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Endogenous RNA interference (RNAi) pathways regulate a wide range of cellular processes in diverse eukaryotes, yet in the ciliated eukaryote, Tetrahymena thermophila, the cellular purpose of RNAi pathways that generate ∼23-24 nucleotide (nt) small (s)RNAs has remained unknown. Here, we investigated the phenotypic and gene expression impacts on vegetatively growing cells when genes involved in ∼23-24 nt sRNA biogenesis are disrupted. We observed slower proliferation and increased expression of genes involved in DNA metabolism and chromosome organization and maintenance in sRNA biogenesis mutants RSP1Δ, RDN2Δ, and RDF2Δ. In addition, RSP1Δ and RDN2Δ cells frequently exhibited enlarged chromatin extrusion bodies, which are nonnuclear, DNA-containing structures that may be akin to mammalian micronuclei. Expression of homologous recombination factor Rad51 was specifically elevated in RSP1Δ and RDN2Δ strains, with Rad51 and double-stranded DNA break marker γ-H2A.X localized to discrete macronuclear foci. In addition, an increase in Rad51 and γ-H2A.X foci was also found in knockouts of TWI8, a macronucleus-localized PIWI protein. Together, our findings suggest that an evolutionarily conserved role for RNAi pathways in maintaining genome integrity may be extended even to the early branching eukaryotic lineage that gave rise to Tetrahymena thermophila.

Codon bias and mRNA folding strength (mF) are hypothesized molecular mechanisms by which polymorphisms in genes modify protein expression. Natural patterns of codon bias and mF across genes as well as effects of altering codon bias and mF suggest the influence of these two mechanisms may vary depending on the specific location of polymorphisms within a transcript. Despite the central role codon bias and mF may play in natural trait variation within populations, systematic studies of how polymorphic codon bias and mF relate to protein expression variation are lacking. To address this need, we analyzed genomic, transcriptomic, and proteomic data for 22 Saccharomyces cerevisiae isolates, estimated protein accumulation for each allele of 1620 genes as the log of protein molecules per RNA molecule (logPPR), and built linear mixed effects models associating allelic variation in codon bias and mF with allelic variation in logPPR. We found codon bias and mF interact synergistically in a positive association with logPPR and this interaction explains almost all the effect of codon bias and mF. We examined how the locations of polymorphisms within transcripts influence their effects and found that codon bias primarily acts through polymorphisms in domain encoding and 3’ coding sequences while mF acts most significantly through coding sequences with weaker effects from UTRs. Our results present the most comprehensive characterization to date of how polymorphisms in transcripts influence protein expression.

The discovery that experimental delivery of dsRNA can induce gene silencing at target genes revolutionized genetics research, by both uncovering essential biological processes and creating new tools for developmental geneticists. However, wild-type C. elegans strains vary dramatically in their response to exogenous RNAi, challenging our characterization of RNAi in the lab relative to its activity and significance in nature. Here, we investigate why some strains fail to mount a robust RNAi response to germline targets. We observe diversity in mechanism: in some strains, the response is stochastic, either on or off among individuals, while in others the response is consistent but delayed. Increased activity of the Argonaute PPW-1, which is required for germline RNAi in the laboratory strain N2, rescues the response in some strains, but dampens it further in others. Across strains, we observe variability in expression of known RNAi genes and strain-specific instances of pseudogenization and allelic divergence. Our results support the conclusions that Argonautes share overlapping functions, that germline RNAi incompetence is strain-specific but likely caused by genetic variants at common genes, and that RNAi pathways are evolving rapidly and dynamically. This work expands our understanding of RNAi by identifying conserved and variable pathway components, and it offers new access into characterizing gene function, identifying pathway interactions, and elucidating the biological significance of RNAi.

Endogenous RNA interference (RNAi) pathways regulate a wide range of cellular processes in diverse eukaryotes, yet in the ciliated eukaryote, Tetrahymena thermophila, the cellular purpose of RNAi pathways that generate ∼23–24 nucleotide (nt) small (s)RNAs has remained unknown. Here, we investigated the phenotypic and gene expression impacts on vegetatively growing cells when genes involved in ∼23–24 nt sRNA biogenesis are disrupted. We observed slower proliferation and increased expression of genes involved in DNA metabolism and chromosome organization and maintenance in sRNA biogenesis mutants RSP1Δ, RDN2Δ, and RDF2Δ. In addition, RSP1Δ and RDN2Δ cells frequently exhibited enlarged chromatin extrusion bodies, which are nonnuclear, DNA-containing structures that may be akin to mammalian micronuclei. Expression of homologous recombination factor Rad51 was specifically elevated in RSP1Δ and RDN2Δ strains, with Rad51 and double-stranded DNA break marker γ-H2A.X localized to discrete macronuclear foci. In addition, an increase in Rad51 and γ-H2A.X foci was also found in knockouts of TWI8, a macronucleus-localized PIWI protein. Together, our findings suggest that an evolutionarily conserved role for RNAi pathways in maintaining genome integrity may be extended even to the early branching eukaryotic lineage that gave rise to Tetrahymena thermophila.

IntroductionHypoglycaemia is a frequent adverse event and major barrier for achieving optimal blood glucose levels in people with type 1 or type 2 diabetes using insulin. The Hypo-RESOLVE (Hypoglycaemia—Redefining SOLutions for better liVEs) consortium aims to further our understanding of the day-to-day impact of hypoglycaemia. The Hypo-METRICS (Hypoglycaemia—MEasurement, ThResholds and ImpaCtS) application (app) is a novel app for smartphones. This app is developed as part of the Hypo-RESOLVE project, using ecological momentary assessment methods that will minimise recall bias and allow for robust investigation of the day-to-day impact of hypoglycaemia. In this paper, the development and planned psychometric analyses of the app are described.Methods and analysisThe three phases of development of the Hypo-METRICS app are: (1) establish a working group—comprising diabetologists, psychologists and people with diabetes—to define the problem and identify relevant areas of daily functioning; (2) develop app items, with user-testing, and implement into the app platform; and (3) plan a large-scale, multicountry study including interviews with users and psychometric validation. The app includes 7 modules (29 unique items) assessing: self-report of hypoglycaemic episodes (during the day and night, respectively), sleep quality, well-being/cognitive function, social interactions, fear of hypoglycaemia/hyperglycaemia and work/productivity. The app is designed for use within three fixed time intervals per day (morning, afternoon and evening). The first version was released mid-2020 for use (in conjunction with continuous glucose monitoring and activity tracking) in the Hypo-METRICS study; an international observational longitudinal study. As part of this study, semistructured user-experience interviews and psychometric analyses will be conducted.Ethics and disseminationUse of the novel Hypo-METRICS app in a multicountry clinical study has received ethical approval in each of the five countries involved (Oxford B Research Ethics Committee, CMO Region Arnhem-Nijmegen, Ethikkommission der Medizinischen Universität Graz, Videnskabsetisk Komite for Region Hovedstaden and the Comite Die Protection Des Personnes SUD Mediterranne IV). The results from the study will be published in peer review journals and presented at national and international conferences.Trial registration numberNCT04304963.

Although mRNA is a necessary precursor to protein, several studies have argued that the relationship between mRNA and protein levels is often weak. This claim undermines the functional relevance of conclusions based on quantitative analyses of mRNA levels, which are ubiquitous in modern biology from the single gene to the whole genome scale. Furthermore, if post-translational processes vary between strains and species, then comparative studies based on mRNA alone would miss an important driver of diversity. However, gene expression is dynamic, and most studies examining relationship between mRNA and protein levels at the genome scale have analyzed single timepoints. We measure yeast gene expression after pheromone exposure and show that, for most genes, protein timecourses can be predicted from mRNA timecourses through a simple, gene-specific, generative model. By comparing model parameters and predictions between strains, we find that while mRNA variation often leads to protein differences, evolution also manipulates protein-specific processes to amplify or buffer transcriptional regulation.

We provide guidelines for using statistical methods to analyze the types of experiments reported in cellular and molecular biology journals such as Molecular Biology of the Cell. Our aim is to help experimentalists use these methods skillfully, avoid mistakes, and extract the maximum amount of information from their laboratory work. We focus on comparing the average values of control and experimental samples. A Supplemental Tutorial provides examples of how to analyze experimental data using R software.

Resolving the genetic complexity of heritable phenotypic variation is fundamental to understanding the mechanisms of evolution and the etiology of human disease. Trait variation among isolates from genetically efficient model organisms offers the opportunity to dissect genetic architectures and identify the molecular mechanisms of causation. Here we present a genetic analysis of loss of sensitivity to gene knockdown via exogenous RNA interference in the germline of a wild isolate of the roundworm Caenorhabditis elegans. We find that the loss of RNA interference sensitivity in the wild isolate CB4856 is recessive to the sensitivity of the lab strain N2. A cross of the strains produced F2 with intermediate sensitivities, and the segregation of the trait among F2s strongly deviated from a single locus recessive allele expectation. Linkage analysis in recombinant inbred lines derived from CB4856 and N2 identified a single significant locus on chromosome I that includes the argonaute gene ppw-1. The alleles for ppw-1 were unable to explain the sensitivity of 18 (12.1%) of the recombinant inbred lines. Complementation tests and F2 segregation analysis of these recombinant inbred lines revealed cases of complex epistatic suppression and enhancement of the effects of ppw-1. We conclude that the variation in RNA interference sensitivity between CB4856 and N2 likely involves the nonadditive interactions of eight or more genes in addition to ppw-1.

Heritable variation in gene expression patterns plays a fundamental role in trait variation and evolution, making understanding the mechanisms by which genetic variation acts on gene expression patterns a major goal for biology. Both theoretical and empirical work have largely focused on variation in steady-state mRNA levels and mRNA synthesis rates, particularly of protein-coding genes. Yet in order for this variation to affect higher order traits it must lead to differences at the protein level. Variation in protein-specific processes including protein synthesis rates and protein decay rates could amplify, mask, or even reverse effects transmitted from the transcript level, but the extent to which this happens is unclear. Moreover, mechanisms that underlie protein expression variation under dynamic conditions have not been examined. To address this challenge, we analyzed how mRNA and protein expression dynamics covary between two strains ofSaccharomyces cerevisiaeduring mating pheromone response. Although divergentsteady-statemRNA expression levels explained divergentsteady-stateprotein levels for four out of five genes in our study, the same was true for only one out of five genes for expressiondynamics. By integrating decay rate and allele-specific protein expression analyses, we resolved that expression divergence for Fig1p was caused by genetic variation acting intranson protein synthesis rate, expression divergence for Ina1p was caused bycis-by-transepistatic effects on transcript level and protein synthesis rate, and expression divergence for Fus3p and Tos6p were caused by divergence in protein synthesis rates. Our study demonstrates that steady-state analysis of gene expression is insufficient to understand the impact of genetic variation on gene expression variation. An integrated and dynamic approach to gene expression analysis - comparing mRNA levels, protein levels, protein decay rates, and allele-specific protein expression - allows for a detailed analysis of the genetic mechanisms underlying protein expression divergences.

Dermal penetration and absorption of jet fuels in general, and JP-8 in particular, is not well understood, even though government and industry, worldwide, use over 4.5 billion gallons of JP-8 per year. Exposures to JP-8 can occur from vapor, liquid, or aerosol. Inhalation and dermal exposure are the most prevalent routes. JP-8 may cause irritation during repeated or prolonged exposures, but it is unknown whether systemic toxicity can occur from dermal penetration of fuels. The purpose of this investigation was to measure the penetration and absorption of JP-8 and its major constituents with rat skin, so that the potential for effects with human exposures can be assessed. We used static diffusion cells to measure both the flux of JP-8 and components across the skin and the kinetics of absorption into the skin. Total flux of the hydrocarbon components was 20.3 micrograms/cm(2)/h. Thirteen individual components of JP-8 penetrated into the receptor solution. The fluxes ranged from a high of 51.5 micrograms/cm(2)/h (an additive, diethylene glycol monomethyl ether) to a low of 0.334 micrograms/cm(2)/h (tridecane). Aromatic components penetrated most rapidly. Six components (all aliphatic) were identified in the skin. Concentrations absorbed into the skin at 3.5 h ranged from 0.055 micrograms per gram skin (tetradecane) to 0.266 micrograms per gram skin (undecane). These results suggest: (1) that JP-8 penetration will not cause systemic toxicity because of low fluxes of all the components; and (2) the absorption of aliphatic components into the skin may be a cause of skin irritation.

Recombinant inbred lines (RILs) are a collection of strains that can be used to map quantitative trait loci. Parent strains are crossed to create recombinants that are then inbred to isogenicity, resulting in a permanent resource for trait mapping and analysis. Here I describe the process of designing and constructing RILs. This consists of the following steps. Parent strains are selected based on phenotype, marker availability, and compatibility, and they may be genetically engineered to remove unwanted variation or to introduce reporters. A construction design scheme is determined, including the target population size, if and how advanced intercrossing will be done, and the number of generations of inbreeding. Parent crosses and F1 crosses are performed to create an F2 population. Depending on design, advanced intercrossing may be implemented to increase mapping resolution through the accumulation of additional meiotic crossover events. Finally, lines are inbred to create genetically stable recombinant lines. I discuss tips and techniques for maximizing mapping power and resolution and minimizing resource investment for each stage of the process.

Recombinant inbred lines (RILs) are a collection of strains that can be used to map quantitative trait loci. Parent strains are crossed to create recombinants that are then inbred to isogenicity, resulting in a permanent resource for trait mapping and analysis. Here I describe the process of designing and constructing RILs. This consists of the following steps. Parent strains are selected based on phenotype, marker availability, and compatibility, and they may be genetically engineered to remove unwanted variation or to introduce reporters. A construction design scheme is determined, including the target population size, if and how advanced intercrossing will be done, and the number of generations of inbreeding. Parent crosses and F1 crosses are performed to create an F2 population. Depending on design, advanced intercrossing may be implemented to increase mapping resolution through the accumulation of additional meiotic crossover events. Finally, lines are inbred to create genetically stable recombinant lines. I discuss tips and techniques for maximizing mapping power and resolution and minimizing resource investment for each stage of the process.

The hydraulic fluid oil polychlorotrifluoroethylene (PCTFE) is hepato- and nephrotoxic in the rat. Male Fischer 344 rats were exposed to PCTFE either for a single 6-hr exposure (0.5 or 0.25 mg/liter) or daily 5 days/week, 6 hr/day, for 13 weeks (0.5, 0.25, or 0.01 mg/liter). Blood, tissue, and urinary PCTFE concentrations measured postexposure were used to develop a physiologically based pharmacokinetic (PB-PK) model. The PCTFE hydraulic fluid used was a mixture of trimeric and tetrameric oligomers with minor amounts of other chain lengths. The PB-PK model was designed to describe the behavior, not of individual oligomers, but of total mass for the trimer and tetramer in each tissue. Partition coefficients were estimated using the model to optimize tissue/blood concentration ratios measured at the end of the 13-week exposure. First-order metabolic rate constants for both trimeric (2.0 hr-1) and tetrameric (1.0 hr-1) portions were estimated by optimization against urinary fluoride data assuming release of 0.77 mole fluoride per mole trimer and 0.844 mole fluoride per mole tetramer metabolized. To obtain accurate simulation of pharmacokinetic data it was necessary to hypothesize two fat compartments with diffusion-limited exchange of PCTFE oligomer with the blood. Relative concentrations of trimer and tetramer in venous blood, liver, and fat after a single 6-hr exposure were proportional to inhaled concentrations. Tetramer accumulated preferentially with multiple exposure. Components of PCTFE were metabolized to carboxylic acids with release of fluoride. Due to their persistence tetrameric oligomers appear to be more important than trimeric oligomers as causative agents of PCTFE hepato- and nephrotoxicity in the rat.

Identifying the genomic regions bound by sequence-specific regulatory factors is central both to deciphering the complex DNA cis-regulatory code that controls transcription in metazoans and to determining the range of genes that shape animal morphogenesis. We used whole-genome tiling arrays to map sequences bound in Drosophila melanogaster embryos by the six maternal and gap transcription factors that initiate anterior–posterior patterning. We find that these sequence-specific DNA binding proteins bind with quantitatively different specificities to highly overlapping sets of several thousand genomic regions in blastoderm embryos. Specific high- and moderate-affinity in vitro recognition sequences for each factor are enriched in bound regions. This enrichment, however, is not sufficient to explain the pattern of binding in vivo and varies in a context-dependent manner, demonstrating that higher-order rules must govern targeting of transcription factors. The more highly bound regions include all of the over 40 well-characterized enhancers known to respond to these factors as well as several hundred putative new cis-regulatory modules clustered near developmental regulators and other genes with patterned expression at this stage of embryogenesis. The new targets include most of the microRNAs (miRNAs) transcribed in the blastoderm, as well as all major zygotically transcribed dorsal–ventral patterning genes, whose expression we show to be quantitatively modulated by anterior–posterior factors. In addition to these highly bound regions, there are several thousand regions that are reproducibly bound at lower levels. However, these poorly bound regions are, collectively, far more distant from genes transcribed in the blastoderm than highly bound regions; are preferentially found in protein-coding sequences; and are less conserved than highly bound regions. Together these observations suggest that many of these poorly bound regions are not involved in early-embryonic transcriptional regulation, and a significant proportion may be nonfunctional. Surprisingly, for five of the six factors, their recognition sites are not unambiguously more constrained evolutionarily than the immediate flanking DNA, even in more highly bound and presumably functional regions, indicating that comparative DNA sequence analysis is limited in its ability to identify functional transcription factor targets., Author Summary One of the largest classes of regulatory proteins in animals, sequence-specific DNA binding transcription factors determine in which cells genes will be expressed and so control the development of an animal from a single cell to a morphologically complex adult. Understanding how this process is coordinated depends on knowing the number and types of genes that each transcription factor binds and regulates. Using immunoprecipitation of in vivo crosslinked chromatin coupled with DNA microarray hybridization (ChIP/chip), we have determined the genomic binding sites in early embryos of six transcription factors that play a crucial role in early development of the fruit fly Drosophila melanogaster. We find that these proteins bind to several thousand genomic regions that lie close to approximately half the protein coding genes. Although this is a much larger number of genes than these factors are generally thought to regulate, we go on to show that whereas the more highly bound genes generally look to be functional targets, many of the genes bound at lower levels do not appear to be regulated by these factors. Our conclusions differ from those of other groups who have not distinguished between different levels of DNA binding in vivo using similar assays and who have generally assumed that all detected binding is functional., ChIP/chip analysis indicates that sequence-specific transcription factors bind to overlapping sets of thousands of genomic regions in Drosophila embryos, but most regions are bound at low levels and many may not be functional targets of these factors.

Affiliations des auteurs : cf page 216 de l'article; International audience; Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

The phylogenetic relationship of the now fully sequenced species Drosophila erecta and D. yakuba with respect to the D. melanogaster species complex has been a subject of controversy. All three possible groupings of the species have been reported in the past, though recent multi-gene studies suggest that D. erecta and D. yakuba are sister species. Using the whole genomes of each of these species as well as the four other fully sequenced species in the subgenus Sophophora, we set out to investigate the placement of D. erecta and D. yakuba in the D. melanogaster species group and to understand the cause of the past incongruence. Though we find that the phylogeny grouping D. erecta and D. yakuba together is the best supported, we also find widespread incongruence in nucleotide and amino acid substitutions, insertions and deletions, and gene trees. The time inferred to span the two key speciation events is short enough that under the coalescent model, the incongruence could be the result of incomplete lineage sorting. Consistent with the lineage-sorting hypothesis, substitutions supporting the same tree were spatially clustered. Support for the different trees was found to be linked to recombination such that adjacent genes support the same tree most often in regions of low recombination and substitutions supporting the same tree are most enriched roughly on the same scale as linkage disequilibrium, also consistent with lineage sorting. The incongruence was found to be statistically significant and robust to model and species choice. No systematic biases were found. We conclude that phylogenetic incongruence in the D. melanogaster species complex is the result, at least in part, of incomplete lineage sorting. Incomplete lineage sorting will likely cause phylogenetic incongruence in many comparative genomics datasets. Methods to infer the correct species tree, the history of every base in the genome, and comparative methods that control for and/or utilize this information will be valuable advancements for the field of comparative genomics., Synopsis To take full advantage of the growing number of genome sequences from different organisms, it is necessary to understand the evolutionary relationships (phylogeny) between organisms. Unfortunately, phylogenies inferred from individual genes often conflict, reflecting either poor inferences or real variation in the history of genes. In this study, the authors examine relationships within the Drosophila melanogaster species subgroup, a group of flies with three fully sequenced species in which phylogeny has been a source of controversy. Although the bulk of the data support a phylogeny with Drosophila melanogaster as an outgroup to sister species Drosophila erecta and Drosophila yakuba, large portions of their genes support alternative phylogenies. According to the authors, the most plausible explanation for these observations is that polymorphisms in the ancestral population were maintained during the two rapid speciation events that led to these species. Subsequent to speciation, polymorphisms were randomly fixed in each species, and in some cases non-sister species fixed the same ancestral polymorphisms, while sister species did not. In these cases the genes are correctly inferred to have conflicting phylogenies. The authors note that rapid speciation events will often lead to such conflict, which needs to be accounted for in evolutionary analyses.

Background Molecular evolutionary studies of noncoding sequences rely on multiple alignments. Yet how multiple alignment accuracy varies across sequence types, tree topologies, divergences and tools, and further how this variation impacts specific inferences, remains unclear. Results Here we develop a molecular evolution simulation platform, CisEvolver, with models of background noncoding and transcription factor binding site evolution, and use simulated alignments to systematically examine multiple alignment accuracy and its impact on two key molecular evolutionary inferences: transcription factor binding site conservation and divergence estimation. We find that the accuracy of multiple alignments is determined almost exclusively by the pairwise divergence distance of the two most diverged species and that additional species have a negligible influence on alignment accuracy. Conserved transcription factor binding sites align better than surrounding noncoding DNA yet are often found to be misaligned at relatively short divergence distances, such that studies of binding site gain and loss could easily be confounded by alignment error. Divergence estimates from multiple alignments tend to be overestimated at short divergence distances but reach a tool specific divergence at which they cease to increase, leading to underestimation at long divergences. Our most striking finding was that overall alignment accuracy, binding site alignment accuracy and divergence estimation accuracy vary greatly across branches in a tree and are most accurate for terminal branches connecting sister taxa and least accurate for internal branches connecting sub-alignments. Conclusion Our results suggest that variation in alignment accuracy can lead to errors in molecular evolutionary inferences that could be construed as biological variation. These findings have implications for which species to choose for analyses, what kind of errors would be expected for a given set of species and how multiple alignment tools and phylogenetic inference methods might be improved to minimize or control for alignment errors.

We introduce a method (MONKEY) to identify conserved transcription-factor binding sites in multispecies alignments. MONKEY employs probabilistic models of factor specificity and binding-site evolution, on which basis we compute the likelihood that putative sites are conserved and assign statistical significance to each hit. Using genomes from the genus Saccharomyces, we illustrate how the significance of real sites increases with evolutionary distance and explore the relationship between conservation and function.

In follow-up studies to this work [1], we have identified an error in a single line of code responsible for parsing BLASTZ [2] alignments that affects our previously published results for this alignment tool. This error resulted in a reduction in overall alignment coverage, with a concomitant underestimation of alignment sensitivity and overestimation of alignment specificity. As BLASTZ is an important and widely used alignment tool, we present here the revised results of our performance evaluations for BLASTZ together with previously reported results for the other alignment tools studied, which have been subsequently verified (Figures 1-4). The general conclusions presented in [1] remain unchanged, although the following sections concerning BLASTZ performance must be modified in light of our recent findings.

Background: Numerous tools have been developed to align genomic sequences. However, their relative performance in specific applications remains poorly characterized. Alignments of proteincoding sequences typically have been benchmarked against "correct" alignments inferred from structural data. For noncoding sequences, where such independent validation is lacking, simulation provides an effective means to generate "correct" alignments with which to benchmark alignment tools. Results: Using rates of noncoding sequence evolution estimated from the genus Drosophila, we simulated alignments over a range of divergence times under varying models incorporating point substitution, insertion/deletion events, and short blocks of constrained sequences such as those found in cis-regulatory regions. We then compared "correct" alignments generated by a modified version of the ROSE simulation platform to alignments of the simulated derived sequences produced by eight pairwise alignment tools (Avid, BlastZ, Chaos, ClustalW, DiAlign, Lagan, Needle, and WABA) to determine the off-the-shelf performance of each tool. As expected, the ability to align noncoding sequences accurately decreases with increasing divergence for all tools, and declines faster in the presence of insertion/deletion evolution. Global alignment tools (Avid, ClustalW, Lagan, and Needle) typically have higher sensitivity over entire noncoding sequences as well as in constrained sequences. Local tools (BlastZ, Chaos, and WABA) have lower overall sensitivity as a consequence of incomplete coverage, but have high specificity to detect constrained sequences as well as high sensitivity within the subset of sequences they align. Tools such as DiAlign, which generate both local and global outputs, produce alignments of constrained sequences with both high sensitivity and specificity for divergence distances in the range of 1.25–3.0 substitutions per site. Conclusion: For species with genomic properties similar to Drosophila, we conclude that a single pair of optimally diverged species analyzed with a high performance alignment tool can yield accurate and specific alignments of functionally constrained noncoding sequences. Further algorithm development, optimization of alignment parameters, and benchmarking studies will be necessary to extract the maximal biological information from alignments of functional noncoding

Correction for: Li Xy, MacArthur S, Bourgon R, Nix D, Pollard DA, et al. (2008) Transcription factors bind thousands of active and inactive regions in the Drosophila blastoderm. PLoS Biol 6(2): e27. doi:10.1371/journal.pbio.0060027 The information in Table 1 for RNA polymerase II was incorrectly given for the form of the enzyme unphosphorylated at the C-terminal tail, which is recognized by the 8WG16 monoclonal antibody. The corrected version of the Table below gives the intended information for the enzyme phosphorylated at the C terminus, which is recognized by the H14 monoclonal antibody. Table 1 Number of Regions Bound by Transcription Factors