AnaLysis of Expression on human chromosome 21, ALE-HSA21: a pilot integrated web resource

Consequences of aneuploidy in human fibroblasts with trisomy 21

An abnormal number of chromosomes or aneuploidy accounts for most spontaneous abortions, as missegregation of a single chromosome during development is often lethal. Only individuals with trisomy 21, which causes Down syndrome, can live to adulthood but show cognitive disabilities, increased risk for leukemias, autoimmune disorders, and clinical symptoms associated with premature aging. The mechanisms by which aneuploidy affects cellular function to cause Down syndrome are not understood. Our studies revealed that aneuploidy causes several defects in cells from individuals with Down syndrome. These include increased gene and protein expression, lower viability, and increased dependency on serine to proliferate. Our studies establish a critical role of aneuploidy, independent of triplicated gene identity, in driving cellular defects associated with trisomy 21.

An extra copy of chromosome 21 causes Down syndrome, the most common genetic disease in humans. The mechanisms contributing to aneuploidy-related pathologies in this syndrome, independent of the identity of the triplicated genes, are not well defined. To characterize aneuploidy-driven phenotypes in trisomy 21 cells, we performed global transcriptome, proteome, and phenotypic analyses of primary human fibroblasts from individuals with Patau (trisomy 13), Edwards (trisomy 18), or Down syndromes. On average, mRNA and protein levels were increased by 1.5-fold in all trisomies, with a subset of proteins enriched for subunits of macromolecular complexes showing signs of posttranscriptional regulation. These results support the lack of evidence for widespread dosage compensation or dysregulation of chromosomal domains in human autosomes. Furthermore, we show that several aneuploidy-associated phenotypes are present in trisomy 21 cells, including lower viability and increased dependency on serine-driven lipid synthesis. Our studies establish a critical role of aneuploidy, independent of triplicated gene identity, in driving cellular defects associated with trisomy 21.

Defining housekeeping genes suitable for RNA-seq analysis of the human allograft kidney biopsy tissue

BACKGROUND

RNA-seq is poised to play a major role in the management of kidney transplant patients. Rigorous definition of housekeeping genes (HKG) is essential for further progress in this field. Using single genes or a limited set HKG is inherently problematic since their expression might be altered by specific diseases in the patients being studied.

METHODS

To generate a HKG set specific for kidney transplantation, we performed RNA-sequencing from renal allograft biopsies collected in a variety of clinical settings. Various normalization methods were applied to identify transcripts that had a coefficient of variation of expression that was below the 2nd percentile across all samples, and the corresponding genes were designated as housekeeping genes. Comparison with transcriptomic data from the Gene Expression Omnibus (GEO) database, pathway analysis and molecular biological functions were utilized to validate the housekeeping genes set.

RESULTS

We have developed a bioinformatics solution to this problem by using nine different normalization methods to derive large HKG gene sets from a RNA-seq data set of 47,611 transcripts derived from 30 biopsies. These biopsies were collected in a variety of clinical settings, including normal function, acute rejection, interstitial nephritis, interstitial fibrosis/tubular atrophy and polyomavirus nephropathy. Transcripts with coefficient of variation below the 2nd percentile were designated as HKG, and validated by showing their virtual absence in diseased allograft derived transcriptomic data sets available in the GEO. Pathway analysis indicated a role for these genes in maintenance of cell morphology, pyrimidine metabolism, and intracellular protein signaling.

CONCLUSIONS

Utilization of these objectively defined HKG data sets will guard against errors resulting from focusing on individual genes like 18S RNA, actin & tubulin, which do not maintain constant expression across the known spectrum of renal allograft pathology.

Trisomy 21 causes changes in the circulating proteome indicative of chronic autoinflammation

Trisomy 21 (T21) causes Down syndrome (DS), but the mechanisms by which T21 produces the different disease spectrum observed in people with DS are unknown. We recently identified an activated interferon response associated with T21 in human cells of different origins, consistent with overexpression of the four interferon receptors encoded on chromosome 21, and proposed that DS could be understood partially as an interferonopathy. However, the impact of T21 on systemic signaling cascades in living individuals with DS is undefined. To address this knowledge gap, we employed proteomics approaches to analyze blood samples from 263 individuals, 165 of them with DS, leading to the identification of dozens of proteins that are consistently deregulated by T21. Most prominent among these proteins are numerous factors involved in immune control, the complement cascade, and growth factor signaling. Importantly, people with DS display higher levels of many pro-inflammatory cytokines (e.g. IL-6, MCP-1, IL-22, TNF-α) and pronounced complement consumption, resembling changes seen in type I interferonopathies and other autoinflammatory conditions. Therefore, these results are consistent with the hypothesis that increased interferon signaling caused by T21 leads to chronic immune dysregulation, and justify investigations to define the therapeutic value of immune-modulatory strategies in DS.

An Atlas of annotations of Hydra vulgaris transcriptome

Background

RNA sequencing takes advantage of the Next Generation Sequencing (NGS) technologies for analyzing RNA transcript counts with an excellent accuracy. Trying to interpret this huge amount of data in biological information is still a key issue, reason for which the creation of web-resources useful for their analysis is highly desiderable.

Results

Starting from a previous work, Transcriptator, we present the Atlas of Hydra’s vulgaris, an extensible web tool in which its complete transcriptome is annotated. In order to provide to the users an advantageous resource that include the whole functional annotated transcriptome of Hydra vulgaris water polyp, we implemented the Atlas web-tool contains 31.988 accesible and downloadable transcripts of this non-reference model organism.

Conclusion

Atlas, as a freely available resource, can be considered a valuable tool to rapidly retrieve functional annotation for transcripts differentially expressed in Hydra vulgaris exposed to the distinct experimental treatments.

Web resource URL

http://www-labgtp.na.icar.cnr.it/Atlas.

Trisomy 21 consistently activates the interferon response

Although it is clear that trisomy 21 causes Down syndrome, the molecular events acting downstream of the trisomy remain ill defined. Using complementary genomics analyses, we identified the interferon pathway as the major signaling cascade consistently activated by trisomy 21 in human cells. Transcriptome analysis revealed that trisomy 21 activates the interferon transcriptional response in fibroblast and lymphoblastoid cell lines, as well as circulating monocytes and T cells. Trisomy 21 cells show increased induction of interferon-stimulated genes and decreased expression of ribosomal proteins and translation factors. An shRNA screen determined that the interferon-activated kinases JAK1 and TYK2 suppress proliferation of trisomy 21 fibroblasts, and this defect is rescued by pharmacological JAK inhibition. Therefore, we propose that interferon activation, likely via increased gene dosage of the four interferon receptors encoded on chromosome 21, contributes to many of the clinical impacts of trisomy 21, and that interferon antagonists could have therapeutic benefits.

Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes

Type 2 diabetes (T2D) is one of the most frequent mortality causes in western countries, with rapidly increasing prevalence. Anti-diabetic drugs are the first therapeutic approach, although many patients develop drug resistance. Most drug responsiveness variability can be explained by genetic causes. Inter-individual variability is principally due to single nucleotide polymorphisms, and differential drug responsiveness has been correlated to alteration in genes involved in drug metabolism (CYP2C9) or insulin signaling (IRS1, ABCC8, KCNJ11 and PPARG). However, most genome-wide association studies did not provide clues about the contribution of DNA variations to impaired drug responsiveness. Thus, characterizing T2D drug responsiveness variants is needed to guide clinicians toward tailored therapeutic approaches. Here, we extensively investigated polymorphisms associated with altered drug response in T2D, predicting their effects in silico. Combining different computational approaches, we focused on the expression pattern of genes correlated to drug resistance and inferred evolutionary conservation of polymorphic residues, computationally predicting the biochemical properties of polymorphic proteins. Using RNA-Sequencing followed by targeted validation, we identified and experimentally confirmed that two nucleotide variations in the CAPN10 gene—currently annotated as intronic—fall within two new transcripts in this locus. Additionally, we found that a Single Nucleotide Polymorphism (SNP), currently reported as intergenic, maps to the intron of a new transcript, harboring CAPN10 and GPR35 genes, which undergoes non-sense mediated decay. Finally, we analyzed variants that fall into non-coding regulatory regions of yet underestimated functional significance, predicting that some of them can potentially affect gene expression and/or post-transcriptional regulation of mRNAs affecting the splicing.

Alternative Splicing in Adhesion- and Motility-Related Genes in Breast Cancer

Breast cancer is the most common tumor and the second leading cause of cancer death among woman, mainly caused by the metastatic spread. Tumor invasiveness is due to an altered expression of adhesion molecules. Among them, semaphorins are of peculiar interest. Cancer cells can manipulate alternative splicing patterns to modulate the expression of adhesion- and motility-related molecules, also at the isoform level. In this study, combining RNA-Sequencing on MCF-7 to targeted experimental validations—in human breast cell lines and breast tumor biopsies—we identified 12 new alternative splicing transcripts in genes encoding adhesion- and motility-related molecules, including semaphorins, their receptors and co-receptors. Among them, a new SEMA3F transcript is expressed in all breast cell lines and breast cancer biopsies, and is translated into a new semaphorin 3F isoform. In silico analysis predicted that most of the new putative proteins lack functional domains, potentially missing some functions and acquiring new ones. Our findings better describe the extent of alternative splicing in breast cancer and highlight the need to further investigate adhesion- and motility-related molecules to gain insights into breast cancer progression.

A genomic approach to study down syndrome and cancer inverse comorbidity: untangling the chromosome 21

Down syndrome (DS), one of the most common birth defects and the most widespread genetic cause of intellectual disabilities, is caused by extra genetic material on chromosome 21 (HSA21). The increased genomic dosage of trisomy 21 is thought to be responsible for the distinct DS phenotypes, including an increased risk of developing some types of childhood leukemia and germ cell tumors. Patients with DS, however, have a strikingly lower incidence of many other solid tumors. We hypothesized that the third copy of genes located in HSA21 may have an important role on the protective effect that DS patients show against most types of solid tumors. Focusing on Copy Number Variation (CNV) array data, we have generated frequencies of deleted regions in HSA21 in four different tumor types from which DS patients have been reported to be protected. We describe three different regions of deletion pointing to a set of candidate genes that could explain the inverse comorbidity phenomenon between DS and solid tumors. In particular we found RCAN1 gene in Wilms tumors and a miRNA cluster containing miR-99A, miR-125B2 and miR-LET7C in lung, breast, and melanoma tumors as the main candidates for explaining the inverse comorbidity observed between solid tumors and DS.

Novel transcription factor variants through RNA-sequencing: the importance of being "alternative"

Alternative splicing is a pervasive mechanism of RNA maturation in higher eukaryotes, which increases proteomic diversity and biological complexity. It has a key regulatory role in several physiological and pathological states. The diffusion of Next Generation Sequencing, particularly of RNA-Sequencing, has exponentially empowered the identification of novel transcripts revealing that more than 95% of human genes undergo alternative splicing. The highest rate of alternative splicing occurs in transcription factors encoding genes, mostly in Krüppel-associated box domains of zinc finger proteins. Since these molecules are responsible for gene expression, alternative splicing is a crucial mechanism to "regulate the regulators". Indeed, different transcription factors isoforms may have different or even opposite functions. In this work, through a targeted re-analysis of our previously published RNA-Sequencing datasets, we identified nine novel transcripts in seven transcription factors genes. In silico analysis, combined with RT-PCR, cloning and Sanger sequencing, allowed us to experimentally validate these new variants. Through computational approaches we also predicted their novel structural and functional properties. Our findings indicate that alternative splicing is a major determinant of transcription factor diversity, confirming that accurate analysis of RNA-Sequencing data can reliably lead to the identification of novel transcripts, with potentially new functions.