Recent CIG publications Archive

BACKGROUND:

The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.

RESULTS:

Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.

CONCLUSION:

We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.

MOTIVATION:

The potentially low precision associated with the geographic origin of sampled sequences represents an important limitation for spatially-explicit (i.e. continuous) phylogeographic inference of fast-evolving pathogens such as RNA viruses. A substantial proportion of publicly available sequences are geo-referenced at broad spatial scale such as, for example, the administrative unit of origin rather than more exact locations (e.g. GPS coordinates). Most frequently, such sequences are either discarded prior to continuous phylogeographic inference or arbitrarily assigned to the geographic coordinates of the centroid of their administrative area of origin for lack of a better possibility.

RESULTS:

We here implement and describe a new approach that allows to incorporate heterogeneous prior sampling probabilities over a geographic area. External data, such as outbreak locations, are used to specify these prior sampling probabilities over a collection of sub-polygons. We apply this new method to the analysis of highly pathogenic avian influenza (HPAI) H5N1 clade data in the Mekong region. Our method allows to properly include, in continuous phylogeographic analyses, H5N1 sequences that are only associated with large administrative areas of origin and assign them with more accurate locations. Finally, we use continuous phylogeographic reconstructions to analyse the dispersal dynamics of different H5N1 clades and investigate the impact of environmental factors on lineage dispersal velocities.

AVAILABILITY:

Our new method allowing heterogeneous sampling priors for continuous phylogeographic inference is implemented in the open-source multi-platform software package BEAST 1.10.

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online and on figshare.com.

© The Author(s) (2019). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The timing and duration of sleep results from the interaction between a homeostatic sleep-wake-driven process and a periodic circadian process, and involves changes in gene regulation and expression. Unraveling the contributions of both processes and their interaction to transcriptional and epigenomic regulatory dynamics requires sampling over time under conditions of unperturbed and perturbed sleep. We profiled mRNA expression and chromatin accessibility in the cerebral cortex of mice over a 3-d period, including a 6-h sleep deprivation (SD) on day 2. We used mathematical modeling to integrate time series of mRNA expression data with sleep-wake history, which established that a large proportion of rhythmic genes are governed by the homeostatic process with varying degrees of interaction with the circadian process, sometimes working in opposition. Remarkably, SD caused long-term effects on gene-expression dynamics, outlasting phenotypic recovery, most strikingly illustrated by a damped oscillation of most core clock genes, including Arntl/Bmal1, suggesting that enforced wakefulness directly impacts the molecular clock machinery. Chromatin accessibility proved highly plastic and dynamically affected by SD. Dynamics in distal regions, rather than promoters, correlated with mRNA expression, implying that changes in expression result from constitutively accessible promoters under the influence of enhancers or repressors. Serum response factor (SRF) was predicted as a transcriptional regulator driving immediate response, suggesting that SRF activity mirrors the build-up and release of sleep pressure. Our results demonstrate that a single, short SD has long-term aftereffects at the genomic regulatory level and highlights the importance of the sleep-wake distribution to diurnal rhythmicity and circadian processes.

Copyright © 2019 the Author(s). Published by PNAS.

Recent research into structural variants (SVs) has established their importance to medicine and molecular biology, elucidating their role in various diseases, regulation of gene expression, ethnic diversity, and large-scale chromosome evolution-giving rise to the differences within populations and among species. Nevertheless, characterizing SVs and determining the optimal approach for a given experimental design remains a computational and scientific challenge. Multiple approaches have emerged to target various SV classes, zygosities, and size ranges. Here, we review these approaches with respect to their ability to infer SVs across the full spectrum of large, complex variations and present computational methods for each approach.

Phytochromes are bilin-binding photosensory receptors which control development over a broad range of environmental conditions and throughout the whole plant life cycle. Light-induced conformational changes enable phytochromes to interact with signaling partners, in particular transcription factors or proteins that regulate them, resulting in large-scale transcriptional reprograming. Phytochromes also regulate promoter usage, mRNA splicing and translation through less defined routes. In this review we summarize our current understanding of plant phytochrome signaling, emphasizing recent work performed in Arabidopsis. We compare and contrast phytochrome responses and signaling mechanisms among land plants and highlight open questions in phytochrome research.

Our goal was to describe and illustrate prenatal cerebral imaging features of the most severe form of a new syndromic entity related to KIAA1109 pathogenic variants based on a retrospective multicentric study of seven cases. All cases demonstrated a similar complex severe cerebral malformative pattern. This pattern included, within the supratentorial space, major cerebral parenchymal thinning with a lissencephalic cortical pattern, voluminous germinal matrices, severe ventriculomegaly, and corpus callosum agenesis. Within the infra-tentorial space, cerebellar hypoplasia was associated with characteristic brainstem dysgenesis including elongation of the pons, as well as a variable degree of kinking of the brainstem. This cerebral pattern, which was suggestive of the more severe phenotypes related to disrupting variants of tubulin-encoding genes, was associated in all cases with clubfoot and/or arthrogryposis, and in most cases with cardiac and ophthalmologic anomalies. In all cases, exome sequencing led to the identification of KIAA1109 pathogenic variants.

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