A Sequence-Indexed Reverse Genetics Resource for Maize: A Set of Lines with Single Ds-GFP Insertions Spread throughout the Genome

Project Details


PI: Hugo K. Dooner (Rutgers University)

CoPI: Charles Du (Montclair State University)

The availability of a mutant line in which a single gene has been disrupted gives biologists a powerful tool in understanding the action of that gene. Thus, sequence-indexed collections of single insertions are critical resources for elucidating gene function in organisms with sequenced genomes and are deemed essential by the community to fully exploit the maize genome sequence. It has recently become feasible to combine high-throughput sequencing with multi-dimensional pooling strategies to sequence and index hundreds of new insertions at a time. This work will complete the production of a reverse genetics resource based on the transposon Ds that will enable the community to generate and build up a single-gene knockout resource for maize. Specifically, the work will: (1) characterize the transposition frequency of 78 single Ds-GFP (or Ds*) launching platforms generated by Agrobacterium transformation during the previous grant period and map them to the genome. Highly active platforms will be identified and deposited in the Stock Center to complement the 82 already mapped. These platforms will allow visual selection of transpositions from many regions of the genome and, thus, enable researchers to create regional gene knock-out collections; (2) generate collections of 480 Ds* transpositions each from 24 Ds* launching platforms located on all 10 chromosomes which, together with the 9 collections currently at hand, will serve as the foundation for a Ds*-based maize single-gene knockout resource; and (3) sequence-index these collections by high throughput MiSeq Illumina sequencing of 3-D DNA pools. To this end, a specific software package (InsertionMapper) was developed to extract Ds* transposon junctions from the large amount of sequencing data and map them to the maize genome.

This project will integrate high throughput sequencing at Rutgers with bioinformatic sequence analysis at Montclair State University, a predominantly undergraduate institution in NJ. MSU students will annotate all Ds*-adjacent sequences generated by the NextGen sequencer. The project will provide informatics and molecular biology students at that institution with the opportunity to participate directly in maize research and fulfill their independent research requirement for graduation. Students at both Rutgers and MSU will work in the project as summer interns in the molecular biology lab and maize genetics nursery of the PI. The PI and coPI are members of underrepresented groups and have a record of fruitful prior collaborations. They have collaborated in previous NSF PGRP-funded projects which led to the development of a bioinformatics tool and the publication of three joint papers. About a third of the Genomics students participating in the project at MSU are members of underrepresented minorities. MSU has added the research opportunity from this project to its outreach campaign to attract and retain minority high school graduates. This project is relevant to U.S. agriculture in that it deals with maize, the most important American crop today. It addresses a critical need in that it will deliver a sequence-indexed reverse genetics resource, considered essential for researchers to fully exploit the maize genome sequence. All data will be made available through a web-searchable database of insertion site sequences (http://www.acdsinsertions.org/) that are cross-referenced to ~10000 seed stocks available from the Maize Genetics Cooperation Stock Center (http://maizecoop.cropsci.uiuc.edu). All relevant information from this project will be accessible through http://www.acdsinsertions.org/ and long-term through MaizeGDB (http://www.maizegdb.org).

Effective start/end date15/04/1431/03/19


  • National Science Foundation: $2,073,995.00


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.