Number of rare germline CNVs and <Emphasis Type="Italic">TP53</Emphasis> mutation types

Background

The Li-Fraumeni syndrome (LFS), an inherited rare cancer predisposition syndrome characterized by a variety of early-onset tumors, is caused by different highly penetrant germline mutations in the TP53 gene; each separate mutation has dissimilar functional and phenotypic effects, which partially clarifies the reported heterogeneity between LFS families. Increases in copy number variation (CNV) have been reported in TP53 mutated individuals, and are also postulated to contribute to LFS phenotypic variability. The Brazilian p.R337H TP53 mutation has particular functional and regulatory properties that differ from most other common LFS TP53 mutations, by conferring a strikingly milder phenotype.

Methods

We compared the CNV profiles of controls, and LFS individuals carrying either p.R337H or DNA binding domain (DBD) TP53 mutations by high resolution array-CGH.

Results

Although we did not find any significant difference in the frequency of CNVs between LFS patients and controls, our data indicated an increased proportion of rare CNVs per genome in patients carrying DBD mutations compared to both controls (p=0.0002***) and p.R337H (0.0156*) mutants.

Conclusions

The larger accumulation of rare CNVs in DBD mutants may contribute to the reported anticipation and severity of the syndrome; likewise the fact that p.R337H individuals do not present the same magnitude of rare CNV accumulation may also explain the maintenance of this mutation at relatively high frequency in some populations.

     

Genetic diagnosis of neurofibromatosis type 1: targeted next- generation sequencing with Multiple Ligation-Dependent Probe Amplification analysis

Background

Neurofibromatosis type 1 (NF1) is a dominantly inherited tumor predisposition syndrome that targets the peripheral nervous system. It is caused by mutations of the NF1 gene which serve as a negative regulator of the cellular Ras/MAPK (mitogen-activated protein kinases) signaling pathway. Owing to the complexity in some parts of clinical diagnoses and the need for better understanding of its molecular relationships, a genetic characterization of this disorder will be helpful in the clinical setting.

Methods

In this study, we present a customized targeted gene panel of NF1/KRAS/BRAF/p53 and SPRED1 genes combined with Multiple Ligation-Dependent Probe Amplification analysis for the NF1 mutation screening in a cohort of patients clinically suspected as NF1.

Results

In this study, we identified 73 NF1 mutations and two BRAF novel variants from 100 NF1 patients who were suspected as having NF1. These genetic alterations are heterogeneous and distribute in a complicated way without clustering in either cysteine–serine-rich domain or within the GAP-related domain. We also detected fifteen multi-exon deletions within the NF1 gene by MLPA Analysis.

Conclusions

Our results suggested that a genetic screening using a NGS panel with high coverage of Ras–signaling components combined with Multiple Ligation-Dependent Probe Amplification analysis will enable differential diagnosis of patients with overlapping clinical features.

     

<Emphasis Type="Italic">NIPTeR</Emphasis>: an R package for fast and accurate trisomy prediction in non-invasive prenatal testing

Background

Various algorithms have been developed to predict fetal trisomies using cell-free DNA in non-invasive prenatal testing (NIPT). As basis for prediction, a control group of non-trisomy samples is needed. Prediction accuracy is dependent on the characteristics of this group and can be improved by reducing variability between samples and by ensuring the control group is representative for the sample analyzed.

Results

NIPTeR is an open-source R Package that enables fast NIPT analysis and simple but flexible workflow creation, including variation reduction, trisomy prediction algorithms and quality control. This broad range of functions allows users to account for variability in NIPT data, calculate control group statistics and predict the presence of trisomies.

Conclusion

NIPTeR supports laboratories processing next-generation sequencing data for NIPT in assessing data quality and determining whether a fetal trisomy is present. NIPTeR is available under the GNU LGPL v3 license and can be freely downloaded from https://github.com/molgenis/NIPTeR or CRAN.

     

A comparative study of <Emphasis Type="Italic">k</Emphasis>-spectrum-based error correction methods for next-generation sequencing data analysis

Background

Innumerable opportunities for new genomic research have been stimulated by advancement in high-throughput next-generation sequencing (NGS). However, the pitfall of NGS data abundance is the complication of distinction between true biological variants and sequence error alterations during downstream analysis. Many error correction methods have been developed to correct erroneous NGS reads before further analysis, but independent evaluation of the impact of such dataset features as read length, genome size, and coverage depth on their performance is lacking. This comparative study aims to investigate the strength and weakness as well as limitations of some newest k-spectrum-based methods and to provide recommendations for users in selecting suitable methods with respect to specific NGS datasets.

Methods

Six k-spectrum-based methods, i.e., Reptile, Musket, Bless, Bloocoo, Lighter, and Trowel, were compared using six simulated sets of paired-end Illumina sequencing data. These NGS datasets varied in coverage depth (10× to 120×), read length (36 to 100 bp), and genome size (4.6 to 143 MB). Error Correction Evaluation Toolkit (ECET) was employed to derive a suite of metrics (i.e., true positives, false positive, false negative, recall, precision, gain, and F-score) for assessing the correction quality of each method.

Results

Results from computational experiments indicate that Musket had the best overall performance across the spectra of examined variants reflected in the six datasets. The lowest accuracy of Musket (F-score?=?0.81) occurred to a dataset with a medium read length (56 bp), a medium coverage (50×), and a small-sized genome (5.4 MB). The other five methods underperformed (F-score?<?0.80) and/or failed to process one or more datasets.

Conclusions

This study demonstrates that various factors such as coverage depth, read length, and genome size may influence performance of individual k-spectrum-based error correction methods. Thus, efforts have to be paid in choosing appropriate methods for error correction of specific NGS datasets. Based on our comparative study, we recommend Musket as the top choice because of its consistently superior performance across all six testing datasets. Further extensive studies are warranted to assess these methods using experimental datasets generated by NGS platforms (e.g., 454, SOLiD, and Ion Torrent) under more diversified parameter settings (k-mer values and edit distances) and to compare them against other non-k-spectrum-based classes of error correction methods.

     

High resolution chromosomal microarray analysis in paediatric obsessive-compulsive disorder

Background

Obsessive-Compulsive Disorder (OCD) is a common and chronic disorder in which a person has uncontrollable, reoccurring thoughts and behaviours. It is a complex genetic condition and, in case of early onset (EO), the patients manifest a more severe phenotype, and an increased heritability. Large (>500 kb) copy number variations (CNVs) previously associated with autism and schizophrenia have been reported in OCD. Recently, rare CNVs smaller than 500 kb overlapping risk loci for other neurodevelopmental conditions have also been reported in OCD, stressing the importance of examining CNVs of any size range. The aim of this study was to further investigate the role of rare and small CNVs in the aetiology of EO-OCD.

Methods

We performed high-resolution chromosomal microarray analysis in 121 paediatric OCD patients and in 124 random controls to identify rare CNVs (>50 kb) which might contribute to EO-OCD.

Results

The frequencies and the size of the observed rare CNVs in the patients did not differ from the controls. However, we observed a significantly higher frequency of rare CNVs affecting brain related genes, especially deletions, in the patients (OR?=?1.98, 95% CI 1.02–3.84; OR?=?3.61, 95% CI 1.14–11.41, respectively). Similarly, enrichment-analysis of CNVs gene content, performed with three independent methods, confirmed significant clustering of predefined genes involved in synaptic/brain related functional pathways in the patients but not in the controls. In two patients we detected de-novo CNVs encompassing genes previously associated with different neurodevelopmental disorders (NRXN1, ANKS1B, UHRF1BP1).

Conclusions

Our results further strengthen the role of small rare CNVs, particularly deletions, as susceptibility factors for paediatric OCD.

     

rDolphin: a GUI R package for proficient automatic profiling of 1D <Superscript>1</Superscript>H-NMR spectra of study datasets

Introduction

Adoption of automatic profiling tools for ¹H-NMR-based metabolomic studies still lags behind other approaches in the absence of the flexibility and interactivity necessary to adapt to the properties of study data sets of complex matrices.

Objectives

To provide an open source tool that fully integrates these needs and enables the reproducibility of the profiling process.

Methods

rDolphin incorporates novel techniques to optimize exploratory analysis, metabolite identification, and validation of profiling output quality.

Results

The information and quality achieved in two public datasets of complex matrices are maximized.

Conclusion

rDolphin is an open-source R package (http://github.com/danielcanueto/rDolphin) able to provide the best balance between accuracy, reproducibility and ease of use.

     

Metabolic response of porcine colon explants to in vitro infection by <Emphasis Type="Italic">Brachyspira hyodysenteriae</Emphasis>: a leap into disease pathophysiology

Introduction

Swine dysentery caused by Brachyspira hyodysenteriae is a production limiting disease in pig farming. Currently antimicrobial therapy is the only treatment and control method available.

Objective

The aim of this study was to characterize the metabolic response of porcine colon explants to infection by B. hyodysenteriae.

Methods

Porcine colon explants exposed to B. hyodysenteriae were analyzed for histopathological, metabolic and pro-inflammatory gene expression changes.

Results

Significant epithelial necrosis, increased levels of l-citrulline and IL-1α were observed on explants infected with B. hyodysenteriae.

Conclusions

The spirochete induces necrosis in vitro likely through an inflammatory process mediated by IL-1α and NO.

     

OptPipe - a pipeline for optimizing metabolic engineering targets

Background

We propose OptPipe - a Pipeline for Optimizing Metabolic Engineering Targets, based on a consensus approach. The method generates consensus hypotheses for metabolic engineering applications by combining several optimization solutions obtained from distinct algorithms. The solutions are ranked according to several objectives, such as biomass and target production, by using the rank product tests corrected for multiple comparisons.

Results

OptPipe was applied in a genome-scale model of Corynebacterium glutamicum for maximizing malonyl-CoA, which is a valuable precursor for many phenolic compounds. In vivo experimental validation confirmed increased malonyl-CoA level in case of ΔsdhCAB deletion, as predicted in silico.

Conclusions

A method was developed to combine the optimization solutions provided by common knockout prediction procedures and rank the suggested mutants according to the expected growth rate, production and a new adaptability measure. The implementation of the pipeline along with the complete documentation is freely available at https://github.com/AndrasHartmann/OptPipe.

     

Iridoid and phenylethanoid/phenylpropanoid metabolite profiles of <Emphasis Type="Italic">Scrophularia</Emphasis> and <Emphasis Type="Italic">Verbascum</Emphasis> species used medicinally in North America

Introduction

Botanicals containing iridoid and phenylethanoid/phenylpropanoid glycosides are used worldwide for the treatment of inflammatory musculoskeletal conditions that are primary causes of human years lived with disability, such as arthritis and lower back pain.

Objectives

We report the analysis of candidate anti-inflammatory metabolites of several endemic Scrophularia species and Verbascum thapsus used medicinally by peoples of North America.

Methods

Leaves, stems, and roots were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and partial least squares-discriminant analysis (PLS-DA) was performed in MetaboAnalyst 3.0 after processing the datasets in Progenesis QI.

Results

Comparison of the datasets revealed significant and differential accumulation of iridoid and phenylethanoid/phenylpropanoid glycosides in the tissues of the endemic Scrophularia species and Verbascum thapsus.

Conclusions

Our investigation identified several species of pharmacological interest as good sources for harpagoside and other important anti-inflammatory metabolites.

     

Modular and configurable optimal sequence alignment software: <Emphasis Type="Italic">Cola</Emphasis>

Background

The fundamental challenge in optimally aligning homologous sequences is to define a scoring scheme that best reflects the underlying biological processes. Maximising the overall number of matches in the alignment does not always reflect the patterns by which nucleotides mutate. Efficiently implemented algorithms that can be parameterised to accommodate more complex non-linear scoring schemes are thus desirable.

Results

We present Cola, alignment software that implements different optimal alignment algorithms, also allowing for scoring contiguous matches of nucleotides in a nonlinear manner. The latter places more emphasis on short, highly conserved motifs, and less on the surrounding nucleotides, which can be more diverged. To illustrate the differences, we report results from aligning 14,100 sequences from 3' untranslated regions of human genes to 25 of their mammalian counterparts, where we found that a nonlinear scoring scheme is more consistent than a linear scheme in detecting short, conserved motifs.

Conclusions

Cola is freely available under LPGL from https://github.com/nedaz/cola.

     

Whole exome sequencing of a single osteosarcoma case—integrative analysis with whole transcriptome RNA-seq data

Background

Osteosarcoma (OS) is a prevalent primary malignant bone tumour with unknown etiology. These highly metastasizing tumours are among the most frequent causes of cancer-related deaths. Thus, there is an urgent need for different markers, and with our study, we were aiming towards finding novel biomarkers for OS.

Methods

For that, we analysed the whole exome of the tumorous and non-tumour bone tissue from the same patient with OS applying next-generation sequencing. For data analysis, we used several softwares and combined the exome data with RNA-seq data from our previous study.

Results

In the tumour exome, we found wide genomic rearrangements, which should qualify as chromotripsis—we detected almost 3,000 somatic single nucleotide variants (SNVs) and small indels and more than 2,000 copy number variants (CNVs) in different chromosomes. Furthermore, the somatic changes seem to be associated to bone tumours, whereas germline mutations to cancer in general. We confirmed the previous findings that the most significant pathway involved in OS pathogenesis is probably the WNT/β-catenin signalling pathway. Also, the IGF1/IGF2 and IGF1R homodimer signalling and TP53 (including downstream tumour suppressor gene EI24) pathways may have a role. Additionally, the mucin family genes, especially MUC4 and cell cycle controlling gene CDC27 may be considered as potential biomarkers for OS.

Conclusions

The genes, in which the mutations were detected, may be considered as targets for finding biomarkers for OS. As the study is based on a single case and only DNA and RNA analysis, further confirmative studies are required.

     

Isolation and characterization of marine biofilm forming bacteria from a ship’s hull

Background

Diverse aquatic microorganisms are capable of colonizing living and non-living surfaces leading to the formation of biofilms. Commonly visualized as a slimy layer, these biofilms are filled with hundreds of other microorganisms compared to free living planktonic cells. Microbial surface colonization and surface-associated metabolic activities also exert several macroscale deleterious effects, including biofouling, biocorrosion and the persistence and transmission of harmful or pathogenic microorganisms and virulence determinants. The present study deals with the isolation and screening of marine bacteria for biofilm formation. The screened isolates were characterized and identified as Pychrobacter celer, Pychrobacter alimentarius and Kocuria rhizophila by 16S rRNA sequencing.

Methods

Biofilm forming bacteria were isolated by spread plate technique and subjected to screening by microtiter plate assay. The potent biofilm formers were identified by molecular characterization using 16S rRNA gene sequencing.

Results

Twelve bacterial isolates were obtained by pour plate technique and subjected to biofilm assay. Among the 12 isolates three isolates which showed maximum biofilm formation were subjected to molecular characterizationby 16S rRNA gene sequencing method. The isolates were identified as Pychrobacter celer, Pychrobacter alimentarius and Kocuria rhizophila. The EPS produced by the three biofilm forming bacteria was extracted and the protein and carbohydrate content determined.

Conclusion

Among the isolates screened, isolate 8 (Kocuria rhizophila) produced maximum protein and carbohydrate which was also in accordance with the results of microtiter plate assay.

     

The bacterial community associated with rose-scented geranium (<Emphasis Type="Italic">Pelargonium graveolens</Emphasis>) leaves responds to anthracnose symptoms

Background

The fungus Colletotrichum is a plant pathogen that causes the anthracnose disease, resulting in huge losses in various crops including the rose-scented geranium (Pelargonium graveolens). Although the bacterial community associated with plants has an important role in the establishment of plant diseases, little is known about what happens in P. graveolens.

Aims

To increase the knowledge about the bacterial community associated with P. graveolens and its relationship with anthracnose disease symptoms.

Methods

Quantitative PCR and high-throughput sequencing were combined to determine the presence of the fungus Colletotrichum and to reveal the bacterial communities associated with different plant parts – root, stem and leaf – and in the rhizosphere and bulk soil, and also to determine the respective bacterial communities associated with P. graveolens leaves symptomatic and asymptomatic for anthracnose disease.

Results

The fungus Colletotrichum was detected in all plant parts and in the surrounding soil. Bacterial communities varied spatially in plants, and the disease symptoms also influenced the composition of the bacterial community. Abundances of operational taxonomic units (OTUs) assigned to the phylum Actinobacteria and to the genus Streptococcus were greatly increased in asymptomatic leaves.

Conclusions

The bacterial community associated to geranium leaves responds to anthracnose symptoms.

     

Strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens

Background

Noninvasive prenatal screening (NIPS) of common aneuploidies using cell-free DNA from maternal plasma is part of routine prenatal care and is widely used in both high-risk and low-risk patient populations. High specificity is needed for clinically acceptable positive predictive values. Maternal copy-number variants (mCNVs) have been reported as a source of false-positive aneuploidy results that compromises specificity.

Methods

We surveyed the mCNV landscape in 87,255 patients undergoing NIPS. We evaluated both previously reported and novel algorithmic strategies for mitigating the effects of mCNVs on the screen’s specificity. Further, we analyzed the frequency, length, and positional distribution of CNVs in our large dataset to investigate the curation of novel fetal microdeletions, which can be identified by NIPS but are challenging to interpret clinically.

Results

mCNVs are common, with 65% of expecting mothers harboring an autosomal CNV spanning more than 200 kb, underscoring the need for robust NIPS analysis strategies. By analyzing empirical and simulated data, we found that general, outlier-robust strategies reduce the rate of mCNV-caused false positives but not as appreciably as algorithms specifically designed to account for mCNVs. We demonstrate that large-scale tabulation of CNVs identified via routine NIPS could be clinically useful: together with the gene density of a putative microdeletion region, we show that the region’s relative tolerance to duplications versus deletions may aid the interpretation of microdeletion pathogenicity.

Conclusions

Our study thoroughly investigates a common source of NIPS false positives and demonstrates how to bypass its corrupting effects. Our findings offer insight into the interpretation of NIPS results and inform the design of NIPS algorithms suitable for use in screening in the general obstetric population.

     

Role of <Emphasis Type="Italic">PUF60</Emphasis> gene in Verheij syndrome: a case report of the first Chinese Han patient with a de novo pathogenic variant and review of the literature

Background

Verheij syndrome is a rare microdeletion syndrome of chromosome 8q24.3 that harbors PUF60, SCRIB, and NRBP2 genes. Subsequently, loss of function mutations in PUF60 have been found in children with clinical features significantly overlapping with Verheij.

Case presentation

Here we present the first Chinese Han patient with a de novo nonsense variant (c.1357C?>?T, p.Gln453*) in PUF60 by clinical whole exome sequencing. The 5-year-old boy presents with dysmorphic facial features, intellectual disability, and growth retardation but without apparent cardiac, renal, ocular, and spinal anomalies.

Conclusions

Our finding contributes to the understanding of the genotype and phenotype in PUF60 related disorder.

     

Targeted next generation sequencing identifies novel NOTCH3 gene mutations in CADASIL diagnostics patients

Background

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a monogenic, hereditary, small vessel disease of the brain causing stroke and vascular dementia in adults. CADASIL has previously been shown to be caused by varying mutations in the NOTCH3 gene. The disorder is often misdiagnosed due to its significant clinical heterogeneic manifestation with familial hemiplegic migraine and several ataxia disorders as well as the location of the currently identified causative mutations. The aim of this study was to develop a new, comprehensive and efficient single assay strategy for complete molecular diagnosis of NOTCH3 mutations through the use of a custom next-generation sequencing (NGS) panel for improved routine clinical molecular diagnostic testing.

Results

Our custom NGS panel identified nine genetic variants in NOTCH3 (p.D139V, p.C183R, p.R332C, p.Y465C, p.C597W, p.R607H, p.E813E, p.C977G and p.Y1106C). Six mutations were stereotypical CADASIL mutations leading to an odd number of cysteine residues in one of the 34 NOTCH3 gene epidermal growth factor (EGF)-like repeats, including three new typical cysteine mutations identified in exon 11 (p.C597W; c.1791C>G); exon 18 (p.C977G; c.2929T>G) and exon 20 (p.Y1106C; c.3317A>G). Interestingly, a novel missense mutation in the CACNA1A gene was also identified in one CADASIL patient. All variants identified (novel and known) were further investigated using in silico bioinformatic analyses and confirmed through Sanger sequencing.

Conclusions

NGS provides an improved and effective methodology for the diagnosis of CADASIL. The NGS approach reduced time and cost for comprehensive genetic diagnosis, placing genetic diagnostic testing within reach of more patients.

     

Does centrifugation matter? Centrifugal force and spinning time alter the plasma metabolome

Background

Centrifugation is an indispensable procedure for plasma sample preparation, but applied conditions can vary between labs.

Aim

Determine whether routinely used plasma centrifugation protocols (1500×g 10 min; 3000×g 5 min) influence non-targeted metabolomic analyses.

Methods

Nuclear magnetic resonance spectroscopy (NMR) and High Resolution Mass Spectrometry (HRMS) data were evaluated with sparse partial least squares discriminant analyses and compared with cell count measurements.

Results

Besides significant differences in platelet count, we identified substantial alterations in NMR and HRMS data related to the different centrifugation protocols.

Conclusion

Already minor differences in plasma centrifugation can significantly influence metabolomic patterns and potentially bias metabolomics studies.

     

NormalizeMets: assessing,selecting and implementing statistical methods for normalizing metabolomics data

Introduction

In metabolomics studies, unwanted variation inevitably arises from various sources. Normalization, that is the removal of unwanted variation, is an essential step in the statistical analysis of metabolomics data. However, metabolomics normalization is often considered an imprecise science due to the diverse sources of variation and the availability of a number of alternative strategies that may be implemented.

Objectives

We highlight the need for comparative evaluation of different normalization methods and present software strategies to help ease this task for both data-oriented and biological researchers.

Methods

We present NormalizeMets—a joint graphical user interface within the familiar Microsoft Excel and freely-available R software for comparative evaluation of different normalization methods. The NormalizeMets R package along with the vignette describing the workflow can be downloaded from https://cran.r-project.org/web/packages/NormalizeMets/. The Excel Interface and the Excel user guide are available on https://metabolomicstats.github.io/ExNormalizeMets.

Results

NormalizeMets allows for comparative evaluation of normalization methods using criteria that depend on the given dataset and the ultimate research question. Hence it guides researchers to assess, select and implement a suitable normalization method using either the familiar Microsoft Excel and/or freely-available R software. In addition, the package can be used for visualisation of metabolomics data using interactive graphical displays and to obtain end statistical results for clustering, classification, biomarker identification adjusting for confounding variables, and correlation analysis.

Conclusion

NormalizeMets is designed for comparative evaluation of normalization methods, and can also be used to obtain end statistical results. The use of freely-available R software offers an attractive proposition for programming-oriented researchers, and the Excel interface offers a familiar alternative to most biological researchers. The package handles the data locally in the user’s own computer allowing for reproducible code to be stored locally.