Details
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Type:
Task
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Status: Closed (View Workflow)
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Priority:
Major
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Resolution: Done
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Affects Version/s: None
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Fix Version/s: None
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Labels:None
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Story Points:2
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Epic Link:
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Sprint:Spring 6 2023 Mar 20, Spring 7 2023 Apr 10
Description
Muday Lab has detected possible sample switching in their time course data from three genotypes: ARE (mutant), F3H-OX3 (transgenic), and VF36 (wild-type, parent strain for F3H-OX3)
It was easy to identify which samples were ARE and not VF36 or F3H-OX3.
We need a way to distinguish F3H-OX3 from VF36 samples due to the sample switching issue.
To do this, we can use the fact that F3H-OX3 contains transgenic construct and VF36 does not.
Previously, we have found that the plant selective marker gene was expressed in soybean seeds in a transgenic line.
For this task, we'll investigate whether we can use the F3H-OX3 line's plant selection marker gene to distinguish transgenic from non-transgenic lines.
See:
- Open access article link: https://bmcbiotechnol.biomedcentral.com/articles/10.1186/s12896-015-0207-z
- Code repository: https://bitbucket.org/lorainelab/soyseq
Maarten has sent us three files with the construct information in them. These are added to the git repository here:
- ExternalDataSets/pK7WG2-F3H.fa
- ExternalDataSets/pK7WG2-F3H.gb
In this experiment, the plant selection gene was a kanamycin resistance gene.
For this task, use the kanamycin gene either as a query or a target in a search of the fastq files to identify samples that contain RNA-Seq reads from the kanamycin-resistance gene.
To do this, we need to investigate the different tools that might be available for this task.
Let's try to find an easy-to-use tool or approach that will let us identify RNA-Seq samples containing "kan" gene sequence.
Attachments
Issue Links
- relates to
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IGBF-3290 Use new sample labels recommended by Muday Lab
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- Closed
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Activity
Added gb and fa file with construct info to the repository.
See:
Also, ask for help on BioStars. Post a question and hope somebody gives us a great answer!
This might help:
Fastq files Directory: /nobackup/tomato_genome/muday-144/nfcore-2022/investigate_samples
Tool Resource: https://jasonjwilliamsny.github.io/shell-genomics/lessons/03_searching_files.html
Control: Solyc01G000038 (SL5)=Solyc01g005430(SL4)
- Control Genomic Sequence: https://solgenomics.net/feature/17666541/details
grep -B1 -A2 GTTTTAGCAA 7-are-15-min-28C_R1_001.fastq | wc -l 50044
Kanamycin Gene Sequence Origin:
grep -B1 -A2 GGCCCTCTAG 7-are-15-min-28C_R1_001.fastq | wc -l 2357
Candidate positive control sequence from the region flanking the first intron of Solyc01G000038 in SL5 assembly
left side of intron:
GATTGATAGACAG
right side of intron:
ATTAAAGTGTTCTTTTCTGTTCCGG
Search the two sequences spliced together as:
GATTGATAGACAGATTAAAGTGTTCTTTTCTGTTCCGG
Using IGB to count overlapping reads with gaps yields 3260 aligned reads that could match the query sequence. This is the upper limit for what should be returned. If there are more than this, then the sequence is not specific to the gene.
DONT USE - too complicated
Search a longer sequence from the Kannamycin gene to reduce false positives.
Don't uncompress the fastq files. To avoid this, use gunzip -c.
Here is an example of how to do this:
gunzip -c sample.fa.gz | grep -B1 -A2 | wc -l
Once you've got it working to your satisfaction, you can write a simple script and run it in parallel on the cluster.
Trying a different positive control query:
gene: Solyc01G001422 (one intron)
left side of intron: TTATCAGAGTGCTTCCTTCA
right side of intron: GTGCCATTGGAAATGGATTT
query sequence: TTATCAGAGTGCTTCCTTCAGTGCCATTGGAAATGGATTT
Expected result: No more than 925 but definitely more than 0 for either R1 or R2 fastq files, but not both.
Positive Control Query Sequence (R1 vs. R2) Solyc01G001422:
grep -B1 -A2 TTATCAGAGTGCTTCCTTCAGTGCCATTGGAAATGGATTT 7-are-15-min-28C_R1_001.fastq | wc -l 4 grep -B1 -A2 TTATCAGAGTGCTTCCTTCAGTGCCATTGGAAATGGATTT 7-are-15-min-28C_R2_001.fastq | wc -l 1918
Slurm Script
Directory: /nobackup/tomato_genome/muday-144/nfcore-2022/investigate_samples
#! /bin/bash #SBATCH --job-name=investigate-labels #SBATCH --partition=Orion #SBATCH --nodes=1 #SBATCH --ntasks-per-node=1 #SBATCH --mem=40gb #SBATCH --output=%x_%j.out #SBATCH --time=24:00:00 #SBATCH --array=1-144 #setting up where to grab files from file=$(sed -n -e "${SLURM_ARRAY_TASK_ID}p" /nobackup/tomato_genome/muday-144/nfcore-2022/investigate_samples/runlist_labels.txt) cd /nobackup/tomato_genome/muday-144/nfcore-2022/investigate_samples echo "Positive Control Query Sequence Solyc01G001422: $file"; gunzip -c /nobackup/tomato_genome/muday-144/nfcore-2022/$file | grep -B1 -A2 TTATCAGAGTGCTTCCTTCAGTGCCATTGGAAATGGATTT | wc -l echo "Kanamycin Gene Sequence Primer-Bind: $file"; gunzip -c /nobackup/tomato_genome/muday-144/nfcore-2022/$file | grep -B1 -A2 GGGGACCACTTTGTACAAGAAAGCTGGGTA | wc -l echo "----------------------------------------------------"
cat *.out > out2.txt # combine .out files
Results Head:
---------------------------------------------------- Positive Control Query Sequence Solyc01G001422: 7-are-15-min-28C_R1_001.fastq.gz 4 Kanamycin Gene Sequence Primer-Bind: 7-are-15-min-28C_R1_001.fastq.gz 0 ---------------------------------------------------- Positive Control Query Sequence Solyc01G001422: 7-are-15-min-28C_R2_001.fastq.gz 1918 Kanamycin Gene Sequence Primer-Bind: 7-are-15-min-28C_R2_001.fastq.gz 0 ---------------------------------------------------- Positive Control Query Sequence Solyc01G001422: 7-are-15-min-34C_R1_001.fastq.gz 0 Kanamycin Gene Sequence Primer-Bind: 7-are-15-min-34C_R1_001.fastq.gz 0 ---------------------------------------------------- Positive Control Query Sequence Solyc01G001422: 7-are-15-min-34C_R2_001.fastq.gz 1812 Kanamycin Gene Sequence Primer-Bind: 7-are-15-min-34C_R2_001.fastq.gz 0 ---------------------------------------------------- Positive Control Query Sequence Solyc01G001422: 7-are-30-min-28C_R1_001.fastq.gz 9 Kanamycin Gene Sequence Primer-Bind: 7-are-30-min-28C_R1_001.fastq.gz 0 ---------------------------------------------------- Positive Control Query Sequence Solyc01G001422: 7-are-30-min-28C_R2_001.fastq.gz 1396 Kanamycin Gene Sequence Primer-Bind: 7-are-30-min-28C_R2_001.fastq.gz 0 ----------------------------------------------------
Comment: Need help finding a sequence query for Kanamycin.
[~aloraine]
We expect that kanamycin resistance gene RNA-Seq sequences are present in the F3H-OX3 samples and absent in ARE and VF36 samples.
However, if you get a negative result (no matches to the query sequences) in the F3H-OX3 files, there are at least three possible reasons for a negative result. First reason: the F3H-OX3 files are mislabeled and are not from transgenic lines. Second reason: they could be transgenic lines but the kanamycin gene is not expressed in pollen tube tissue type. Third reason: They are transgenic lines and the kanamycin gene is expressed but the test is not working for some reason.
You need a positive control that will allow you to rule out option three.
For this, I recommend using a fastq file from an experiment where we are 100% confident that the kanamycin gene is expressed. Note that previously I mistakenly thought the soybean experimental construct from the paper listed above used the same kanamycin resistance gene as F3H-OX3. It does not. Thus, we do not have an example dataset that can serve as a positive control.
To rule out reason 2, you need a different positive control, a fastq file from a sample where you are 100% certain the transgene is present. For this, you could use the 120 minute time points samples from F3H-OX3 and/or F3H-OX4. If kanamycin gene is not detected in those samples, but it is detected in the soybean samples, then probably this would mean that the gene is simply not expressed in pollen tubes.
Suggestion: modify your script to produce comma-separated data, a single line:
column 1: name of target file
column 2: query sequence used
column 3: gene of origin for the query sequence
column 4: number of matches found
Use "squeue-doIt" script in flavonoid rnaseq repository "src" folder to submits jobs for every fastq.gz file in a directory. (These can be symbolic links of course)
The end result is that you will get many tab-delimited files with one line per file. That is OK. When finished, use cat and redirection operator to bind them into a single file, e.g.,:
cat *.csv > result.csv
When done, we will place all the scripts and the final results file into a single folder in the repository to document the experiment and the results of the experiment.
I used the F3H.fasta file that Maarten sent and created some different Kanamycin sequence queries. After running a couple of different sequences with the fastq files, there were two consistent fastq samples that kept producing results with each Kanamycin sequence I gave it. Those are:
- 7-VF36-45-min-34C_R1_001.fastq.gz
- 7-VF36-75-min-28C_R1_001.fastq.gz
Results can be found in this directory: /nobackup/tomato_genome/muday-144/nfcore-2022/investigate_samples
Next step: Find a control fastq file for Kanamycin to check sequence query.
https://trace.ncbi.nlm.nih.gov/Traces/?view=run_browser&acc=SRR15568707&display=download
Dr. Reid took chunks out of the functional domain of Kan sequence (kanR2_SeqfromAnthony-funcDomain.fna) and made the following file to make queries with my grep script:
/nobackup/tomato_genome/muday-144/nfcore-202215nt_chunksof_KanR2.fna
>Kan-R2 - 5 primed end GTCTGGAAAGAAATG >Kan-R2-middle1 CCTTATTTTTGACGA >Kan-R2-middle2 TCTTGCCATCCTATG >Kan-R2-middle3 TAATCCTGATATGAA >Kan-R2-middle4 AAATGGGCTCGCGAT >Kan-R2-middle5 TTGTTTCTGAAACAT >Kan-R2-middle6 GAATTTATGCCTCTT >Kan-R2-middle7 GGAAAAACAGCATTC >Kan-R2-middle8 TGCGCCGGTTGCATT >Kan-R2-middle9 TCACGAATGAATAAC >Kan-R2-middle10 TGGAAAGAAATGCAT >Kan-R2-middle11 TATTTTTGACGAGGG >Kan-R2-middle12 TGCCATCCTATGGAA >Kan-R2-middle13 ATCCTGATATGAATA >Kan-R2-3 primed end TGCTCGATGAGTTTT
Results Directory for each query: /nobackup/tomato_genome/muday-144/nfcore-2022/investigate_samples
Dr. Reid had idea to run nextflow on the AreWeThere dataset on SL5 (Gloria's old dataset). One idea was to take the old dataset. Treat those gene expressions as gospel. And then cluster each of the muday144 samples with the old set. And see where they land:
Directory: /nobackup/tomato_genome/areYouThere-nfcoreSL5
We have run these samples through nf-core using SL5 as the reference already. It's in the first SRA batch we downloaded and these data are also available for visualization in IGB.
Some other notes related to this.
On Tuesday's tech meeting, the group discussed other possibilities that we could collectively try.
In the end, not much came up as things we can try.
Gloria is hunting down the original plasmid that was used in the transformation. Maybe from that there is some sequence we can also hunt for.
I talked about this with Rick White. He has done plant transformations and was fascinated by the problem. (And impressed how IGB was able to detect the mislabeling by the read count profiles!!). He suspected that we would not be able to detect kanamycin. Maybe in genome sequence but that too would be a long shot.
During discussion in scrum we realized that results are inconclusive from the kanamycin grep strategy. Let's halt this approach and try the approach from the soybean paper mentioned above. Making a new Jira issue to pursue this other strategy.
Closing this "investigate" ticket to try the other strategy.
The STAR run to see if ANY read sequences align to the kanamycin gene that Anthony from Gloria's lab sent.
He sent it in a Word doc: (KANR2)
GTCTGGAAAGAAATGCATAAACTTTTGCCATTCTCACCGGATTCAGTCGTCACTCATGGTGATTTCTCACTTGATAA
CCTTATTTTTGACGAGGGGAAATTAATAGGTTGTATTGATGTTGGACGAGTCGGAATCGCAGACCGATACCAGGA
TCTTGCCATCCTATGGAACTGCCTCGGTGAGTTTTCTCCTTCATTACAGAAACGGCTTTTTCAAAAATATGGTATTGA
TAATCCTGATATGAATAAATTGCAGTTTCATTTGATGCTCGATGAGTTTTAACATGGATGCTGATTTATATGGGTAT
AAATGGGCTCGCGATAATGTCGGGCAATCAGGTGCGACAATCTATCGCTTGTATGGGAAGCCCGATGCGCCAGAG
TTGTTTCTGAAACATGGCAAAGGTAGCGTTGCCAATGATGTTACAGATGAGATGGTCAGACTAAACTGGCTGACG
GAATTTATGCCTCTTCCGACCATCAAGCATTTTATCCGTACTCCTGATGATGCATGGTTACTCACCACTGCGATCCCC
GGAAAAACAGCATTCCAGGTATTAGAAGAATATCCTGATTCAGGTGAAAATATTGTTGATGCGCTGGCAGTGTTCC
TGCGCCGGTTGCATTCGATTCCTGTTTGTAATTGTCCTTTTAACAGCGATCGCGTATTTCGTCTCGCTCAGGCGCAA
TCACGAATGAATAACGGTTTGGTTGATGCGAGTGATTTTGATGACGAGCGTAATGGCTGGCCTGTTGAACAAGTC
TGGAAAGAAATGCATAAACTTTTGCCATTCTCACCGGATTCAGTCGTCACTCATGGTGATTTCTCACTTGATAACCT
TATTTTTGACGAGGGGAAATTAATAGGTTGTATTGATGTTGGACGAGTCGGAATCGCAGACCGATACCAGGATCT
TGCCATCCTATGGAACTGCCTCGGTGAGTTTTCTCCTTCATTACAGAAACGGCTTTTTCAAAAATATGGTATTGATA
ATCCTGATATGAATAAATTGCAGTTTCATTTGATGCTCGATGAGTTTT
I made a fasta out of this and is on the cluster at this location:
/nobackup/tomato_genome/muday-144/nfcore-2022/kanhunt/kanR2_SeqfromAnthony-fullsequence.fna
I treated the above sequence as the reference file for a STAR alignment.
Results to go here:
/nobackup/tomato_genome/muday-144/nfcore-2022/kanhunt/star
First step in STAR is the make a genome index file.
This is done once via this script:
/nobackup/tomato_genome/muday-144/nfcore-2022/kanhunt/star-generategenome.slurm
And then we run 144 jobs as an array, 1 for each read sequence in the experiment:
star-chunks.slurm
(silly name, I first planned to align to small chunks, named it this way)
We get 144 bam files, all of which are empty. The log files appear that STAR ran successfully.
Blast RUN:
Just like Star run but for blast.
Location:
/nobackup/tomato_genome/muday-144/nfcore-2022/kanhunt/blast
Script:
/nobackup/tomato_genome/muday-144/nfcore-2022/kanhunt/
-Need to run seqtk to convert the fastq to fasta to run blast.
So far there is an issue. 35 jobs complete. And the rest do not.
Getting kicked off the cluster because of my internet. Hope to resolve from office.
Of the 35 jobs that completed, no sequences were found to hit at a e-score cutofff = 1e-25.
Using kan-r gene in this way does not yield much. Closing this ticket.
Next strategy to try will be running an RNA-Seq alignment tool on the fastq files and the new plasmid genome, either by itself or with the rest of the tomato SL5 genome assembly, using the fasta file and bed file made by [~molly] in IGBF-3306.
We will make a new ticket for running this RNA-Seq alignment strategy to detect Kan-r expression.
Ann's first idea on what to do:
Augment the tomato SL5 genome assembly and gene model annotations by adding a new "fake" chromosome containing the construct sequence and construct annotations provided by Maarten. Then, we use this as the target assembly in a fresh run of the nf-core rnaseq pipeline. This should produce a new "counts" file with counts for the newly added construct gene locations, including counts for the kanamycin resistance gene. This might not be a great idea! We might be able to find a more direct and simple approach that would be less work. But if we can't, I'm pretty sure this would get the job done.