Models of Somatic Hypermutation Targeting and Substitution Based on Synonymous Mutations from High-Throughput Immunoglobulin Sequencing Data

Analyses of somatic hypermutation (SHM) patterns in B cell immunoglobulin (Ig) sequences contribute to our basic understanding of adaptive immunity, and have broad applications not only for understanding the immune response to pathogens, but also to determining the role of SHM in autoimmunity and B cell cancers. Although stochastic, SHM displays intrinsic biases that can confound statistical analysis, especially when combined with the particular codon usage and base composition in Ig sequences. Analysis of B cell clonal expansion, diversification, and selection processes thus critically depends on an accurate background model for SHM micro-sequence targeting (i.e., hot/cold-spots) and nucleotide substitution. Existing models are based on small numbers of sequences/mutations, in part because they depend on data from non-coding regions or non-functional sequences to remove the confounding influences of selection. Here, we combine high-throughput Ig sequencing with new computational analysis methods to produce improved models of SHM targeting and substitution that are based only on synonymous mutations, and are thus independent of selection. The resulting “S5F” models are based on 806,860 Synonymous mutations in 5-mer motifs from 1,145,182 Functional sequences and account for dependencies on the adjacent four nucleotides (two bases upstream and downstream of the mutation). The estimated profiles can explain almost half of the variance in observed mutation patterns, and clearly show that both mutation targeting and substitution are significantly influenced by neighboring bases. While mutability and substitution profiles were highly conserved across individuals, the variability across motifs was found to be much larger than previously estimated. The model and method source code are made available at http://clip.med.yale.edu/SH

A Multicomponent Animal Virus Isolated from Mosquitoes

RNA viruses exhibit a variety of genome organization strategies, including multicomponent genomes in which each segment is packaged separately. Although multicomponent genomes are common among viruses infecting plants and fungi, their prevalence among those infecting animals remains unclear. We characterize a multicomponent RNA virus isolated from mosquitoes, designated Guaico Culex virus (GCXV). GCXV belongs to a diverse clade of segmented viruses (Jingmenvirus) related to the prototypically unsegmented Flaviviridae. The GCXV genome comprises five segments, each of which appears to be separately packaged. The smallest segment is not required for replication, and its presence is variable in natural infections. We also describe a variant of Jingmen tick virus, another Jingmenvirus, sequenced from a Ugandan red colobus monkey, thus expanding the host range of this segmented and likely multicomponent virus group. Collectively, this study provides evidence for the existence of multicomponent animal viruses and their potential relevance for animal and human health.RNA viruses exhibit a variety of genome organization strategies, including multicomponent genomes in which each segment is packaged separately. Although multicomponent genomes are common among viruses infecting plants and fungi, their prevalence among those infecting animals remains unclear. We characterize a multicomponent RNA virus isolated from mosquitoes, designated Guaico Culex virus (GCXV). GCXV belongs to a diverse clade of segmented viruses (Jingmenvirus) related to the prototypically unsegmented Flaviviridae. The GCXV genome comprises five segments, each of which appears to be separately packaged. The smallest segment is not required for replication, and its presence is variable in natural infections. We also describe a variant of Jingmen tick virus, another Jingmenvirus, sequenced from a Ugandan red colobus monkey, thus expanding the host range of this segmented and likely multicomponent virus group. Collectively, this study provides evidence for the existence of multicomponent animal viruses and their potential relevance for animal and human health

The Postpartum Specific Anxiety Scale: development and preliminary validation

Perinatal symptoms of anxiety are increasingly recognised due to their high prevalence and impact. Studies using pregnancy-specific anxiety measures have found that they may predict perinatal outcomes more effectively than general measures. However, no such measure exists to assess anxieties specific to the postpartum. This study aimed to develop and validate a measure (Postpartum Specific Anxiety Scale; PSAS) that accurately represents the specific anxieties faced by postpartum women, using a four-stage methodology: (1) 51 items were generated from interviews conducted with a group of 19 postpartum women at two time points, (2) the scale was reviewed and refined by a diverse expert panel, (3) an online pilot study (n = 146) was conducted to assess comprehensibility and acceptability and (4) an online sample of 1282 mothers of infants up to 6 months old completed the PSAS against a battery of convergent measures. A subsample (n = 262) repeated the PSAS 2 weeks later. The PSAS possessed good face and content validity and was comprehensible and acceptable to postpartum women. PSAS scores were significantly correlated with other measures indicating good convergent validity. Principal component analyses (PCA) revealed a simple four-factor structure. Reliability of the overall scale and individual PSAS factors proved to be good to excellent. A preliminary receiver operating characteristic (ROC) analysis also suggested that the PSAS may be a useful screening tool. The psychometric evidence suggests that the PSAS is an acceptable, valid, and reliable research tool to assess anxieties, which are specific to the postpartum period. Next steps in the iterative validation process are considered for both research and screening purposes

Guidelines for investigating causality of sequence variants in human disease

The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development

Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of l

Proceedings of the Thirteenth International Society of Sports Nutrition (ISSN) Conference and Expo

Meeting Abstracts: Proceedings of the Thirteenth International Society of Sports Nutrition (ISSN) Conference and Expo Clearwater Beach, FL, USA. 9-11 June 201