27
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Molecular genetic analysis of PKHD1 by next-generation sequencing in Czech families with autosomal recessive polycystic kidney disease

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Autosomal recessive polycystic kidney disease (ARPKD) is an early-onset form of polycystic kidney disease that often leads to devastating outcomes for patients. ARPKD is caused by mutations in the PKHD1 gene, an extensive gene that encodes for the ciliary protein fibrocystin/polyductin. Next-generation sequencing is presently the best option for molecular diagnosis of ARPKD. Our aim was to set up the first study of ARPKD patients from the Czech Republic, to determine the composition of their mutations and genotype-phenotype correlations, along with establishment of next-generation sequencing of the PKHD1 gene that could be used for the diagnosis of ARPKD patients.

          Methods

          Mutational analysis of the PKHD1 gene was performed in 24 families using the amplicon-based next-generation sequencing (NGS) technique. In patients without 2 causal mutations identified by NGS, subsequent MLPA analysis of the PKHD1 gene was carried out.

          Results

          Two underlying mutations were detected in 54 % of families ( n = 13), one mutation in 13 % of families ( n = 3), and in 33 % of families ( n = 8) no mutation could be detected. Overall, seventeen different mutations (5 novel) were detected, including deletion of one exon. The detection rate in our study reached 60 % in the entire cohort of patients; but 90 % in the group of patients who fulfilled all clinical criteria of ARPKD, and 42 % in the group of patients with unknown kidney pathology. The most frequent mutation was T36M, accounting for nearly 21 % of all identified mutations.

          Conclusions

          Next-generation sequencing of the PKHD1 gene is a very useful method of molecular diagnosis in patients with a full clinical picture of ARPKD, and it has a high detection rate. Furthermore, its relatively low costs and rapidity allow the molecular genetic analysis of patients without the full clinical criteria of ARPKD, who might also have mutations in the PKHD1 gene.

          Related collections

          Most cited references17

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Human Splicing Finder: an online bioinformatics tool to predict splicing signals

          Thousands of mutations are identified yearly. Although many directly affect protein expression, an increasing proportion of mutations is now believed to influence mRNA splicing. They mostly affect existing splice sites, but synonymous, non-synonymous or nonsense mutations can also create or disrupt splice sites or auxiliary cis-splicing sequences. To facilitate the analysis of the different mutations, we designed Human Splicing Finder (HSF), a tool to predict the effects of mutations on splicing signals or to identify splicing motifs in any human sequence. It contains all available matrices for auxiliary sequence prediction as well as new ones for binding sites of the 9G8 and Tra2-β Serine-Arginine proteins and the hnRNP A1 ribonucleoprotein. We also developed new Position Weight Matrices to assess the strength of 5′ and 3′ splice sites and branch points. We evaluated HSF efficiency using a set of 83 intronic and 35 exonic mutations known to result in splicing defects. We showed that the mutation effect was correctly predicted in almost all cases. HSF could thus represent a valuable resource for research, diagnostic and therapeutic (e.g. therapeutic exon skipping) purposes as well as for global studies, such as the GEN2PHEN European Project or the Human Variome Project.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Prediction of human mRNA donor and acceptor sites from the DNA sequence.

            Artificial neural networks have been applied to the prediction of splice site location in human pre-mRNA. A joint prediction scheme where prediction of transition regions between introns and exons regulates a cutoff level for splice site assignment was able to predict splice site locations with confidence levels far better than previously reported in the literature. The problem of predicting donor and acceptor sites in human genes is hampered by the presence of numerous amounts of false positives: here, the distribution of these false splice sites is examined and linked to a possible scenario for the splicing mechanism in vivo. When the presented method detects 95% of the true donor and acceptor sites, it makes less than 0.1% false donor site assignments and less than 0.4% false acceptor site assignments. For the large data set used in this study, this means that on average there are one and a half false donor sites per true donor site and six false acceptor sites per true acceptor site. With the joint assignment method, more than a fifth of the true donor sites and around one fourth of the true acceptor sites could be detected without accompaniment of any false positive predictions. Highly confident splice sites could not be isolated with a widely used weight matrix method or by separate splice site networks. A complementary relation between the confidence levels of the coding/non-coding and the separate splice site networks was observed, with many weak splice sites having sharp transitions in the coding/non-coding signal and many stronger splice sites having more ill-defined transitions between coding and non-coding.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Anomalies of the TCF2 gene are the main cause of fetal bilateral hyperechogenic kidneys.

              Prenatal discovery of fetal bilateral hyperechogenic kidneys is very stressful for pregnant women and their family, and accurate diagnosis of the cause of the moderate forms of this pathology is very difficult. Hepatocyte nuclear factor-1beta that is encoded by the TCF2 gene is involved in the embryonic development of the kidneys. Sixty-two pregnancies with fetal bilateral hyperechogenic kidneys including 25 fetuses with inaccurate diagnosis were studied. TCF2 gene anomalies were detected in 18 (29%) of these 62 patients, and 15 of these 18 patients presented a complete heterozygous deletion of the TCF2 gene. Family screening revealed de novo TCF2 anomalies in more than half of the patients. TCF2 anomalies were associated with normal amniotic fluid volume and normal-sized kidneys between -2 and +2 SD in all patients except for two sisters. Antenatal cysts were detected in 11 of 18 patients, unilaterally in eight of 11. After birth, cysts appeared during the first year (17 of 18), and in patients with antenatal cysts, the number increased and developed bilaterally with decreased renal growth. In these 18 patients, the GFR decreased with longer follow-up and was lower in patients with solitary functioning dysplastic kidney. Heterozygous deletion of the TCF2 gene is an important cause of fetal hyperechogenic kidneys in this study and showed to be linked with early disease expression. The renal phenotype and the postnatal evolution were extremely variable and need a prospective long-term follow-up. Extrarenal manifestations are frequent in TCF2-linked pathologies. Therefore, prenatal counseling and follow-up should be multidisciplinary.
                Bookmark

                Author and article information

                Contributors
                lena.obeidova@gmail.com
                tomas.seeman@lfmotol.cuni.cz
                velisakova@post.cz
                JReiterova@seznam.cz
                Alena.puchmajerova@lfmotol.cuni.cz
                jstek@lf1.cuni.cz
                Journal
                BMC Med Genet
                BMC Med. Genet
                BMC Medical Genetics
                BioMed Central (London )
                1471-2350
                22 December 2015
                22 December 2015
                2015
                : 16
                : 116
                Affiliations
                [ ]Institute of Biology and Medical Genetics of the First Faculty of Medicine, General University Hospital in Prague, Prague, Czech
                [ ]Department of Paediatrics, 2nd Faculty of Medicine, Charles University in Prague and Motol University Hospital, Prague, Czech
                [ ]Department of Nephrology, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech
                [ ]Department of Biology and Medical Genetics, 2nd Faculty of Medicine, Charles University in Prague and Motol University Hospital, Prague, Czech
                Article
                261
                10.1186/s12881-015-0261-3
                4689053
                26695994
                cfe6db1f-c3cf-4290-9a50-d1aea8c2fb1e
                © Obeidova et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 13 May 2015
                : 11 December 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Genetics
                autosomal recessive polycystic kidney disease,arpkd,pkhd1,mutation analysis,next-generation sequencing

                Comments

                Comment on this article