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.

     

High accuracy operon prediction method based on STRING database scores

We present a simple and highly accurate computational method for operon prediction, based on intergenic distances and functional relationships between the protein products of contiguous genes, as defined by STRING database (Jensen,L.J., Kuhn,M., Stark,M., Chaffron,S., Creevey,C., Muller,J., Doerks,T., Julien,P., Roth,A., Simonovic,M. et al. (2009) STRING 8–a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res., 37, D412–D416). These two parameters were used to train a neural network on a subset of experimentally characterized Escherichia coli and Bacillus subtilis operons. Our predictive model was successfully tested on the set of experimentally defined operons in E. coli and B. subtilis, with accuracies of 94.6 and 93.3%, respectively. As far as we know, these are the highest accuracies ever obtained for predicting bacterial operons. Furthermore, in order to evaluate the predictable accuracy of our model when using an organism''s data set for the training procedure, and a different organism''s data set for testing, we repeated the E. coli operon prediction analysis using a neural network trained with B. subtilis data, and a B. subtilis analysis using a neural network trained with E. coli data. Even for these cases, the accuracies reached with our method were outstandingly high, 91.5 and 93%, respectively. These results show the potential use of our method for accurately predicting the operons of any other organism. Our operon predictions for fully-sequenced genomes are available at http://operons.ibt.unam.mx/OperonPredictor/.     

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.

     

Flow Cytometry Bioinformatics

Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform.

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

     

Birds do it,bees do it,worms and ciliates do it too: DNA methylation from unexpected corners of the tree of life

Studies describing intricate patterns of DNA methylation in nematode and ciliate are controversial due to the uncertainty of genomic evolutionary conservation of DNA methylation enzymes.See related research articles http://genomebiology.com/2012/13/10/R99 and http://genomebiology.com/2012/13/10/R100     

Online database for mosquito (Diptera,Culicidae) occurrence records in French Guiana

A database providing information on mosquito specimens (Arthropoda: Diptera: Culicidae) collected in French Guiana is presented. Field collections were initiated in 2013 under the auspices of the CEnter for the study of Biodiversity in Amazonia (CEBA: http://www.labexceba.fr/en/). This study is part of an ongoing process aiming to understand the distribution of mosquitoes, including vector species, across French Guiana. Occurrences are recorded after each collecting trip in a database managed by the laboratory Evolution et Diversité Biologique (EDB), Toulouse, France. The dataset is updated monthly and is available online. Voucher specimens and their associated DNA are stored at the laboratory Ecologie des Forêts de Guyane (Ecofog), Kourou, French Guiana. The latest version of the dataset is accessible through EDB’s Integrated Publication Toolkit at http://130.120.204.55:8080/ipt/resource.do?r=mosquitoes_of_french_guiana or through the Global Biodiversity Information Facility data portal at http://www.gbif.org/dataset/5a8aa2ad-261c-4f61-a98e-26dd752fe1c5 It can also be viewed through the Guyanensis platform at http://guyanensis.ups-tlse.fr     

A multi-split mapping algorithm for circular RNA,splicing, trans-splicing and fusion detection

Numerous high-throughput sequencing studies have focused on detecting conventionally spliced mRNAs in RNA-seq data. However, non-standard RNAs arising through gene fusion, circularization or trans-splicing are often neglected. We introduce a novel, unbiased algorithm to detect splice junctions from single-end cDNA sequences. In contrast to other methods, our approach accommodates multi-junction structures. Our method compares favorably with competing tools for conventionally spliced mRNAs and, with a gain of up to 40% of recall, systematically outperforms them on reads with multiple splits, trans-splicing and circular products. The algorithm is integrated into our mapping tool segemehl (http://www.bioinf.uni-leipzig.de/Software/segemehl/).     

Stimulation of Chromosomal Rearrangements by Ribonucleotides

We show by whole genome sequence analysis that loss of RNase H2 activity increases loss of heterozygosity (LOH) in Saccharomyces cerevisiae diploid strains harboring the pol2-M644G allele encoding a mutant version of DNA polymerase ε that increases ribonucleotide incorporation. This led us to analyze the effects of loss of RNase H2 on LOH and on nonallelic homologous recombination (NAHR) in mutant diploid strains with deletions of genes encoding RNase H2 subunits (rnh201Δ, rnh202Δ, and rnh203Δ), topoisomerase 1 (TOP1Δ), and/or carrying mutant alleles of DNA polymerases ε, α, and δ. We observed an ∼7-fold elevation of the LOH rate in RNase H2 mutants encoding wild-type DNA polymerases. Strains carrying the pol2-M644G allele displayed a 7-fold elevation in the LOH rate, and synergistic 23-fold elevation in combination with rnh201Δ. In comparison, strains carrying the pol2-M644L mutation that decreases ribonucleotide incorporation displayed lower LOH rates. The LOH rate was not elevated in strains carrying the pol1-L868M or pol3-L612M alleles that result in increased incorporation of ribonucleotides during DNA synthesis by polymerases α and δ, respectively. A similar trend was observed in an NAHR assay, albeit with smaller phenotypic differentials. The ribonucleotide-mediated increases in the LOH and NAHR rates were strongly dependent on TOP1. These data add to recent reports on the asymmetric mutagenicity of ribonucleotides caused by topoisomerase 1 processing of ribonucleotides incorporated during DNA replication.     

Resection Activity of the Sgs1 Helicase Alters the Affinity of DNA Ends for Homologous Recombination Proteins in Saccharomyces cerevisiae

The RecQ helicase family is critical during DNA damage repair, and mutations in these proteins are associated with Bloom, Werner, or Rothmund-Thompson syndromes in humans, leading to cancer predisposition and/or premature aging. In the budding yeast Saccharomyces cerevisiae, mutations in the RecQ homolog, SGS1, phenocopy many of the defects observed in the human syndromes. One challenge to studying RecQ helicases is that their disruption leads to a pleiotropic phenotype. Using yeast, we show that the separation-of-function allele of SGS1, sgs1-D664Δ, has impaired activity at DNA ends, resulting in a resection processivity defect. Compromising Sgs1 resection function in the absence of the Sae2 nuclease causes slow growth, which is alleviated by making the DNA ends accessible to Exo1 nuclease. Furthermore, fluorescent microscopy studies reveal that, when Sgs1 resection activity is compromised in sae2Δ cells, Mre11 repair foci persist. We suggest a model where the role of Sgs1 in end resection along with Sae2 is important for removing Mre11 from DNA ends during repair.     

NeuronGrowth, a software for automatic quantification of neurite and filopodial dynamics from time-lapse sequences of digital images

We developed NeuronGrowth, a software for the automatic quantification of extension and retraction of neurites and filopodia, from time-lapse sequences of two-dimensional digital micrographs. NeuronGrowth requires a semiautomatic characterization of individual neurites in a reference frame, which is then used for automatic tracking and measurement of every neurite over the whole image sequence. Modules for sequence alignment, background subtraction, flat field correction, light normalization, and cropping have been integrated to improve the quality of the analysis. Moreover, NeuronGrowth incorporates a deconvolution filter that corrects the shadow-cast effect of differential interference contrast (DIC) images. NeuronGrowth was tested by analyzing the formation of outgrowth patterns by individual leech neurons cultured under two different conditions. Phase contrast images were obtained from neurons plated on CNS homogenates and DIC images were obtained from similar neurons plated on ganglion capsules as substrates. Filopodia were measured from fluorescent growth-cones of chick dorsal root ganglion cells. Quantitative data of neurite extension and retraction obtained by three different users applying NeuronGrowth and two other manually operated software packages were similar. However, NeuronGrowth required less user participation and had a better time performance when compared with the other software packages. NeuronGrowth may be used in general to quantify the dynamics of tubular structures such as blood vessels. NeuronGrowth is a free plug-in for the free software ImageJ and can be downloaded along with a user manual, a troubleshooting section and other information required for its use from http://www.ifc.unam.mx or http://www.ifc.unam.mx/ffm/index.html.     

Wide-Ranging Effects of the Yeast Ptc1 Protein Phosphatase Acting Through the MAPK Kinase Mkk1

The Saccharomyces cerevisiae type 2C protein phosphatase Ptc1 is required for a wide variety of cellular functions, although only a few cellular targets have been identified. A genetic screen in search of mutations in protein kinase–encoding genes able to suppress multiple phenotypic traits caused by the ptc1 deletion yielded a single gene, MKK1, coding for a MAPK kinase (MAPKK) known to activate the cell-wall integrity (CWI) Slt2 MAPK. In contrast, mutation of the MKK1 paralog, MKK2, had a less significant effect. Deletion of MKK1 abolished the increased phosphorylation of Slt2 induced by the absence of Ptc1 both under basal and CWI pathway stimulatory conditions. We demonstrate that Ptc1 acts at the level of the MAPKKs of the CWI pathway, but only the Mkk1 kinase activity is essential for ptc1 mutants to display high Slt2 activation. We also show that Ptc1 is able to dephosphorylate Mkk1 in vitro. Our results reveal the preeminent role of Mkk1 in signaling through the CWI pathway and strongly suggest that hyperactivation of Slt2 caused by upregulation of Mkk1 is at the basis of most of the phenotypic defects associated with lack of Ptc1 function.     

The Principal Role of Ku in Telomere Length Maintenance Is Promotion of Est1 Association with Telomeres

Telomere length is tightly regulated in cells that express telomerase. The Saccharomyces cerevisiae Ku heterodimer, a DNA end-binding complex, positively regulates telomere length in a telomerase-dependent manner. Ku associates with the telomerase RNA subunit TLC1, and this association is required for TLC1 nuclear retention. Ku–TLC1 interaction also impacts the cell-cycle-regulated association of the telomerase catalytic subunit Est2 to telomeres. The promotion of TLC1 nuclear localization and Est2 recruitment have been proposed to be the principal role of Ku in telomere length maintenance, but neither model has been directly tested. Here we study the impact of forced recruitment of Est2 to telomeres on telomere length in the absence of Ku’s ability to bind TLC1 or DNA ends. We show that tethering Est2 to telomeres does not promote efficient telomere elongation in the absence of Ku–TLC1 interaction or DNA end binding. Moreover, restoration of TLC1 nuclear localization, even when combined with Est2 recruitment, does not bypass the role of Ku. In contrast, forced recruitment of Est1, which has roles in telomerase recruitment and activation, to telomeres promotes efficient and progressive telomere elongation in the absence of Ku–TLC1 interaction, Ku DNA end binding, or Ku altogether. Ku associates with Est1 and Est2 in a TLC1-dependent manner and enhances Est1 recruitment to telomeres independently of Est2. Together, our results unexpectedly demonstrate that the principal role of Ku in telomere length maintenance is to promote the association of Est1 with telomeres, which may in turn allow for efficient recruitment and activation of the telomerase holoenzyme.     

New Insights into the Post-Translational Regulation of DNA Damage Response and Double-Strand Break Repair in Caenorhabditis elegans

Although a growing number of studies have reported the importance of SUMOylation in genome maintenance and DNA double-strand break repair (DSBR), relevant target proteins and how this modification regulates their functions are yet to be clarified. Here, we analyzed SUMOylation of ZTF-8, the homolog of mammalian RHINO, to test the functional significance of this protein modification in the DSBR and DNA damage response (DDR) pathways in the Caenorhabditis elegans germline. We found that ZTF-8 is a direct target for SUMOylation in vivo and that its modification is required for DNA damage checkpoint induced apoptosis and DSBR. Non-SUMOylatable mutants of ZTF-8 mimic the phenotypes observed in ztf-8 null mutants, including reduced fertility, impaired DNA damage repair, and defective DNA damage checkpoint activation. However, while mutants for components acting in the SUMOylation pathway fail to properly localize ZTF-8, its localization is not altered in the ZTF-8 non-SUMOylatable mutants. Taken together, these data show that direct SUMOylation of ZTF-8 is required for its function in DSBR as well as DDR but not its localization. ZTF-8’s human ortholog is enriched in the germline, but its meiotic role as well as its post-translational modification has never been explored. Therefore, our discovery may assist in understanding the regulatory mechanism of this protein in DSBR and DDR in the germline.     

Replisome Function During Replicative Stress Is Modulated by Histone H3 Lysine 56 Acetylation Through Ctf4

Histone H3 lysine 56 acetylation in Saccharomyces cerevisiae is required for the maintenance of genome stability under normal conditions and upon DNA replication stress. Here we show that in the absence of H3 lysine 56 acetylation replisome components become deleterious when replication forks collapse at natural replication block sites. This lethality is not a direct consequence of chromatin assembly defects during replication fork progression. Rather, our genetic analyses suggest that in the presence of replicative stress H3 lysine 56 acetylation uncouples the Cdc45–Mcm2-7–GINS DNA helicase complex and DNA polymerases through the replisome component Ctf4. In addition, we discovered that the N-terminal domain of Ctf4, necessary for the interaction of Ctf4 with Mms22, an adaptor protein of the Rtt101-Mms1 E3 ubiquitin ligase, is required for the function of the H3 lysine 56 acetylation pathway, suggesting that replicative stress promotes the interaction between Ctf4 and Mms22. Taken together, our results indicate that Ctf4 is an essential member of the H3 lysine 56 acetylation pathway and provide novel mechanistic insights into understanding the role of H3 lysine 56 acetylation in maintaining genome stability upon replication stress.