Pierluigi Strippoli

Systematic reanalysis of partial trisomy 21 cases with or without Down syndrome suggests a small region on 21q22.13 as critical to the phenotype

A ‘Down Syndrome critical region’ (DSCR) sufficient to induce the most constant phenotypes of Down syndrome (DS) had been identified by studying partial (segmental) trisomy 21 (PT21) as an interval of 0.6–8.3 Mb within human chromosome 21 (Hsa21), although its existence was later questioned. We propose an innovative, systematic reanalysis of all described PT21 cases (from 1973 to 2015). In particular, we built an integrated, comparative map from 125 cases with or without DS fulfilling stringent cytogenetic and clinical criteria. The map allowed to define or exclude as candidates for DS fine Hsa21 sequence intervals, also integrating duplication copy number variants (CNVs) data. A highly restricted DSCR (HR-DSCR) of only 34 kb on distal 21q22.13 has been identified as the minimal region whose duplication is shared by all DS subjects and is absent in all non-DS subjects. Also being spared by any duplication CNV in healthy subjects, HR-DSCR is proposed as a candidate for the typical DS features, the intellectual disability and some facial phenotypes. HR-DSCR contains no known gene and has relevant homology only to the chimpanzee genome. Searching for HR-DSCR functional loci might become a priority for understanding the fundamental genotype-phenotype relationships in DS.

A quantitative transcriptome reference map of the normal human brain.

We performed an innovative systematic meta-analysis of 60 gene expression profiles of whole normal human brain, to provide a quantitative transcriptome reference map of it, i.e. a reference typical value of expression for each of the 39,250 known, mapped and 26,026 uncharacterized (unmapped) transcripts. To this aim, we used the software named Transcriptome Mapper (TRAM), which is able to generate transcriptome maps based on gene expression data from multiple sources. We also analyzed differential expression by comparing the brain transcriptome with those derived from human foetal brain gene expression, from a pool of human tissues (except the brain) and from the two normal human brain regions cerebellum and cerebral cortex, which are two of the main regions severely affected when cognitive impairment occurs, as happens in the case of trisomy 21. Data were downloaded from microarray databases, processed and analyzed using TRAM software and validated in vitro by assaying gene expression through several magnitude orders by ‘real-time’ reverse transcription polymerase chain reaction (RT-PCR). The excellent agreement between in silico and experimental data suggested that our transcriptome maps may be a useful quantitative reference benchmark for gene expression studies related to the human brain. Furthermore, our analysis yielded biological insights about those genes which have an intrinsic over-/under-expression in the brain, in addition offering a basis for the regional analysis of gene expression. This could be useful for the study of chromosomal alterations associated to cognitive impairment, such as trisomy 21, the most common genetic cause of intellectual disability.

Integrated differential transcriptome maps of Acute Megakaryoblastic Leukemia (AMKL) in children with or without Down Syndrome (DS).

BackgroundThe incidence of Acute Megakaryoblastic Leukemia (AMKL) is 500-fold higher in children with Down Syndrome (DS) compared with non-DS children, but the relevance of trisomy 21 as a specific background of AMKL in DS is still an open issue. Several Authors have determined gene expression profiles by microarray analysis in DS and/or non-DS AMKL. Due to the rarity of AMKL, these studies were typically limited to a small group of samples.MethodsWe generated integrated quantitative transcriptome maps by systematic meta-analysis from any available gene expression profile dataset related to AMKL in pediatric age. This task has been accomplished using a tool recently described by us for the generation and the analysis of quantitative transcriptome maps, TRAM (Transcriptome Mapper), which allows effective integration of data obtained from different experimenters, experimental platforms and data sources. This allowed us to explore gene expression changes involved in transition from normal megakaryocytes (MK, n=19) to DS (n=43) or non-DS (n=45) AMKL blasts, including the analysis of Transient Myeloproliferative Disorder (TMD, n=20), a pre-leukemia condition.ResultsWe propose a biological model of the transcriptome depicting progressive changes from MK to TMD and then to DS AMKL. The data indicate the repression of genes involved in MK differentiation, in particular the cluster on chromosome 4 including PF4 (platelet factor 4) and PPBP (pro-platelet basic protein); the gene for the mitogen-activated protein kinase MAP3K10 and the thrombopoietin receptor gene MPL. Moreover, comparing both DS and non-DS AMKL with MK, we identified three potential clinical markers of progression to AMKL: TMEM241 (transmembrane protein 241) was the most over-expressed single gene, while APOC2 (apolipoprotein C-II) and ZNF587B (zinc finger protein 587B) appear to be the most discriminant markers of progression, specifically to DS AMKL. Finally, the chromosome 21 (chr21) genes resulted to be the most over-expressed in DS and non-DS AMKL, as well as in TMD, pointing out a key role of chr21 genes in differentiating AMKL from MK.ConclusionsOur study presents an integrated original model of the DS AMLK transcriptome, providing the identification of genes relevant for its pathophysiology which can potentially be new clinical markers.

A quantitative transcriptome reference map of the normal human hippocampus

We performed an innovative systematic meta‐analysis of 41 gene expression profiles of normal human hippocampus to provide a quantitative transcriptome reference map of it, i.e. a reference typical value of expression for each of the 30,739 known mapped and the 16,258 uncharacterized (unmapped) transcripts. For this aim, we used the software called TRAM (Transcriptome Mapper), which is able to generate transcriptome maps based on gene expression data from multiple sources. We also analyzed differential expression by comparing the hippocampus with the whole brain transcriptome map to identify a typical expression pattern of this subregion compared with the whole organ. Finally, due to the fact that the hippocampus is one of the main brain region to be severely affected in trisomy 21 (the best known genetic cause of intellectual disability), a particular attention was paid to the expression of chromosome 21 (chr21) genes. Data were downloaded from microarray databases, processed, and analyzed using TRAM software. Among the main findings, the most over‐expressed loci in the hippocampus are the expressed sequence tag cluster Hs.732685 and the member of the calmodulin gene family CALM2. The tubulin folding cofactor B (TBCB) gene is the best gene at behaving like a housekeeping gene. The hippocampus vs. the whole brain differential transcriptome map shows the over‐expression of LINC00114, a long non‐coding RNA mapped on chr21. The hippocampus transcriptome map was validated in vitro by assaying gene expression through several magnitude orders by “Real‐Time” reverse transcription polymerase chain reaction (RT‐PCR). The highly significant agreement between in silico and experimental data suggested that our transcriptome map may be a useful quantitative reference benchmark for gene expression studies related to human hippocampus. Furthermore, our analysis yielded biological insights about those genes that have an intrinsic over‐/under‐expression in the hippocampus.

Identification of minimal eukaryotic introns through GeneBase, a user-friendly tool for parsing the NCBI Gene databank

We have developed GeneBase, a full parser of the National Center for Biotechnology Information (NCBI) Gene database, which generates a fully structured local database with an intuitive user-friendly graphic interface for personal computers. Features of all the annotated eukaryotic genes are accessible through three main software tables, including for each entry details such as the gene summary, the gene exon/intron structure and the specific Gene Ontology attributions. The structuring of the data, the creation of additional calculation fields and the integration with nucleotide sequences allow users to make many types of comparisons and calculations that are useful for data retrieval and analysis. We provide an original example analysis of the existing introns across all the available species, through which the classic biological problem of the ‘minimal intron’ may find a solution using available data. Based on all currently available data, we can define the shortest known eukaryotic GT-AG intron length, setting the physical limit at the 30 base pair intron belonging to the human MST1L gene. This ‘model intron’ will shed light on the minimal requirement elements of recognition used for conventional splicing functioning. Remarkably, this size is indeed consistent with the sum of the splicing consensus sequence lengths.

Systematic large-scale meta-analysis identifies a panel of two mRNAs as blood biomarkers for colorectal cancer detection

Colorectal cancer (CRC) is the third most common cancer in the world. A significant survival rate is achieved if it is detected at an early stage. A whole blood screening test, without any attempt to isolate blood fractions, could be an important tool to improve early detection of colorectal cancer. We searched for candidate markers with a novel approach based on the Transcriptome Mapper (TRAM), aimed at identifying specific RNAs with the highest differential expression ratio between colorectal cancer tissue and normal blood samples. This tool permits a large-scale systematic meta-analysis of all available data obtained by microarray experiments. The targeting of RNA took into consideration that tumour phenotypic variation is associated with changes in the mRNA levels of genes regulating or affecting this variation. A real time quantitative reverse transcription polymerase chain reaction (qRT- PCR) was applied to the validation of candidate markers in the blood of 67 patients and 67 healthy controls. The expression of genes: TSPAN8, LGALS4, COL1A2 and CEACAM6 resulted as being statistically different. In particular ROC curves attested for TSPAN8 an AUC of 0.751 with a sensitivity of 83.6% and a specificity of 58.2% at a cut off of 10.85, while the panel of the two best genes showed an AUC of 0.861 and a sensitivity of 92.5% with a specificity of 67.2%. Our preliminary study on a total of 134 subjects showed promising results for a blood screening test to be validated in a larger cohort with the staging stratification and in patients with other gastrointestinal diseases.

Characterization of human gene locus CYYR1: a complex multi-transcript system.

Cysteine/tyrosine-rich 1 (CYYR1) is a gene we previously identified on human chromosome 21 starting from an in-depth bioinformatics analysis of chromosome 21 segment 40/105 (21q21.3), where no coding region had previously been predicted. CYYR1 was initially characterized as a four-exon gene, whose brain-derived cDNA sequencing predicts a 154-amino acid product. In this study we provide, with in silico and in vitro analyses, the first detailed description of the human CYYR1 locus. The analysis of this locus revealed that it is composed of a multi-transcript system, which includes at least seven CYYR1 alternative spliced isoforms and a new CYYR1 antisense gene (named CYYR1-AS1). In particular, we cloned, for the first time, the following isoforms: CYYR1-1,2,3,4b and CYYR1-1,2,3b, which present a different 3′ transcribed region, with a consequent different carboxy-terminus of the predicted proteins; CYYR1-1,2,4 lacks exon 3; CYYR1-1,2,2bis,3,4 presents an additional exon between exon 2 and exon 3; CYYR1-1b,2,3,4 presents a different 5′ untranslated region when compared to CYYR1. The complexity of the locus is enriched by the presence of an antisense transcript. We have cloned a long transcript overlapping with CYYR1 as an antisense RNA, probably a non-coding RNA. Expression analysis performed in different normal tissues, tumour cell lines as well as in trisomy 21 and euploid fibroblasts has confirmed a quantitative and qualitative variability in the expression pattern of the multi-transcript locus, suggesting a possible role in complex diseases that should be further investigated.

Improving mRNA 5' coding sequence determination in the mouse genome.

The incomplete determination of the mRNA 5′ end sequence may lead to the incorrect assignment of the first AUG codon and to errors in the prediction of the encoded protein product. Due to the significance of the mouse as a model organism in biomedical research, we performed a systematic identification of coding regions at the 5′ end of all known mouse mRNAs, using an automated expressed sequence tag (EST)-based approach which we have previously described. By parsing almost 4xa0million BLAT alignments we found 351 mouse loci, out of 20,221 analyzed, in which an extension of the mRNA 5′ coding region was identified. Proof-of-concept confirmation was obtained by in vitro cloning and sequencing for Apc2 and Mknk2 cDNAs. We also generated a list of 16,330 mouse mRNAs where the presence of an in-frame stop codon upstream of the known start codon indicates completeness of the coding sequence at 5′ end in the current form. Systematic searches in the main mouse genome databases and genome browsers showed that 82xa0% of our results are original and have not been identified by their annotation pipelines. Moreover, the same information is not easily derivable from RNA-Seq data, due to short sequence length and laboriousness in building full-length transcript structures. In conclusion, our results improve the determination of full-length 5′ coding sequences and might be useful in order to reduce errors when studying mouse gene structure and function in biomedical research.

Systematic identification of human housekeeping genes possibly useful as references in gene expression studies

The ideal reference, or control, gene for the study of gene expression in a given organism should be expressed at a medium-high level for easy detection, should be expressed at a constant/stable level throughout different cell types and within the same cell type undergoing different treatments, and should maintain these features through as many different tissues of the organism. From a biological point of view, these theoretical requirements of an ideal reference gene appear to be best suited to housekeeping (HK) genes. Recent advancements in the quality and completeness of human expression microarray data and in their statistical analysis may provide new clues toward the quantitative standardization of human gene expression studies in biology and medicine, both cross- and within-tissue. The systematic approach used by the present study is based on the Transcriptome Mapper tool and exploits the automated reassignment of probes to corresponding genes, intra- and inter-sample normalization, elaboration and representation of gene expression values in linear form within an indexed and searchable database with a graphical interface recording quantitative levels of expression, expression variability and cross-tissue width of expression for more than 31,000 transcripts. The present study conducted a meta-analysis of a pool of 646 expression profile data sets from 54 different human tissues and identified actin γ 1 as the HK gene that best fits the combination of all the traditional criteria to be used as a reference gene for general use; two ribosomal protein genes, RPS18 and RPS27, and one aquaporin gene, POM121 transmembrane nucleporin C, were also identified. The present study provided a list of tissue- and organ-specific genes that may be most suited for the following individual tissues/organs: Adipose tissue, bone marrow, brain, heart, kidney, liver, lung, ovary, skeletal muscle and testis; and also provides in these cases a representative, quantitative portrait of the relative, typical gene-expression profile in the form of searchable database tables.

A molecular view of the normal human thyroid structure and function reconstructed from its reference transcriptome map

BackgroundThe thyroid is the earliest endocrine structure to appear during human development, and thyroid hormones are necessary for proper organism development, in particular for the nervous system and heart, normal growth and skeletal maturation. To date a quantitative, validated transcriptional atlas of the whole normal human thyroid does not exist and the availability of a detailed expression map might be an excellent occasion to investigate the many features of the thyroid transcriptome.ResultsWe present a view at the molecular level of the normal human thyroid histology and physiology obtained by a systematic meta-analysis of all the available gene expression profiles for the whole organ. A quantitative transcriptome reference map was generated by using the TRAM (Transcriptome Mapper) software able to combine, normalize and integrate a total of 35 suitable datasets from different sources thus providing a typical reference expression value for each of the 27,275 known, mapped transcripts obtained. The experimental in vitro validation of data was performed by “Real-Time” reverse transcription polymerase chain reaction showing an excellent correlation coefficient (rxa0=xa00.93) with data obtained in silico.ConclusionsOur study provides a quantitative global reference portrait of gene expression in the normal human thyroid and highlights differential expression between normal human thyroid and a pool of non-thyroid tissues useful for modeling correlations between thyroidal gene expression and specific thyroid functions and diseases. The experimental in vitro validation supports the possible usefulness of the human thyroid transcriptome map as a reference for molecular studies of the physiology and pathology of this organ.