Batch alignment via retention orders for preprocessing large-scale multi-batch LC-MS experiments.

MOTIVATION: Meticulous selection of chromatographic peak detection parameters and algorithms is a crucial step in preprocessing liquid chromatography-mass spectrometry (LC-MS) data. However, as mass-to-charge ratio and retention time shifts are larger between batches than within batches, finding apt parameters for all samples of a large-scale multi-batch experiment with the aim of minimizing information loss becomes a challenging task. Preprocessing independent batches individually can curtail said problems but requires a method for aligning and combining them for further downstream analysis. RESULTS: We present two methods for aligning and combining individually preprocessed batches in multi-batch LC-MS experiments. Our developed methods were tested on six sets of simulated and six sets of real datasets. Furthermore, by estimating the probabilities of peak insertion, deletion and swap between batches in authentic datasets, we demonstrate that retention order swaps are not rare in untargeted LC-MS data. AVAILABILITY AND IMPLEMENTATION: kmersAlignment and rtcorrectedAlignment algorithms are made available as an R package with raw data at https://metabocombiner.img.cas.cz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Semantic clustering analysis of E3-ubiquitin ligases in gastrointestinal tract defines genes ontology clusters with tissue expression patterns.

BACKGROUND: Ubiquitin ligases (Ub-ligases) are essential intracellular enzymes responsible for the regulation of proteome homeostasis, signaling pathway crosstalk, cell differentiation and stress responses. Individual Ub-ligases exhibit their unique functions based on the nature of their substrates. They create a complex regulatory network with alternative and feedback pathways to maintain cell homeostasis, being thus important players in many physiological and pathological conditions. However, the functional classification of Ub-ligases needs to be revised and extended. METHODS: In the current study, we used a novel semantic biclustering technique for expression profiling of Ub-ligases and ubiquitination-related genes in the murine gastrointestinal tract (GIT). We accommodated a general framework of the algorithm for finding tissue-specific gene expression clusters in GIT. In order to test identified clusters in a biological system, we used a model of epithelial regeneration. For this purpose, a dextran sulfate sodium (DSS) mouse model, following with in situ hybridization, was used to expose genes with possible compensatory features. To determine cell-type specific distribution of Ub-ligases and ubiquitination-related genes, principal component analysis (PCA) and Uniform Manifold Approximation and Projection technique (UMAP) were used to analyze the Tabula Muris scRNA-seq data of murine colon followed by comparison with our clustering results. RESULTS: Our established clustering protocol, that incorporates the semantic biclustering algorithm, demonstrated the potential to reveal interesting expression patterns. In this manner, we statistically defined gene clusters consisting of the same genes involved in distinct regulatory pathways vs distinct genes playing roles in functionally similar signaling pathways. This allowed us to uncover the potentially redundant features of GIT-specific Ub-ligases and ubiquitination-related genes. Testing the statistically obtained results on the mouse model showed that genes clustered to the same ontology group simultaneously alter their expression pattern after induced epithelial damage, illustrating their complementary role during tissue regeneration. CONCLUSIONS: An optimized semantic clustering protocol demonstrates the potential to reveal a readable and unique pattern in the expression profiling of GIT-specific Ub-ligases, exposing ontologically relevant gene clusters with potentially redundant features. This extends our knowledge of ontological relationships among Ub-ligases and ubiquitination-related genes, providing an alternative and more functional gene classification. In a similar way, semantic cluster analysis could be used for studding of other enzyme families, tissues and systems.

Posterior corneal vesicles are not associated with the genetic variants that cause posterior polymorphous corneal dystrophy.

PURPOSE: Posterior corneal vesicles (PCVs) have clinical features that are similar to posterior polymorphous corneal dystrophy (PPCD). To help determine whether there is a shared genetic basis, we screened 38 individuals with PCVs for changes in the three genes identified as causative for PPCD. METHODS: We prospectively recruited patients for this study. We examined all individuals clinically, with their first-degree relatives when available. We used a combination of Sanger and exome sequencing to screen regulatory regions of OVOL2 and GRHL2, and the entire ZEB1 coding sequence. RESULTS: The median age at examination was 37.5 years (range 4.7-84.0 years), 20 (53%) were male and in 19 (50%) the PCVs were unilateral. Most individuals were discharged to optometric review, but five had follow-up for a median of 12 years (range 5-13 years) with no evidence of progression. In cases with unilateral PCVs, there was statistically significant evidence that the change in the affected eye was associated with a lower endothelial cell density (p = 0.0003), greater central corneal thickness (p = 0.0277) and a steeper mean keratometry (p = 0.0034), but not with a higher keratometric astigmatism or a reduced LogMAR visual acuity. First-degree relatives of 13 individuals were available for examination, and in 3 (23%), PCVs were identified. No possibly pathogenic variants were identified in the PPCD-associated genes screened. CONCLUSION: We found no evidence that PCVs share the same genetic background as PPCD. In contrast to PPCD, we confirm that PCVs is a mild, non-progressive condition with no requirement for long-term review. However, subsequent cataract surgery can lead to corneal oedema.

Comprehensive phenotypic and functional analysis of dominant and recessive FOXE3 alleles in ocular developmental disorders.

The forkhead transcription factor FOXE3 is critical for vertebrate eye development. Recessive and dominant variants cause human ocular disease but the full range of phenotypes and mechanisms of action for the two classes of variants are unknown. We identified FOXE3 variants in individuals with congenital eye malformations and carried out in vitro functional analysis on selected alleles. Sixteen new recessive and dominant families, including six novel variants, were identified. Analysis of new and previously reported genetic and clinical data demonstrated a broad phenotypic range with an overlap between recessive and dominant disease. Most families with recessive alleles, composed of truncating and forkhead-domain missense variants, had severe corneal opacity (90%; sclerocornea in 47%), aphakia (83%) and microphthalmia (80%), but some had milder features including isolated cataract. The phenotype was most variable for recessive missense variants, suggesting that the functional consequences may be highly dependent on the type of amino acid substitution and its position. When assessed, aniridia or iris hypoplasia were noted in 89% and optic nerve anomalies in 60% of recessive cases, indicating that these defects are also common and may be underrecognized. In dominant pedigrees, caused by extension variants, normal eye size (96%), cataracts (99%) and variable anterior segment anomalies were seen in most, but some individuals had microphthalmia, aphakia or sclerocornea, more typical of recessive disease. Functional studies identified variable effects on the protein stability, DNA binding, nuclear localization and transcriptional activity for recessive FOXE3 variants, whereas dominant alleles showed severe impairment in all areas and dominant-negative characteristics.

Finding semantic patterns in omics data using concept rule learning with an ontology-based refinement operator.

BACKGROUND: Identification of non-trivial and meaningful patterns in omics data is one of the most important biological tasks. The patterns help to better understand biological systems and interpret experimental outcomes. A well-established method serving to explain such biological data is Gene Set Enrichment Analysis. However, this type of analysis is restricted to a specific type of evaluation. Abstracting from details, the analyst provides a sorted list of genes and ontological annotations of the individual genes; the method outputs a subset of ontological terms enriched in the gene list. Here, in contrary to enrichment analysis, we introduce a new tool/framework that allows for the induction of more complex patterns of 2-dimensional binary omics data. This extension allows to discover and describe semantically coherent biclusters. RESULTS: We present a new rapid method called sem1R that reveals interpretable hidden rules in omics data. These rules capture semantic differences between two classes: a target class as a collection of positive examples and a non-target class containing negative examples. The method is inspired by the CN2 rule learner and introduces a new refinement operator that exploits prior knowledge in the form of ontologies. In our work this knowledge serves to create accurate and interpretable rules. The novel refinement operator uses two reduction procedures: Redundant Generalization and Redundant Non-potential, both of which help to dramatically prune the rule space and consequently, speed-up the entire process of rule induction in comparison with the traditional refinement operator as is presented in CN2. CONCLUSIONS: Efficiency and effectivity of the novel refinement operator were tested on three real different gene expression datasets. Concretely, the Dresden Ovary Dataset, DISC, and m2816 were employed. The experiments show that the ontology-based refinement operator speeds-up the pattern induction drastically. The algorithm is written in C++ and is published as an R package available at http://github.com/fmalinka/sem1r.

Pseudodominant Nanophthalmos in a Roma Family Caused by a Novel PRSS56 Variant.

BACKGROUND: The aim of the study was to identify the molecular genetic cause of two different Mendelian traits with ocular involvement present in the members of a single consanguineous Czech Roma family. METHODS: We have performed ocular examination and review of medical records in two individuals diagnosed with nanophthalmos (proband and her father) and one individual followed for bilateral congenital cataract and microcornea (uncle of the proband). DNA of subjects with nanophthalmos was analysed by exome sequencing. Sanger sequencing was applied for targeted screening of potentially pathogenic variants and to follow segregation of identified variants within the family. RESULTS: A homozygous variant c.1509G>C; p.(Met503Ile), in PRSS56 was found in the two individuals affected with nanophthalmos. The change was absent from the gnomAD dataset, but two out of 118 control Roma individuals were also shown to be heterozygous carriers. Analysis of single nucleotide polymorphisms in linkage disequilibrium with the c.1509G>C in PRSS56 suggested a shared chromosomal segment. The nanophthalmos phenotype, characterized in detail in the younger individual, encompassed bilateral corneal steepening, retinal folds, buried optic head drusen, and restricted visual fields, but no signs of retinal dystrophy. A known pathogenic founder CTDP1 variant c.863+389C>T in a homozygous state was identified in the other family member confirming the suspected diagnosis of congenital cataracts, facial dysmorphism, and demyelinating neuropathy syndrome. CONCLUSIONS: Herein, we report the first occurrence of nanophthalmos in the Roma population. We have identified pseudodominant inheritance for this phenotype caused by a novel variant in PRSS56, representing a possible founder effect. Despite advances in genetic technologies such as exome sequencing, careful phenotype evaluation in patients from an isolated population, along with an awareness of population-specific founder effects, is necessary to ensure that accurate molecular diagnoses are made.

Brittle cornea syndrome: Disease-causing mutations in ZNF469 and two novel variants identified in a patient followed for 26 years.

AIMS: Brittle cornea syndrome (BCS) is a rare autosomal recessive disorder. The aim of this study was to review ZNF469 mutations associated with BCS type 1 to date and to describe an additional case of Czech/Polish background. METHODS: Whole genome sequencing was undertaken to identify the molecular genetic cause of disease in the proband. Sequence variants in ZNF469 previously reported as BCS type 1-causing were searched in the literature, manually curated and aligned to the reference sequence NM_001127464.2. RESULTS: The proband has been reviewed since childhood with progressive myopia and hearing loss. Aged 13 years had been diagnosed with Stickler syndrome. Aged 16.5 years, he developed acute hydrops in the left eye managed by corneal transplantation. At the age of 26, he experienced right corneal rupture after blunt trauma, also managed by grafting. He had a number of secondary complications and despite regular follow-up and timely management, the right eye became totally blind and the left eye had light perception at the last follow-up visit, aged 42. He was found to be a compound heterozygote for two novel mutations c.1705C>T; p.(Gln569*) and c.1402_1411del; p.(Pro468Alafs*31) in ZNF469. In total 22 disease-causing variants in ZNF469 have been identified, mainly in consanguineous families or endogamous populations. Only four probands, including the case described in the current study, harboured compound heterozygous mutations. CONCLUSION: BCS occurs very rarely in outbred populations which may cause diagnostic errors due to poor awareness of the disease. Investigation into the underlying molecular genetic cause in patients with connective tissue disorders may lead to a re-evaluation of their clinical diagnosis.

The utility of massively parallel sequencing for posterior polymorphous corneal dystrophy type 3 molecular diagnosis.

The aim of this study was to identify the molecular genetic cause of disease in posterior polymorphous corneal dystrophy (PPCD) probands of diverse origin and to assess the utility of massively parallel sequencing in the detection of ZEB1 mutations. We investigated a total of 12 families (five British, four Czech, one Slovak and two Swiss). Ten novel and two recurrent disease-causing mutations in ZEB1, were identified in probands by Sanger (n = 5), exome (n = 4) and genome (n = 3) sequencing. Sanger sequencing was used to confirm the mutations detected by massively parallel sequencing, and to perform segregation analysis. Genome sequencing revealed that one proband harboured a novel ∼0.34 Mb heterozygous de novo deletion spanning exons 1-7 and part of exon 8. Transcript analysis confirmed that the ZEB1 transcript is detectable in blood-derived RNA samples and that the disease-associated variant c.482-2A>G leads to aberrant pre-mRNA splicing. De novo mutations, which are a feature of PPCD3, were found in the current study with an incidence rate of at least 16.6%. In general, massively parallel sequencing is a time-efficient way to detect PPCD3-associated mutations and, importantly, genome sequencing enables the identification of full or partial heterozygous ZEB1 deletions that can evade detection by both Sanger and exome sequencing. These findings contribute to our understanding of PPCD3, for which currently, 49 pathogenic variants have been identified, all of which are predicted to be null alleles.

Semantic biclustering for finding local, interpretable and predictive expression patterns.

BACKGROUND: One of the major challenges in the analysis of gene expression data is to identify local patterns composed of genes showing coherent expression across subsets of experimental conditions. Such patterns may provide an understanding of underlying biological processes related to these conditions. This understanding can further be improved by providing concise characterizations of the genes and situations delimiting the pattern. RESULTS: We propose a method called semantic biclustering with the aim to detect interpretable rectangular patterns in binary data matrices. As usual in biclustering, we seek homogeneous submatrices, however, we also require that the included elements can be jointly described in terms of semantic annotations pertaining to both rows (genes) and columns (samples). To find such interpretable biclusters, we explore two strategies. The first endows an existing biclustering algorithm with the semantic ingredients. The other is based on rule and tree learning known from machine learning. CONCLUSIONS: The two alternatives are tested in experiments with two Drosophila melanogaster gene expression datasets. Both strategies are shown to detect sets of compact biclusters with semantic descriptions that also remain largely valid for unseen (testing) data. This desirable generalization aspect is more emphasized in the strategy stemming from conventional biclustering although this is traded off by the complexity of the descriptions (number of ontology terms employed), which, on the other hand, is lower for the alternative strategy.