Data

Transcriptome of multiple herbicide resistant and susceptible Lolium rigidum plants

The University of Western Australia
Yu, Qin ; Han, Heping ; Beffa, Roland ; Maiwald, Frank ; Powles, Steve
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://research-repository.uwa.edu.au/en/datasets/e38a3c47-7efd-48f7-bb79-f433e75d6423&rft.title=Transcriptome of multiple herbicide resistant and susceptible Lolium rigidum plants&rft.identifier=e38a3c47-7efd-48f7-bb79-f433e75d6423&rft.publisher=EMBL-EBI&rft.description=This dataset presents RNA-sequencing (RNA-Seq) results of multiple herbicide resistant versus susceptible Lolium rigidum plants. The data was generated in a project identifying cytochrome P450 genes involved in metabolic herbicide resistance in L. rigidum. The herbicide resistant (R) L. rigidum population (SLR31) was originally collected from Bordertown, South Australia (S 36°18', E 140°46') exhibiting resistance to many different herbicides. The metabolism-based resistant sub-population was generated by plant vegetative cloning plus target-site ACCase/ALS gene sequencing, and herbicide/P450 inhibitor (malathion) treatments. The purified metabolic resistant plants did not possess resistance ACCase and ALS mutations. The susceptible (S) population (VLR1) is a commercial biotype from Victoria, Australia, which is susceptible to all herbicides used for ryegrass control. F2 populations were generated from pair crosses of the R and S parent plants. This dataset included raw RNA-Seq data of 4 parent R versus 4 parent S and 4 F2 R versus 4 F2 S samples. RNA-Seq was conducted with an Illumina HiSeq High-Output sequencer on PE125 reads. &rft.creator=Yu, Qin &rft.creator=Han, Heping &rft.creator=Beffa, Roland &rft.creator=Maiwald, Frank &rft.creator=Powles, Steve &rft.date=2020&rft.relation=http://research-repository.uwa.edu.au/en/publications/4dfc6aa3-c223-4fe0-9514-09496833281d&rft.relation=http://research-repository.uwa.edu.au/en/publications/0c2f3391-fb0d-4363-96a8-84be36cea808&rft.coverage=The herbicide resistant population SLR31 was originally collected from Bordertown, South Australia, S 36°18', E 140°46'&rft_subject=GRDC&rft_subject=Lolium rigidum&rft_subject=RNA-sequencing&rft_subject=Metabolic herbicide resistance&rft.type=dataset&rft.language=English Access the data

Access:

Open

Full description

This dataset presents RNA-sequencing (RNA-Seq) results of multiple herbicide resistant versus susceptible Lolium rigidum plants. The data was generated in a project identifying cytochrome P450 genes involved in metabolic herbicide resistance in L. rigidum. The herbicide resistant (R) L. rigidum population (SLR31) was originally collected from Bordertown, South Australia (S 36°18', E 140°46') exhibiting resistance to many different herbicides. The metabolism-based resistant sub-population was generated by plant vegetative cloning plus target-site ACCase/ALS gene sequencing, and herbicide/P450 inhibitor (malathion) treatments. The purified metabolic resistant plants did not possess resistance ACCase and ALS mutations. The susceptible (S) population (VLR1) is a commercial biotype from Victoria, Australia, which is susceptible to all herbicides used for ryegrass control. F2 populations were generated from pair crosses of the R and S parent plants. This dataset included raw RNA-Seq data of 4 parent R versus 4 parent S and 4 F2 R versus 4 F2 S samples. RNA-Seq was conducted with an Illumina HiSeq High-Output sequencer on PE125 reads.

Notes

External Organisations
Bayer AG
Associated Persons
Roland Beffa (Creator); Frank Maiwald (Creator)

Created: 2016 to 2016

Issued: 2020

This dataset is part of a larger collection

Click to explore relationships graph

Spatial Coverage And Location

text: The herbicide resistant population SLR31 was originally collected from Bordertown, South Australia, S 36°18', E 140°46'

Subjects

User Contributed Tags    

Login to tag this record with meaningful keywords to make it easier to discover

Identifiers
  • global : e38a3c47-7efd-48f7-bb79-f433e75d6423