A role of SCN9A in human epilepsies, as a cause of febrile seizures and as a potential modifier of Dravet syndrome

A follow-up study of a large Utah family with significant linkage to chromosome 2q24 led us to identify a new febrile seizure (FS) gene, SCN9A encoding Na(v)1.7. In 21 affected members, we uncovered a potential mutation in a highly conserved amino acid, p.N641Y, in the large cytoplasmic loop between transmembrane domains I and II that was absent from 586 ethnically matched population control chromosomes. To establish a functional role for this mutation in seizure susceptibility, we introduced the orthologous mutation into the murine Scn9a ortholog using targeted homologous recombination. Compared to wild-type mice, homozygous Scn9a(N641Y/N641Y) knockin mice exhibit significantly reduced thresholds to electrically induced clonic and tonic-clonic seizures, and increased corneal kindling acquisition rates. Together, these data strongly support the SCN9A p.N641Y mutation as disease-causing in this family. To confirm the role of SCN9A in FS, we analyzed a collection of 92 unrelated FS patients and identified additional highly conserved Na(v)1.7 missense variants in 5% of the patients. After one of these children with FS later developed Dravet syndrome (severe myoclonic epilepsy of infancy), we sequenced the SCN1A gene, a gene known to be associated with Dravet syndrome, and identified a heterozygous frameshift mutation. Subsequent analysis of 109 Dravet syndrome patients yielded nine Na(v)1.7 missense variants (8% of the patients), all in highly conserved amino acids. Six of these Dravet syndrome patients with SCN9A missense variants also harbored either missense or splice site SCN1A mutations and three had no SCN1A mutations. This study provides evidence for a role of SCN9A in human epilepsies, both as a cause of FS and as a partner with SCN1A mutations

Using a (Higher-Order) Magnus Method to Solve the Sturm-Liouville Problem

The main purpose of this paper is to describe techniques for the numerical solution of a Sturm-Liouville equation (in its Schrodinger form) by employing a Magnus expansion. With a suitable method to approximate the highly oscillatory integrals which appear in the Magnus series, high order schemes can be constructed. A method of order ten is presented. Even when the solution is highly-oscillatory, the scheme can accurately integrate the problem using stepsizes typically much larger than the solution "wavelength". This makes the method well suited to be applied in a shooting process to locate the eigenvalues of a boundary value problem

Representative transcript sets for evaluating a translational initiation sites predictor

<p>Abstract</p> <p>Background</p> <p>Translational initiation site (TIS) prediction is a very important and actively studied topic in bioinformatics. In order to complete a comparative analysis, it is desirable to have several benchmark data sets which can be used to test the effectiveness of different algorithms. An ideal benchmark data set should be reliable, representative and readily available. Preferably, proteins encoded by members of the data set should also be representative of the protein population actually expressed in cellular specimens.</p> <p>Results</p> <p>In this paper, we report a general algorithm for constructing a reliable sequence collection that only includes mRNA sequences whose corresponding protein products present an average profile of the general protein population of a given organism, with respect to three major structural parameters. Four representative transcript collections, each derived from a model organism, have been obtained following the algorithm we propose. Evaluation of these data sets shows that they are reasonable representations of the spectrum of proteins obtained from cellular proteomic studies. Six state-of-the-art predictors have been used to test the usefulness of the construction algorithm that we proposed. Comparative study which reports the predictors' performance on our data set as well as three other existing benchmark collections has demonstrated the actual merits of our data sets as benchmark testing collections.</p> <p>Conclusion</p> <p>The proposed data set construction algorithm has demonstrated its property of being a general and widely applicable scheme. Our comparison with published proteomic studies has shown that the expression of our data set of transcripts generates a polypeptide population that is representative of that obtained from evaluation of biological specimens. Our data set thus represents "real world" transcripts that will allow more accurate evaluation of algorithms dedicated to identification of TISs, as well as other translational regulatory motifs within mRNA sequences. The algorithm proposed by us aims at compiling a redundancy-free data set by removing redundant copies of homologous proteins. The existence of such data sets may be useful for conducting statistical analyses of protein sequence-structure relations. At the current stage, our approach's focus is to obtain an "average" protein data set for any particular organism without posing much selection bias. However, with the three major protein structural parameters deeply integrated into the scheme, it would be a trivial task to extend the current method for obtaining a more selective protein data set, which may facilitate the study of some particular protein structure.</p

CO2 wettability of seal and reservoir rocks and the implications for carbon geo-sequestration

We review the literature data published on the topic of CO2 wettability of storage and seal rocks. We first introduce the concept of wettability and explain why it is important in the context of carbon geo-sequestration (CGS) projects, and review how it is measured. This is done to raise awareness of this parameter in the CGS community, which, as we show later on in this text, may have a dramatic impact on structural and residual trapping of CO2. These two trapping mechanisms would be severely and negatively affected in case of CO2-wet storage and/or seal rock. Overall, at the current state of the art, a substantial amount of work has been completed, and we find that: 1. Sandstone and limestone, plus pure minerals such as quartz, calcite, feldspar, and mica are strongly water wet in a CO2-water system. 2. Oil-wet limestone, oil-wet quartz, or coal is intermediate wet or CO2 wet in a CO2-water system. 3. The contact angle alone is insufficient for predicting capillary pressures in reservoir or seal rocks. 4. The current contact angle data have a large uncertainty. 5. Solid theoretical understanding on a molecular level of rock-CO2-brine interactions is currently limited. 6. In an ideal scenario, all seal and storage rocks in CGS formations are tested for their CO2 wettability. 7. Achieving representative subsurface conditions (especially in terms of the rock surface) in the laboratory is of key importance but also very challenging

Re-Annotation Is an Essential Step in Systems Biology Modeling of Functional Genomics Data

One motivation of systems biology research is to understand gene functions and interactions from functional genomics data such as that derived from microarrays. Up-to-date structural and functional annotations of genes are an essential foundation of systems biology modeling. We propose that the first essential step in any systems biology modeling of functional genomics data, especially for species with recently sequenced genomes, is gene structural and functional re-annotation. To demonstrate the impact of such re-annotation, we structurally and functionally re-annotated a microarray developed, and previously used, as a tool for disease research. We quantified the impact of this re-annotation on the array based on the total numbers of structural- and functional-annotations, the Gene Annotation Quality (GAQ) score, and canonical pathway coverage. We next quantified the impact of re-annotation on systems biology modeling using a previously published experiment that used this microarray. We show that re-annotation improves the quantity and quality of structural- and functional-annotations, allows a more comprehensive Gene Ontology based modeling, and improves pathway coverage for both the whole array and a differentially expressed mRNA subset. Our results also demonstrate that re-annotation can result in a different knowledge outcome derived from previous published research findings. We propose that, because of this, re-annotation should be considered to be an essential first step for deriving value from functional genomics data

The UniProt-GO Annotation database in 2011

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360 000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set

The human phylome

The human phylome, which includes evolutionary relationships of all human proteins and their homologs among thirty-nine fully sequenced eukaryotes, is reconstructed

Perspectives on tracking data reuse across biodata resources

c The Author(s) 2024. Published by Oxford University Press.Motivation: Data reuse is a common and vital practice in molecular biology and enables the knowledge gathered over recent decades to drive discovery and innovation in the life sciences. Much of this knowledge has been collated into molecular biology databases, such as UniProtKB, and these resources derive enormous value from sharing data among themselves. However, quantifying and documenting this kind of data reuse remains a challenge. Results: The article reports on a one-day virtual workshop hosted by the UniProt Consortium in March 2023, attended by representatives from biodata resources, experts in data management, and NIH program managers. Workshop discussions focused on strategies for tracking data reuse, best practices for reusing data, and the challenges associated with data reuse and tracking. Surveys and discussions showed that data reuse is widespread, but critical information for reproducibility is sometimes lacking. Challenges include costs of tracking data reuse, tensions between tracking data and open sharing, restrictive licenses, and difficulties in tracking commercial data use. Recommendations that emerged from the discussion include: development of standardized formats for documenting data reuse, education about the obstacles posed by restrictive licenses, and continued recognition by funding agencies that data management is a critical activity that requires dedicated resources