David Salgado

The king cobra genome reveals dynamic gene evolution and adaptation in the snake venom system

Significance Snake venoms are toxic protein cocktails used for prey capture. To investigate the evolution of these complex biological weapon systems, we sequenced the genome of a venomous snake, the king cobra, and assessed the composition of venom gland expressed genes, small RNAs, and secreted venom proteins. We show that regulatory components of the venom secretory system may have evolved from a pancreatic origin and that venom toxin genes were co-opted by distinct genomic mechanisms. After co-option, toxin genes important for prey capture have massively expanded by gene duplication and evolved under positive selection, resulting in protein neofunctionalization. This diverse and dramatic venom-related genomic response seemingly occurs in response to a coevolutionary arms race between venomous snakes and their prey. Snakes are limbless predators, and many species use venom to help overpower relatively large, agile prey. Snake venoms are complex protein mixtures encoded by several multilocus gene families that function synergistically to cause incapacitation. To examine venom evolution, we sequenced and interrogated the genome of a venomous snake, the king cobra (Ophiophagus hannah), and compared it, together with our unique transcriptome, microRNA, and proteome datasets from this species, with data from other vertebrates. In contrast to the platypus, the only other venomous vertebrate with a sequenced genome, we find that snake toxin genes evolve through several distinct co-option mechanisms and exhibit surprisingly variable levels of gene duplication and directional selection that correlate with their functional importance in prey capture. The enigmatic accessory venom gland shows a very different pattern of toxin gene expression from the main venom gland and seems to have recruited toxin-like lectin genes repeatedly for new nontoxic functions. In addition, tissue-specific microRNA analyses suggested the co-option of core genetic regulatory components of the venom secretory system from a pancreatic origin. Although the king cobra is limbless, we recovered coding sequences for all Hox genes involved in amniote limb development, with the exception of Hoxd12. Our results provide a unique view of the origin and evolution of snake venom and reveal multiple genome-level adaptive responses to natural selection in this complex biological weapon system. More generally, they provide insight into mechanisms of protein evolution under strong selection.

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

BackgroundDetermining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them.ResultsA total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthews Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89% and the best AUC iP/R was 68%. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53%, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35%) the macro-averaged precision ranged between 50% and 80%, with a maximum F-Score of 55%.ConclusionsThe results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging. Nevertheless, text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results. Detecting associations between full text articles and interaction detection method PSI-MI terms (IMT) is more difficult than might be anticipated. This is due to the variability of method term mentions, errors resulting from pre-processing of articles provided as PDF files, and the heterogeneity and different granularity of method term concepts encountered in the ontology. However, combining the sophisticated techniques developed by the participants with supporting evidence strings derived from the articles for human interpretation could result in practical modules for biological annotation workflows.

Neural crest regulates myogenesis through the transient activation of NOTCH

How dynamic signalling and extensive tissue rearrangements interact to generate complex patterns and shapes during embryogenesis is poorly understood. Here we characterize the signalling events taking place during early morphogenesis of chick skeletal muscles. We show that muscle progenitors present in somites require the transient activation of NOTCH signalling to undergo terminal differentiation. The NOTCH ligand Delta1 is expressed in a mosaic pattern in neural crest cells that migrate past the somites. Gain and loss of Delta1 function in neural crest modifies NOTCH signalling in somites, which results in delayed or premature myogenesis. Our results indicate that the neural crest regulates early muscle formation by a unique mechanism that relies on the migration of Delta1-expressing neural crest cells to trigger the transient activation of NOTCH signalling in selected muscle progenitors. This dynamic signalling guarantees a balanced and progressive differentiation of the muscle progenitor pool.

The ANISEED database: Digital representation, formalization, and elucidation of a chordate developmental program

Developmental biology aims to understand how the dynamics of embryonic shapes and organ functions are encoded in linear DNA molecules. Thanks to recent progress in genomics and imaging technologies, systemic approaches are now used in parallel with small-scale studies to establish links between genomic information and phenotypes, often described at the subcellular level. Current model organism databases, however, do not integrate heterogeneous data sets at different scales into a global view of the developmental program. Here, we present a novel, generic digital system, NISEED, and its implementation, ANISEED, to ascidians, which are invertebrate chordates suitable for developmental systems biology approaches. ANISEED hosts an unprecedented combination of anatomical and molecular data on ascidian development. This includes the first detailed anatomical ontologies for these embryos, and quantitative geometrical descriptions of developing cells obtained from reconstructed three-dimensional (3D) embryos up to the gastrula stages. Fully annotated gene model sets are linked to 30,000 high-resolution spatial gene expression patterns in wild-type and experimentally manipulated conditions and to 528 experimentally validated cis-regulatory regions imported from specialized databases or extracted from 160 literature articles. This highly structured data set can be explored via a Developmental Browser, a Genome Browser, and a 3D Virtual Embryo module. We show how integration of heterogeneous data in ANISEED can provide a system-level understanding of the developmental program through the automatic inference of gene regulatory interactions, the identification of inducing signals, and the discovery and explanation of novel asymmetric divisions.

Minimum information specification for in situ hybridization and immunohistochemistry experiments (MISFISHIE)

One purpose of the biomedical literature is to report results in sufficient detail that the methods of data collection and analysis can be independently replicated and verified. Here we present reporting guidelines for gene expression localization experiments: the minimum information specification for in situ hybridization and immunohistochemistry experiments (MISFISHIE). MISFISHIE is modeled after the Minimum Information About a Microarray Experiment (MIAME) specification for microarray experiments. Both guidelines define what information should be reported without dictating a format for encoding that information. MISFISHIE describes six types of information to be provided for each experiment: experimental design, biomaterials and treatments, reporters, staining, imaging data and image characterizations. This specification has benefited the consortium within which it was developed and is expected to benefit the wider research community. We welcome feedback from the scientific community to help improve our proposal.

The TREAT‐NMD Duchenne Muscular Dystrophy Registries: Conception, Design, and Utilization by Industry and Academia

Duchenne muscular dystrophy (DMD) is an X‐linked genetic disease, caused by the absence of the dystrophin protein. Although many novel therapies are under development for DMD, there is currently no cure and affected individuals are often confined to a wheelchair by their teens and die in their twenties/thirties. DMD is a rare disease (prevalence <5/10,000). Even the largest countries do not have enough affected patients to rigorously assess novel therapies, unravel genetic complexities, and determine patient outcomes. TREAT‐NMD is a worldwide network for neuromuscular diseases that provides an infrastructure to support the delivery of promising new therapies for patients. The harmonized implementation of national and ultimately global patient registries has been central to the success of TREAT‐NMD. For the DMD registries within TREAT‐NMD, individual countries have chosen to collect patient information in the form of standardized patient registries to increase the overall patient population on which clinical outcomes and new technologies can be assessed. The registries comprise more than 13,500 patients from 31 different countries. Here, we describe how the TREAT‐NMD national patient registries for DMD were established. We look at their continued growth and assess how successful they have been at fostering collaboration between academia, patient organizations, and industry.

BioCreative III interactive task: an overview

BackgroundThe BioCreative challenge evaluation is a community-wide effort for evaluating text mining and information extraction systems applied to the biological domain. The biocurator community, as an active user of biomedical literature, provides a diverse and engaged end user group for text mining tools. Earlier BioCreative challenges involved many text mining teams in developing basic capabilities relevant to biological curation, but they did not address the issues of system usage, insertion into the workflow and adoption by curators. Thus in BioCreative III (BC-III), the InterActive Task (IAT) was introduced to address the utility and usability of text mining tools for real-life biocuration tasks. To support the aims of the IAT in BC-III, involvement of both developers and end users was solicited, and the development of a user interface to address the tasks interactively was requested.ResultsA User Advisory Group (UAG) actively participated in the IAT design and assessment. The task focused on gene normalization (identifying gene mentions in the article and linking these genes to standard database identifiers), gene ranking based on the overall importance of each gene mentioned in the article, and gene-oriented document retrieval (identifying full text papers relevant to a selected gene). Six systems participated and all processed and displayed the same set of articles. The articles were selected based on content known to be problematic for curation, such as ambiguity of gene names, coverage of multiple genes and species, or introduction of a new gene name. Members of the UAG curated three articles for training and assessment purposes, and each member was assigned a system to review. A questionnaire related to the interface usability and task performance (as measured by precision and recall) was answered after systems were used to curate articles. Although the limited number of articles analyzed and users involved in the IAT experiment precluded rigorous quantitative analysis of the results, a qualitative analysis provided valuable insight into some of the problems encountered by users when using the systems. The overall assessment indicates that the system usability features appealed to most users, but the system performance was suboptimal (mainly due to low accuracy in gene normalization). Some of the issues included failure of species identification and gene name ambiguity in the gene normalization task leading to an extensive list of gene identifiers to review, which, in some cases, did not contain the relevant genes. The document retrieval suffered from the same shortfalls. The UAG favored achieving high performance (measured by precision and recall), but strongly recommended the addition of features that facilitate the identification of correct gene and its identifier, such as contextual information to assist in disambiguation.DiscussionThe IAT was an informative exercise that advanced the dialog between curators and developers and increased the appreciation of challenges faced by each group. A major conclusion was that the intended users should be actively involved in every phase of software development, and this will be strongly encouraged in future tasks. The IAT Task provides the first steps toward the definition of metrics and functional requirements that are necessary for designing a formal evaluation of interactive curation systems in the BioCreative IV challenge.

Overview of the interactive task in BioCreative V

Fully automated text mining (TM) systems promote efficient literature searching, retrieval, and review but are not sufficient to produce ready-to-consume curated documents. These systems are not meant to replace biocurators, but instead to assist them in one or more literature curation steps. To do so, the user interface is an important aspect that needs to be considered for tool adoption. The BioCreative Interactive task (IAT) is a track designed for exploring user-system interactions, promoting development of useful TM tools, and providing a communication channel between the biocuration and the TM communities. In BioCreative V, the IAT track followed a format similar to previous interactive tracks, where the utility and usability of TM tools, as well as the generation of use cases, have been the focal points. The proposed curation tasks are user-centric and formally evaluated by biocurators. In BioCreative V IAT, seven TM systems and 43 biocurators participated. Two levels of user participation were offered to broaden curator involvement and obtain more feedback on usability aspects. The full level participation involved training on the system, curation of a set of documents with and without TM assistance, tracking of time-on-task, and completion of a user survey. The partial level participation was designed to focus on usability aspects of the interface and not the performance per se. In this case, biocurators navigated the system by performing pre-designed tasks and then were asked whether they were able to achieve the task and the level of difficulty in completing the task. In this manuscript, we describe the development of the interactive task, from planning to execution and discuss major findings for the systems tested. Database URL: http://www.biocreative.org

UMD-Predictor: A High-Throughput Sequencing Compliant System for Pathogenicity Prediction of any Human cDNA Substitution

Whole‐exome sequencing (WES) is increasingly applied to research and clinical diagnosis of human diseases. It typically results in large amounts of genetic variations. Depending on the mode of inheritance, only one or two correspond to pathogenic mutations responsible for the disease and present in affected individuals. Therefore, it is crucial to filter out nonpathogenic variants and limit downstream analysis to a handful of candidate mutations. We have developed a new computational combinatorial system UMD‐Predictor (http://umd‐predictor.eu) to efficiently annotate cDNA substitutions of all human transcripts for their potential pathogenicity. It combines biochemical properties, impact on splicing signals, localization in protein domains, variation frequency in the global population, and conservation through the BLOSUM62 global substitution matrix and a protein‐specific conservation among 100 species. We compared its accuracy with the seven most used and reliable prediction tools, using the largest reference variation datasets including more than 140,000 annotated variations. This system consistently demonstrated a better accuracy, specificity, Matthews correlation coefficient, diagnostic odds ratio, speed, and provided the shortest list of candidate mutations for WES. Webservices allow its implementation in any bioinformatics pipeline for next‐generation sequencing analysis. It could benefit to a wide range of users and applications varying from gene discovery to clinical diagnosis.

A mutation in the Gardos channel is associated with hereditary xerocytosis

The Gardos channel is a Ca(2+)-sensitive, intermediate conductance, potassium selective channel expressed in several tissues including erythrocytes and pancreas. In normal erythrocytes, it is involved in cell volume modification. Here, we report the identification of a dominantly inherited mutation in the Gardos channel in 2 unrelated families and its association with chronic hemolysis and dehydrated cells, also referred to as hereditary xerocytosis (HX). The affected individuals present chronic anemia that varies in severity. Their red cells exhibit a panel of various shape abnormalities such as elliptocytes, hemighosts, schizocytes, and very rare stomatocytic cells. The missense mutation concerns a highly conserved residue among species, located in the region interacting with Calmodulin and responsible for the channel opening and the K(+) efflux. Using 2-microelectrode experiments on Xenopus oocytes and patch-clamp electrophysiology on HEK293 cells, we demonstrated that the mutated channel exhibits a higher activity and a higher Ca(2+) sensitivity compared with the wild-type (WT) channel. The mutated channel remains sensitive to inhibition suggesting that treatment of this type of HX by a specific inhibitor of the Gardos channel could be considered. The identification of a KCNN4 mutation associated with chronic hemolysis constitutes the first report of a human disease caused by a defect of the Gardos channel.