Limits...
A combination of LongSAGE with Solexa sequencing is well suited to explore the depth and the complexity of transcriptome.

Hanriot L, Keime C, Gay N, Faure C, Dossat C, Wincker P, Scoté-Blachon C, Peyron C, Gandrillon O - BMC Genomics (2008)

Bottom Line: Both LongSAGE and MPSS rely on the isolation of 21 pb tag sequences from each transcript.However, a bias in the complexity of the transcriptome representation obtained by MPSS was recently uncovered.We then compared it to a LongSAGE library of mouse hypothalamus sequenced with the Sanger method.

View Article: PubMed Central - HTML - PubMed

Affiliation: UMR5534 CNRS Université Claude Bernard Lyon1, Université de Lyon, Institut Fédératif des Neurosciences de Lyon, Lyon cedex, France. lucie.hanriot@hotmail.fr

ABSTRACT

Background: "Open" transcriptome analysis methods allow to study gene expression without a priori knowledge of the transcript sequences. As of now, SAGE (Serial Analysis of Gene Expression), LongSAGE and MPSS (Massively Parallel Signature Sequencing) are the mostly used methods for "open" transcriptome analysis. Both LongSAGE and MPSS rely on the isolation of 21 pb tag sequences from each transcript. In contrast to LongSAGE, the high throughput sequencing method used in MPSS enables the rapid sequencing of very large libraries containing several millions of tags, allowing deep transcriptome analysis. However, a bias in the complexity of the transcriptome representation obtained by MPSS was recently uncovered.

Results: In order to make a deep analysis of mouse hypothalamus transcriptome avoiding the limitation introduced by MPSS, we combined LongSAGE with the Solexa sequencing technology and obtained a library of more than 11 millions of tags. We then compared it to a LongSAGE library of mouse hypothalamus sequenced with the Sanger method.

Conclusion: We found that Solexa sequencing technology combined with LongSAGE is perfectly suited for deep transcriptome analysis. In contrast to MPSS, it gives a complex representation of transcriptome as reliable as a LongSAGE library sequenced by the Sanger method.

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Related in: MedlinePlus

Repartition of the number of tags according to their occurrence number in the Sanger_Hypo and Solexa_Hypo libraries. A: Barplot for the Sanger_Hypo library, a mouse hypothalamic LongSAGE library sequenced by the Sanger method containing 68,023 total tags. B: Barplot for the Solexa_Hypo library, a mouse hypothalamic LongSAGE library sequenced by the Solexa technique containing 11,017,712 total tags. Please note that the Barplot representation displays only the observed values (if no tag is observed for a given count, the  Y value is not reported).
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Figure 4: Repartition of the number of tags according to their occurrence number in the Sanger_Hypo and Solexa_Hypo libraries. A: Barplot for the Sanger_Hypo library, a mouse hypothalamic LongSAGE library sequenced by the Sanger method containing 68,023 total tags. B: Barplot for the Solexa_Hypo library, a mouse hypothalamic LongSAGE library sequenced by the Solexa technique containing 11,017,712 total tags. Please note that the Barplot representation displays only the observed values (if no tag is observed for a given count, the Y value is not reported).

Mentions: Since both libraries have been generated from the same tissue, we were however able to compared the distribution of tag occurrence between the two libraries. This distribution is highly similar between Sanger_Hypo and Solexa_Hypo libraries (Figure 4). A high proportion of tags is present in only one copy in the Sanger_Hypo library (68%) while they represent only 32% of the tags of the Solexa_Hypo library (Table 1), confirming that the depth of sequencing of the Sanger_Hypo library is not sufficient. It has been previously reported [19] that the distribution of large scale expression data is skewed by many low abundance transcripts. This has lead to the conclusion that all genes are expressed in all cells [19], although at a very low abundance, a process also known as «illegitimate transcription» [20]. Furthermore, we are dealing with populations of cells, harboring stochasticity detectable at the single-cell transcriptome level [21]. Finally, one also knows that part of the tags with a count of one is simply sequencing errors. Taken together, all those reasons are probably combined to produce the "classical" transcriptome profile displayed on Figure 4, which never shows its finite nature.


A combination of LongSAGE with Solexa sequencing is well suited to explore the depth and the complexity of transcriptome.

Hanriot L, Keime C, Gay N, Faure C, Dossat C, Wincker P, Scoté-Blachon C, Peyron C, Gandrillon O - BMC Genomics (2008)

Repartition of the number of tags according to their occurrence number in the Sanger_Hypo and Solexa_Hypo libraries. A: Barplot for the Sanger_Hypo library, a mouse hypothalamic LongSAGE library sequenced by the Sanger method containing 68,023 total tags. B: Barplot for the Solexa_Hypo library, a mouse hypothalamic LongSAGE library sequenced by the Solexa technique containing 11,017,712 total tags. Please note that the Barplot representation displays only the observed values (if no tag is observed for a given count, the  Y value is not reported).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2562395&req=5

Figure 4: Repartition of the number of tags according to their occurrence number in the Sanger_Hypo and Solexa_Hypo libraries. A: Barplot for the Sanger_Hypo library, a mouse hypothalamic LongSAGE library sequenced by the Sanger method containing 68,023 total tags. B: Barplot for the Solexa_Hypo library, a mouse hypothalamic LongSAGE library sequenced by the Solexa technique containing 11,017,712 total tags. Please note that the Barplot representation displays only the observed values (if no tag is observed for a given count, the Y value is not reported).
Mentions: Since both libraries have been generated from the same tissue, we were however able to compared the distribution of tag occurrence between the two libraries. This distribution is highly similar between Sanger_Hypo and Solexa_Hypo libraries (Figure 4). A high proportion of tags is present in only one copy in the Sanger_Hypo library (68%) while they represent only 32% of the tags of the Solexa_Hypo library (Table 1), confirming that the depth of sequencing of the Sanger_Hypo library is not sufficient. It has been previously reported [19] that the distribution of large scale expression data is skewed by many low abundance transcripts. This has lead to the conclusion that all genes are expressed in all cells [19], although at a very low abundance, a process also known as «illegitimate transcription» [20]. Furthermore, we are dealing with populations of cells, harboring stochasticity detectable at the single-cell transcriptome level [21]. Finally, one also knows that part of the tags with a count of one is simply sequencing errors. Taken together, all those reasons are probably combined to produce the "classical" transcriptome profile displayed on Figure 4, which never shows its finite nature.

Bottom Line: Both LongSAGE and MPSS rely on the isolation of 21 pb tag sequences from each transcript.However, a bias in the complexity of the transcriptome representation obtained by MPSS was recently uncovered.We then compared it to a LongSAGE library of mouse hypothalamus sequenced with the Sanger method.

View Article: PubMed Central - HTML - PubMed

Affiliation: UMR5534 CNRS Université Claude Bernard Lyon1, Université de Lyon, Institut Fédératif des Neurosciences de Lyon, Lyon cedex, France. lucie.hanriot@hotmail.fr

ABSTRACT

Background: "Open" transcriptome analysis methods allow to study gene expression without a priori knowledge of the transcript sequences. As of now, SAGE (Serial Analysis of Gene Expression), LongSAGE and MPSS (Massively Parallel Signature Sequencing) are the mostly used methods for "open" transcriptome analysis. Both LongSAGE and MPSS rely on the isolation of 21 pb tag sequences from each transcript. In contrast to LongSAGE, the high throughput sequencing method used in MPSS enables the rapid sequencing of very large libraries containing several millions of tags, allowing deep transcriptome analysis. However, a bias in the complexity of the transcriptome representation obtained by MPSS was recently uncovered.

Results: In order to make a deep analysis of mouse hypothalamus transcriptome avoiding the limitation introduced by MPSS, we combined LongSAGE with the Solexa sequencing technology and obtained a library of more than 11 millions of tags. We then compared it to a LongSAGE library of mouse hypothalamus sequenced with the Sanger method.

Conclusion: We found that Solexa sequencing technology combined with LongSAGE is perfectly suited for deep transcriptome analysis. In contrast to MPSS, it gives a complex representation of transcriptome as reliable as a LongSAGE library sequenced by the Sanger method.

Show MeSH
Related in: MedlinePlus