Biology subjects

Allen, A.

Publications and source records attributed to Allen, A..

3 recordsLinked to original sources

bioRxiv2018

Pupil responses to hidden photoreceptor-specific modulations in movies

Under typical daytime light levels, the human pupillary light response (PLR) is driven by the activity of the L, M, and S cones, and melanopsin expressed in the so-called intrinsically photosensitive retinal ganglion cells (ipRGCs). However, the importance of each of these photoreceptive mechanisms in defining pupil size under real-world viewing conditions remains to be established. To address this question, we embedded photoreceptor-specific modulations in a movie displayed using a novel projector-based five-primary spatial stimulation system, which allowed for the precise control of photoreceptor activations in time and space. We measured the pupillary light response in eleven observers, who viewed short cartoon movies which contained hidden low-frequency (0.25 Hz) silent-substitution modulations of the L, M and S cones (no stimulation of melanopsin), melanopsin (no stimulation of L, M and S cones), both L, M, and S cones and melanopsin or no modulation at all. We find that all photoreceptors active at photopic light levels regulate pupil size under this condition. Our data imply that embedding modulations in photoreceptor contrast could provide a method to manipulate key adaptive aspects of the human visual system in everyday, real-world activities such as watching a movie.

neuroscience↗

bioRxiv2018

Improved Pathogenic Variant Localization using a Hierarchical Model of Sub-regional Intolerance

Different parts of a gene can be of differential importance to development and health. This regional heterogeneity is also apparent in the distribution of disease mutations which often cluster in particular regions of disease genes. The ability to precisely estimate functionally important sub-regions of genes will be key in correctly deciphering relationships between genetic variation and disease. Previous methods have had some success using standing human variation to characterize this variability in importance by measuring sub-regional intolerance, i.e., the depletion in functional variation from expectation within a given region of a gene. However, the ability to precisely estimate local intolerance was restricted by the fact that only information within a given sub-region is used, leading to instability in local estimates, especially for small regions. We show that borrowing information across regions using a Bayesian hierarchical model, stabilizes estimates, leading to lower variability and improved predictive utility. Specifically, our approach more effectively identifies regions enriched for ClinVar pathogenic variants. We also identify significant correlations between sub-region intolerance and the distribution of pathogenic variation in disease genes, with AUCs for classifying de novo missense variants in Online Mendelian Inheritance in Man (OMIM) genes of up to 0.86 using exonic sub-regions and 0.91 using sub-regions defined by protein domains. This result immediately suggests that considering the intolerance of regions in which variants are found may improve diagnostic interpretation. We also illustrate the utility of integrating regional intolerance into gene-level disease association tests with a study of known disease genes for epileptic encephalopathy.

genetics↗

bioRxiv2018

Regional collapsing of rare variation implicates specific genic regions in ALS

Large-scale sequencing efforts in amyotrophic lateral sclerosis (ALS) have implicated novel genes using gene-based collapsing methods. However, pathogenic mutations may be concentrated in specific genic regions. To address this, we developed two collapsing strategies, one focuses rare variation collapsing on homology-based protein domains as the unit for collapsing and another gene-level approach that, unlike standard methods, leverages existing evidence of purifying selection against missense variation on said domains. The application of these two collapsing methods to 3,093 ALS cases and 8,186 controls of European ancestry, and also 3,239 cases and 11,808 controls of diversified populations, pinpoints risk regions of ALS genes including SOD1, NEK1, TARDBP and FUS. While not clearly implicating novel ALS genes, the new analyses not only pinpoint risk regions in known genes but also highlight candidate genes as well.

genetics↗