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**kmcarr** · 02-10-2011, 07:02 AM

No experience with the ScriptSeq kit but I will relate our experience with strand specific RNA-Seq.

We have recently been working with some ssRNA-Seq data from a non-model plant. The library was prepared using the Illumina RNA-ligation method. We found that the depth of read coverage across contig assemblies was extremely uneven, by >2 orders of magnitude in some cases. It seems that this is a typical outcome with this library prep method.

Check out this paper by Levin et al. "Comprehensive comparative analysis of strand-specific RNA sequencing methods." Nat Methods (2010) vol. 7 (9) pp. 709-15 (Link). They examine several methods of preparing ssRNA-Seq libraries. They did not test the ScriptSeq kit themselves but it appears that the ScriptSeq method would falls into the "not so random" or "not not so random" class. This method did not fare well in their analysis. The best method by their estimation is the dUTP second strand method, with the Illumina ligation protocol a close second (despite the unevenness problems noted above). In our core we are looking at implementing the dUTP protocol for future ssRNA-Seq preps.

**Pepe** · 02-10-2011, 08:08 AM

Thanks for your reply.
We have decided to do the same, the hope is that we can integrate the new Truseq kits (high throughput) and the dUTP methods (best quality according to Levin et al.).

Please feel free to PM us or write here to give us any advice you have on how to do this.
I'll be glad to keep you posted about our developments, although it will take some time to set up everything here.

**upendra_35** · 07-13-2011, 10:30 AM

I have used ScriptSeq and though i can detect reads from antisense strand but the protocol suffers from very biases such as 3' end and G bias at the beginning of the read. Also note that it is not a high throughput protocol and is very expensive per library. Hope this helps

**upendra_35** · 10-21-2011, 12:36 PM

Originally posted by Pepe View Post

Thanks for your reply.
We have decided to do the same, the hope is that we can integrate the new Truseq kits (high throughput) and the dUTP methods (best quality according to Levin et al.).

Please feel free to PM us or write here to give us any advice you have on how to do this.
I'll be glad to keep you posted about our developments, although it will take some time to set up everything here.

hi pepe

Just wondering have you figured out how to integrate the TruSeq kit for the strand specific libraries?

Thanks in advance.....

**perrinwang** · 10-27-2011, 07:58 AM

A Low-Cost Library Construction Protocol and Data Analysis Pipeline for Illumina-Based Strand-Specific Multiplex RNA-Seq

http://dx.plos.org/10.1371/journal.pone.0026426

The emergence of NextGen sequencing technology has generated much interest in the exploration of transcriptomes. Currently, Illumina Inc. (San Diego, CA) provides one of the most widely utilized sequencing platforms for gene expression analysis. While Illumina reagents and protocols perform adequately in RNA-sequencing (RNA-seq), alternative reagents and protocols promise a higher throughput at a much lower cost. We have developed a low-cost and robust protocol to produce Illumina-compatible (GAIIx and HiSeq2000 platforms) RNA-seq libraries by combining several recent improvements. First, we designed balanced adapter sequences for multiplexing of samples; second, dUTP incorporation in 2nd strand synthesis was used to enforce strand-specificity; third, we simplified RNA purification, fragmentation and library size-selection steps thus drastically reducing the time and increasing throughput of library construction; fourth, we included an RNA spike-in control for validation and normalization purposes. To streamline informatics analysis for the community, we established a pipeline within the iPlant Collaborative. These scripts are easily customized to meet specific research needs and improve on existing informatics and statistical treatments of RNA-seq data. In particular, we apply significance tests for determining differential gene expression and intron retention events. To demonstrate the potential of both the library-construction protocol and data-analysis pipeline, we characterized the transcriptome of the rice leaf. Our data supports novel gene models and can be used to improve current rice genome annotation. Additionally, using the rice transcriptome data, we compared different methods of calculating gene expression and discuss the advantages of a strand-specific approach to detect bona-fide anti-sense transcripts and to detect intron retention events. Our results demonstrate the potential of this low cost and robust method for RNA-seq library construction and data analysis.

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