Entropy of complex relevant components of Boolean networks

Boolean network models of strongly connected modules are capable of capturing the high regulatory complexity of many biological gene regulatory circuits. We study numerically the previously introduced basin entropy, a parameter for the dynamical uncertainty or information storage capacity of a network as well as the average transient time in random relevant components as a function of their connectivity. We also demonstrate that basin entropy can be estimated from time-series data and is therefore also applicable to non-deterministic networks models.Comment: 8 pages, 6 figure

The allele distribution in next-generation sequencing data sets is accurately described as the result of a stochastic branching process

With the availability of next-generation sequencing (NGS) technology, it is expected that sequence variants may be called on a genomic scale. Here, we demonstrate that a deeper understanding of the distribution of the variant call frequencies at heterozygous loci in NGS data sets is a prerequisite for sensitive variant detection. We model the crucial steps in an NGS protocol as a stochastic branching process and derive a mathematical framework for the expected distribution of alleles at heterozygous loci before measurement that is sequencing. We confirm our theoretical results by analyzing technical replicates of human exome data and demonstrate that the variance of allele frequencies at heterozygous loci is higher than expected by a simple binomial distribution. Due to this high variance, mutation callers relying on binomial distributed priors are less sensitive for heterozygous variants that deviate strongly from the expected mean frequency. Our results also indicate that error rates can be reduced to a greater degree by technical replicates than by increasing sequencing depth

Significantly different clinical phenotypes associated with mutations in synthesis and transamidase+remodeling glycosylphosphatidylinositol (GPI)-anchor biosynthesis genes.

BACKGROUND: Defects in the glycosylphosphatidylinositol (GPI) biosynthesis pathway can result in a group of congenital disorders of glycosylation known as the inherited GPI deficiencies (IGDs). To date, defects in 22 of the 29 genes in the GPI biosynthesis pathway have been identified in IGDs. The early phase of the biosynthetic pathway assembles the GPI anchor (Synthesis stage) and the late phase transfers the GPI anchor to a nascent peptide in the endoplasmic reticulum (ER) (Transamidase stage), stabilizes the anchor in the ER membrane using fatty acid remodeling and then traffics the GPI-anchored protein to the cell surface (Remodeling stage). RESULTS: We addressed the hypothesis that disease-associated variants in either the Synthesis stage or Transamidase+Remodeling-stage GPI pathway genes have distinct phenotypic spectra. We reviewed clinical data from 58 publications describing 152 individual patients and encoded the phenotypic information using the Human Phenotype Ontology (HPO). We showed statistically significant differences between the Synthesis and Transamidase+Remodeling Groups in the frequencies of phenotypes in the musculoskeletal system, cleft palate, nose phenotypes, and cognitive disability. Finally, we hypothesized that phenotypic defects in the IGDs are likely to be at least partially related to defective GPI anchoring of their target proteins. Twenty-two of one hundred forty-two proteins that receive a GPI anchor are associated with one or more Mendelian diseases and 12 show some phenotypic overlap with the IGDs, represented by 34 HPO terms. Interestingly, GPC3 and GPC6, members of the glypican family of heparan sulfate proteoglycans bound to the plasma membrane through a covalent GPI linkage, are associated with 25 of these phenotypic abnormalities. CONCLUSIONS: IGDs associated with Synthesis and Transamidase+Remodeling stages of the GPI biosynthesis pathway have significantly different phenotypic spectra. GPC2 and GPC6 genes may represent a GPI target of general disruption to the GPI biosynthesis pathway that contributes to the phenotypes of some IGDs

Juvenile arthritis caused by a novel FAMIN (LACC1) mutation in two children with systemic and extended oligoarticular course

Background The pathophysiological origin of juvenile idiopathic arthritis (JIA) is largely unknown. However, individuals with presumably pathogenic mutations in FAMIN have been reported, associating this gene with a rare subtype of this disorder. FAMIN, that is formerly also referred to as LACC1 or C13orf31, has recently been shown to play a crucial role in immune-metabolic functions and is involved in regulation of inflammasome activation and promotion of ROS production. Case presentation We describe two siblings with severe familial forms of juvenile arthritis in which whole-exome-sequencing revealed a novel homozygous frameshift mutation (NM_153218.2:c.827delC¸. p.(T276fs*2) in FAMIN. Conclusions The observation of a new deleterious mutation adds further evidence that pathogenic mutations in FAMIN are causal for a monogenic form of JIA. Furthermore the associated phenotype is not restricted to systemic JIA, but can also be found in other forms of familial juvenile arthritis

Combining callers improves the detection of copy number variants from whole-genome sequencing

Copy Number Variants (CNVs) are deletions, duplications or insertions larger than 50 base pairs. They account for a large percentage of the normal genome variation and play major roles in human pathology. While array-based approaches have long been used to detect them in clinical practice, whole-genome sequencing (WGS) bears the promise to allow concomitant exploration of CNVs and smaller variants. However, accurately calling CNVs from WGS remains a difficult computational task, for which a consensus is still lacking. In this paper, we explore practical calling options to reach the best compromise between sensitivity and sensibility. We show that callers based on different signal (paired-end reads, split reads, coverage depth) yield complementary results. We suggest approaches combining four selected callers (Manta, Delly, ERDS, CNVnator) and a regenotyping tool (SV2), and show that this is applicable in everyday practice in terms of computation time and further interpretation. We demonstrate the superiority of these approaches over array-based Comparative Genomic Hybridization (aCGH), specifically regarding the lack of resolution in breakpoint definition and the detection of potentially relevant CNVs. Finally, we confirm our results on the NA12878 benchmark genome, as well as one clinically validated sample. In conclusion, we suggest that WGS constitutes a timely and economically valid alternative to the combination of aCGH and whole-exome sequencing

Molecular mechanism of CHRDL1-mediated X-linked megalocornea in humans and in Xenopus model

Chordin-Like 1 (CHRDL1) mutations cause non-syndromic X-linked megalocornea (XMC) characterized by enlarged anterior eye segments. Mosaic corneal degeneration, presenile cataract and secondary glaucoma are associated with XMC. Beside that CHRDL1 encodes Ventroptin, a secreted bone morphogenetic protein (BMP) antagonist, the molecular mechanism of XMC is not well understood yet. In a family with broad phenotypic variability of XMC, we identified the novel CHRDL1 frameshift mutation c.807_808delTC [p.H270Wfs*22] presumably causing CHRDL1 loss of function. Using Xenopus laevis as model organism, we demonstrate that chrdl1 is specifically expressed in the ocular tissue at late developmental stages. The chrdl1 knockdown directly resembles the human XMC phenotype and confirms CHRDL1 deficiency to cause XMC. Interestingly, secondary to this bmp4 is down-regulated in the Xenopus eyes. Moreover, phospho-SMAD1/5 is altered and BMP receptor 1A is reduced in a XMC patient. Together, we classify these observations as negative-feedback regulation due to the deficient BMP antagonism in XMC. As CHRDL1 is preferentially expressed in the limbal stem cell niche of adult human cornea, we assume that CHRDL1 plays a key role in cornea homeostasis. In conclusion, we provide novel insights into the molecular mechanism of XMC as well as into the specific role of CHRDL1 during cornea organogenesis, among others by the establishment of the first XMC in vivo model. We show that unravelling monogenic cornea disorders like XMC—with presumably disturbed cornea growth and differentiation—contribute to the identification of potential limbal stem cell niche factors that are promising targets for regenerative therapies of corneal injurie

AI-based multi-PRS models outperform classical single-PRS models

Polygenic risk scores (PRS) calculate the risk for a specific disease based on the weighted sum of associated alleles from different genetic loci in the germline estimated by regression models. Recent advances in genetics made it possible to create polygenic predictors of complex human traits, including risks for many important complex diseases, such as cancer, diabetes, or cardiovascular diseases, typically influenced by many genetic variants, each of which has a negligible effect on overall risk. In the current study, we analyzed whether adding additional PRS from other diseases to the prediction models and replacing the regressions with machine learning models can improve overall predictive performance. Results showed that multi-PRS models outperform single-PRS models significantly on different diseases. Moreover, replacing regression models with machine learning models, i.e., deep learning, can also improve overall accuracy