[edge]

Hi petang, I'm also just start my research about RNA-seq.
Do you have any idea to identify alternative splice variants without reference genome of RNA-seq data right now?

[petang]

I am working on the transcriptome sequecning (GAII 75bp pair-end) of a nematode without reference genome. We tried CLC V4.5 and SOAPdenono to assemble the reads. My approach is to limit the number of mismatch to zero and overlapping region to 50% for the first round of assembly to obatin a reliable reference contig. Then use the reference contigs from the 1st assemble to re-assemble with the un-assembled reads, and set mis-2 for the second round of assembly. The largest contig we assembled is a 18KBp titin gene.
Depends on the compexity of the intron/exon of the organism and the depth of sequecning, around 30000-70000 transcripts with reads more than 100 should be identified.
The remaining steps is the same as for classical EST annotation start from Blastx uniprot, NCBI nr and interprot.
The last problem for RNAseq sequencing of an organism without a genome is how to identify the splice variants.

[KevinLam]

This might be an interesting read

Transcriptome sequencing in an ecologically important tree species: assembly, annotation, and marker discovery

http://www.biomedcentral.com/1471-2164/11/180

DNASTAR also lists de novo transcriptome assembly
http://www.dnastar.com/t-sub-nextgen...scriptome.aspx

I am curious if anyone managed to do de novo transcriptome with the shorter SOLiD reads?

[Melissa]

Interesting question, Blackgore! Without a reference/gene model/ESTs, how to evaluate a de novo transcriptome assembly?

Since we assembled correctly the longest genes in plants including BIG (>15 kb) we believe the approach works.

More technical notes on filtering the reads and Velvet parameters used are here:
http://atgc-illumina.googlecode.com/...k_090910_D.pdf

I also found a 15kb contig homologs to Arabidopsis BIG/ubiquitin-protein ligase in my plant transcriptome. I was told that similar result is obtained in P.trichocarpa. Therefore, I think BIG/ubiquitin-protein ligase can serve as an indicator for plant transcriptome assembly. Long genes like BIG/ubiquitin-protein ligase won't be assembled in poorly sequenced transcriptome.

Anyway, both methods (including N50) doesn't say much about the scaffolds quality. There can be scaffolds with lots of Ns due to poorly sequenced insert gaps. Compare two datasets with the same N50 and longest contig but one with lots of Ns, how can you tell the difference?

[blackgore]

How are people evaluating their transcriptome assemblies? The standard N50 assessment can't be that useful, as the goal here isn't exactly to generate a tiny set of huge contigs...?

[MarcelS]

Hi all,
also, what software would you recommend for this?
hope someone can help
best regards
neil

Hi Neil,
I would recommend our new software Oases see the thread Oases: De novo transcriptome assembly of very short reads or http://www.ebi.ac.uk/~zerbino/oases/.
The software is designed to cope with alternative splicing and repetitive regions that normally break up contigs (for example if genome assemblers are used). Oases can produce full length transcripts if the coverage allows it and does also support/exploit paired-end information. And yes, paired-end information does improve the results. Oases already supports longer reads (e.g. 75 bp) that are produced by the current technologies.

Bests,
Marcel

[Marta]

The experiment CLC did for this white paper does not reflect the actual performance of the CLC assembler. I think the assembler is much better than what the paper claims.

I use CLC Genomics WorkBench on Windows with 32GB RAM. A few days ago I started to test the latest (beta) version of the assembler for Workbench. It performs much better than the older one. My input is 92.5 Million of transcriptome single reads that are up to 85 nt long (IGA, filtered fasta).

About Velvet - my understanding that there is not much sense in changing expCov for transcriptome reads. We work with normalized mRNA libraries, but still the coverage between different transcrips varies a lot. About cvCut you need to contact alex_kozik (he is a member here). He is the one who ran all Velvet assemblies on the same set.

[Zigster]

From section 4.2 and 4.3 of the new CLC white paper, it appears that the old CLC assembler made slightly longer contigs (unpaired max CLC69kbp vs VEL60kbp, N50 CLC23kbp vs VEL16kbp) at the expensive of more incorrect ones (CLC: 36 wrong, VEL :1 wrong). The newer one leans too far the other way. Who knows what velvet parameters were used - probably the ones that most closely matched the total CLC assembly size.
http://www.clcbio.com/files/whitepap...C_NGS_Cell.pdf

I'm not so sure there is a free lunch here.

Marta, what cvCut and expCov parameters did you use in your Velvet assemblies? The cvCut parameter has a huge effect on N50, assembly size, and read usage.

[Marta]

KevinLam,

The data is unpublished. We are re-assembling the reads using the latest version of CLC assembler and Velvet with adjusted parameters. The number of transcriptome contigs in our latest assemblies went down from ~70K to ~57K. I have a presentation on-line with results from last summer assemblies here:

https://docs.google.com/fileview?id=0B9g4lIAKxQTaMjViZDJkYTMtYmEyYS00MjI1LWFhMjEtNDlhNDllMWYzNjkz&hl=en

Since we assembled correctly the longest genes in plants including BIG (>15 kb) we believe the approach works.

More technical notes on filtering the reads and Velvet parameters used are here:

http://atgc-illumina.googlecode.com/files/ILLUPA_Overview_AKozik_090910_D.pdf

[Peter Bjarke Olsen]

We have done several de Novo transcriptome projects mainly using Illumina technology and the Abyss assembler. In general it works but the problem is getting full length sequences (from start to stop codon). We have recently learned that some labs uses coligation of the transcipts prior to the nebulization. It should increase the number of full length genes. The reason is that the fragmentation is non random at the ends making the ends underrepresented in the library.

[KevinLam]

We assembled lettuce transcriptome using 85 nt IGA single reads. We used CLC and Velvet followed by CAP3.

Are your results published in a paper already? Would love to read it!

[krobison]

While this is not de novo assembly of a novel transcriptome, in some ways it is better because it can be compared against a known transcriptome (which was not used in the assembly as far as I know

http://bioinformatics.oxfordjournals...&pmid=19528083
Bioinformatics. 2009 Nov 1;25(21):2872-7. Epub 2009 Jun 15.
De novo transcriptome assembly with ABySS.
Birol I, Jackman SD, Nielsen CB, Qian JQ, Varhol R, Stazyk G, Morin RD, Zhao Y, Hirst M, Schein JE, Horsman DE, Connors JM, Gascoyne RD, Marra MA, Jones SJ.

Genome Sciences Centre, Vancouver, BC V5Z 4S6, Canada. [email protected]
MOTIVATION: Whole transcriptome shotgun sequencing data from non-normalized samples offer unique opportunities to study the metabolic states of organisms. One can deduce gene expression levels using sequence coverage as a surrogate, identify coding changes or discover novel isoforms or transcripts. Especially for discovery of novel events, de novo assembly of transcriptomes is desirable. RESULTS: Transcriptome from tumor tissue of a patient with follicular lymphoma was sequenced with 36 base pair (bp) single- and paired-end reads on the Illumina Genome Analyzer II platform. We assembled approximately 194 million reads using ABySS into 66 921 contigs 100 bp or longer, with a maximum contig length of 10 951 bp, representing over 30 million base pairs of unique transcriptome sequence, or roughly 1% of the genome. AVAILABILITY AND IMPLEMENTATION: Source code and binaries of ABySS are freely available for download at http://www.bcgsc.ca/platform/bioinfo/software/abyss. Assembler tool is implemented in C++. The parallel version uses Open MPI. ABySS-Explorer tool is implemented in Java using the Java universal network/graph framework. CONTACT: [email protected].

PMID: 19528083

[Marta]

We assembled lettuce transcriptome using 85 nt IGA single reads. We used CLC and Velvet followed by CAP3.

[KevinLam]

So in short no one has done de novo transcriptome assembly for new organism before?
can we use a closely related species like fish to do that for de novo?

how about taking it further with doing expression profiling on the new organism?

[Melissa]

oh, sorry. I found repetitive elements which are reverses transcriptases, located at 3' UTR of different genes. How can I differenciate the origin of my blast results?

The only way to tell a 3' UTR is the presence of polyA tail at sequence end. Considering our contigs are short, are you sure this is not misassemblies? How long is the repetitive element you found and what's the similarity?

If you are using blast to annotate your contigs, using 3' UTR is not a good idea because that region can varies even within the same species.

I have used CENSOR to find repeats in my ESTs but there's no significant hits. Most hits are around 100bp with 80% similarity (The original genomic repeat is several kb long) and it only exist once in the ESTs. Maybe plants repeat databases are not well-characterized. In the end, I just ignore them.

Found a related thread on repeat at

http://seqanswers.com/forums/showthread.php?t=1504