Universal tight correlation of codon bias and pool of RNA codons (codonome): The genome is optimized to allow any distribution of gene expression values in the transcriptome from bacteria to humans

De Novo Assembly and Characterization of the Transcriptome of an Omnivorous Camel Cricket (Tachycines meditationis)

Tachycines meditationis (Orthoptera: Rhaphidophoridae: Tachycines) is a widely distributed insect in eastern Asia. This species is common in urban environments, and its unique omnivorous diet may contribute to its success in various habitats. However, molecular studies on the species are scarce. Here, we obtained the first transcriptome sequence of T. meditationis and performed preliminary analyses to test whether the evolution of coding sequences fits the expectations based on the species' ecology. We retrieved 476,495 effective transcripts and annotated 46,593 coding sequences (CDS). We analysed the codon usage and found that directional mutation pressure was the leading cause of codon usage bias in this species. This genome-wide relaxed codon usage pattern in T. meditationis is surprising, given the potentially large population size of this species. Moreover, despite the omnivorous diet, the chemosensory genes of this species do not exhibit codon usage deviating significantly from the genome-level pattern. They also do not seem to experience more gene family expansion than other cave cricket species do. A thorough search for rapidly evolved genes using the dN/dS value showed that genes associated with substance synthesis and metabolic pathways, such as retinol metabolism, aminoacyl-tRNA biosynthesis, and fatty acid metabolism, underwent species-specific positive selection. While some results seem to contradict the species ecology, our transcriptome assembly provides a valuable molecular resource for future studies on camel cricket evolution and molecular genetics for feeding ecology in insects, in general.

Phenotypic screening models for rapid diagnosis of genetic variants and discovery of personalized therapeutics

Precision medicine strives for highly individualized treatments for disease under the notion that each individual's unique genetic makeup and environmental exposures imprints upon them not only a disposition to illness, but also an optimal therapeutic approach. In the realm of rare disorders, genetic predisposition is often the predominant mechanism driving disease presentation. For such, mostly, monogenic disorders, a causal gene to phenotype association is likely. As a result, it becomes important to query the patient's genome for the presence of pathogenic variations that are likely to cause the disease. Determining whether a variant is pathogenic or not is critical to these analyses and can be challenging, as many disease-causing variants are novel and, ergo, have no available functional data to help categorize them. This problem is exacerbated by the need for rapid evaluation of pathogenicity, since many genetic diseases present in young children who will experience increased morbidity and mortality without rapid diagnosis and therapeutics. Here, we discuss the utility of animal models, with a focus mainly on C. elegans, as a contrast to tissue culture and in silico approaches, with emphasis on how these systems are used in determining pathogenicity of variants with uncertain significance and then used to screen for novel therapeutics.

Strong Selectional Forces Fine-Tune CpG Content in Genes Involved in Neurological Disorders as Revealed by Codon Usage Patterns

Neurodegenerative disorders cause irreversible damage to the neurons and adversely affect the quality of life. Protein misfolding and their aggregation in specific parts of the brain, mitochondrial dysfunction, calcium load, proteolytic stress, and oxidative stress are among the causes of neurodegenerative disorders. In addition, altered metabolism has been associated with neurodegeneration as evidenced by reductions in glutamine and alanine in transient global amnesia patients, higher homocysteine-cysteine disulfide, and lower methionine decline in serum urea have been observed in Alzheimer's disease patients. Neurodegeneration thus appears to be a culmination of altered metabolism. The study's objective is to analyze various attributes like composition, physical properties of the protein, and factors like selectional and mutational forces, influencing codon usage preferences in a panel of genes involved directly or indirectly in metabolism and contributing to neurodegeneration. Various parameters, including gene composition, dinucleotide analysis, Relative synonymous codon usage (RSCU), Codon adaptation index (CAI), neutrality and parity plots, and different protein indices, were computed and analyzed to determine the codon usage pattern and factors affecting it. The correlation of intrinsic protein properties such as the grand average of hydropathicity index (GRAVY), isoelectric point, hydrophobicity, and acidic, basic, and neutral amino acid content has been found to influence codon usage. In genes up to 800 amino acids long, the GC3 content was highly variable, while GC12 content was relatively constant. An optimum CpG content is present in genes to maintain a high expression level as required for genes involved in metabolism. Also observed was a low codon usage bias with a higher protein expression level. Compositional parameters and nucleotides at the second position of codons played essential roles in explaining the extent of bias. Overall analysis indicated that the dominance of selection pressure and compositional constraints and mutational forces shape codon usage.

SARS-CoV-2 Codon Usage Bias Downregulates Host Expressed Genes With Similar Codon Usage

Severe acute respiratory syndrome has spread quickly throughout the world and was declared a pandemic by the World Health Organization (WHO). The pathogenic agent is a new coronavirus (SARS-CoV-2) that infects pulmonary cells with great effectiveness. In this study we focus on the codon composition for the viral protein synthesis and its relationship with the protein synthesis of the host. Our analysis reveals that SARS-CoV-2 preferred codons have poor representation of G or C nucleotides in the third position, a characteristic which could result in an unbalance in the tRNAs pools of the infected cells with serious implications in host protein synthesis. By integrating this observation with proteomic data from infected cells, we observe a reduced translation rate of host proteins associated with highly expressed genes and that they share the codon usage bias of the virus. The functional analysis of these genes suggests that this mechanism of epistasis can contribute to understanding how this virus evades the immune response and the etiology of some deleterious collateral effect as a result of the viral replication. In this manner, our finding contributes to the understanding of the SARS-CoV-2 pathogeny and could be useful for the design of a vaccine based on the live attenuated strategy.

Pathological changes are associated with shifts in the employment of synonymous codons at the transcriptome level

BACKGROUND

The usage of different synonymous codons reflects the genome organization and has been connected to parameters such as mRNA abundance and protein folding. It is also been established that mutations targeting specific synonymous codons can trigger disease.

RESULTS

We performed a systematic meta-analysis of transcriptome results from 75 datasets representing 40 pathologies. We found that a subset of codons was preferentially employed in abundant transcripts, while other codons were preferentially found in low-abundance transcripts. By comparing control and pathological transcriptomes, we observed a shift in the employment of synonymous codons for every analyzed disease. For example, cancerous tissue employed preferentially A- or U-ending codons, shifting from G- or C-ending codons, which were preferred by control tissues. This analysis was able to discriminate patients and controls with high specificity and sensitivity.

CONCLUSIONS

Here we show that the employment of specific synonymous codons, quantified at the whole transcriptome level, changes profoundly in many diseases. We propose that the changes in codon employment offer a novel perspective for disease studies, and could be used to design new diagnostic tools.

Human protein-coding genes and gene feature statistics in 2019

Objective

A well-known limit of genome browsers is that the large amount of genome and gene data is not organized in the form of a searchable database, hampering full management of numerical data and free calculations. Due to the continuous increase of data deposited in genomic repositories, their content revision and analysis is recommended. Using GeneBase, a software with a graphical interface able to import and elaborate National Center for Biotechnology Information (NCBI) Gene database entries, we provide tabulated spreadsheets updated to 2019 about human nuclear protein-coding gene data set ready to be used for any type of analysis about genes, transcripts and gene organization.

Results

Comparison with previous reports reveals substantial change in the number of known nuclear protein-coding genes (now 19,116), the protein-coding non-redundant transcriptome space [now 59,281,518 base pair (bp), 10.1% increase], the number of exons (now 562,164, 36.2% increase) due to a relevant increase of the RNA isoforms recorded. Other parameters such as gene, exon or intron mean and extreme length appear to have reached a stability that is unlikely to be substantially modified by human genome data updates, at least regarding protein-coding genes. Finally, we confirm that there are no human introns shorter than 30 bp.

On the length, weight and GC content of the human genome

Objective

Basic parameters commonly used to describe genomes including length, weight and relative guanine-cytosine (GC) content are widely cited in absence of a primary source. By using updated data and original software we determined these values to the best of our knowledge as standard reference for the whole human nuclear genome, for each chromosome and for mitochondrial DNA. We also devised a method to calculate the relative GC content in the whole messenger RNA sequence set and in transcriptomes by multiplying the GC content of each gene by its mean expression level.

Results

The male nuclear diploid genome extends for 6.27 Gigabase pairs (Gbp), is 205.00 cm (cm) long and weighs 6.41 picograms (pg). Female values are 6.37 Gbp, 208.23 cm, 6.51 pg. The individual variability and the implication for the DNA informational density in terms of bits/volume were discussed. The genomic GC content is 40.9%. Following analysis in different transcriptomes and species, we showed that the greatest deviation was observed in the pathological condition analysed (trisomy 21 leukaemic cells) and in Caenorhabditis elegans. Our results may represent a solid basis for further investigation on human structural and functional genomics while also providing a framework for other genome comparative analysis.

Electronic supplementary material

The online version of this article (10.1186/s13104-019-4137-z) contains supplementary material, which is available to authorized users.

Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells

Down syndrome (DS) is due to the presence of an extra full or partial chromosome 21 (Hsa21). The identification of genes contributing to DS pathogenesis could be the key to any rational therapy of the associated intellectual disability. We aim at generating quantitative transcriptome maps in DS integrating all gene expression profile datasets available for any cell type or tissue, to obtain a complete model of the transcriptome in terms of both expression values for each gene and segmental trend of gene expression along each chromosome. We used the TRAM (Transcriptome Mapper) software for this meta-analysis, comparing transcript expression levels and profiles between DS and normal brain, lymphoblastoid cell lines, blood cells, fibroblasts, thymus and induced pluripotent stem cells, respectively. TRAM combined, normalized, and integrated datasets from different sources and across diverse experimental platforms. The main output was a linear expression value that may be used as a reference for each of up to 37,181 mapped transcripts analyzed, related to both known genes and expression sequence tag (EST) clusters. An independent example in vitro validation of fibroblast transcriptome map data was performed through “Real-Time” reverse transcription polymerase chain reaction showing an excellent correlation coefficient (r = 0.93, p < 0.0001) with data obtained in silico. The availability of linear expression values for each gene allowed the testing of the gene dosage hypothesis of the expected 3:2 DS/normal ratio for Hsa21 as well as other human genes in DS, in addition to listing genes differentially expressed with statistical significance. Although a fraction of Hsa21 genes escapes dosage effects, Hsa21 genes are selectively over-expressed in DS samples compared to genes from other chromosomes, reflecting a decisive role in the pathogenesis of the syndrome. Finally, the analysis of chromosomal segments reveals a high prevalence of Hsa21 over-expressed segments over the other genomic regions, suggesting, in particular, a specific region on Hsa21 that appears to be frequently over-expressed (21q22). Our complete datasets are released as a new framework to investigate transcription in DS for individual genes as well as chromosomal segments in different cell types and tissues.

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.

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

BACKGROUND

The 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.

RESULTS

We 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 (r = 0.93) with data obtained in silico.

CONCLUSIONS

Our 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.

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.

Genotype-phenotype correlation for congenital heart disease in Down syndrome through analysis of partial trisomy 21 cases

Among Down syndrome (DS) children, 40-50% have congenital heart disease (CHD). Although trisomy 21 is not sufficient to cause CHD, three copies of at least part of chromosome 21 (Hsa21) increases the risk for CHD. In order to establish a genotype-phenotype correlation for CHD in DS, we built an integrated Hsa21 map of all described partial trisomy 21 (PT21) cases with sufficient indications regarding presence or absence of CHD (n=107), focusing on DS PT21 cases. We suggest a DS CHD candidate region on 21q22.2 (0.96Mb), being shared by most PT21 cases with CHD and containing three known protein-coding genes (DSCAM, BACE2, PLAC4) and four known non-coding RNAs (DSCAM-AS1, DSCAM-IT1, LINC00323, MIR3197). The characterization of a DS CHD candidate region provides a useful approach to identify specific genes contributing to the pathology and to orient further investigations and possibly more effective therapy in relation to the multifactorial pathogenesis of CHD.

Difficulty in obtaining the complete mRNA coding sequence at 5' region (5' end mRNA artifact): Causes, consequences in biology and medicine and possible solutions for obtaining the actual amino acid sequence of proteins (Review)

The known difficulty in obtaining the actual full length, complete sequence of a messenger RNA (mRNA) may lead to the erroneous determination of its coding sequence at the 5' region (5' end mRNA artifact), and consequently to the wrong assignment of the translation start codon, leading to the inaccurate prediction of the encoded polypeptide at its amino terminus. Among the known human genes whose study was affected by this artifact, we can include disco interacting protein 2 homolog A (DIP2A; KIAA0184), Down syndrome critical region 1 (DSCR1), SON DNA binding protein (SON), trefoil factor 3 (TFF3) and URB1 ribosome biogenesis 1 homolog (URB1; KIAA0539) on chromosome 21, as well as receptor for activated C kinase 1 (RACK1, also known as GNB2L1), glutaminyl‑tRNA synthetase (QARS) and tyrosyl-DNA phosphodiesterase 2 (TDP2) along with another 474 loci, including interleukin 16 (IL16). In this review, we discuss the causes of this issue, its quantitative incidence in biomedical research, the consequences in biology and medicine, and the possible solutions for obtaining the actual amino acid sequence of proteins in the post-genomics era.

GeneBase 1.1: a tool to summarize data from NCBI gene datasets and its application to an update of human gene statistics

We release GeneBase 1.1, a local tool with a graphical interface useful for parsing, structuring and indexing data from the National Center for Biotechnology Information (NCBI) Gene data bank. Compared to its predecessor GeneBase (1.0), GeneBase 1.1 now allows dynamic calculation and summarization in terms of median, mean, standard deviation and total for many quantitative parameters associated with genes, gene transcripts and gene features (exons, introns, coding sequences, untranslated regions). GeneBase 1.1 thus offers the opportunity to perform analyses of the main gene structure parameters also following the search for any set of genes with the desired characteristics, allowing unique functionalities not provided by the NCBI Gene itself. In order to show the potential of our tool for local parsing, structuring and dynamic summarizing of publicly available databases for data retrieval, analysis and testing of biological hypotheses, we provide as a sample application a revised set of statistics for human nuclear genes, gene transcripts and gene features. In contrast with previous estimations strongly underestimating the length of human genes, a ‘mean’ human protein-coding gene is 67 kbp long, has eleven 309 bp long exons and ten 6355 bp long introns. Median, mean and extreme values are provided for many other features offering an updated reference source for human genome studies, data useful to set parameters for bioinformatic tools and interesting clues to the biomedical meaning of the gene features themselves.

Database URL: http://apollo11.isto.unibo.it/software/

Integrated Transcriptome Map Highlights Structural and Functional Aspects of the Normal Human Heart

A systematic meta-analysis of the available gene expression profiling datasets for the whole normal human heart generated a quantitative transcriptome reference map of this organ. Transcriptome Mapper (TRAM) software integrated 32 gene expression profile datasets from different sources returning a reference value of expression for each of the 43,360 known, mapped transcripts assayed by any of the experimental platforms used in this regard. Main findings include the visualization at the gene and chromosomal levels of the classical description of the basic histology and physiology of the heart, the identification of suitable housekeeping reference genes, the analysis of stoichiometry of gene products, and the focusing on chromosome 21 genes, which are present in one excess copy in Down syndrome subjects, presenting cardiovascular defects in 30-40% of cases. Independent in vitro validation showed an excellent correlation coefficient (r = 0.98) with the in silico data. Remarkably, heart/non-cardiac tissue expression ratio may also be used to anticipate that effects of mutations will most probably affect or not the heart. The quantitative reference global portrait of gene expression in the whole normal human heart illustrates the structural and functional aspects of the whole organ and is a general model to understand the mechanisms underlying heart pathophysiology. J. Cell. Physiol. 232: 759-770, 2017. © 2016 Wiley Periodicals, Inc.

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.

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.

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

BACKGROUND

The 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.

METHODS

We 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.

RESULTS

We 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.

CONCLUSIONS

Our 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 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.