HapTree: A Novel Bayesian Framework for Single Individual Polyplotyping Using NGS Data

As the more recent next-generation sequencing (NGS) technologies provide longer read sequences, the use of sequencing datasets for complete haplotype phasing is fast becoming a reality, allowing haplotype reconstruction of a single sequenced genome. Nearly all previous haplotype reconstruction studies have focused on diploid genomes and are rarely scalable to genomes with higher ploidy. Yet computational investigations into polyploid genomes carry great importance, impacting plant, yeast and fish genomics, as well as the studies of the evolution of modern-day eukaryotes and (epi)genetic interactions between copies of genes. In this paper, we describe a novel maximum-likelihood estimation framework, HapTree, for polyploid haplotype assembly of an individual genome using NGS read datasets. We evaluate the performance of HapTree on simulated polyploid sequencing read data modeled after Illumina sequencing technologies. For triploid and higher ploidy genomes, we demonstrate that HapTree substantially improves haplotype assembly accuracy and efficiency over the state-of-the-art; moreover, HapTree is the first scalable polyplotyping method for higher ploidy. As a proof of concept, we also test our method on real sequencing data from NA12878 (1000 Genomes Project) and evaluate the quality of assembled haplotypes with respect to trio-based diplotype annotation as the ground truth. The results indicate that HapTree significantly improves the switch accuracy within phased haplotype blocks as compared to existing haplotype assembly methods, while producing comparable minimum error correction (MEC) values. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.National Science Foundation (U.S.) (NSF/NIH BIGDATA Grant R01GM108348-01)National Science Foundation (U.S.) (Graduate Research Fellowship)Simons Foundatio

Evaluation of genetic susceptibility to childhood allergy and asthma in an African American urban population

<p>Abstract</p> <p>Background</p> <p>Asthma and allergy represent complex phenotypes, which disproportionately burden ethnic minorities in the United States. Strong evidence for genomic factors predisposing subjects to asthma/allergy is available. However, methods to utilize this information to identify high risk groups are variable and replication of genetic associations in African Americans is warranted.</p> <p>Methods</p> <p>We evaluated 41 single nucleotide polymorphisms (SNP) and a deletion corresponding to 11 genes demonstrating association with asthma in the literature, for association with asthma, atopy, testing positive for food allergens, eosinophilia, and total serum IgE among 141 African American children living in Detroit, Michigan. Independent SNP and haplotype associations were investigated for association with each trait, and subsequently assessed in concert using a genetic risk score (GRS).</p> <p>Results</p> <p>Statistically significant associations with asthma were observed for SNPs in <it>GSTM1, MS4A2</it>, and <it>GSTP1 </it>genes, after correction for multiple testing. Chromosome 11 haplotype CTACGAGGCC (corresponding to <it>MS4A2 </it>rs574700, rs1441586, rs556917, rs502581, rs502419 and <it>GSTP1 </it>rs6591256, rs17593068, rs1695, rs1871042, rs947895) was associated with a nearly five-fold increase in the odds of asthma (Odds Ratio (OR) = 4.8, <it>p </it>= 0.007). The GRS was significantly associated with a higher odds of asthma (OR = 1.61, 95% Confidence Interval = 1.21, 2.13; <it>p </it>= 0.001).</p> <p>Conclusions</p> <p>Variation in genes associated with asthma in predominantly non-African ethnic groups contributed to increased odds of asthma in this African American study population. Evaluating all significant variants in concert helped to identify the highest risk subset of this group.</p

A communal catalogue reveals Earth's multiscale microbial diversity

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe

An Energy Taxis Transducer Promotes Root Colonization by Azospirillum brasilense

Motility responses triggered by changes in the electron transport system are collectively known as energy taxis. In Azospirillum brasilense, energy taxis was shown to be the principal form of locomotor control. In the present study, we have identified a novel chemoreceptor-like protein, named Tlp1, which serves as an energy taxis transducer. The Tlp1 protein is predicted to have an N-terminal periplasmic region and a cytoplasmic C-terminal signaling module homologous to those of other chemoreceptors. The predicted periplasmic region of Tlp1 comprises a conserved domain that is found in two types of microbial sensory receptors: chemotaxis transducers and histidine kinases. However, the function of this domain is currently unknown. We characterized the behavior of a tlp1 mutant by a series of spatial and temporal gradient assays. The tlp1 mutant is deficient in (i) chemotaxis to several rapidly oxidizable substrates, (ii) taxis to terminal electron acceptors (oxygen and nitrate), and (iii) redox taxis. Taken together, the data strongly suggest that Tlp1 mediates energy taxis in A. brasilense. Using qualitative and quantitative assays, we have also demonstrated that the tlp1 mutant is impaired in colonization of plant roots. This finding supports the hypothesis that energy taxis and therefore bacterial metabolism might be key factors in determining host specificity in Azospirillum-grass associations

Behavioral Deficits at 18-22 Months of Age Are Associated with Early Cerebellar Injury and Cognitive and Language Performance in Children Born Extremely Preterm

© 2018 Elsevier Inc. Objective: To investigate associations in toddlers born extremely preterm (\u3c28 weeks) between neonatal neuroimaging and 18- to 22-month developmental and behavioral outcomes. Study design: Cohort analysis from the Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network Surfactant Positive Airway Pressure and Pulse Oximetry Trial Neuroimaging and Neurodevelopmental Outcomes Study of infants born extremely preterm. Subjects underwent cranial ultrasonography and near-term magnetic resonance imaging (MRI). At 18-22 months of corrected age, the assessment included the Brief Infant Toddler Social Emotional Assessment (BITSEA) Problem and Competence Scale scores and the Bayley Scales of Infant Development, Third Edition (Bayley-III). The BITSEA Problem Scale assesses dysregulation; the Competence Scale assesses social-emotional competence. We examined associations of Problem and Competence scores and positive screen rates with cranial ultrasonography and near-term MRI. Mean BITSEA and Bayley-III scores were compared using ANOVA and positive screen rates with the χ 2 test. We computed correlations between BITSEA and Bayley-III scores. Results: Of the 397 children, positive BITSEA screens were found in 34% for the Problem score and 26% for the Competence score. Presence of lesions on near-term MRI that included cerebellar lesions were significantly associated with lower BITSEA Competence but not with Problem scores; Competence scores were inversely related to the presence/significance of lesions. Positive screens on Competence scores and on both Competence and Problem scores were significantly associated with Bayley-III cognitive and language scores \u3c85 (P \u3c.001). Conclusions: Social–emotional competence contributes to deficits in cognitive and language development. Presence of injury on near-term MRI that includes cerebellar lesions is associated with later social–emotional competence and may be a useful predictor to guide early assessment and intervention. Trial registration: ClinicalTrials.gov: NCT00063063 and NCT00233324

A Bayesian framework for multiple trait colocalization from summary association statistics

Motivation:Most genetic variants implicated in complex diseases by genome-wide association studies (GWAS) are non-coding, making it challenging to understand the causative genes involved in disease. Integrating external information such as quantitative trait locus (QTL) mapping of molecular traits (e.g. expression, methylation) is a powerful approach to identify the subset of GWAS signals explained by regulatory effects. In particular, expression QTLs (eQTLs) help pinpoint the responsible gene among the GWAS regions that harbor many genes, while methylation QTLs (mQTLs) help identify the epigenetic mechanisms that impact gene expression which in turn affect disease risk. In this work, we propose multiple-trait-coloc (moloc), a Bayesian statistical framework that integrates GWAS summary data with multiple molecular QTL data to identify regulatory effects at GWAS risk loci. Results:We applied moloc to schizophrenia (SCZ) and eQTL/mQTL data derived from human brain tissue and identified 52 candidate genes that influence SCZ through methylation. Our method can be applied to any GWAS and relevant functional data to help prioritize disease associated genes. Availability and implementation: moloc is available for download as an R package (https://github.com/clagiamba/moloc). We also developed a web site to visualize the biological findings (icahn.mssm.edu/moloc). The browser allows searches by gene, methylation probe and scenario of interest. Supplementary information:Supplementary data are available at Bioinformatics online

Neurobehavioral Assessment Predicts Motor Outcome in Preterm Infants

OBJECTIVE: To determine whether Neonatal Intensive Care Unit Network Neurobehavior Scales (NNNS) at 44 weeks predict motor outcome at 2 years in preterm infants from the Maternal Lifestyles Study (MLS). STUDY DESIGN: Data were collected on all preterm infants (<36 weeks) in the MLS who had an NNNS at 44 weeks (n=395) and neurologic exam at 12–36 months or Bayley Psychomotor Development Index (PDI) at 24 months (n=270). Logistic regression analyzed NNNS summary scores associated with Cerebral Palsy (CP) or PDI <70, while controlling for birth weight 1250g. RESULTS: Eighteen of 395 infants (5%) had CP; 24 of 270 infants (9%) had PDI <70. CP was associated with low quality of movement (OR 1.95, 95% CI 1.24–3.06, p=0.004) and high lethargy (OR 1.67, 95% CI 1.01–2.76, p=0.045). The model contributed 19% of the variance in CP diagnosis at 12–36 months (R(2)=0.19, p<0.001). Low PDI was associated with low handling (OR 1.83; 95% CI 1.12–2.99, p=0.017), low quality of movement (OR 2.16; 95%CI 1.38–3.38, p=0.001), and hypotonia (OR 1.63; 95% CI 1.14–2.32, p=0.007). The model contributed 26% of the variance in PDI <70 at 24 months (R(2)=0.26, p<0.001). CONCLUSIONS: The neurobehavioral profile of underarousal in 44 week preterm infants may predict poor motor outcome