Wham: Identifying Structural Variants of Biological Consequence

Existing methods for identifying structural variants (SVs) from short read datasets are inaccurate. This complicates disease-gene identification and efforts to understand the consequences of genetic variation. In response, we have created Wham (Whole-genome Alignment Metrics) to provide a single, integrated framework for both structural variant calling and association testing, thereby bypassing many of the difficulties that currently frustrate attempts to employ SVs in association testing. Here we describe Wham, benchmark it against three other widely used SV identification tools–Lumpy, Delly and SoftSearch–and demonstrate Wham’s ability to identify and associate SVs with phenotypes using data from humans, domestic pigeons, and vaccinia virus. Wham and all associated software are covered under the MIT License and can be freely downloaded from github (https://github.com/zeeev/wham), with documentation on a wiki (http://zeeev.github.io/wham/). For community support please post questions to https://www.biostars.org/.

This is PLOS Computational Biology software paper.

     

POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis

Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biological interpretation of the results. Because of this, combined with the computational programming skills needed for this type of analysis, several bioinformatic tools aimed at simplifying metabolomics and proteomics data analysis have emerged. However, sometimes the analysis is still limited to a few hidebound statistical methods and to data sets with limited flexibility. POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for the visualization, exploration and statistical analysis of metabolomics and proteomics data. This tool integrates several statistical methods, some of them widely used in other types of omics, and it is based on the POMA R/Bioconductor package, which increases the reproducibility and flexibility of analyses outside the web environment. POMAShiny and POMA are both freely available at https://github.com/nutrimetabolomics/POMAShiny and https://github.com/nutrimetabolomics/POMA, respectively.     

Evolving Digital Ecological Networks

“It is hard to realize that the living world as we know it is just one among many possibilities” [1]. Evolving digital ecological networks are webs of interacting, self-replicating, and evolving computer programs (i.e., digital organisms) that experience the same major ecological interactions as biological organisms (e.g., competition, predation, parasitism, and mutualism). Despite being computational, these programs evolve quickly in an open-ended way, and starting from only one or two ancestral organisms, the formation of ecological networks can be observed in real-time by tracking interactions between the constantly evolving organism phenotypes. These phenotypes may be defined by combinations of logical computations (hereafter tasks) that digital organisms perform and by expressed behaviors that have evolved. The types and outcomes of interactions between phenotypes are determined by task overlap for logic-defined phenotypes and by responses to encounters in the case of behavioral phenotypes. Biologists use these evolving networks to study active and fundamental topics within evolutionary ecology (e.g., the extent to which the architecture of multispecies networks shape coevolutionary outcomes, and the processes involved).

This is a “Topic Page” article for PLOS Computational Biology.

     

Viral Phylodynamics

Viral phylodynamics is defined as the study of how epidemiological, immunological, and evolutionary processes act and potentially interact to shape viral phylogenies. Since the coining of the term in 2004, research on viral phylodynamics has focused on transmission dynamics in an effort to shed light on how these dynamics impact viral genetic variation. Transmission dynamics can be considered at the level of cells within an infected host, individual hosts within a population, or entire populations of hosts. Many viruses, especially RNA viruses, rapidly accumulate genetic variation because of short generation times and high mutation rates. Patterns of viral genetic variation are therefore heavily influenced by how quickly transmission occurs and by which entities transmit to one another. Patterns of viral genetic variation will also be affected by selection acting on viral phenotypes. Although viruses can differ with respect to many phenotypes, phylodynamic studies have to date tended to focus on a limited number of viral phenotypes. These include virulence phenotypes, phenotypes associated with viral transmissibility, cell or tissue tropism phenotypes, and antigenic phenotypes that can facilitate escape from host immunity. Due to the impact that transmission dynamics and selection can have on viral genetic variation, viral phylogenies can therefore be used to investigate important epidemiological, immunological, and evolutionary processes, such as epidemic spread [2], spatio-temporal dynamics including metapopulation dynamics [3], zoonotic transmission, tissue tropism [4], and antigenic drift [5]. The quantitative investigation of these processes through the consideration of viral phylogenies is the central aim of viral phylodynamics.

This is a “Topic Page” article for PLOS Computational Biology.

     

VDJtools: Unifying Post-analysis of T Cell Receptor Repertoires

Despite the growing number of immune repertoire sequencing studies, the field still lacks software for analysis and comprehension of this high-dimensional data. Here we report VDJtools, a complementary software suite that solves a wide range of T cell receptor (TCR) repertoires post-analysis tasks, provides a detailed tabular output and publication-ready graphics, and is built on top of a flexible API. Using TCR datasets for a large cohort of unrelated healthy donors, twins, and multiple sclerosis patients we demonstrate that VDJtools greatly facilitates the analysis and leads to sound biological conclusions. VDJtools software and documentation are available at https://github.com/mikessh/vdjtools.     

Approximate Bayesian Computation

Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology).

This is a “Topic Page” article for PLOS Computational Biology.

     

The Mps1 Kinase Modulates the Recruitment and Activity of Cnn1CENP-T at Saccharomyces cerevisiae Kinetochores

Kinetochores are conserved protein complexes that bind the replicated chromosomes to the mitotic spindle and then direct their segregation. To better comprehend Saccharomyces cerevisiae kinetochore function, we dissected the phospho-regulated dynamic interaction between conserved kinetochore protein Cnn1^CENP-T, the centromere region, and the Ndc80 complex through the cell cycle. Cnn1 localizes to kinetochores at basal levels from G1 through metaphase but accumulates abruptly at anaphase onset. How Cnn1 is recruited and which activities regulate its dynamic localization are unclear. We show that Cnn1 harbors two kinetochore-localization activities: a C-terminal histone-fold domain (HFD) that associates with the centromere region and a N-terminal Spc24/Spc25 interaction sequence that mediates linkage to the microtubule-binding Ndc80 complex. We demonstrate that the established Ndc80 binding site in the N terminus of Cnn1, Cnn1^60–84, should be extended with flanking residues, Cnn1^25–91, to allow near maximal binding affinity to Ndc80. Cnn1 localization was proposed to depend on Mps1 kinase activity at Cnn1–S74, based on in vitro experiments demonstrating the Cnn1–Ndc80 complex interaction. We demonstrate that from G1 through metaphase, Cnn1 localizes via both its HFD and N-terminal Spc24/Spc25 interaction sequence, and deletion or mutation of either region results in anomalous Cnn1 kinetochore levels. At anaphase onset (when Mps1 activity decreases) Cnn1 becomes enriched mainly via the N-terminal Spc24/Spc25 interaction sequence. In sum, we provide the first in vivo evidence of Cnn1 preanaphase linkages with the kinetochore and enrichment of the linkages during anaphase.     

New Regulators of Clathrin-Mediated Endocytosis Identified in Saccharomyces cerevisiae by Systematic Quantitative Fluorescence Microscopy

Despite the importance of clathrin-mediated endocytosis (CME) for cell biology, it is unclear if all components of the machinery have been discovered and many regulatory aspects remain poorly understood. Here, using Saccharomyces cerevisiae and a fluorescence microscopy screening approach we identify previously unknown regulatory factors of the endocytic machinery. We further studied the top scoring protein identified in the screen, Ubx3, a member of the conserved ubiquitin regulatory X (UBX) protein family. In vivo and in vitro approaches demonstrate that Ubx3 is a new coat component. Ubx3-GFP has typical endocytic coat protein dynamics with a patch lifetime of 45 ± 3 sec. Ubx3 contains a W-box that mediates physical interaction with clathrin and Ubx3-GFP patch lifetime depends on clathrin. Deletion of the UBX3 gene caused defects in the uptake of Lucifer Yellow and the methionine transporter Mup1 demonstrating that Ubx3 is needed for efficient endocytosis. Further, the UBX domain is required both for localization and function of Ubx3 at endocytic sites. Mechanistically, Ubx3 regulates dynamics and patch lifetime of the early arriving protein Ede1 but not later arriving coat proteins or actin assembly. Conversely, Ede1 regulates the patch lifetime of Ubx3. Ubx3 likely regulates CME via the AAA-ATPase Cdc48, a ubiquitin-editing complex. Our results uncovered new components of the CME machinery that regulate this fundamental process.     

Redundant Regulation of Cdk1 Tyrosine Dephosphorylation in Saccharomyces cerevisiae

Cdk1 activity drives both mitotic entry and the metaphase-to-anaphase transition in all eukaryotes. The kinase Wee1 and the phosphatase Cdc25 regulate the mitotic activity of Cdk1 by the reversible phosphorylation of a conserved tyrosine residue. Mutation of cdc25 in Schizosaccharomyces pombe blocks Cdk1 dephosphorylation and causes cell cycle arrest. In contrast, deletion of MIH1, the cdc25 homolog in Saccharomyces cerevisiae, is viable. Although Cdk1-Y19 phosphorylation is elevated during mitosis in mih1∆ cells, Cdk1 is dephosphorylated as cells progress into G₁, suggesting that additional phosphatases regulate Cdk1 dephosphorylation. Here we show that the phosphatase Ptp1 also regulates Cdk1 dephosphorylation in vivo and can directly dephosphorylate Cdk1 in vitro. Using a novel in vivo phosphatase assay, we also show that PP2A bound to Rts1, the budding yeast B56-regulatory subunit, regulates dephosphorylation of Cdk1 independently of a function regulating Swe1, Mih1, or Ptp1, suggesting that PP2A^Rts1 either directly dephosphorylates Cdk1-Y19 or regulates an unidentified phosphatase.     

The Jaw of the Worm: GTPase-activating Protein EAT-17 Regulates Grinder Formation in Caenorhabditis elegans

Constitutive transport of cellular materials is essential for cell survival. Although multiple small GTPase Rab proteins are required for the process, few regulators of Rabs are known. Here we report that EAT-17, a novel GTPase-activating protein (GAP), regulates RAB-6.2 function in grinder formation in Caenorhabditis elegans. We identified EAT-17 as a novel RabGAP that interacts with RAB-6.2, a protein that presumably regulates vesicle trafficking between Golgi, the endoplasmic reticulum, and plasma membrane to form a functional grinder. EAT-17 has a canonical GAP domain that is critical for its function. RNA interference against 25 confirmed and/or predicted RABs in C. elegans shows that RNAi against rab-6.2 produces a phenotype identical to eat-17. A directed yeast two-hybrid screen using EAT-17 as bait and each of the 25 RAB proteins as prey identifies RAB-6.2 as the interacting partner of EAT-17, confirming that RAB-6.2 is a specific substrate of EAT-17. Additionally, deletion mutants of rab-6.2 show grinder defects identical to those of eat-17 loss-of-function mutants, and both RAB-6.2 and EAT-17 are expressed in the terminal bulb of the pharynx where the grinder is located. Collectively, these results suggest that EAT-17 is a specific GTPase-activating protein for RAB-6.2. Based on the conserved function of Rab6 in vesicular transport, we propose that EAT-17 regulates the turnover rate of RAB-6.2 activity in cargo trafficking for grinder formation.     

Caenorhabditis elegans PIG-1/MELK Acts in a Conserved PAR-4/LKB1 Polarity Pathway to Promote Asymmetric Neuroblast Divisions

Asymmetric cell divisions produce daughter cells with distinct sizes and fates, a process important for generating cell diversity during development. Many Caenorhabditis elegans neuroblasts, including the posterior daughter of the Q cell (Q.p), divide to produce a larger neuron or neuronal precursor and a smaller cell that dies. These size and fate asymmetries require the gene pig-1, which encodes a protein orthologous to vertebrate MELK and belongs to the AMPK-related family of kinases. Members of this family can be phosphorylated and activated by the tumor suppressor kinase LKB1, a conserved polarity regulator of epithelial cells and neurons. In this study, we present evidence that the C. elegans orthologs of LKB1 (PAR-4) and its partners STRAD (STRD-1) and MO25 (MOP-25.2) regulate the asymmetry of the Q.p neuroblast division. We show that PAR-4 and STRD-1 act in the Q lineage and function genetically in the same pathway as PIG-1. A conserved threonine residue (T169) in the PIG-1 activation loop is essential for PIG-1 activity, consistent with the model that PAR-4 (or another PAR-4-regulated kinase) phosphorylates and activates PIG-1. We also demonstrate that PIG-1 localizes to centrosomes during cell divisions of the Q lineage, but this localization does not depend on T169 or PAR-4. We propose that a PAR-4-STRD-1 complex stimulates PIG-1 kinase activity to promote asymmetric neuroblast divisions and the generation of daughter cells with distinct fates. Changes in cell fate may underlie many of the abnormal behaviors exhibited by cells after loss of PAR-4 or LKB1.     

lra: A long read aligner for sequences and contigs

It is computationally challenging to detect variation by aligning single-molecule sequencing (SMS) reads, or contigs from SMS assemblies. One approach to efficiently align SMS reads is sparse dynamic programming (SDP), where optimal chains of exact matches are found between the sequence and the genome. While straightforward implementations of SDP penalize gaps with a cost that is a linear function of gap length, biological variation is more accurately represented when gap cost is a concave function of gap length. We have developed a method, lra, that uses SDP with a concave-cost gap penalty, and used lra to align long-read sequences from PacBio and Oxford Nanopore (ONT) instruments as well as de novo assembly contigs. This alignment approach increases sensitivity and specificity for SV discovery, particularly for variants above 1kb and when discovering variation from ONT reads, while having runtime that are comparable (1.05-3.76×) to current methods. When applied to calling variation from de novo assembly contigs, there is a 3.2% increase in Truvari F1 score compared to minimap2+htsbox. lra is available in bioconda (https://anaconda.org/bioconda/lra) and github (https://github.com/ChaissonLab/LRA).     

The Role of Dbf4-Dependent Protein Kinase in DNA Polymerase ζ-Dependent Mutagenesis in Saccharomyces cerevisiae

The yeast Dbf4-dependent kinase (DDK) (composed of Dbf4 and Cdc7 subunits) is an essential, conserved Ser/Thr protein kinase that regulates multiple processes in the cell, including DNA replication, recombination and induced mutagenesis. Only DDK substrates important for replication and recombination have been identified. Consequently, the mechanism by which DDK regulates mutagenesis is unknown. The yeast mcm5-bob1 mutation that bypasses DDK’s essential role in DNA replication was used here to examine whether loss of DDK affects spontaneous as well as induced mutagenesis. Using the sensitive lys2ΔA746 frameshift reversion assay, we show DDK is required to generate “complex” spontaneous mutations, which are a hallmark of the Polζ translesion synthesis DNA polymerase. DDK co-immunoprecipitated with the Rev7 regulatory, but not with the Rev3 polymerase subunit of Polζ. Conversely, Rev7 bound mainly to the Cdc7 kinase subunit and not to Dbf4. The Rev7 subunit of Polζ may be regulated by DDK phosphorylation as immunoprecipitates of yeast Cdc7 and also recombinant Xenopus DDK phosphorylated GST-Rev7 in vitro. In addition to promoting Polζ-dependent mutagenesis, DDK was also important for generating Polζ-independent large deletions that revert the lys2ΔA746 allele. The decrease in large deletions observed in the absence of DDK likely results from an increase in the rate of replication fork restart after an encounter with spontaneous DNA damage. Finally, nonepistatic, additive/synergistic UV sensitivity was observed in cdc7Δ pol32Δ and cdc7Δ pol30-K127R,K164R double mutants, suggesting that DDK may regulate Rev7 protein during postreplication “gap filling” rather than during “polymerase switching” by ubiquitinated and sumoylated modified Pol30 (PCNA) and Pol32.