Further exploration on germplasm ‘7263 NLLY’

CottonGen BLAST Home Page Now we are going to show how to run sequence BLAST on CottonGen. <click> from Toos dropdown list, select BLAST+, we see cottongen blast home page <click> the top part gives options of different blast programs <click> the lower part lists source of cottongen BLAST sequence databases and their descriptions <click> assume we want to use a nt sequence to search against a nt seq db (i.e. to run a blastn program)

Future Work - MapViewer

Future Work - 2002-2016 non-fiber trait data

Future Work – Integration of genomic information

Future Work Genomic information Adding RBTN 2002-2016 non-fiber trait data Further development of cotton breeding tools (BIMS) Collection and curation of more genetic maps, markers and QTLs Implementing new Map Viewer