We got RNA-seq done on rice (Nipponbare). The sequencing facility aligned the reads to the reference transcriptome (Ensembl Oryza_sativa_japonica IRGSP-1.0). Ensembl database does not match rice database at MSU as far as Gene/Locus ID goes (http://rice.plantbiology.msu.edu/index.shtml).
Ensembl nomenclature is different than MSU database. What is the easiest way (other than BLAST) to see which gene in MSU database corresponds to Ensembl ones. In general, when people do RNA-seq on rice, which reference transcriptome/genome database they use to align the reads? I am not happy with the annotation/gene description of Ensembl database. Please let me know. Thanks!
Did you check at the BGI Rise Database?
http://rise2.genomics.org.cn/page/rice/index.jsp
Hello, I am not a specialist of the rice genome but I often treats RNA-Seq data so if you want I can try to give you my help within the limits of the possible.
However, could you give me the type of sequencing that you used and the fully detail the protocol.
Then, and if I understand you have 2 questions:
Q1 : What is the easiest way (other than BLAST) to see which gene in MSU database corresponds to Ensembl ones?
R1: I do not know if there is a website to match the 2 identifiers. However I think you can make a comparison by performing intersection between the two annotation files to find out which genes or transcripts that match between the two files (eg bedtools intersect). Or you can try to reannote one of the two files with each other using cufflinks (cuffcompare or cuffmerge).
Q2 : In general, when people do RNA-seq on rice, which reference transcriptome/genome database they use to align the reads?
R2: For the little I know, the rice genome are very varied, so either you aligned your data on several defferents genomes and you compare (merge/join) results or you should try to make your own Denovo genome and compare with current available genome.
Here are two papers that I read and that can help you, I think:
http://www.thericejournal.com/content/6/1/4
http://www.biomedcentral.com/1471-2164/12/165
you can also use the Rice Genome Project : http://rice.plantbiology.msu.edu/
Pleasure to help you.
Hi,
I would suggest you to perform short read alignment on Os-Nipponbare-Reference-IRGSP-1.0 pseudomolecules by using bowtie2 or BWA. As you have generated reads from Nipponbare genotype than it will always be good to procure the same reference.
Second, I agree with Marc for de-novo approach and a comparison with other rice genomes.
Hope this will help you.
a single database search may not give you the optimum result. It is better if you consider more than one related database in your study.
For rice, Robin Buell's RGAP is the best shot one can have. Since they have added the informations from IRGSP as well this makes them more robust.
In their FTP, you can find the data what you want and use any next gen aligner like STAR, BOWtie etc. STAR is faster, efficient and also has the feature to align sequences to the annotated regions. Have a look at their manual.
http://rice.plantbiology.msu.edu/
Hope this help.
Thanks to all. I was told by MSU staff that the genome assembly pseudomolecules at Ensemble, RAP-DB, and MSU are the same if they say (Os-Nipponbare-Reference-IRGSP-1.0).
The data I got have just the IDs without any gene description, please see attached the "data file", just a few genes as an example). For 11,000 genes how will I know which one is which, unless I do them manually, one by one. RAP-DB has a locus converter tool but the website is down for a while, not sure we can convert loci names putting a hundred of Ensembl gene IDs at a time, is it possible? I was looking for a locus converter to give me MSU nomenclature in bulk.
From the data like this, I was wondering, how can I get gene description for most genes which just have the IDs with column "D" having nothing but the ID name again, any suggestions how to get the gene description? I was looking for gene description, something like this in column B of the another attached file.
Helo Sachin,
You can do two things.
Either you can paste your IDs in the below mentioned form from RAPDB..
http://rice.plantbiology.msu.edu/downloads_gad.shtml
or you can have a file from RAPDB FTP which has detail for all the accession from the below mentioned link.
ftp://ftp.plantbiology.msu.edu/pub/data/Eukaryotic_Projects/o_sativa/annotation_dbs/pseudomolecules/version_7.0/all.dir/all.locus_brief_info.7.0
This file contains the information you are looking for. And using either MS Excel or any text processing tool, you can have annotation of your required IDs.
Hope this helps.
http://rice.plantbiology.msu.edu/downloads_gad.shtml
Hello Vinay and others,
Thank you very much. My IDs were Ensembl IDs and I had to convert to MSU ID. RAP-DB site is down so I used these two converter:
http://doggsea.ncpgr.cn/convert/?convert2=rap-msu&ids=OS07G0295000%0D%0AOS02G0154600%0D%0AOS04G0653100%0D%0AOS08G0540400%0D%0AOS04G0430600%0D%0AOS04G0467800%0D%0AOS07G0609000%0D%0AOS06G0155900%0D%0A
http://bioinf.mind.meiji.ac.jp/OryzaExpress/ID_converter.php
Once I got MSU gene ID for my genes, I used your link to retrieve the annotations, so it was very fast, thanks once again.
But I got about 11000 genes differentially expressed in my data. I believe, it could be due to different cell types/tissues owing to severe developmental disorder. Please see the attached image of my rice plant, with the wild type on the left and 3 mutants (used as 3 biological replicates on the right). They are affected severely, developmentally and physiologically. These are miRNA mutants and their target genes are expectedly up in the RNA-seq data.
The data analysis was done by a professional bioinformatician from the sequencing facility, and they took three criteria for differentially expressed transcripts:
1. Test Status OK
2. FDR (q-value) = Threshold or
Well thats an interesting situation.
Its not very surprising to see these many numbers of differentially expressed genes.
Now to analyze these differentially expressed genes to come to a conclusive point, you have to use some enrichment analysis based on functional connotations.
Here are the steps you should follow which I feel could be relevant to give you some hint.
1. From the same site of RGAP, download the GO (Gene Ontology) slim IDs of your differntially expressed genes.
2. Use Cytoscape along with BINGO plugin to get those GO which are significantly enriched. THis will give you some information about your genes based on their categorization in different GOs.
3. Finally you have to identify some key genes based on your expectations that in what pathway your mutated gene in question is sitting and how does it is regulated. In what way it is regulating the various developmental aspects. Like for example if there are any link to homeotic genes in your downregulated set of genes. Also you could identify some genes which controls cell division and its expansion. Like BRI1 etc.
This answer is a hint about how you can proceed. Basically you have to find needle in haystack. These techniques and tools has been used to make the haystack size smaller.
All the best ahead.
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