Biology subjects

Johnson, D. S.

Publications and source records attributed to Johnson, D. S..

5 recordsLinked to original sources

bioRxiv2018

A Continuous-Time Semi-Markov Model for Animal Movement in a Dynamic Environment

We consider an extension to discrete-space continuous-time models animal movement that have previously be presented in the literature. The extension from a continuous-time Markov formulation to a continuous-time semi-Markov formulation allows for the inclusion of temporally dynamic habitat conditions as well as temporally changing movement responses by animals to that environment. We show that with only a little additional consideration, the Poisson likelihood approximation for the Markov version can still be used within the multiple imputation framework commonly employed for analysis of telemetry data. In addition, we consider a Bayesian model selection methodology with the imputation framework. The model selection method uses a Laplace approximation to the posterior model probability to provide a computationally feasible approach. The full methodology is then used to analyze movements of 15 northern fur seal (Callorhinus ursinus) pups with respect to surface winds, geostrophic currents, and sea surface temperature. The highest posterior model probabilities belonged to those models containing only winds and current, SST did not seem to be a significant factor for modeling their movement.

ecology↗

bioRxiv2018

Timing of ESCRT-III protein recruitment and membrane scission during HIV-1 assembly

The Endosomal Sorting Complexes Required for Transport III (ESCRT-III) proteins are critical for cellular membrane scission processes with topologies inverted relative to clathrin-mediated endocytosis. Some viruses appropriate ESCRT-IIIs for their release. By imaging single assembling viral-like particles of HIV-1, we observed that ESCRT-IIIs and the ATPase VPS4 arrive after most of the virion membrane is bent, linger for tens of seconds, and depart [~]20 seconds before scission. These observations suggest ESCRT-IIIs are recruited by a combination of membrane curvature and the late domains of the HIV-1 Gag protein. ESCRT-IIIs may pull the neck into a narrower form but must leave to allow scission. If scission does not occur within minutes of ESCRT departure, ESCRT-III and VPS4 are recruited again. This mechanistic insight is likely relevant for other ESCRT dependent scission processes including cell division, endosome tubulation, multivesicular body and nuclear envelope formation, and secretion of exosomes and ectosomes.

cell biology↗

bioRxiv2018

The contribution of non-canonical splicing mutations to severe dominant developmental disorders

Mutations which perturb normal pre-mRNA splicing are significant contributors to human disease. We used exome sequencing data from 7,833 probands with developmental disorders (DD) and their unaffected parents, as well as >60,000 aggregated exomes from the Exome Aggregation Consortium, to investigate selection around the splice site, and quantify the contribution of splicing mutations to DDs. Patterns of purifying selection, a deficit of variants in highly constrained genes in healthy subjects and excess de novo mutations in patients highlighted particular positions within and around the consensus splice site of greater functional relevance. Using mutational burden analyses in this large cohort of proband-parent trios, we could estimate in an unbiased manner the relative contributions of mutations at canonical dinucleotides (73%) and flanking non-canonical positions (27%), and calculated the positive predictive value of pathogenicity for different classes of mutations. We identified 18 patients with likely diagnostic de novo mutations in dominant DD-associated genes at non-canonical positions in splice sites. We estimate 35-40% of pathogenic variants in non-canonical splice site positions are missing from public databases.

genetics↗

bioRxiv2017

Autosomal recessive coding variants explain only a small proportion of undiagnosed developmental disorders in the British Isles

Large exome-sequencing datasets offer an unprecedented opportunity to understand the genetic architecture of rare diseases, informing clinical genetics counseling and optimal study designs for disease gene identification. We analyzed 7,448 exome-sequenced families from the Deciphering Developmental Disorders study, and, for the first time, estimated the causal contribution of recessive coding variation exome-wide. We found that the proportion of cases attributable to recessive coding variants is surprisingly low in patients of European ancestry, at only 3.6%, versus 50% of cases explained by de novo coding mutations. Surprisingly, we found that, even in European probands with affected siblings, recessive coding variants are only likely to explain ~12% of cases. In contrast, they account for 31% of probands with Pakistani ancestry due to elevated autozygosity. We tested every gene for an excess of damaging homozygous or compound heterozygous genotypes and found three genes that passed stringent Bonferroni correction: EIF3F, KDM5B, and THOC6. EIF3F is a novel disease gene, and KDM5B has previously been reported as a dominant disease gene. KDM5B appears to follow a complex mode of inheritance, in which heterozygous loss-of-function variants (LoFs) show incomplete penetrance and biallelic LoFs are fully penetrant. Our results suggest that a large proportion of undiagnosed developmental disorders remain to be explained by other factors, such as noncoding variants and polygenic risk.

genetics↗

bioRxiv2016

Confronting preferential sampling in wildlife surveys: diagnosis and model-based triage

SummaryO_LIWildlife surveys are often used to estimate the density, abundance, or distribution of animal populations. Recently, model-based approaches to analyzing survey data have become popular because one can more readily accommodate departures from pre-planned survey routes and construct more detailed maps than one can with design-based procedures.\nC_LIO_LISpecies distribution models fitted to wildlife survey data often make the implicit assumption that locations chosen for sampling and animal abundance at those locations are conditionally independent given modeled covariates. However, this assumption is likely violated in many cases when survey effort is non-randomized, leading to preferential sampling.\nC_LIO_LIWe develop a hierarchical statistical modeling framework for detecting and alleviating the biasing effects of preferential sampling in species distribution models fitted to count data. The approach works by jointly modeling wildlife state variables and the locations selected for sampling, and specifying a dependent correlation structure between the two models.\nC_LIO_LIUsing simulation, we show that moderate levels of preferential sampling can lead to large (e.g. 40%) bias in estimates of animal density, and that our modeling approach can considerably reduce this bias.\nC_LIO_LIWe apply our approach to aerial survey counts of bearded seals (Erignathus barbatus) in the eastern Bering Sea. Models that included a preferential sampling effect led to lower estimates of abundance than models without, but the effect size of the preferential sampling parameter decreased in models that included explanatory environmental covariates.\nC_LIO_LIWhen wildlife surveys are conducted without a well-defined sampling frame, ecologists should recognize the potentially biasing effects of preferential sampling. Joint models, such as those described in this paper, can be used to test and correct for such biases. Predictive covariates are also useful for bias reduction, but ultimately the best way to avoid preferential sampling bias is to incorporate design-based principles such as randomization and/or systematic sampling into survey design.\nC_LI

ecology↗