Whole-Genome Assembly of the maize NAM founders

NSF funded project for assembling 27 diverse maize lines

About this project

Maize is not only an important crop but an important study species for answering basic questions about how plants grow and adapt to different environments. Genome assemblies, which are complete representations of the genetic information in a plant variety, are critical resources for answering these important questions. However, currently only a single type specimen is used as the sequence reference for most of the genetic information in maize, leaving unknown much of the highly valuable natural variation in maize. This project will assemble the genomes of 26 additional maize lines, chosen to represent a broad cross section of the maize lines used in modern breeding. The sequence assemblies will be enhanced by adding information about the nature of the genes and how the genomes differ from each other. All information will be released on an accelerated schedule through public databases.

Technical Abstract

Maize is an important crop and model organism for plant genetics. However, currently nearly all forms of sequence analysis are referenced to the single B73 inbred. Beyond B73, the most extensively researched maize lines are the core set of 25 inbreds known as the NAM founder lines, which represent a broad cross section of modern maize diversity. Prior data show that gene content can differ by more than 5% across lines and that as much as half of the functional genetic information lies outside of genes in highly variable intergenic spaces. To capture and utilize this variation, the NAM founder inbreds and a twenty-sixth line containing abnormal chromosome 10 will be sequenced and assembled using a mate-pair strategy. Scaffolds will be validated by BioNano optical mapping, and ordered and oriented using linkage data. RNA-seq data from multiple tissues will be used to annotate each genome, and assemblies and annotations will be released with genome browser support through MaizeGDB, NCBI, and Cyverse. Comparative genomic tools will be used to identify and to catalog the maize pangenome, and to assess the role of structural variation such as presence-absence variation and copy number variation in the determination of agronomic traits. Results will be disseminated through a project web site and a CyVerse/Gramene/MaizeCODE Workshop at the annual Maize Genetics Conference.

Deliverables

All genomes (including PacBio long reads, Illumina reads, optical maps, scaffolds, and AGP files) are uploaded to EBI and will be released on publication or January, 2020, whichever comes first. B73 Ab10 (BioProject ID PRJEB35367) will only be released after publication. Links will be active on Jan 9th, 2020.

1. Raw datasets (PacBio, BioNano, Illumina and RNASeq) and Genome Assemblies

2. Genome Assembly and Annotations

  • MaizeGDB FTP site for bulk download.

  • CyVerse download via iRods (public folder: /iplant/home/shared/NAM/NAM_genome_and_annotation_Jan2020_release). Details on how to use iRods for bulk download can be found here.

  • MaizeGDB genome browser.

3. Other information

  • MaizeGDB NAM metadata and general information link.

  • Scripts and protocols (in progress) GitHub.

Team

Principal Investigators

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R. Kelly Dawe

Distinguished Research Professor, Department of Genetics, University of Georgia

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Doreen Ware

Adjunct Associate Professor, USDA-ARS, CSHL, Ohio State University

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Matthew Hufford

Associate Professor, Department of Ecology, Evolution, and Organismal Biology, Iowa State University

Collaborators

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Carson Andorf

Computational Biologist and Lead scientist, MaizeGDB, USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA

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Ethalinda Cannon

Bioinformatic Engineer, MaizeGDB, USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA

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Kevin Fengler

Corteva AgriScience, Clive, IA

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Candice Hirsch

Associate Professor, Department of Agronomy and Plant Genetics, University of Minnesota

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Victor Llaca

Corteva Agriscience, Agriculture Division of DowDuPont

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John Portwood

IT Specialist, MaizeGDB, USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA

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Jianming Yu

Professor, Pioneer Distinguished Chair in Maize Breeding, Department of Agronomy, Iowa State University

Staff

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Kapeel Chougule

Computational Science Developer II, Ware Lab, CSHL.

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Jonathan Gent

Senior Research Associate, Dawe Lab, UGA

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Amanda Gilbert

Lab Manager, Hirsch lab, UMN.

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Xianran Li

Scientist I/Adjunct Associate Professor,Yu Lab, ISU

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Zhenyuan Lu

Computational Science Developer, Ware Lab, CSHL.

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Arun Seetharam

Associate Scientist, Genome Informatics Facility, ISU

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Joshua Stein

Manager, Computational Science III, Ware Lab.

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Michael Syring

Lab manager, Hufford lab, ISU

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Marcela K. Tello-Ruiz

Computational Science Manager, Ware Lab, CSHL.

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Sharon Wei

Computational Science Analyst II, Ware Lab, CSHL

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Maggie Woodhouse

Computational Biologist, MaizeGDB, USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA

Post-docs

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Tingting Guo

Postdoc Research Associate, Yu Lab, ISU.

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Christine O'Connor

Postdoc Research Associate, Hirsch Lab, UMN

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Shujun Ou

Joint-Postdoc Research Associate, Hufford Lab & Hirsch Lab

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Bo Wang

Postdoc Research Associate, Ware Lab, CSHL.

Graduate Students

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Rafael Della Coletta

PhD Student, Hirsch lab, UMN.

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David Hufnagel

PhD Student, Hufford lab, ISU.

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Jianing Liu

PhD Student, Dawe lab, UGA

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Nancy Manchanda

PhD Student, Hufford lab, ISU

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Sarah Pedersen

PhD Student, Hufford lab, ISU

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Rebecca Piri

PhD Student, Dawe lab, UGA

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Sam Snodgrass

PhD Student, Hufford lab, ISU

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Na Wang

PhD Student, Dawe lab, UGA

Collaborators