NSF funded project for assembling 27 diverse maize lines
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.
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.
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
For all 25 NAM assemblies: BioProject ID PRJEB31061 and ArrayExpress ID (RNASeq) E-MTAB-8633 .
For B73 version 5: BioProject ID PRJEB32225 and ArrayExpress ID (RNASeq) E-MTAB-8628.
For EM-seq data (methylation) ArrayExpress ID E-MTAB-10088.
For ATAC-seq data NCBI-GEO ID GSE165787.
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_Jan2021_release). Details on how to use iRods for bulk download can be found here.
MaizeGDB genome browser.
3. Other information
Associate Professor, Department of Ecology, Evolution, and Organismal Biology, Iowa State University
Computational Biologist and Lead scientist, MaizeGDB, USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA
Bioinformatic Engineer, MaizeGDB, USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA
Corteva AgriScience, Clive, IA
Associate Professor, Department of Agronomy and Plant Genetics, University of Minnesota
Corteva Agriscience, Agriculture Division of DowDuPont
IT Specialist, MaizeGDB, USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA
Professor, Pioneer Distinguished Chair in Maize Breeding, Department of Agronomy, Iowa State University
Computational Science Developer II, Ware Lab, CSHL.
Senior Research Associate, Dawe Lab, UGA
Lab Manager, Hirsch lab, UMN.
Scientist I/Adjunct Associate Professor,Yu Lab, ISU
Computational Science Developer, Ware Lab, CSHL.
Associate Scientist, Genome Informatics Facility, ISU
Manager, Computational Science III, Ware Lab.
Lab manager, Hufford lab, ISU
Computational Science Manager, Ware Lab, CSHL.
Computational Science Analyst II, Ware Lab, CSHL
Computational Biologist, MaizeGDB, USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA
Postdoc Research Associate, Yu Lab, ISU.
Postdoc Research Associate, Hirsch Lab, UMN
Joint-Postdoc Research Associate, Hufford Lab & Hirsch Lab
Postdoc Research Associate, Ware Lab, CSHL.
PhD Student, Hirsch lab, UMN.
PhD Student, Hufford lab, ISU.
PhD Student, Dawe lab, UGA
PhD Student, Hufford lab, ISU
PhD Student, Hufford lab, ISU
PhD Student, Dawe lab, UGA
PhD Student, Hufford lab, ISU
PhD Student, Dawe lab, UGA