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A Combination of LongSAGE With Solexa Sequencing Is Well Suited to Explore the Depth and the Complexity of Transcriptome

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A Combination of LongSAGE With Solexa Sequencing Is Well Suited to Explore the Depth and the Complexity of Transcriptome

Lucie Hanriot et al. BMC Genomics.

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.

Figures

Figure 1
Figure 1
Schematic illustration of the LongSAGE-Solexa procedure. From left to right is shown the initial SAGE procedure ([6]), the improvements brought by the DeepSAGE procedure ([14]) in terms of a simpler protocol and of depth of sampling. On the right is reported the LongSAGE-Solexa procedure described in this study, which provided a major improvement along those two lines. One has to note that in the LongSAGE-Solexa procedure, a single tag is sequenced for each sequenced molecule.
Figure 2
Figure 2
Illustration of the extent of tissue collection. A: Photograph of a frontal 400 μm-thick section of a mouse brain at the level of the hypothalamus. The hypothalamus, centered on the perifornical nucleus was collected bilaterally using a trocard of 1 mm diameter. Scale bar = 1 mm. B: Schematic drawing of the section presented in A and extracted from the mouse atlas of G Paxinos & KB Franklin, (+1,98 mm interaural). The blue circle highlights the extent of the brain area taken off. 3V: third ventricule; Arc: arcuate nucleus; CM: centro-medial thalamic nucleus; cp: cerebral pedoncule; DMH: dorsomedial hypothalamic nucleus; f: fornix; ic: internal capsule; LH: lateral hypothalamic area, ml: median lemniscus; mt: mammillothalamic tract; opt: optic tract; PeF: perifornical nucleus; PH: posterior hypothalamic area; Re: thalamic reuniens nucleus; st: stria terminalis; VMH: ventromedial hypothalamic nucleus.
Figure 3
Figure 3
Expression level for 3 well-known genes of the hypothalamus, using three different techniques. The level of expression of three genes (pro-melanin concentrating hormone (Pmch), preprohypocretin (Hcrt) and prodynorphin (Pdyn)) known to be expressed in the hypothalamus is evaluated as their number of occurrence from the Sanger_Hypo library (darkest bars) and the Solexa_Hypo library (lighest bars) as tags per million (left axis). The level of expression of these 3 genes is also evaluated from 6 independent hypothalamic samples by qPCR (right axis). The mean and standard deviation are reported in copies of transcripts (right axis).
Figure 4
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 null Y value is not reported).
Figure 5
Figure 5
Effect of the library size on the number of unique tags identified. The three figures represent the number of unique tags identified as a function of the total number of tags in random libraries. These libraries were obtained by random sampling of X tags in the library considered (Sanger_Hypo or Solexa_Hypo), where X vary from 1 to the total number of tags in this library. In each of the obtained samples, we also calculated the number of unique tags that matches to the mouse genome (dotted lines). We considered that a tag matches to the genome when it has 100% identity over its whole length (21 bp). A: Figure for the Sanger_Hypo library. B: Figure for the Solexa_Hypo library. C: Figure comparing the number of unique tags identified as a function of the total number of tags between the Sanger_Hypo and the Solexa_Hypo library. The size of the random samples varies consequently from 1 to the size of the Sanger_Hypo library (the smallest of the two libraries).

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