Identification of microRNAs and their target genes in Alport syndrome using deep sequencing of iPSCs samples

Potential Renal Damage Biomarkers in Alport Syndrome—A Review of the Literature

Alport syndrome (AS) is the second most common cause of inherited chronic kidney disease. This disorder is caused by genetic variants on COL4A3, COL4A4 and COL4A5 genes. These genes encode the proteins that constitute collagen type IV of the glomerular basement membrane (GBM). The heterodimer COL4A3A4A5 constitutes the majority of the GBM, and it is essential for the normal function of the glomerular filtration barrier (GFB). Alterations in any of collagen type IV constituents cause disruption of the GMB structure, allowing leakage of red blood cells and albumin into the urine, and compromise the architecture of the GFB, inducing inflammation and fibrosis, thus resulting in kidney damage and loss of renal function. The advances in DNA sequencing technologies, such as next-generation sequencing, allow an accurate diagnose of AS. Due to the important risk of the development of progressive kidney disease in AS patients, which can be delayed or possibly prevented by timely initiation of therapy, an early diagnosis of this condition is mandatory. Conventional biomarkers such as albuminuria and serum creatinine increase relatively late in AS. A panel of biomarkers that might detect early renal damage, monitor therapy, and reflect the prognosis would have special interest in clinical practice. The aim of this systematic review is to summarize the biomarkers of renal damage in AS as described in the literature. We found that urinary Podocin and Vascular Endothelial Growth Factor A are important markers of podocyte injury. Urinary Epidermal Growth Factor has been related to tubular damage, interstitial fibrosis and rapid progression of the disease. Inflammatory markers such as Transforming Growth Factor Beta 1, High Motility Group Box 1 and Urinary Monocyte Chemoattractant Protein- 1 are also increased in AS and indicate a higher risk of kidney disease progression. Studies suggest that miRNA-21 is elevated when renal damage occurs. Novel techniques, such as proteomics and microRNAs, are promising.

Multiomics landscape of the autosomal dominant osteopetrosis type II disease-specific induced pluripotent stem cells

BACKGROUND

Autosomal dominant osteopetrosis type II (ADO2) is a genetically and phenotypically metabolic bone disease, caused by osteoclast abnormalities. The pathways dysregulated in ADO2 could lead to the defects in osteoclast formation and function. However, the mechanism remains elusive.

MATERIALS AND METHODS

To systematically explore the molecular characterization of ADO2, we performed a multi-omics profiling from the autosomal dominant osteopetrosis type II iPSCs (ADO2-iPSCs) and healthy normal control iPSCs (NC-iPSCs) using whole genome re-sequencing, DNA methylation and N6-methyladenosine (m6A) analysis in this study.

RESULTS

Totally, we detected 7,095,817 single nucleotide polymorphisms (SNPs) and 1,179,573 insertion and deletions (InDels), 1,001,943 differentially methylated regions (DMRs) and 2984 differential m6A peaks, and the comprehensive multi-omics profile was generated from the two cells. Interestingly, the ISG15 m6A level in ADO2-iPSCs is higher than NC-iPSCs by IGV software, and the differentially expressed m6A-modified genes (DEMGs) were highly enriched in the osteoclast differentiation and p53 signaling pathway, which associated with the development of osteopetrosis. In addition, combining our previously published transcriptome and proteome datasets, we found that the change in DNA methylation levels correlates inversely with some gene expression levels.

CONCLUSION

Our results indicate that the global multi-omics landscape not only provides a high-quality data resource but also reveals a dynamic pattern of gene expression, and found that the pathogenesis of ADO2 may begin early in life.

Gene locations may contribute to predicting gene regulatory relationships

We propose that locations of genes on chromosomes can contribute to the prediction of gene regulatory relationships. We constructed a time-based gene regulatory network of zebrafish cardiogenesis on the basis of a spatio-temporal neighborhood method. Through the network, specific regulatory pathways and order of gene expression during zebrafish cardiogenesis were obtained. By comparing the order with locations of these genes on chromosomes, we discovered that there exists a reversal phenomenon between the order and order of gene locations. The discovery provides an inherent rule to instruct exploration of gene regulatory relationships. Specifically, the discovery can help to predict if regulatory relationships between genes exist and contribute to evaluating the correctness of discovered gene regulatory relationships.

Modeling Kidney Disease with iPS Cells

Induced pluripotent stem cells (iPSCs) are somatic cells that have been transcriptionally reprogrammed to an embryonic stem cell (ESC)-like state. iPSCs are a renewable source of diverse somatic cell types and tissues matching the original patient, including nephron-like kidney organoids. iPSCs have been derived representing several kidney disorders, such as ADPKD, ARPKD, Alport syndrome, and lupus nephritis, with the goals of generating replacement tissue and ‘disease in a dish’ laboratory models. Cellular defects in iPSCs and derived kidney organoids provide functional, personalized biomarkers, which can be correlated with genetic and clinical information. In proof of principle, disease-specific phenotypes have been described in iPSCs and ESCs with mutations linked to polycystic kidney disease or focal segmental glomerulosclerosis. In addition, these cells can be used to model nephrotoxic chemical injury. Recent advances in directed differentiation and CRISPR genome editing enable more specific iPSC models and present new possibilities for diagnostics, disease modeling, therapeutic screens, and tissue regeneration using human cells. This review outlines growth opportunities and design strategies for this rapidly expanding and evolving field.