Benchmarking tools for the alignment of functional noncoding DNA

Accuracy of multiple sequence alignment methods in the reconstruction of transposable element families

The construction of a high-quality multiple sequence alignment (MSA) from copies of a transposable element (TE) is a critical step in the characterization of a new TE family. Most studies of MSA accuracy have been conducted on protein or RNA sequence families, where structural features and strong signals of selection may assist with alignment. Less attention has been given to the quality of sequence alignments involving neutrally evolving DNA sequences such as those resulting from TE replication. Transposable element sequences are challenging to align due to their wide divergence ranges, fragmentation, and predominantly-neutral mutation patterns. To gain insight into the effects of these properties on MSA accuracy, we developed a simulator of TE sequence evolution, and used it to generate a benchmark with which we evaluated the MSA predictions produced by several popular aligners, along with Refiner, a method we developed in the context of our RepeatModeler software. We find that MAFFT and Refiner generally outperform other aligners for low to medium divergence simulated sequences, while Refiner is uniquely effective when tasked with aligning high-divergent and fragmented instances of a family.

Methods for making multiple alignment of genomic sequences for severe acute respiratory syndrome coronavirus 2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 and caused a pandemic. To monitor the global transmission pattern of SARS-CoV-2, it is required to constantly update the phylogenetic tree of genomic sequences with 29.9 kb, which may be time consuming. Phylogenetic analysis of SARS-CoV-2 may be accelerated by making a multiple alignment of nucleotide sequences using the CPA (combining pairwise alignments) method, in which a pairwise alignment is made for a reference and each of other sequences, and the pairwise alignments are combined into a multiple alignment. Here it is shown from the analysis of 3729 genomic sequences for SARS-CoV-2 and outgroup strains that the CPA method can produce a multiple alignment with an elevated or a reduced number of variable sites depending on the reference compared to the OMA (ordinary multiple alignment) method, which was considered to be the most reliable. In particular, the topology of the phylogenetic tree constructed from the multiple alignment made using the CPA method adopting the outgroup sequence as the reference was considerably different from that using the OMA method, suggesting that the outgroup sequence may not be suitable as the reference in the CPA method.

MySSP: Non-stationary evolutionary sequence simulation, including indels

MySSP is a new program for the simulation of DNA sequence evolution across a phylogenetic tree. Although many programs are available for sequence simulation, MySSP is unique in its inclusion of indels, flexibility in allowing for non-stationary patterns, and output of ancestral sequences. Some of these features can individually be found in existing programs, but have not all have been previously available in a single package.

A review on multiple sequence alignment from the perspective of genetic algorithm

Sequence alignment is an active research area in the field of bioinformatics. It is also a crucial task as it guides many other tasks like phylogenetic analysis, function, and/or structure prediction of biological macromolecules like DNA, RNA, and Protein. Proteins are the building blocks of every living organism. Although protein alignment problem has been studied for several decades, unfortunately, every available method produces alignment results differently for a single alignment problem. Multiple sequence alignment is characterized as a very high computational complex problem. Many stochastic methods, therefore, are considered for improving the accuracy of alignment. Among them, many researchers frequently use Genetic Algorithm. In this study, we have shown different types of the method applied in alignment and the recent trends in the multiobjective genetic algorithm for solving multiple sequence alignment. Many recent studies have demonstrated considerable progress in finding the alignment accuracy.

BLSSpeller: exhaustive comparative discovery of conserved cis-regulatory elements

MOTIVATION

The accurate discovery and annotation of regulatory elements remains a challenging problem. The growing number of sequenced genomes creates new opportunities for comparative approaches to motif discovery. Putative binding sites are then considered to be functional if they are conserved in orthologous promoter sequences of multiple related species. Existing methods for comparative motif discovery usually rely on pregenerated multiple sequence alignments, which are difficult to obtain for more diverged species such as plants. As a consequence, misaligned regulatory elements often remain undetected.

RESULTS

We present a novel algorithm that supports both alignment-free and alignment-based motif discovery in the promoter sequences of related species. Putative motifs are exhaustively enumerated as words over the IUPAC alphabet and screened for conservation using the branch length score. Additionally, a confidence score is established in a genome-wide fashion. In order to take advantage of a cloud computing infrastructure, the MapReduce programming model is adopted. The method is applied to four monocotyledon plant species and it is shown that high-scoring motifs are significantly enriched for open chromatin regions in Oryza sativa and for transcription factor binding sites inferred through protein-binding microarrays in O.sativa and Zea mays. Furthermore, the method is shown to recover experimentally profiled ga2ox1-like KN1 binding sites in Z.mays.

AVAILABILITY AND IMPLEMENTATION

BLSSpeller was written in Java. Source code and manual are available at http://bioinformatics.intec.ugent.be/blsspeller

CONTACT

Klaas.Vandepoele@psb.vib-ugent.be or jan.fostier@intec.ugent.be.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Association of obesity with serum leptin, adiponectin, and serotonin and gut microflora in beagle dogs

Background

Serotonin (5‐hydroxytryptamine, 5HT) is involved in hypothalamic regulation of energy consumption. Also, the gut microbiome can influence neuronal signaling to the brain through vagal afferent neurons. Therefore, serotonin concentrations in the central nervous system and the composition of the microbiota can be related to obesity.

Objective

To examine adipokine, and, serotonin concentrations, and the gut microbiota in lean dogs and dogs with experimentally induced obesity.

Animals

Fourteen healthy Beagle dogs were used in this study.

Methods

Seven Beagle dogs in the obese group were fed commercial food ad libitum, over a period of 6 months to increase their weight and seven Beagle dogs in lean group were fed a restricted amount of the same diet to maintain optimal body condition over a period of 6 months. Peripheral leptin, adiponectin, 5HT, and cerebrospinal fluid (CSF‐5HT) levels were measured by ELISA. Fecal samples were collected in lean and obese groups 6 months after obesity was induced. Targeted pyrosequencing of the 16S rRNA gene was performed using a Genome Sequencer FLX plus system.

Results

Leptin concentrations were higher in the obese group (1.98 ± 1.00) compared to those of the lean group (1.12 ± 0.07, P = .025). Adiponectin and 5‐hydroytryptamine of cerebrospinal fluid (CSF‐5HT) concentrations were higher in the lean group (27.1 ± 7.28) than in the obese group (14.4 ± 5.40, P = .018). Analysis of the microbiome revealed that the diversity of the microbial community was lower in the obese group. Microbes from the phylum Firmicutes (85%) were predominant group in the gut microbiota of lean dogs. However, bacteria from the phylum Proteobacteria (76%) were the predominant group in the gut microbiota of dogs in the obese group.

Conclusions and Clinical Importance

Decreased 5HT levels in obese group might increase the risk of obesity because of increased appetite. Microflora enriched with gram‐negative might be related with chronic inflammation status in obese dogs.

FOGSAA: Fast Optimal Global Sequence Alignment Algorithm

In this article we propose a Fast Optimal Global Sequence Alignment Algorithm, FOGSAA, which aligns a pair of nucleotide/protein sequences faster than any optimal global alignment method including the widely used Needleman-Wunsch (NW) algorithm. FOGSAA is applicable for all types of sequences, with any scoring scheme, and with or without affine gap penalty. Compared to NW, FOGSAA achieves a time gain of (70–90)% for highly similar nucleotide sequences (> 80% similarity), and (54–70)% for sequences having (30–80)% similarity. For other sequences, it terminates with an approximate score. For protein sequences, the average time gain is between (25–40)%. Compared to three heuristic global alignment methods, the quality of alignment is improved by about 23%–53%. FOGSAA is, in general, suitable for aligning any two sequences defined over a finite alphabet set, where the quality of the global alignment is of supreme importance.

Use of ChIP-Seq data for the design of a multiple promoter-alignment method

We address the challenge of regulatory sequence alignment with a new method, Pro-Coffee, a multiple aligner specifically designed for homologous promoter regions. Pro-Coffee uses a dinucleotide substitution matrix estimated on alignments of functional binding sites from TRANSFAC. We designed a validation framework using several thousand families of orthologous promoters. This dataset was used to evaluate the accuracy for predicting true human orthologs among their paralogs. We found that whereas other methods achieve on average 73.5% accuracy, and 77.6% when trained on that same dataset, the figure goes up to 80.4% for Pro-Coffee. We then applied a novel validation procedure based on multi-species ChIP-seq data. Trained and untrained methods were tested for their capacity to correctly align experimentally detected binding sites. Whereas the average number of correctly aligned sites for two transcription factors is 284 for default methods and 316 for trained methods, Pro-Coffee achieves 331, 16.5% above the default average. We find a high correlation between a method's performance when classifying orthologs and its ability to correctly align proven binding sites. Not only has this interesting biological consequences, it also allows us to conclude that any method that is trained on the ortholog data set will result in functionally more informative alignments.

Methods to detect selection on noncoding DNA

Vast tracts of noncoding DNA contain elements that regulate gene expression in higher eukaryotes. Describing these regulatory elements and understanding how they evolve represent major challenges for biologists. Advances in the ability to survey genome-scale DNA sequence data are providing unprecedented opportunities to use evolutionary models and computational tools to identify functionally important elements and the mode of selection acting on them in multiple species. This chapter reviews some of the current methods that have been developed and applied on noncoding DNA, what they have shown us, and how they are limited. Results of several recent studies reveal that a significantly larger fraction of noncoding DNA in eukaryotic organisms is likely to be functional than previously believed, implying that the functional annotation of most noncoding DNA in these organisms is largely incomplete. In Drosophila, recent studies have further suggested that a large fraction of noncoding DNA divergence observed between species may be the product of recurrent adaptive substitution. Similar studies in humans have revealed a more complex pattern, with signatures of recurrent positive selection being largely concentrated in conserved noncoding DNA elements. Understanding these patterns and the extent to which they generalize to other organisms awaits the analysis of forthcoming genome-scale polymorphism and divergence data from more species.

Evolutionary divergence and limits of conserved non-coding sequence detection in plant genomes

The discovery of regulatory motifs embedded in upstream regions of plants is a particularly challenging bioinformatics task. Previous studies have shown that motifs in plants are short compared with those found in vertebrates. Furthermore, plant genomes have undergone several diversification mechanisms such as genome duplication events which impact the evolution of regulatory motifs. In this article, a systematic phylogenomic comparison of upstream regions is conducted to further identify features of the plant regulatory genomes, the component of genomes regulating gene expression, to enable future de novo discoveries. The findings highlight differences in upstream region properties between major plant groups and the effects of divergence times and duplication events. First, clear differences in upstream region evolution can be detected between monocots and dicots, thus suggesting that a separation of these groups should be made when searching for novel regulatory motifs, particularly since universal motifs such as the TATA box are rare. Second, investigating the decay rate of significantly aligned regions suggests that a divergence time of ~100 mya sets a limit for reliable conserved non-coding sequence (CNS) detection. Insights presented here will set a framework to help identify embedded motifs of functional relevance by understanding the limits of bioinformatics detection for CNSs.

A genome alignment algorithm based on compression

BACKGROUND

Traditional genome alignment methods consider sequence alignment as a variation of the string edit distance problem, and perform alignment by matching characters of the two sequences. They are often computationally expensive and unable to deal with low information regions. Furthermore, they lack a well-principled objective function to measure the performance of sets of parameters. Since genomic sequences carry genetic information, this article proposes that the information content of each nucleotide in a position should be considered in sequence alignment. An information-theoretic approach for pairwise genome local alignment, namely XMAligner, is presented. Instead of comparing sequences at the character level, XMAligner considers a pair of nucleotides from two sequences to be related if their mutual information in context is significant. The information content of nucleotides in sequences is measured by a lossless compression technique.

RESULTS

Experiments on both simulated data and real data show that XMAligner is superior to conventional methods especially on distantly related sequences and statistically biased data. XMAligner can align sequences of eukaryote genome size with only a modest hardware requirement. Importantly, the method has an objective function which can obviate the need to choose parameter values for high quality alignment. The alignment results from XMAligner can be integrated into a visualisation tool for viewing purpose.

CONCLUSIONS

The information-theoretic approach for sequence alignment is shown to overcome the mentioned problems of conventional character matching alignment methods. The article shows that, as genomic sequences are meant to carry information, considering the information content of nucleotides is helpful for genomic sequence alignment.

AVAILABILITY

Downloadable binaries, documentation and data can be found at ftp://ftp.infotech.monash.edu.au/software/DNAcompress-XM/XMAligner/.

Issues in bioinformatics benchmarking: the case study of multiple sequence alignment

The post-genomic era presents many new challenges for the field of bioinformatics. Novel computational approaches are now being developed to handle the large, complex and noisy datasets produced by high throughput technologies. Objective evaluation of these methods is essential (i) to assure high quality, (ii) to identify strong and weak points of the algorithms, (iii) to measure the improvements introduced by new methods and (iv) to enable non-specialists to choose an appropriate tool. Here, we discuss the development of formal benchmarks, designed to represent the current problems encountered in the bioinformatics field. We consider several criteria for building good benchmarks and the advantages to be gained when they are used intelligently. To illustrate these principles, we present a more detailed discussion of benchmarks for multiple alignments of protein sequences. As in many other domains, significant progress has been achieved in the multiple alignment field and the datasets have become progressively more challenging as the existing algorithms have evolved. Finally, we propose directions for future developments that will ensure that the bioinformatics benchmarks correspond to the challenges posed by the high throughput data.

Comparative analysis of acute and chronic corticosteroid pharmacogenomic effects in rat liver: transcriptional dynamics and regulatory structures

Background

Comprehensively understanding corticosteroid pharmacogenomic effects is an essential step towards an insight into the underlying molecular mechanisms for both beneficial and detrimental clinical effects. Nevertheless, even in a single tissue different methods of corticosteroid administration can induce different patterns of expression and regulatory control structures. Therefore, rich in vivo datasets of pharmacological time-series with two dosing regimens sampled from rat liver are examined for temporal patterns of changes in gene expression and their regulatory commonalities.

Results

The study addresses two issues, including (1) identifying significant transcriptional modules coupled with dynamic expression patterns and (2) predicting relevant common transcriptional controls to better understand the underlying mechanisms of corticosteroid adverse effects. Following the orientation of meta-analysis, an extended computational approach that explores the concept of agreement matrix from consensus clustering has been proposed with the aims of identifying gene clusters that share common expression patterns across multiple dosing regimens as well as handling challenges in the analysis of microarray data from heterogeneous sources, e.g. different platforms and time-grids in this study. Six significant transcriptional modules coupled with typical patterns of expression have been identified. Functional analysis reveals that virtually all enriched functions (gene ontologies, pathways) in these modules are shown to be related to metabolic processes, implying the importance of these modules in adverse effects under the administration of corticosteroids. Relevant putative transcriptional regulators (e.g. RXRF, FKHD, SP1F) are also predicted to provide another source of information towards better understanding the complexities of expression patterns and the underlying regulatory mechanisms of those modules.

Conclusions

We have proposed a framework to identify significant coexpressed clusters of genes across multiple conditions experimented from different microarray platforms, time-grids, and also tissues if applicable. Analysis on rich in vivo datasets of corticosteroid time-series yielded significant insights into the pharmacogenomic effects of corticosteroids, especially the relevance to metabolic side-effects. This has been illustrated through enriched metabolic functions in those transcriptional modules and the presence of GRE binding motifs in those enriched pathways, providing significant modules for further analysis on pharmacogenomic corticosteroid effects.

Cgaln: fast and space-efficient whole-genome alignment

BACKGROUND

Whole-genome sequence alignment is an essential process for extracting valuable information about the functions, evolution, and peculiarities of genomes under investigation. As available genomic sequence data accumulate rapidly, there is great demand for tools that can compare whole-genome sequences within practical amounts of time and space. However, most existing genomic alignment tools can treat sequences that are only a few Mb long at once, and no state-of-the-art alignment program can align large sequences such as mammalian genomes directly on a conventional standalone computer.

RESULTS

We previously proposed the CGAT (Coarse-Grained AlignmenT) algorithm, which performs an alignment job in two steps: first at the block level and then at the nucleotide level. The former is "coarse-grained" alignment that can explore genomic rearrangements and reduce the sizes of the regions to be analyzed in the next step. The latter is detailed alignment within limited regions. In this paper, we present an update of the algorithm and the open-source program, Cgaln, that implements the algorithm. We compared the performance of Cgaln with those of other programs on whole genomic sequences of several bacteria and of some mammalian chromosome pairs. The results showed that Cgaln is several times faster and more memory-efficient than the best existing programs, while its sensitivity and accuracy are comparable to those of the best programs. Cgaln takes less than 13 hours to finish an alignment between the whole genomes of human and mouse in a single run on a conventional desktop computer with a single CPU and 2 GB memory.

CONCLUSIONS

Cgaln is not only fast and memory efficient but also effective in coping with genomic rearrangements. Our results show that Cgaln is very effective for comparison of large genomes, especially of intact chromosomal sequences. We believe that Cgaln provides novel viewpoint for reducing computational complexity and will contribute to various fields of genome science.

Towards realistic benchmarks for multiple alignments of non-coding sequences

BACKGROUND

With the continued development of new computational tools for multiple sequence alignment, it is necessary today to develop benchmarks that aid the selection of the most effective tools. Simulation-based benchmarks have been proposed to meet this necessity, especially for non-coding sequences. However, it is not clear if such benchmarks truly represent real sequence data from any given group of species, in terms of the difficulty of alignment tasks.

RESULTS

We find that the conventional simulation approach, which relies on empirically estimated values for various parameters such as substitution rate or insertion/deletion rates, is unable to generate synthetic sequences reflecting the broad genomic variation in conservation levels. We tackle this problem with a new method for simulating non-coding sequence evolution, by relying on genome-wide distributions of evolutionary parameters rather than their averages. We then generate synthetic data sets to mimic orthologous sequences from the Drosophila group of species, and show that these data sets truly represent the variability observed in genomic data in terms of the difficulty of the alignment task. This allows us to make significant progress towards estimating the alignment accuracy of current tools in an absolute sense, going beyond only a relative assessment of different tools. We evaluate six widely used multiple alignment tools in the context of Drosophila non-coding sequences, and find the accuracy to be significantly different from previously reported values. Interestingly, the performance of most tools degrades more rapidly when there are more insertions than deletions in the data set, suggesting an asymmetric handling of insertions and deletions, even though none of the evaluated tools explicitly distinguishes these two types of events. We also examine the accuracy of two existing tools for annotating insertions versus deletions, and find their performance to be close to optimal in Drosophila non-coding sequences if provided with the true alignments.

CONCLUSION

We have developed a method to generate benchmarks for multiple alignments of Drosophila non-coding sequences, and shown it to be more realistic than traditional benchmarks. Apart from helping to select the most effective tools, these benchmarks will help practitioners of comparative genomics deal with the effects of alignment errors, by providing accurate estimates of the extent of these errors.

Patterns of DNA-sequence divergence between Drosophila miranda and D. pseudoobscura

Contrary to the classical view, a large amount of non-coding DNA seems to be selectively constrained in Drosophila and other species. Here, using Drosophila miranda BAC sequences and the Drosophila pseudoobscura genome sequence, we aligned coding and non-coding sequences between D. pseudoobscura and D. miranda, and investigated their patterns of evolution. We found two patterns that have previously been observed in comparisons between Drosophila melanogaster and its relatives. First, there is a negative correlation between intron divergence and intron length, suggesting that longer non-coding sequences may contain more regulatory elements than shorter sequences. Our other main finding is a negative correlation between the rate of non-synonymous substitutions (d(N)) and codon usage bias (F(op)), showing that fast-evolving genes have a lower codon usage bias, consistent with strong positive selection interfering with weak selection for codon usage.

A model of evolution and structure for multiple sequence alignment

We have developed a phylogeny-aware progressive alignment method that recognizes insertions and deletions as distinct evolutionary events and thus avoids systematic errors created by traditional alignment methods. We now extend this method to simultaneously model regional heterogeneity and evolution. This novel method can be flexibly adapted to alignment of nucleotide or amino acid sequences evolving under processes that vary over genomic regions and, being fully probabilistic, provides an estimate of regional heterogeneity of the evolutionary process along the alignment and a measure of local reliability of the solution. Furthermore, the evolutionary modelling of substitution process permits adjusting the sensitivity and specificity of the alignment and, if high specificity is aimed at, leaving sequences unaligned when their divergence is beyond a meaningful detection of homology.

Alignment and prediction of cis-regulatory modules based on a probabilistic model of evolution

Cross-species comparison has emerged as a powerful paradigm for predicting cis-regulatory modules (CRMs) and understanding their evolution. The comparison requires reliable sequence alignment, which remains a challenging task for less conserved noncoding sequences. Furthermore, the existing models of DNA sequence evolution generally do not explicitly treat the special properties of CRM sequences. To address these limitations, we propose a model of CRM evolution that captures different modes of evolution of functional transcription factor binding sites (TFBSs) and the background sequences. A particularly novel aspect of our work is a probabilistic model of gains and losses of TFBSs, a process being recognized as an important part of regulatory sequence evolution. We present a computational framework that uses this model to solve the problems of CRM alignment and prediction. Our alignment method is similar to existing methods of statistical alignment but uses the conserved binding sites to improve alignment. Our CRM prediction method deals with the inherent uncertainties of binding site annotations and sequence alignment in a probabilistic framework. In simulated as well as real data, we demonstrate that our program is able to improve both alignment and prediction of CRM sequences over several state-of-the-art methods. Finally, we used alignments produced by our program to study binding site conservation in genome-wide binding data of key transcription factors in the Drosophila blastoderm, with two intriguing results: (i) the factor-bound sequences are under strong evolutionary constraints even if their neighboring genes are not expressed in the blastoderm and (ii) binding sites in distal bound sequences (relative to transcription start sites) tend to be more conserved than those in proximal regions. Our approach is implemented as software, EMMA (Evolutionary Model-based cis-regulatory Module Analysis), ready to be applied in a broad biological context.

Comparison of noncoding DNA sequences across species has the potential to significantly improve our understanding of gene regulation and our ability to annotate regulatory regions of the genome. This potential is evident from recent publications analyzing 12 Drosophila genomes for regulatory annotation. However, because noncoding sequences are much less structured than coding sequences, their interspecies comparison presents technical challenges, such as ambiguity about how to align them and how to predict transcription factor binding sites, which are the fundamental units that make up regulatory sequences. This article describes how to build an integrated probabilistic framework that performs alignment and binding site prediction simultaneously, in the process improving the accuracy of both tasks. It defines a stochastic model for the evolution of entire “cis-regulatory modules,” with its highlight being a novel theoretical treatment of the commonly observed loss and gain of binding sites during evolution. This new evolutionary model forms the backbone of newly developed software for the prediction of new cis-regulatory modules, alignment of known modules to elucidate general principles of cis-regulatory evolution, or both. The new software is demonstrated to provide benefits in performance of these two crucial genomics tasks.

Dispensability of mammalian DNA

In the lab, the cis-regulatory network seems to exhibit great functional redundancy. Many experiments testing enhancer activity of neighboring cis-regulatory elements show largely overlapping expression domains. Of recent interest, mice in which cis-regulatory ultraconserved elements were knocked out showed no obvious phenotype, further suggesting functional redundancy. Here, we present a global evolutionary analysis of mammalian conserved nonexonic elements (CNEs), and find strong evidence to the contrary. Given a set of CNEs conserved between several mammals, we characterize functional dispensability as the propensity for the ancestral element to be lost in mammalian species internal to the spanned species tree. We show that ultraconserved-like elements are over 300-fold less likely than neutral DNA to have been lost during rodent evolution. In fact, many thousands of noncoding loci under purifying selection display near uniform indispensability during mammalian evolution, largely irrespective of nucleotide conservation level. These findings suggest that many genomic noncoding elements possess functions that contribute noticeably to organism fitness in naturally evolving populations.

The cis-regulatory map of Shewanella genomes

While hundreds of microbial genomes are sequenced, the challenge remains to define their cis-regulatory maps. Here, we present a comparative genomic analysis of the cis-regulatory map of Shewanella oneidensis, an important model organism for bioremediation because of its extraordinary abilities to use a wide variety of metals and organic molecules as electron acceptors in respiration. First, from the experimentally verified transcriptional regulatory networks of Escherichia coli, we inferred 24 DNA motifs that are conserved in S. oneidensis. We then applied a new comparative approach on five Shewanella genomes that allowed us to systematically identify 194 nonredundant palindromic DNA motifs and corresponding regulons in S. oneidensis. Sixty-four percent of the predicted motifs are conserved in at least three of the seven newly sequenced and distantly related Shewanella genomes. In total, we obtained 209 unique DNA motifs in S. oneidensis that cover 849 unique transcription units. Besides conservation in other genomes, 77 of these motifs are supported by at least one additional type of evidence, including matching to known transcription factor binding motifs and significant functional enrichment or expression coherence of the corresponding target genes. Using the same approach on a more focused gene set, 990 differentially expressed genes derived from published microarray data of S. oneidensis during exposure to metal ions, we identified 31 putative cis-regulatory motifs (16 with at least one type of additional supporting evidence) that are potentially involved in the process of metal reduction. The majority (18/31) of those motifs had been found in our whole-genome comparative approach, further demonstrating that such an approach is capable of uncovering a large fraction of the regulatory map of a genome even in the absence of experimental data. The integrated computational approach developed in this study provides a useful strategy to identify genome-wide cis-regulatory maps and a novel avenue to explore the regulatory pathways for particular biological processes in bacterial systems.

Phylogenetic simulation of promoter evolution: estimation and modeling of binding site turnover events and assessment of their impact on alignment tools

BACKGROUND

The phenomenon of functional site turnover has important implications for the study of regulatory region evolution, such as for promoter sequence alignments and transcription factor binding site (TFBS) identification. At present, it remains difficult to estimate TFBS turnover rates on real genomic sequences, as reliable mappings of functional sites across related species are often not available. As an alternative, we introduce a flexible new simulation system, Phylogenetic Simulation of Promoter Evolution (PSPE), designed to study functional site turnovers in regulatory sequences.

RESULTS

Using PSPE, we study replacement turnover rates of different individual TFBSs and simple modules of two sites under neutral evolutionary functional constraints. We find that TFBS replacement turnover can happen rapidly in promoters, and turnover rates vary significantly among different TFBSs and modules. We assess the influence of different constraints such as insertion/deletion rate and translocation distances. Complementing the simulations, we give simple but effective mathematical models for TFBS turnover rate prediction. As one important application of PSPE, we also present a first systematic evaluation of multiple sequence aligners regarding their capability of detecting TFBSs in promoters with site turnovers.

CONCLUSION

PSPE allows researchers for the first time to investigate TFBS replacement turnovers in promoters systematically. The assessment of alignment tools points out the limitations of current approaches to identify TFBSs in non-coding sequences, where turnover events of functional sites may happen frequently, and where we are interested in assessing the similarity on the functional level. PSPE is freely available at the authors' website.

Prediction of genomic functional elements

As the number of sequenced genomes increases, the ability to deduce genome function becomes increasingly salient. For many genome sequences, the only annotation that will be available for the foreseeable future will be based on computational predictions and comparisons with functional elements in related species. Here we discuss computational approaches for automated genome-wide annotation of functional elements in mammalian genomes. These include methods for ab initio and comparative gene-structure predictions. Gene features such as intron splice sites, 3' untranslated regions, promoters, and cis-regulatory elements are discussed, as is a novel method for predicting DNaseI hypersensitive sites. Recent methodologies for predicting noncoding RNA genes, including microRNA genes and their targets, are also reviewed.

Approaches to comparative sequence analysis: towards a functional view of vertebrate genomes

The comparison of genomic sequences is now a common approach to identifying and characterizing functional regions in vertebrate genomes. However, for theoretical reasons and because of practical issues, the generation of these data sets is non-trivial and can have many pitfalls. We are currently seeing an explosion of comparative sequence data, the benefits and limitations of which need to be disseminated to the scientific community. This Review provides a critical overview of the different types of sequence data that are available for analysis and of contemporary comparative sequence analysis methods, highlighting both their strengths and limitations. Approaches to determining the biological significance of constrained sequence are also explored.

Large-scale analysis of transcriptional cis-regulatory modules reveals both common features and distinct subclasses

Analysis of 280 experimentally-verified cis-regulatory modules from Drosophila reveal features both common to all and unique to distinct subclasses of modules.

Background

Transcriptional cis-regulatory modules (for example, enhancers) play a critical role in regulating gene expression. While many individual regulatory elements have been characterized, they have never been analyzed as a class.

Results

We have performed the first such large-scale study of cis-regulatory modules in order to determine whether they have common properties that might aid in their identification and contribute to our understanding of the mechanisms by which they function. A total of 280 individual, experimentally verified cis-regulatory modules from Drosophila were analyzed for a range of sequence-level and functional properties. We report here that regulatory modules do indeed share common properties, among them an elevated GC content, an increased level of interspecific sequence conservation, and a tendency to be transcribed into RNA. However, we find that dense clustering of transcription factor binding sites, especially homotypic clustering, which is commonly believed to be a general characteristic of regulatory modules, is rather a feature that belongs chiefly to a specific subclass. This has important implications for current computational approaches, many of which are biased toward this subset. We explore two new strategies to assess binding site clustering and gauge their performances with respect to their ability to detect all 280 modules and various functionally coherent subsets.

Conclusion

Our findings demonstrate that cis-regulatory modules share common features that help to define them as a class and that may lead to new insights into mechanisms of gene regulation. However, these properties alone may not be sufficient to reliably distinguish regulatory from non-regulatory sequences. We also demonstrate that there are distinct subclasses of cis-regulatory modules that are more amenable to in silico detection than others and that these differences must be taken into account when attempting genome-wide regulatory element discovery.

ReAlignerV: web-based genomic alignment tool with high specificity and robustness estimated by species-specific insertion sequences

Background

Detecting conserved noncoding sequences (CNSs) across species highlights the functional elements. Alignment procedures combined with computational prediction of transcription factor binding sites (TFBSs) can narrow down key regulatory elements. Repeat masking processes are often performed before alignment to mask insertion sequences such as transposable elements (TEs). However, recently such TEs have been reported to influence the gene regulatory network evolution. Therefore, an alignment approach that is robust to TE insertions is meaningful for finding novel conserved TFBSs in TEs.

Results

We constructed a web server 'ReAlignerV' for complex alignment of genomic sequences. ReAlignerV returns ladder-like schematic alignments that integrate predicted TFBSs and the location of TEs. It also provides pair-wise alignments in which the predicted TFBS sites and their names are shown alongside each sequence. Furthermore, we evaluated false positive aligned sites by focusing on the species-specific TEs (SSTEs), and found that ReAlignerV has a higher specificity and robustness to insertions for sequences having more than 20% TE content, compared to LAGAN, AVID, MAVID and BLASTZ.

Conclusion

ReAlignerV can be applied successfully to TE-insertion-rich sequences without prior repeat masking, and this increases the chances of finding regulatory sequences hidden in TEs, which are important sources of the regulatory network evolution. ReAlignerV can be accessed through and downloaded from .

How to usefully compare homologous plant genes and chromosomes as DNA sequences

There are four sequenced and publicly available plant genomes to date. With many more slated for completion, one challenge will be to use comparative genomic methods to detect novel evolutionary patterns in plant genomes. This research requires sequence alignment algorithms to detect regions of similarity within and among genomes. However, different alignment algorithms are optimized for identifying different types of homologous sequences. This review focuses on plant genome evolution and provides a tutorial for using several sequence alignment algorithms and visualization tools to detect useful patterns of conservation: conserved non-coding sequences, false positive noise, subfunctionalization, synteny, annotation errors, inversions and local duplications. Our tutorial encourages the reader to experiment online with the reviewed tools as a companion to the text.

Evaluation of phylogenetic footprint discovery for predicting bacterial cis-regulatory elements and revealing their evolution

Background

The detection of conserved motifs in promoters of orthologous genes (phylogenetic footprints) has become a common strategy to predict cis-acting regulatory elements. Several software tools are routinely used to raise hypotheses about regulation. However, these tools are generally used as black boxes, with default parameters. A systematic evaluation of optimal parameters for a footprint discovery strategy can bring a sizeable improvement to the predictions.

Results

We evaluate the performances of a footprint discovery approach based on the detection of over-represented spaced motifs. This method is particularly suitable for (but not restricted to) Bacteria, since such motifs are typically bound by factors containing a Helix-Turn-Helix domain. We evaluated footprint discovery in 368 Escherichia coli K12 genes with annotated sites, under 40 different combinations of parameters (taxonomical level, background model, organism-specific filtering, operon inference). Motifs are assessed both at the levels of correctness and significance. We further report a detailed analysis of 181 bacterial orthologs of the LexA repressor. Distinct motifs are detected at various taxonomical levels, including the 7 previously characterized taxon-specific motifs. In addition, we highlight a significantly stronger conservation of half-motifs in Actinobacteria, relative to Firmicutes, suggesting an intermediate state in specificity switching between the two Gram-positive phyla, and thereby revealing the on-going evolution of LexA auto-regulation.

Conclusion

The footprint discovery method proposed here shows excellent results with E. coli and can readily be extended to predict cis-acting regulatory signals and propose testable hypotheses in bacterial genomes for which nothing is known about regulation.

Molecular phylogenetics of the lizard genus Microlophus (squamata:tropiduridae): aligning and retrieving indel signal from nuclear introns

We use a multigene data set (the mitochondrial locus and nine nuclear gene regions) to test phylogenetic relationships in the South American "lava lizards" (genus Microlophus) and describe a strategy for aligning noncoding sequences that accounts for differences in tempo and class of mutational events. We focus on seven nuclear introns that vary in size and frequency of multibase length mutations (i.e., indels) and present a manual alignment strategy that incorporates insertions and deletions (indels) for each intron. Our method is based on mechanistic explanations of intron evolution that does not require a guide tree. We also use a progressive alignment algorithm (Probabilistic Alignment Kit; PRANK) and distinguishes insertions from deletions and avoids the "gapcost" conundrum. We describe an approach to selecting a guide tree purged of ambiguously aligned regions and use this to refine PRANK performance. We show that although manual alignment is successful in finding repeat motifs and the most obvious indels, some regions can only be subjectively aligned, and there are limits to the size and complexity of a data matrix for which this approach can be taken. PRANK alignments identified more parsimony-informative indels while simultaneously increasing nucleotide identity in conserved sequence blocks flanking the indel regions. When comparing manual and PRANK with two widely used methods (CLUSTAL, MUSCLE) for the alignment of the most length-variable intron, only PRANK recovered a tree congruent at deeper nodes with the combined data tree inferred from all nuclear gene regions. We take this concordance as an objective function of alignment quality and present a strongly supported phylogenetic hypothesis for Microlophus relationships. From this hypothesis we show that (1) a coded indel data partition derived from the PRANK alignment contributed significantly to nodal support and (2) the indel data set permitted detection of significant conflict between mitochondrial and nuclear data partitions, which we hypothesize arose from secondary contact of distantly related taxa, followed by hybridization and mtDNA introgression.

Uncertainty in homology inferences: assessing and improving genomic sequence alignment

Sequence alignment underpins all of comparative genomics, yet it remains an incompletely solved problem. In particular, the statistical uncertainty within inferred alignments is often disregarded, while parametric or phylogenetic inferences are considered meaningless without confidence estimates. Here, we report on a theoretical and simulation study of pairwise alignments of genomic DNA at human-mouse divergence. We find that >15% of aligned bases are incorrect in existing whole-genome alignments, and we identify three types of alignment error, each leading to systematic biases in all algorithms considered. Careful modeling of the evolutionary process improves alignment quality; however, these improvements are modest compared with the remaining alignment errors, even with exact knowledge of the evolutionary model, emphasizing the need for statistical approaches to account for uncertainty. We develop a new algorithm, Marginalized Posterior Decoding (MPD), which explicitly accounts for uncertainties, is less biased and more accurate than other algorithms we consider, and reduces the proportion of misaligned bases by a third compared with the best existing algorithm. To our knowledge, this is the first nonheuristic algorithm for DNA sequence alignment to show robust improvements over the classic Needleman-Wunsch algorithm. Despite this, considerable uncertainty remains even in the improved alignments. We conclude that a probabilistic treatment is essential, both to improve alignment quality and to quantify the remaining uncertainty. This is becoming increasingly relevant with the growing appreciation of the importance of noncoding DNA, whose study relies heavily on alignments. Alignment errors are inevitable, and should be considered when drawing conclusions from alignments. Software and alignments to assist researchers in doing this are provided at http://genserv.anat.ox.ac.uk/grape/.

How accurately is ncRNA aligned within whole-genome multiple alignments?

Background

Multiple alignment of homologous DNA sequences is of great interest to biologists since it provides a window into evolutionary processes. At present, the accuracy of whole-genome multiple alignments, particularly in noncoding regions, has not been thoroughly evaluated.

Results

We evaluate the alignment accuracy of certain noncoding regions using noncoding RNA alignments from Rfam as a reference. We inspect the MULTIZ 17-vertebrate alignment from the UCSC Genome Browser for all the human sequences in the Rfam seed alignments. In particular, we find 638 instances of chimeric and partial alignments to human noncoding RNA elements, of which at least 225 can be improved by straightforward means. As a byproduct of our procedure, we predict many novel instances of known ncRNA families that are suggested by the alignment.

Conclusion

MULTIZ does a fairly accurate job of aligning these genomes in these difficult regions. However, our experiments indicate that better alignments exist in some regions.

Genomic evolution of the proteasome system among hemiascomycetous yeasts

Components of the proteasome-ubiquitin pathway are highly conserved throughout eukaryotic organisms. In S. cerevisiae, the expression of proteasomal genes is subject to concerted control by a transcriptional regulator, Rpn4p, interacting with a highly conserved cis-regulatory element, PACE, located in the upstream regions of these genes. Taking advantage of sequence data accumulated from 15 Hemiascomycetes, we performed an in silico study to address the problem of how this system might have evolved among these species. We found that in all these species the Rpn4p homologues are well conserved in terms of sequence and characteristic domain features. The "PACE patterns" turned out to be nearly identical among the Saccharomyces "sensu stricto" species, whereas in the evolutionary more distant species the putatively functional cis-regulatory motifs revealed deviations from the "canonical" PACE nonamere sequence in one or two nucleotides. Our findings suggest that during evolution of the Hemiascomycetes such slightly divergent ancestral motifs have converged into a unique PACE element for the majority of the proteasomal genes within the most recent species of this class. Likewise, the Rpn4 factors within the most recent species of this class show a higher degree of similarity in sequence than their ancestral counterparts. By contrast, we did not detect PACE-like motifs among the proteasomal genes in other eukaryotes, such as S. pombe, several filamentous fungi, A. thaliana, or humans, leaving the interesting question which type of concerted regulation of the proteasome system has developed in species other than the Hemiascomycetes.

Computation and Analysis of Genomic Multi-Sequence Alignments

Multi-sequence alignments of large genomic regions are at the core of many computational genome-annotation approaches aimed at identifying coding regions, RNA genes, regulatory regions, and other functional features. Such alignments also underlie many genome-evolution studies. Here we review recent computational advances in the area of multi-sequence alignment, focusing on methods suitable for aligning whole vertebrate genomes. We introduce the key algorithmic ideas in use today, and identify publicly available resources for computing, accessing, and visualizing genomic alignments. Finally, we describe the latest alignment-based approaches to identify and characterize various types of functional sequences. Key areas of research are identified and directions for future improvements are suggested.

Global analysis of exon creation versus loss and the role of alternative splicing in 17 vertebrate genomes

Association of alternative splicing (AS) with accelerated rates of exon evolution in some organisms has recently aroused widespread interest in its role in evolution of eukaryotic gene structure. Previous studies were limited to analysis of exon creation or lost events in mouse and/or human only. Our multigenome approach provides a way for (1) distinguishing creation and loss events on the large scale; (2) uncovering details of the evolutionary mechanisms involved; (3) estimating the corresponding rates over a wide range of evolutionary times and organisms; and (4) assessing the impact of AS on those evolutionary rates. We use previously unpublished independent analyses of alternative splicing in five species (human, mouse, dog, cow, and zebrafish) from the ASAP database combined with genomewide multiple alignment of 17 genomes to analyze exon creation and loss of both constitutively and alternatively spliced exons in mammals, fish, and birds. Our analysis provides a comprehensive database of exon creation and loss events over 360 million years of vertebrate evolution, including tens of thousands of alternative and constitutive exons. We find that exon inclusion level is inversely related to the rate of exon creation. In addition, we provide a detailed in-depth analysis of mechanisms of exon creation and loss, which suggests that a large fraction of nonrepetitive created exons are results of ab initio creation from purely intronic sequences. Our data indicate an important role for alternative splicing in creation of new exons and provide a useful novel database resource for future genome evolution research.

Frequent gain and loss of functional transcription factor binding sites

Cis-regulatory sequences are not always conserved across species. Divergence within cis-regulatory sequences may result from the evolution of species-specific patterns of gene expression or the flexible nature of the cis-regulatory code. The identification of functional divergence in cis-regulatory sequences is therefore important for both understanding the role of gene regulation in evolution and annotating regulatory elements. We have developed an evolutionary model to detect the loss of constraint on individual transcription factor binding sites (TFBSs). We find that a significant fraction of functionally constrained binding sites have been lost in a lineage-specific manner among three closely related yeast species. Binding site loss has previously been explained by turnover, where the concurrent gain and loss of a binding site maintains gene regulation. We estimate that nearly half of all loss events cannot be explained by binding site turnover. Recreating the mutations that led to binding site loss confirms that these sequence changes affect gene expression in some cases. We also estimate that there is a high rate of binding site gain, as more than half of experimentally identified S. cerevisiae binding sites are not conserved across species. The frequent gain and loss of TFBSs implies that cis-regulatory sequences are labile and, in the absence of turnover, may contribute to species-specific patterns of gene expression.

Research in the field of molecular evolution is focused on understanding the genetic basis of functional differences between species. Protein coding sequences have traditionally been the focus of these studies, as the genetic code enables a detailed study of the strength of selection acting on amino acid sequences. However, from the earliest cross-species sequence comparisons, it was clear that protein sequences among closely related species are too similar to explain the observed phenotypic diversity. This led to the hypothesis that the evolution of gene regulation has played a key role in generating diversity between species. The availability of numerous complete genome sequences has made it possible to begin testing this hypothesis. In this work, the authors use an evolutionary model to identify functional divergence within transcription factor binding sites, the core functional elements involved in gene regulation. Applying this model to the baker's yeast, Saccharomyces cerevisiae, and its three closest relatives, the authors find that a substantial fraction of the ancestral binding sites have been lost in a species-specific manner. In some cases the loss of the binding site creates gene expression differences that may be indicative of species-specific changes in gene regulation. This work provides a useful computational framework that will allow further study of the conservation of cis-regulatory sequences and their role in molecular evolution.

Multiple sequence alignment: in pursuit of homologous DNA positions

DNA sequence alignment is a prerequisite to virtually all comparative genomic analyses, including the identification of conserved sequence motifs, estimation of evolutionary divergence between sequences, and inference of historical relationships among genes and species. While it is mere common sense that inaccuracies in multiple sequence alignments can have detrimental effects on downstream analyses, it is important to know the extent to which the inferences drawn from these alignments are robust to errors and biases inherent in all sequence alignments. A survey of investigations into strengths and weaknesses of sequence alignments reveals, as expected, that alignment quality is generally poor for two distantly related sequences and can often be improved by adding additional sequences as stepping stones between distantly related species. Errors in sequence alignment are also found to have a significant negative effect on subsequent inference of sequence divergence, phylogenetic trees, and conserved motifs. However, our understanding of alignment biases remains rudimentary, and sequence alignment procedures continue to be used somewhat like benign formatting operations to make sequences equal in length. Because of the central role these alignments now play in our endeavors to establish the tree of life and to identify important parts of genomes through evolutionary functional genomics, we see a need for increased community effort to investigate influences of alignment bias on the accuracy of large-scale comparative genomics.

Alignment and Topological Accuracy of the Direct Optimization approach via POY and Traditional Phylogenetics via ClustalW + PAUP*

Direct optimization frameworks for simultaneously estimating alignments and phylogenies have recently been developed. One such method, implemented in the program POY, is becoming more common for analyses of variable length sequences (e.g., analyses using ribosomal genes) and for combined evidence analyses (morphology + multiple genes). Simulation of sequences containing insertion and deletion events was performed in order to directly compare a widely used method of multiple sequence alignment (ClustalW) and subsequent parsimony analysis in PAUP* with direct optimization via POY. Data sets were simulated for pectinate, balanced, and random tree shapes under different conditions (clocklike, non-clocklike, and ultrametric). Alignment accuracy scores for the implied alignments from POY and the multiple sequence alignments from ClustalW were calculated and compared. In almost all cases (99.95%), ClustalW produced more accurate alignments than POY-implied alignments, judged by the proportion of correctly identified homologous sites. Topological accuracy (distance to the true tree) for POY topologies and topologies generated under parsimony in PAUP* from the ClustalW alignments were also compared. In 44.94% of the cases, Clustal alignment tree reconstructions via PAUP* were more accurate than POY, whereas in 16.71% of the cases POY reconstructions were more topologically accurate (38.38% of the time they were equally accurate). Comparisons between POY hypothesized alignments and the true alignments indicated that, on average, as alignment error increased, topological accuracy decreased.

MySSP: non-stationary evolutionary sequence simulation, including indels

MySSP is a new program for the simulation of DNA sequence evolution across a phylogenetic tree. Although many programs are available for sequence simulation, MySSP is unique in its inclusion of indels, flexibility in allowing for non-stationary patterns, and output of ancestral sequences. Some of these features can individually be found in existing programs, but have not all have been previously available in a single package.

Considerations in the identification of functional RNA structural elements in genomic alignments

Background

Accurate identification of novel, functional noncoding (nc) RNA features in genome sequence has proven more difficult than for exons. Current algorithms identify and score potential RNA secondary structures on the basis of thermodynamic stability, conservation, and/or covariance in sequence alignments. Neither the algorithms nor the information gained from the individual inputs have been independently assessed. Furthermore, due to issues in modelling background signal, it has been difficult to gauge the precision of these algorithms on a genomic scale, in which even a seemingly small false-positive rate can result in a vast excess of false discoveries.

Results

We developed a shuffling algorithm, shuffle-pair.pl, that simultaneously preserves dinucleotide frequency, gaps, and local conservation in pairwise sequence alignments. We used shuffle-pair.pl to assess precision and recall of six ncRNA search tools (MSARI, QRNA, ddbRNA, RNAz, Evofold, and several variants of simple thermodynamic stability on a test set of 3046 alignments of known ncRNAs. Relative to mononucleotide shuffling, preservation of dinucleotide content in shuffling the alignments resulted in a drastic increase in estimated false-positive detection rates for ncRNA elements, precluding evaluation of higher order alignments, which cannot not be adequately shuffled maintaining both dinucleotides and alignment structure. On pairwise alignments, none of the covariance-based tools performed markedly better than thermodynamic scoring alone. Although the high false-positive rates call into question the veracity of any individual predicted secondary structural element in our analysis, we nevertheless identified intriguing global trends in human genome alignments. The distribution of ncRNA prediction scores in 75-base windows overlapping UTRs, introns, and intergenic regions analyzed using both thermodynamic stability and EvoFold (which has no thermodynamic component) was significantly higher for real than shuffled sequence, while the distribution for coding sequences was lower than that of corresponding shuffles.

Conclusion

Accurate prediction of novel RNA structural elements in genome sequence remains a difficult problem, and development of an appropriate negative-control strategy for multiple alignments is an important practical challenge. Nonetheless, the general trends we observed for the distributions of predicted ncRNAs across genomic features are biologically meaningful, supporting the presence of secondary structural elements in many 3' UTRs, and providing evidence for evolutionary selection against secondary structures in coding regions.

Comparative genomics: a tool to functionally annotate human DNA

The availability of an increasing number of vertebrate genomes has enabled comparative methods to infer functional sequences based on evolutionary constraint. Although this has proved powerful for gene identification, significant progress has also been made in uncovering gene regulatory sequences such as distant acting transcriptional enhancers. These pursuits have led to the development of a variety of valuable databases and resources that should serve as a routine toolbox for biological discovery.

Sequence analyses to study the evolutionary history and cis-regulatory elements of Hedgehog genes

Sequence analysis and comparative genomics are powerful tools to gain knowledge on multiple aspects of gene and protein regulation and function. These have been widely used to understand the evolutionary history and the biochemistry of Hedgehog (Hh) proteins, and the molecular control of Hedgehog gene expression. Here, we report on some of the methods available to retrieve protein and genomic sequences. We describe how protein sequence comparison can produce information on the evolutionary history of Hh proteins. Moreover, we describe the use of genomic sequence analysis including phylogenetic footprinting and transcription factor-binding site search tools, techniques that allow for the characterization of cis-regulatory elements of developmental genes such as the Hedgehog genes.

Alignment of genomic sequences using DIALIGN

DIALIGN is a software program for multiple alignment of DNA or protein sequences that combines global and local alignment features. During the last years, the program has been used extensively to compare syntenic regions in genomic sequences. An anchoring option speeds up the alignment procedure and makes it possible to use user-defined constraints to improve the quality of the program output. This chapter explains features of DIALIGN that are useful if genomic sequences are to be aligned. The program is online available through Göttingen Bioinformatics Compute Server at http://dialign.gobics.de/.

Comparative analysis and visualization of genomic sequences using VISTA browser and associated computational tools

This chapter discusses VISTA Browser and associated computational tools for analysis and visual exploration of genomic alignments. The availability of massive amounts of genomic data produced by sequencing centers stimulated active development of computational tools for analyzing sequences and complete genomes, including tools for comparative analysis. Among algorithmic and computational challenges of such analysis, i.e., efficient and fast alignment, decoding of evolutionary history, the search for functional elements in genomes, and others, visualization of comparative results is of great importance. Only interactive viewing and manipulation of data allow for its in-depth investigation by biologists. We describe the rich capabilities of the interactive VISTA Browser with its extensions and modifications, and provide examples of the examination of alignments of DNA sequences and whole genomes, both eukaryotic and microbial. VISTA portal (http://genome.lbl.gov/vista) provides access to all these tools.

Large-scale discovery of promoter motifs in Drosophila melanogaster

A key step in understanding gene regulation is to identify the repertoire of transcription factor binding motifs (TFBMs) that form the building blocks of promoters and other regulatory elements. Identifying these experimentally is very laborious, and the number of TFBMs discovered remains relatively small, especially when compared with the hundreds of transcription factor genes predicted in metazoan genomes. We have used a recently developed statistical motif discovery approach, NestedMICA, to detect candidate TFBMs from a large set of Drosophila melanogaster promoter regions. Of the 120 motifs inferred in our initial analysis, 25 were statistically significant matches to previously reported motifs, while 87 appeared to be novel. Analysis of sequence conservation and motif positioning suggested that the great majority of these discovered motifs are predictive of functional elements in the genome. Many motifs showed associations with specific patterns of gene expression in the D. melanogaster embryo, and we were able to obtain confident annotation of expression patterns for 25 of our motifs, including eight of the novel motifs. The motifs are available through Tiffin, a new database of DNA sequence motifs. We have discovered many new motifs that are overrepresented in D. melanogaster promoter regions, and offer several independent lines of evidence that these are novel TFBMs. Our motif dictionary provides a solid foundation for further investigation of regulatory elements in Drosophila, and demonstrates techniques that should be applicable in other species. We suggest that further improvements in computational motif discovery should narrow the gap between the set of known motifs and the total number of transcription factors in metazoan genomes.

In contrast to the genomic sequences that encode proteins, little is known about the regulatory elements that instruct the cell as to when and where a given gene should be active. Regulatory elements are thought to consist of clusters of short DNA words (motifs), each of which acts as a binding site for sequence-specific DNA binding protein. Thus, building a comprehensive dictionary of such motifs is an important step towards a broader understanding of gene regulation. Using the recently published NestedMICA method for detecting overrepresented motifs in a set of sequences, we build a dictionary of 120 motifs from regulatory sequences in the fruitfly genome, 87 of which are novel. Analysis of positional biases, conservation across species, and association with specific patterns of gene expression in fruitfly embryos suggest that the great majority of these newly discovered motifs represent functional regulatory elements. In addition to providing an initial motif dictionary for one of the most intensively studied model organisms, this work provides an analytical framework for the comprehensive discovery of regulatory motifs in complex animal genomes.

CGAT: a comparative genome analysis tool for visualizing alignments in the analysis of complex evolutionary changes between closely related genomes

BACKGROUND

The recent accumulation of closely related genomic sequences provides a valuable resource for the elucidation of the evolutionary histories of various organisms. However, although numerous alignment calculation and visualization tools have been developed to date, the analysis of complex genomic changes, such as large insertions, deletions, inversions, translocations and duplications, still presents certain difficulties.

RESULTS

We have developed a comparative genome analysis tool, named CGAT, which allows detailed comparisons of closely related bacteria-sized genomes mainly through visualizing middle-to-large-scale changes to infer underlying mechanisms. CGAT displays precomputed pairwise genome alignments on both dotplot and alignment viewers with scrolling and zooming functions, and allows users to move along the pre-identified orthologous alignments. Users can place several types of information on this alignment, such as the presence of tandem repeats or interspersed repetitive sequences and changes in G+C contents or codon usage bias, thereby facilitating the interpretation of the observed genomic changes. In addition to displaying precomputed alignments, the viewer can dynamically calculate the alignments between specified regions; this feature is especially useful for examining the alignment boundaries, as these boundaries are often obscure and can vary between programs. Besides the alignment browser functionalities, CGAT also contains an alignment data construction module, which contains various procedures that are commonly used for pre- and post-processing for large-scale alignment calculation, such as the split-and-merge protocol for calculating long alignments, chaining adjacent alignments, and ortholog identification. Indeed, CGAT provides a general framework for the calculation of genome-scale alignments using various existing programs as alignment engines, which allows users to compare the outputs of different alignment programs. Earlier versions of this program have been used successfully in our research to infer the evolutionary history of apparently complex genome changes between closely related eubacteria and archaea.

CONCLUSION

CGAT is a practical tool for analyzing complex genomic changes between closely related genomes using existing alignment programs and other sequence analysis tools combined with extensive manual inspection.

How should gaps be treated in parsimony? A comparison of approaches using simulation

Simulation with indels was used to produce alignments where true site homologies in DNA sequences were known; the gaps from these datasets were removed and the sequences were then aligned to produce hypothesized alignments. Both alignments were then analyzed under three widely used methods of treating gaps during tree reconstruction under the maximum parsimony principle. With the true alignments, for many cases (82%), there was no difference in topological accuracy for the different methods of gap coding. However, in cases where a difference was present, coding gaps as a fifth state character or as separate presence/absence characters outperformed treating gaps as unknown/missing data nearly 90% of the time. For the hypothesized alignments, on average, all gap treatment approaches performed equally well. Data sets with higher sequence divergence and more pectinate tree shapes with variable branch lengths are more affected by gap coding than datasets associated with shallower non-pectinate tree shapes.

Detecting the limits of regulatory element conservation and divergence estimation using pairwise and multiple alignments

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.

Multiple sequence alignment accuracy and phylogenetic inference

Phylogenies are often thought to be more dependent upon the specifics of the sequence alignment rather than on the method of reconstruction. Simulation of sequences containing insertion and deletion events was performed in order to determine the role that alignment accuracy plays during phylogenetic inference. Data sets were simulated for pectinate, balanced, and random tree shapes under different conditions (ultrametric equal branch length, ultrametric random branch length, nonultrametric random branch length). Comparisons between hypothesized alignments and true alignments enabled determination of two measures of alignment accuracy, that of the total data set and that of individual branches. In general, our results indicate that as alignment error increases, topological accuracy decreases. This trend was much more pronounced for data sets derived from more pectinate topologies. In contrast, for balanced, ultrametric, equal branch length tree shapes, alignment inaccuracy had little average effect on tree reconstruction. These conclusions are based on average trends of many analyses under different conditions, and any one specific analysis, independent of the alignment accuracy, may recover very accurate or inaccurate topologies. Maximum likelihood and Bayesian, in general, outperformed neighbor joining and maximum parsimony in terms of tree reconstruction accuracy. Results also indicated that as the length of the branch and of the neighboring branches increase, alignment accuracy decreases, and the length of the neighboring branches is the major factor in topological accuracy. Thus, multiple-sequence alignment can be an important factor in downstream effects on topological reconstruction.

MCALIGN2: faster, accurate global pairwise alignment of non-coding DNA sequences based on explicit models of indel evolution

Background

Non-coding DNA sequences comprise a very large proportion of the total genomic content of mammals, most other vertebrates, many invertebrates, and most plants. Unraveling the functional significance of non-coding DNA depends on how well we are able to align non-coding DNA sequences. However, the alignment of non-coding DNA sequences is more difficult than aligning protein-coding sequences.

Results

Here we present an improved pair-hidden-Markov-Model (pair HMM) based method for performing global pairwise alignment of non-coding DNA sequences. The method uses an explicit model of indel length frequency distribution which can be specified, and allows any time reversible model of nucleotide substitution. The method uses a deterministic global optimiser to find the alignment with the highest posterior probability. We test MCALIGN2 in simulations, and compare it to a previous Monte Carlo based method (MCALIGN), to the pair HMM method of Knudsen and Miyamoto, and to a heuristic method (AVID) that performed very well in a previous simulation study. We show that the pair HMM methods have excellent performance for all combinations of parameter values we have considered. MCALIGN2 is up to ten times faster than MCALIGN. MCALIGN2 is more accurate in resolving indels given an accurate explicit model than heuristic methods, but is computationally slower.

Conclusion

MCALIGN2 produces better quality alignments by explicitly using biological knowledge about the indel length distribution and time reversible models of nucleotide substitution. As a result, it can outperform other available sequence alignment methods for the cases we have considered to align non-coding DNA sequences.