Background:Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, and chemotherapy is a key treatment for advanced PDAC. Gemcitabine chemotherapy is still an important component of treatment; however, there is no routine biomarker to predict its efficacy. Predictive tests may help clinicians to decide on the best first-line chemotherapy. Methods:This study is a confirmatory study of a blood-based RNA signature, called the GemciTest. This test measures the expression levels of nine genes using real-time polymerase chain reaction (PCR) processes. Clinical validation was carried out, through a discovery and a validation phases, on 336 patients (mean 68.7 years; range, 37-88 years) for whom blood was collected from two prospective cohorts and two tumor biobanks. These cohorts included previously untreated advanced PDAC patients who received either a gemcitabine- or fluoropyrimidine-based regimen. Results:Gemcitabine-based treated patients with a positive GemciTest (22.9%) had a significantly longer progression-free survival (PFS) {5.3 vs. 2.8 months; hazard ratio (HR) =0.53 [95% confidence interval (CI): 0.31-0.92]; P=0.023} and overall survival (OS) [10.4 vs. 4.8 months; HR =0.49 (95% CI: 0.29-0.85); P=0.0091]. On the contrary, fluoropyrimidine-based treated patients showed no significant difference in PFS and OS using this blood signature. Conclusions:The GemciTest demonstrated that a blood-based RNA signature has the potential to aid in personalized therapy for PDAC, leading to better survival rates for patients receiving a gemcitabine-based first-line treatment.

Currently, there are no reliable biomarkers to predict the effectiveness of FOLFIRINOX/FOLFOX regimens. Predictive tests that assist clinicians in choosing the most appropriate first-line chemotherapy regimen are needed. In 2022, we developed a blood-based RNA signature, the GemciTest, which predicts the response to gemcitabine-based first-line treatment in patients with PDAC. The objective of this study was to evaluate the effectiveness of a complementary blood-based RNA signature (F/FX) to predict the response to FOLFIRINOX/FOLFOX regimens in advanced pancreatic adenocarcinoma. Clinical validation was conducted through a discovery and a validation phase on 164 previously untreated advanced PDAC patients (at baseline) (mean age of 68.7 years; 37-88) who received either a gemcitabine- or fluoropyrimidine-based regimen (Id.: NCT03599154 and NCT02818829). The F/FX test measures the expression levels of ten genes using real-time PCR process (MCEMP1, S100A12, MMP9, RACK1, DSC2, LYN, LPP, ARL4C, ALDOA and AC007877.1). Among FOLFIRINOX/FOLFOX treated patients (n=90), those with a positive F/FX (31.1%) had a significantly longer progression-free survival (PFS) (14.3 vs. 3.5 months; HR=0.21 (95% confidence interval CI: 0.12–0.35); p=5.56e-09) and median overall survival (OS) (23 vs. 7.7 months; HR=0.22 (95% CI: 0.13–0.36); p=3.16e-09). The Pearson correlation coefficient between OS and PFS was 0.73 (95% CI: 0.62-0.81; p=2,2E-16). On the contrary, gem-based treated patients (n=74) showed no significant difference in PFS (11.3 vs. 5.8 months; HR=0.68 (95% CI: 0.24–1.91); p=0.48) and OS (13.6 vs. 7.3 months; HR=0.7 (95% CI: 0.25–1.95); p=0.5) between the patients with a positive F/FX versus the patients with a negative F/FX. The F/FX demonstrates the potential of a blood-based RNA signature as a minimally-invasive alternative to improve patient survival and implement personalized therapy in PDAC for patients treated with a FOLFIRINOX/FOLFOX regimen as first-line treatment. While these data show promise, they should be confirmed in a prospective trial, distinguishing patients with non resectable locally advanced and those with metastatic tumors.

Background Nowadays, evaluation of the efficacy and the duration of treatment, in context of monitoring patients with solid tumors, is based on the RECIST methodology. With these criteria, resistance and/or insensitivity are defined as tumor non-response which does not allow a good understanding of the diversity of the underlying mechanisms. The main objective of the OncoSNIPE® collaborative clinical research program is to identify early and late markers of resistance to treatment. Methods Multicentric, interventional study with the primary objective to identify early and / or late markers of resistance to treatment, in 600 adult patients with locally advanced or metastatic triple negative or Luminal B breast cancer, non-small-cell lung cancer or pancreatic ductal adenocarcinoma. Patients targeted in this study have all rapid progression of their pathology, making it possible to obtain models for evaluating markers of early and / or late responses over the 2-year period of follow-up, and thus provide the information necessary to understand resistance mechanisms. To explore the phenomena of resistance, during therapeutic response and / or progression of the pathology, we will use a multidisciplinary approach including high-throughput sequencing (Exome-seq and RNAseq), clinical data, medical images and immunological profile by ELISA. Patients will have long-term follow-up with different biological samples, at baseline (blood and biopsy) and at each tumoral evaluation or tumoral progression evaluated by medical imaging. Clinical data will be collected through a dedicated Case Report Form (CRF) and enriched by semantic extraction based on the French ConSoRe (Continuum Soins Recherche) initiative, a dedicated Semantic Clinical Data Warehouse (SCDW) to cancer. The study is sponsored by Oncodesign (Dijon, France) and is currently ongoing. Discussion The great diversity of intrinsic or acquired molecular mechanisms involved in resistance to treatment constitutes a real therapeutic issue. Improving understanding of mechanisms of resistance of cancer cells to anti-tumor treatments is therefore a major challenge. The OncoSNIPE cohort will lead to a better understanding of the mechanisms of resistance and will allow to explore new mechanisms of actions and to discover new therapeutic targets or strategies making it possible to circumvent the escape in different types of cancer. Trial registration Clinicaltrial.gov. Registered 16 September 2020, https://clinicaltrials.gov/ct2/show/NCT04548960?term=oncosnipe&draw=2&rank=1 and ANSM ID RCB 2017-A02018-45.

e16238 Background: Pancreatic ductal adenocarcinoma (PDAC) is highly lethal often presents at a later stage. Gemcitabine is still an important component in PDAC treatment however there is no routine biomarker to predict its efficacy. We had previously performed a discovery cohort of two separate RNA-blood signatures in 60 patients (NCT00789633) showing an association with PFS and OS. Called GemciTest, this CE-IVD molecular test requires 2.5ml whole blood sample before starting the patient's 1st line chemotherapy. From this liquid biopsy, IVD measures the expression levels of nine genes using real-time PCR processes. This abstract presents the clinical validation of GemciTest. Methods: In this study, clinical validations were done on 214 patients (mean 68.7-year-old; 37-88) from 3 distinct cohorts with the University of Wisconsin Biobank, GemciPANC trial (NCT03599154), and BACAP (NCT02818829). These cohorts included first-line treatment,with either a gemcitabine or fluoropyrimidine based regimen. Results: Patients with a clinical benefit response identified by GemciTest (31.5%) had a significantly longer progression free survival (PFS) (5.4 months vs. 3.1 months p = 0.0032) and a longer overall survival (OS) (13.1 months vs. 5.4, p < 0.0003). In multivariate analyses including tumor localization and performance status, this signature continued to be associated with PFS (HR = 0.52 (0.34–0.81) p = 0.003) and OS (HR = 0.44 (0.28 – 0.69) p = 0.0002).Conclusions: GemciTest validation was performed, showing a strong association with PFS and OS.[Table: see text]

Pancreatic ductal adenocarcinoma (PDAC) is expected to be the second cause of cancer death by 2022. For nearly 80% of patients, diagnosis occurs at an advanced, nonsurgical stage, making such patients incurable. Gemcitabine is still an important component in PDAC treatment and is most often used as a backbone to test new targeted therapies and there is, to date, no routine biomarker to predict its efficacy. Samples from a phase III randomized trial were used to develop through a large approach based on blood-based liquid biopsy, transcriptome profiling, and machine learning, a nine gene predictive signature for gemcitabine sensitivity. Patients with a positive test (41.6%) had a significantly longer progression free survival (PFS) (3.8 months vs. 1.9 months p = 0.03) and a longer overall survival (OS) (14.5 months vs. 5.1, p < 0.0001). In multivariate analyses, this signature was independently associated with PFS (HR = 0.5 (0.28–0.9) p = 0.025) and OS (HR = 0.39 (0.21–0.7) p = 0.002).

Background: People with trisomy 21 (T21) are predisposed to developing hematological tumors, but have significantly lower-than-expected age-adjusted incidence rates of having a solid tumor. Material and methods: To identify novel genetic factors implicated in the lower breast cancer (BC) frequency observed in women with T21 than in the general population, we compared the transcriptome pattern of women with a homogeneous T21, aged more than 30 years, with or without BC, and tumoral BC tissue of control women with a normal karyotype from the study of Varley et al . (2014). Results: Differential analysis of gene expression between the 15 women in the T21 without BC group and BC patients in the other groups (two women with T21 and fifteen control women, respectively) revealed 154 differentially expressed genes, of which 63 were found to have similar expression profile (up- or downregulated). Of those 63 genes, four were in the same family, namely GIMAP4 , GIMAP6 , GIMAP7 and GIMAP8 , and were strongly upregulated in the T21 without BC group compared to the other groups. A significant decrease in mRNA levels of these genes in BC tissues compared to non-tumor breast tissues was also noted. Conclusion: We found that the expression of some GIMAPs is significantly higher in women with T21 without BC than in patients with sporadic BC. Our findings support the hypothesis that GIMAPs may play a tumor-suppressive role against BC, and open the possibility that they may also have the same role for other solid tumors in T21 patients. The search for new prognostic factors and hopefully new therapeutic or preventive strategies against BC are discussed.

Abstract Pancreatic cancer is currently the 4th leading cause of death by cancer in Europe. If no action is taken, it is set to be 2nd by 2021. For nearly 80% of patients, diagnosis occurs at an advanced stage, too late (metastatic pancreatic adenocarcinoma; mPDAC), making them nonelective for surgery. The high mortality rate (less than 5% of patients alive at 5 years), is partly due to the difficulty to diagnose and to the lack of patients’ stratification for effective treatments. Despite advances in treatment and outcomes, the capability of biomarkers to improve treatment is potentially greater than in any other area of current medical research. Based on a multicenter, randomized, retrospective clinical phase III evaluation (ClinicalTrials.gov: NCT00789633), Acobiom identified an 11-gene blood signature and developed the GemciTest, an IVD associated with gemcitabine treatment in mPDAC. This blood signature evaluates both progression-free survival (PFS) and overall survival (OS) rates, and identifies the patients who are likely to benefit from 1st-line gemcitabine treatment. Briefly, the IVD allows to identify 37% of patients having a median overall survival of 15 months with 1-year survival rate superior to 65%. The GemciTest, a quantitative real-time PCR assay, is currently a prototype in an operational environment through a Clinician Peer Network in EU and US. In this context, Acobiom is always looking for new partnerships (public or private), the right way to open opportunities to develop the GemciTest solution for mPDAC patients (bench-to-bedside), and to assist physicians in routine patient care. Citation Format: Didier Ritter, David Piquemal, Florian Noguier, Fabien Pierrat, Roman Bruno. Patient stratification and precision medicine in pancreatic cancer: GemciTest, an innovative in vitro diagnostic for the decision-making process of pancreatic cancer treatment [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr B42.

RNA-Seq approach is used in a wide variety of applications. These include identifying disease-related genes, analysing the effects of drugs on tissues, and providing insight into disease pathways. The RNA-Seq is widely used to characterise gene expression patterns associated with tumor formation. Since RNA-Seq provides absolute values and does not require any calibration with arbitrary standards, results can be compared at any time with other data, even raised by independent laboratories. Once collected, this data can be digitalised and then easily and reliably compared in silico with the growing library of RNA-Seq databases generated for normal and pathological situations in other laboratories around the world (Human: ~27000 libraries. Average size of a library: 1.7GB. Total size: 120TB). The objectives of MaRS database is to provide and centralize a standardized data used in a wide variety of applications like identifying disease-related genes, analysing the effects of drugs on tissues or providing insight into disease pathways.

Background Biofloc technology (BFT), a rearing method with little or no water exchange, is gaining popularity in aquaculture. In the water column, such systems develop conglomerates of microbes, algae and protozoa, together with detritus and dead organic particles. The intensive microbial community presents in these systems can be used as a pond water quality treatment system, and the microbial protein can serve as a feed additive. The current problem with BFT is the difficulty of controlling its bacterial community composition for both optimal water quality and optimal shrimp health. The main objective of the present study was to investigate microbial diversity of samples obtained from different culture environments (Biofloc technology and clear seawater) as well as from the intestines of shrimp reared in both environments through high-throughput sequencing technology. Results Analyses of the bacterial community identified in water from BFT and “clear seawater” (CW) systems (control) containing the shrimp Litopenaeus stylirostris revealed large differences in the frequency distribution of operational taxonomic units (OTUs). Four out of the five most dominant bacterial communities were different in both culture methods. Bacteria found in great abundance in BFT have two principal characteristics: the need for an organic substrate or nitrogen sources to grow and the capacity to attach to surfaces and co-aggregate. A correlation was found between bacteria groups and physicochemical and biological parameters measured in rearing tanks. Moreover, rearing-water bacterial communities influenced the microbiota of shrimp. Indeed, the biofloc environment modified the shrimp intestine microbiota, as the low level (27 %) of similarity between intestinal bacterial communities from the two treatments. Conclusion This study provides the first information describing the complex biofloc microbial community, which can help to understand the environment-microbiota-host relationship in this rearing system.

Trisomy 21 (T21), or Down syndrome (DS), is the most frequent and recognizable cause of intellectual disabilities. The level of disability, as evaluated by the intelligence quotient (IQ) test, varies considerably between patients independent of other factors. To determine the genetic or molecular basis of this difference, a high throughput transcriptomic analysis was performed on twenty T21 patients with high and low IQ, and 10 healthy controls using Digital Gene Expression. More than 90 millions of tags were sequenced in the three libraries. A total of 80 genes of potential interest were selected for the qPCR experiment validation, and three housekeeping genes were used for normalizing purposes. HLA DQA1 and HLA DRB1 were significantly downregulated among the patients with a low IQ, the values found in the healthy controls being intermediate between those noted in the IQ+ and IQ− T21 patients. Interestingly, the intergenic region between these genes contains a binding sequence for the CCCTC-binding factor, or CTCF, and cohesin (a multisubunit complex), both of which are essential for expression of HLA DQA1 and HLA DRB1 and numerous other genes. Our results might lead to the discovery of genes, or genetic markers, that are directly involved in several phenotypes of DS and, eventually, to the identification of potential targets for therapeutic interventions.

Predatory marine snails of the genus Conus use venom containing a complex mixture of bioactive peptides to subdue their prey. Here we report on a comprehensive analysis of the protein content of injectable venom from Conus consors, an indo-pacific fish-hunting cone snail. By matching MS/MS data against an extensive set of venom gland transcriptomic mRNA sequences, we identified 105 components out of ~400 molecular masses detected in the venom. Among them, we described new conotoxins belonging to the A, M- and O1-superfamilies as well as a novel superfamily of disulphide free conopeptides. A high proportion of the deduced sequences (36%) corresponded to propeptide regions of the A- and M-superfamilies, raising the question of their putative role in injectable venom. Enzymatic digestion of higher molecular mass components allowed the identification of new conkunitzins (~7 kDa) and two proteins in the 25 and 50 kDa molecular mass ranges respectively characterised as actinoporin-like and hyaluronidase-like protein. These results provide the most exhaustive and accurate proteomic overview of an injectable cone snail venom to date, and delineate the major protein families present in the delivered venom. This study demonstrates the feasibility of this analytical approach and paves the way for transcriptomics-assisted strategies in drug discovery.

Since the development of methods for homologous gene recombination, mouse models have played a central role in research in renal pathophysiology. However, many published and unpublished results show that mice with genetic changes mimicking human pathogenic mutations do not display the human phenotype. These functional differences may stem from differences in gene expression between mouse and human kidneys. However, large scale comparison of gene expression networks revealed conservation of gene expression among a large panel of human and mouse tissues including kidneys. Because renal functions result from the spatial integration of elementary processes originating in the glomerulus and the successive segments constituting the nephron, we hypothesized that differences in gene expression profiles along the human and mouse nephron might account for different behaviors. Analysis of SAGE libraries generated from the glomerulus and seven anatomically defined nephron segments from human and mouse kidneys allowed us to identify 4644 pairs of gene orthologs expressed in either one or both species. Quantitative analysis shows that many transcripts are present at different levels in the two species. It also shows poor conservation of gene expression profiles, with less than 10% of the 4644 gene orthologs displaying a higher conservation of expression profiles than the neutral expectation (p<0.05). Accordingly, hierarchical clustering reveals a higher degree of conservation of gene expression patterns between functionally unrelated kidney structures within a given species than between cognate structures from the two species. Similar findings were obtained for sub-groups of genes with either kidney-specific or housekeeping functions. Conservation of gene expression at the scale of the whole organ and divergence at the level of its constituting sub-structures likely account for the fact that although kidneys assume the same global function in the two species, many mouse “models” of human pathologies do not display the expected phenotype.

To gain molecular insight into kidney function, we performed a high-resolution quantitative analysis of gene expression in glomeruli and nine different nephron segments dissected from mouse kidney using Serial Analysis of Gene Expression (SAGE). We also developed dedicated bioinformatics tools and databases to annotate mRNA tags as transcripts. Over 800,000 mRNA SAGE tags were sequenced corresponding to >20,000 different mRNA tags present at least twice in at least one library. Hierarchical clustering analysis of tags demonstrated similarities between the three anatomical subsegments of the proximal tubule, between the cortical and medullary segments of the thick ascending limb of Henle's loop, and between the three segments constituting the aldosterone-sensitive distal nephron segments, whereas the glomerulus and distal convoluted tubule clusterized independently. We also identified highly specific mRNA markers of each subgroup of nephron segments and of most nephron segments. Tag annotation also identified numbers of putative antisense mRNAs. This database constitutes a reference resource in which the quantitative expression of a given gene can be compared with that of other genes in the same nephron segment, or between different segments of the nephron. To illustrate possible applications of this database, we performed a deeper analysis of the glomerulus transcriptome that unexpectedly revealed expression of several ion and water carriers; within the glomerulus, they were found to be preferentially expressed in the parietal sheet. It also revealed the major role of the zinc finger transcription factor Wt1 in the specificity of gene expression in the glomerulus. Finally, functional annotation of glomerulus-specific transcripts suggested a high proliferation activity of glomerular cells. Immunolabeling for PCNA confirmed a high percentage of proliferating cells in the glomerulus parietal sheet.

Background: The shell of the pearl-producing bivalve Pinctada margaritifera is composed of an organic cell-free matrix that plays a key role in the dynamic process of biologically-controlled biomineralization. In order to increase genomic resources and identify shell matrix proteins implicated in biomineralization in P. margaritifera, high-throughput Expressed Sequence Tag (EST) pyrosequencing was undertaken on the calcifying mantle, combined with a proteomic analysis of the shell.Results: We report the functional analysis of 276 738 sequences, leading to the constitution of an unprecedented catalog of 82 P. margaritifera biomineralization-related mantle protein sequences. Components of the current "chitin-silk fibroin gel-acidic macromolecule" model of biomineralization processes were found, in particular a homolog of a biomineralization protein (Pif-177) recently discovered in P. fucata. Among these sequences, we could show the localization of two other biomineralization protein transcripts, pmarg-aspein and pmarg-pearlin, in two distinct areas of the outer mantle epithelium, suggesting their implication in calcite and aragonite formation. Finally, by combining the EST approach with a proteomic mass spectrometry analysis of proteins isolated from the P. margaritifera shell organic matrix, we demonstrated the presence of 30 sequences containing almost all of the shell proteins that have been previously described from shell matrix protein analyses of the Pinctada genus. The integration of these two methods allowed the global composition of biomineralizing tissue and calcified structures to be examined in tandem for the first time.Conclusions: This EST study made on the calcifying tissue of P. margaritifera is the first description of pyrosequencing on a pearl-producing bivalve species. Our results provide direct evidence that our EST data set covers most of the diversity of the matrix protein of P. margaritifera shell, but also that the mantle transcripts encode proteins present in P. margaritifera shell, hence demonstrating their implication in shell formation. Combining transcriptomic and proteomic approaches is therefore a powerful way to identify proteins involved in biomineralization. Data generated in this study supply the most comprehensive list of biomineralization-related sequences presently available among protostomian species, and represent a major breakthrough in the field of molluskan biomineralization.

Analysis of several million expressed gene signatures (tags) revealed an in- creasing number of different sequences, largely exceeding that of annotated genes in mammalian genomes. Serial Analysis of Gene Expression (SAGE) can reveal new RNAs transcribedfrompreviouslyunrecognizedgenomicregions. However, conventionalSAGE tags are too short to identify unambiguously unique sites in large genomes. Here, we de- sign a novel strategy with tags anchored on two different restrictions sites of cDNAs. New transcripts are then tentatively defined by the two SAGE tags in tandem and by the spanning sequence read on the genome between these tagged sites. Having developed a new algorithm to locate these tag-delimited genomic sequences, we first validated its ca- pacity to recognize known genes and its ability to reveal new transcripts with two SAGE libraries built in parallel from a single RNA sample. Our algorithm proves fast enough to experiment this strategy at a large scale. We then collected and processed the com- plete sets of human SAGE tags to predict yet unknown transcripts. A cross-validation with tiling arrays data shows that 47% of these tag-delimited genomic sequences overlap transcriptional active regions. Our method provides a new and complementary approach for complex transcriptome annotation.

for SAGE library sequencing consists of constructing concatemers by ligation of SAGE tags. Concate-mers are cloned into vectors, then transformed in bacterial clones. With this method of SAGE library construction, clones composed of large inserts need to be sequenced using Sanger technology. Since lig-ation of ditags yields concatemers of various sizes, the efficiency of the SAGE protocol is limited by a small average size of cloned concatemers. When using the original SAGE protocol, both purification and concatenation of SAGE ditags are critical for optimal performance. A high-throughput sequencing method-the massively parallel picoliter-scale process provided by the Genome Sequencer System-offers an efficient approach to rapidly sequence DNA. 2 To date, the Genome Sequencer System has been successfully utilized in an increasing number of de novo sequencing projects, including sequencing the genomes of several bacteria and the mitochondrial genome of an extinct species of mammoth, as well as exploring the sequence diversity present in environmental samples. 2-6 Here, we report a further significant reduction in time and cost for SAGE library construction through the successful use of this newly available pyrosequencing method. This method reads short lengths of DNA, averaging 80-120 bases. In this application note, we describe how this technology is well adapted for directly sequencing SAGE ditags and is therefore ideally suited for rapid SAGE library construction. A high-throughput sequencing method has been developed and offers an efficient approach to rapidly sequence DNA. This pyrosequencing method is suitable for directly sequencing ditags for Serial Analysis of Gene Expression (SAGE), and is well adapted to reduce both time and cost of SAGE library construction. This strategy avoids the traditional concatemer construction step, which often requires extensive technical knowledge and experience for high-quality fragment construction. Directly sequencing SAGE ditags may therefore allow more laboratories to become involved in SAGE library construction in the future. Serial Analysis of Gene Expression (SAGE) remains a relevant technique that allows an accurate quantitative and qualitative analysis of cell transcription in a variety of physiological and pathological conditions. 1 Through a series of enzymatic manipulations , the SAGE method reduces cDNA molecules to tags of 14 bp (short SAGE) or 21 bp (long SAGE). Each tag represents one mRNA molecule. Tags are ligated to form concatemers that are cloned and sequenced. Comparing the sequence information from the tags with the GenBank database provides qualitative information about transcribed genes. The frequency of a specific tag within the SAGE …

A high-throughput sequencing method has been developed and offers an efficient approach to rapidly sequence DNA. This pyrosequencing method is suitable for directly sequencing ditags for Serial Analysis of Gene Expression (SAGE), and is well adapted to reduce both time and cost of SAGE library construction. This strategy avoids the traditional concatemer construction step, which often requires extensive technical knowl- edge and experience for high-quality fragment construction. Directly sequencing SAGE ditags may therefore allow more laboratories to become involved in SAGE library construction in the future. Serial Analysis of Gene Expression (SAGE) remains a relevant technique that allows an accurate quanti- tative and qualitative analysis of cell transcription in a variety of physiological and pathological condi- tions.1 Through a series of enzymatic manipula- tions, the SAGE method reduces cDNA molecules to tags of 14 bp (short SAGE) or 21 bp (long SAGE). Each tag represents one mRNA molecule. Tags are ligated to form concatemers that are cloned and sequenced. Comparing the sequence informa- tion from the tags with the GenBank database pro- vides qualitative information about transcribed genes. The frequency of a specific tag within the SAGE tag population correlates with its relative abundance in the cell and gives quantitative infor- mation about expressed genes. The SAGE technique is based on routine molecular biology methods. Nevertheless, only a handful of large genomic centers worldwide have the resources and technical expertise to construct large numbers of SAGE libraries. The most widely used strategy

Analysis of several million expressed gene signatures (tags) revealed an increasing number of different sequences, largely exceeding that of annotated genes in mammalian genomes. Serial analysis of gene expression (SAGE) can reveal new Poly(A) RNAs transcribed from previously unrecognized chromosomal regions. However, conventional SAGE tags are too short to identify unambiguously unique sites in large genomes. Here, we design a novel strategy with tags anchored on two different restrictions sites of cDNAs. New transcripts are then tentatively defined by the two SAGE tags in tandem and by the spanning sequence read on the genome between these tagged sites. Having developed a new algorithm to locate these tag-delimited genomic sequences (TDGS), we first validated its capacity to recognize known genes and its ability to reveal new transcripts with two SAGE libraries built in parallel from a single RNA sample. Our algorithm proves fast enough to experiment this strategy at a large scale. We then collected and processed the complete sets of human SAGE tags to predict yet unknown transcripts. A cross-validation with tiling arrays data shows that 47% of these TDGS overlap transcriptional active regions. Our method provides a new and complementary approach for complex transcriptome annotation.