In recent years, the introduction of massively parallel sequencing platforms for Next Generation Sequencing (NGS) protocols, able to simultaneously sequence hundred thousand DNA fragments, dramatically changed the landscape of the genetics studies. RNA-Seq for transcriptome studies, Chip-Seq for DNA-proteins interaction, CNV-Seq for large genome nucleotide variations are only some of the intriguing new applications supported by these innovative platforms. Among them RNA-Seq is perhaps the most complex NGS application. Expression levels of specific genes, differential splicing, allele-specific expression of transcripts can be accurately determined by RNA-Seq experiments to address many biological-related issues. All these attributes are not readily achievable from previously widespread hybridization-based or tag sequence-based approaches. However, the unprecedented level of sensitivity and the large amount of available data produced by NGS platforms provide clear advantages as well as new challenges and issues. This technology brings the great power to make several new biological observations and discoveries, it also requires a considerable effort in the development of new bioinformatics tools to deal with these massive data files. The paper aims to give a survey of the RNA-Seq methodology, particularly focusing on the challenges that this application presents both from a biological and a bioinformatics point of view.
27 June 2012 in European Journal of Human Genetics
Peroxisome-proliferator-activated receptor γ (PPARγ) regulates glucose and lipid homeostasis, insulin signaling, and adipocyte differentiation. Here, we report the skipping of exon 5 as a legitimate splicing event generating PPARγΔ5, a previously unidentified naturally occurring truncated isoform of PPARγ, which lacks the entire ligand-binding domain. PPARγΔ5 is endogenously expressed in human adipose tissue and, during adipocyte differentiation, lacks ligand-dependent transactivation ability and acts as a dominant-negative isoform reducing PPARγ activity. Ligand-mediated PPARγ activation induces exon 5 skipping in a negative feedback loop, suggesting alternative splicing as a mechanism regulating PPARγ activity. PPARγΔ5 overexpression modifies the PPARγ-induced transcriptional network, significantly impairing the differentiation ability of adipocyte precursor cells. Additionally, PPARγΔ5 expression in subcutaneous adipose tissue positively correlates with BMI in two independent cohorts of overweight or obese and type 2 diabetic patients. From a functional perspective, PPARγΔ5 mimics PPARG dominant-negative mutated receptors, possibly contributing to adipose tissue dysfunction. These findings open an unexplored scenario in PPARG regulation and PPARγ-related diseases.
Pancreatic stellate cells (PSCs) secrete high levels of transforming growth factor-β1 (TGF-β1) that contributes to the development of pancreatic ductal adenocarcinoma (PDAC). TGF-β1 modulates the expression of L1 cell adhesion molecule (L1CAM), but its role in tumour progression still remains controversial. To clarify L1 function in PDAC and cellular phenotypes, we performed L1CAM cell sorting, silencing and overexpression in several primary pancreatic cancer cells. PSCs silenced for TGF-β1 were used for crosstalk experiments. We found that TGF-β1 secreted by PSCs negatively regulates L1CAM expression, through canonical TGF-β-Smad2/3 signalling, leading to a more aggressive PDAC phenotype. Cells with reduced expression of L1CAM harboured enhanced stemness potential and tumourigenicity. Inactivation of TGF-β1 signalling in PSCs strongly reduced the aggressiveness of PDAC cells. Our data provide functional proof and mechanistic insights for the tumour-suppressive function of L1CAM via reducing stemness. Rescuing L1CAM expression in cancer cells through targeting of TGF-β1 reverses stemness and bears the potential to improve the still miserable prognosis of PDAC patients.
The nuclear receptor PPARγis a key regulator of adipogenesis, and alterations of its function are associated with different pathological processes related to metabolic syndrome. We recently identified twoPPARGtranscripts encoding dominant negative PPARγisoforms. The existence of differentPPARGvariants suggests that alternative splicing is crucial to modulate PPARγfunction, underlying some underestimated aspects of its regulation. Here we investigatePPARGexpression in different tissues and cells affected in metabolic syndrome and, in particular, during adipocyte differentiation of human mesenchymal stem cells. We defined the transcript-specific expression pattern ofPPARGvariants encoding both canonical and dominant negative isoforms and identified a novelPPARGtranscript,γ1ORF4. Our analysis indicated that, during adipogenesis, the transcription of alternativePPARGvariants is regulated in a time-specific manner through differential usage of distinct promoters. In addition, our analysis describes—for the first time—the differential contribution of three ORF4 variants to this process, suggesting a still unexplored role for these dominant negative isoforms during adipogenesis. Therefore, our results highlight crucial aspects ofPPARGregulation, suggesting the need of further investigation to rule out the differential impact of allPPARGtranscripts in both physiologic and pathologic conditions, such as metabolism-related disorders.