Technical Evaluation: Identification of Pathogenic Mutations in PKD1 and PKD2 in Patients with Autosomal Dominant Polycystic Kidney Disease by Next-Generation Sequencing and Use of a Comprehensive New Classification System.

Genetic testing of PKD1 and PKD2 is expected to play an increasingly important role in determining allelic influences in autosomal dominant polycystic kidney disease (ADPKD) in the near future. However, to date, genetic testing is not commonly employed because it is expensive, complicated because of genetic heterogeneity, and does not easily identify pathogenic variants. In this study, we developed a genetic testing system based on next-generation sequencing (NGS), long-range polymerase chain reaction, and a new software package. The new software package integrated seven databases and provided access to five cloud-based computing systems. The database integrated 241 polymorphic nonpathogenic variants detected in 140 healthy Japanese volunteers aged >35 years, who were confirmed by ultrasonography as having no cysts in either kidney. Using this system, we identified 60 novel and 30 known pathogenic mutations in 101 Japanese patients with ADPKD, with an overall detection rate of 89.1% (90/101) [95% confidence interval (CI), 83.0%-95.2%]. The sensitivity of the system increased to 93.1% (94/101) (95% CI, 88.1%-98.0%) when combined with multiplex ligation-dependent probe amplification analysis, making it sufficient for use in a clinical setting. In 82 (87.2%) of the patients, pathogenic mutations were detected in PKD1 (95% CI, 79.0%-92.5%), whereas in 12 (12.8%) patients pathogenic mutations were detected in PKD2 (95% CI, 7.5%-21.0%); this is consistent with previously reported findings. In addition, we were able to reconfirm our pathogenic mutation identification results using Sanger sequencing. In conclusion, we developed a high-sensitivity NGS-based system and successfully employed it to identify pathogenic mutations in PKD1 and PKD2 in Japanese patients with ADPKD.

Identification of consensus motifs associated with mitotic recombination and clinical characteristics in patients with paternal uniparental isodisomy of chromosome 11.

Uniparental disomy (UPD) is defined as the inheritance of both homologs of a given genomic region from only one parent. The majority of UPD includes an entire chromosome. However, the extent of UPD is sometimes limited to a subchromosomal region (segmental UPD). Mosaic paternal UPD (pUPD) of chromosome 11 is found in approximately 20% of patients with Beckwith-Wiedemann syndrome (BWS) and almost all pUPDs are segmental isodisomic pUPDs resulting from mitotic recombination at an early embryonic stage. A mechanism initiating a DNA double strand break (DSB) within 11p has been predicted to lead to segmental pUPD. However, no consensus motif has yet been found. Here, we analyzed 32 BWS patients with pUPD by SNP array and searched for consensus motifs. We identified four consensus motifs frequently appearing within breakpoint regions of segmental pUPD. These motifs were found in another nine BWS patients with pUPD. In addition, the seven motifs found in meiotic recombination hot spots could not be found within pUPD breakpoint regions. Histone H3 lysine 4 trimethylation, a marker of DSB initiation, could not be found either. These findings suggest that the mechanism(s) of mitotic recombination leading to segmental pUPD are different from that of meiotic recombination. Furthermore, we found seven patients with paternal uniparental diploidy (PUD) mosaicism. Comparison of clinical features between segmental pUPDs and PUDs showed that developmental disability and cardiac abnormalities were additional characteristic features of PUD mosaicism, along with high risk of tumor development. We also found that macroglossia was characteristic of segmental pUPD mosaicism.

Computational extraction of a neural molecular network through alternative splicing.

BACKGROUND: Generally, the results of high throughput analyses contain information about gene expressions, and about exon expressions. Approximately 90% of primary protein-coding transcripts undergo alternative splicing in mammals. However, changes induced by alternative exons have not been properly analyzed for their impact on important molecular networks or their biological events. Even when alternative exons are identified, they are usually subjected to bioinformatics analysis in the same way as the gene ignoring the possibility of functionality change because of the alteration of domain caused by alternative exon. Here, we reveal an effective computational approach to explore an important molecular network based on potential changes of functionality induced by alternative exons obtained from our comprehensive analysis of neuronal cell differentiation. RESULTS: From our previously identified 262 differentially alternatively spliced exons during neuronal cell differentiations, we extracted 241 sets that changed the amino acid sequences between the alternatively spliced sequences. Conserved domain searches indicated that annotated domain(s) were changed in 128 sets. We obtained 49 genes whose terms overlapped between domain description and gene annotation. Thus, these 49 genes have alternatively differentially spliced in exons that affect their main functions. We performed pathway analysis using these 49 genes and identified the EGFR (epidermal growth factor receptor) and mTOR (mammalian target of rapamycin) signaling pathway as being involved frequently. Recent studies reported that the mTOR pathway is associated with neuronal cell differentiation, vindicating that our approach extracted an important molecular network successfully. CONCLUSIONS: Effective informatics approaches for exons should be more complex than those for genes, because changes in alternative exons affect protein functions via alterations of amino acid sequences and functional domains. Our method extracted alterations of functional domains and identified key alternative splicing events. We identified the EGFR and mTOR signaling pathway as the most affected pathway. The mTOR pathway is important for neuronal differentiation, suggesting that this in silico extraction of alternative splicing networks is useful. This preliminary analysis indicated that automated analysis of the effects of alternative splicing would provide a rich source of biologically relevant information.

Comprehensive analysis of alternative splicing and functionality in neuronal differentiation of P19 cells.

BACKGROUND: Alternative splicing, which produces multiple mRNAs from a single gene, occurs in most human genes and contributes to protein diversity. Many alternative isoforms are expressed in a spatio-temporal manner, and function in diverse processes, including in the neural system. METHODOLOGY/PRINCIPAL FINDINGS: The purpose of the present study was to comprehensively investigate neural-splicing using P19 cells. GeneChip Exon Array analysis was performed using total RNAs purified from cells during neuronal cell differentiation. To efficiently and readily extract the alternative exon candidates, 9 filtering conditions were prepared, yielding 262 candidate exons (236 genes). Semiquantitative RT-PCR results in 30 randomly selected candidates suggested that 87% of the candidates were differentially alternatively spliced in neuronal cells compared to undifferentiated cells. Gene ontology and pathway analyses suggested that many of the candidate genes were associated with neural events. Together with 66 genes whose functions in neural cells or organs were reported previously, 47 candidate genes were found to be linked to 189 events in the gene-level profile of neural differentiation. By text-mining for the alternative isoform, distinct functions of the isoforms of 9 candidate genes indicated by the result of Exon Array were confirmed. CONCLUSIONS/SIGNIFICANCE: Alternative exons were successfully extracted. Results from the informatics analyses suggested that neural events were primarily governed by genes whose expression was increased and whose transcripts were differentially alternatively spliced in the neuronal cells. In addition to known functions in neural cells or organs, the uninvestigated alternative splicing events of 11 genes among 47 candidate genes suggested that cell cycle events are also potentially important. These genes may help researchers to differentiate the roles of alternative splicing in cell differentiation and cell proliferation.

Pharmacogenomics of cardiovascular pharmacology: development of an informatics system for analysis of DNA microarray data with a focus on lipid metabolism.

Genome-wide gene-expression data from DNA-microarray technology and molecular-network data from computational text-mining have led to a paradigm shift in biological research. However, interpretation of the huge amount of data is a bottleneck. We have developed an informatics system, which we refer to as bioSpace Explorer, that can extract pathways and molecules of interest from genome-wide data and show the mutual relationships among these pathways and molecules. Differentiation of 3T3-L1 cells into adipocytes and the action of a peroxisome proliferator-activated receptor gamma (PPARgamma) agonist or alpha-linolenic acid on this process was analyzed with bioSpace Explorer. The results suggested a biological basis for adipocyte differentiation and a strategy to enhance lipid oxidation in adipocytes. Clustered changes of molecules were apparent in the insulin, Wnt, and PPARgamma signaling pathways and in the lipogenesis, lipid oxidation, and lipid transport pathways during cell differentiation. A PPARgamma agonist enhanced lipid oxidation in adipocytes and alpha-linolenic acid gave similar results to the PPARgamma agonist. An analysis of sex hormone and thyroid hormone, in addition to PPARgamma signaling, suggested that these molecules are important for enhancement of lipid oxidation in adipocytes. The results indicate the utility of bioSpace Explorer for biological research on genome-wide molecular networks.