Taxonomic analysis of metagenomic data with kASA.

The taxonomic analysis of sequencing data has become important in many areas of life sciences. However, currently available tools for that purpose either consume large amounts of RAM or yield insufficient quality and robustness. Here, we present kASA, a k-mer based tool capable of identifying and profiling metagenomic DNA or protein sequences with high computational efficiency and a user-definable memory footprint. We ensure both high sensitivity and precision by using an amino acid-like encoding of k-mers together with a range of multiple k's. Custom algorithms and data structures optimized for external memory storage enable a full-scale taxonomic analysis without compromise on laptop, desktop, and HPCC.

tSFM 1.0: tRNA Structure-Function Mapper.

MOTIVATION: Structure-conditioned information statistics have proven useful to predict and visualize tRNA Class-Informative Features (CIFs) and their evolutionary divergences. Although permutation P-values can quantify the significance of CIF divergences between two taxa, their naive Monte Carlo approximation is slow and inaccurate. The Peaks-over-Threshold approach of Knijnenburg et al. (2009) promises improvements to both speed and accuracy of permutation P-values, but has no publicly available API. RESULTS: We present tRNA Structure-Function Mapper (tSFM) v1.0, an open-source, multi-threaded application that efficiently computes, visualizes and assesses significance of single- and paired-site CIFs and their evolutionary divergences for any RNA, protein, gene or genomic element sequence family. Multiple estimators of permutation P-values for CIF evolutionary divergences are provided along with confidence intervals. tSFM is implemented in Python 3 with compiled C extensions and is freely available through GitHub (https://github.com/tlawrence3/tSFM) and PyPI. AVAILABILITY AND IMPLEMENTATION: The data underlying this article are available on GitHub at https://github.com/tlawrence3/tSFM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A single ChIP-seq dataset is sufficient for comprehensive analysis of motifs co-occurrence with MCOT package.

Recognition of composite elements consisting of two transcription factor binding sites gets behind the studies of tissue-, stage- and condition-specific transcription. Genome-wide data on transcription factor binding generated with ChIP-seq method facilitate an identification of composite elements, but the existing bioinformatics tools either require ChIP-seq datasets for both partner transcription factors, or omit composite elements with motifs overlapping. Here we present an universal Motifs Co-Occurrence Tool (MCOT) that retrieves maximum information about overrepresented composite elements from a single ChIP-seq dataset. This includes homo- and heterotypic composite elements of four mutual orientations of motifs, separated with a spacer or overlapping, even if recognition of motifs within composite element requires various stringencies. Analysis of 52 ChIP-seq datasets for 18 human transcription factors confirmed that for over 60% of analyzed datasets and transcription factors predicted co-occurrence of motifs implied experimentally proven protein-protein interaction of respecting transcription factors. Analysis of 164 ChIP-seq datasets for 57 mammalian transcription factors showed that abundance of predicted composite elements with an overlap of motifs compared to those with a spacer more than doubled; and they had 1.5-fold increase of asymmetrical pairs of motifs with one more conservative 'leading' motif and another one 'guided'.

Highly efficacious antiviral protection of plants by small interfering RNAs identified in vitro.

In response to a viral infection, the plant's RNA silencing machinery processes viral RNAs into a huge number of small interfering RNAs (siRNAs). However, a very few of these siRNAs actually interfere with viral replication. A reliable approach to identify these immunologically effective siRNAs (esiRNAs) and to define the characteristics underlying their activity has not been available so far. Here, we develop a novel screening approach that enables a rapid functional identification of antiviral esiRNAs. Tests on the efficacy of such identified esiRNAs of a model virus achieved a virtual full protection of plants against a massive subsequent infection in transient applications. We find that the functionality of esiRNAs depends crucially on two properties: the binding affinity to Argonaute proteins and the ability to access the target RNA. The ability to rapidly identify functional esiRNAs could be of great benefit for all RNA silencing-based plant protection measures against viruses and other pathogens.

Transcriptome dynamics at Arabidopsis graft junctions reveal an intertissue recognition mechanism that activates vascular regeneration.

The ability for cut tissues to join and form a chimeric organism is a remarkable property of many plants; however, grafting is poorly characterized at the molecular level. To better understand this process, we monitored genome-wide gene expression changes in grafted Arabidopsis thaliana hypocotyls. We observed a sequential activation of genes associated with cambium, phloem, and xylem formation. Tissues above and below the graft rapidly developed an asymmetry such that many genes were more highly expressed on one side than on the other. This asymmetry correlated with sugar-responsive genes, and we observed an accumulation of starch above the graft junction. This accumulation decreased along with asymmetry once the sugar-transporting vascular tissues reconnected. Despite the initial starvation response below the graft, many genes associated with vascular formation were rapidly activated in grafted tissues but not in cut and separated tissues, indicating that a recognition mechanism was activated independently of functional vascular connections. Auxin, which is transported cell to cell, had a rapidly elevated response that was symmetric, suggesting that auxin was perceived by the root within hours of tissue attachment to activate the vascular regeneration process. A subset of genes was expressed only in grafted tissues, indicating that wound healing proceeded via different mechanisms depending on the presence or absence of adjoining tissues. Such a recognition process could have broader relevance for tissue regeneration, intertissue communication, and tissue fusion events.

Current Understanding of the HIF-1-Dependent Metabolism in Oral Squamous Cell Carcinoma.

Oral squamous cell carcinoma (OSCC) is the 10th most frequent human malignancy and is thus a global burden. Despite some progress in diagnosis and therapy, patients' overall survival rate, between 40 and 55%, has stagnated over the last four decades. Since the tumor node metastasis (TNM) system is not precise enough to predict the disease outcome, additive factors for diagnosis, prognosis, prediction and therapy resistance are urgently needed for OSCC. One promising candidate is the hypoxia inducible factor-1 (HIF-1), which functions as an early regulator of tumor aggressiveness and is a key promoter of energy adaptation. Other parameters comprise the composition of the tumor microenvironment, which determines the availability of nutrients and oxygen. In our opinion, these general processes are linked in the pathogenesis of OSCC. Based on this assumption, the review will summarize the major features of the HIF system-induced activities, its target proteins and related pathways of nutrient utilization and metabolism that are essential for the initiation, progression and therapeutic stratification of OSCC.

Prediction of regulatory targets of alternative isoforms of the epidermal growth factor receptor in a glioblastoma cell line.

BACKGROUND: The epidermal growth factor receptor (EGFR) is a major regulator of proliferation in tumor cells. Elevated expression levels of EGFR are associated with prognosis and clinical outcomes of patients in a variety of tumor types. There are at least four splice variants of the mRNA encoding four protein isoforms of EGFR in humans, named I through IV. EGFR isoform I is the full-length protein, whereas isoforms II-IV are shorter protein isoforms. Nevertheless, all EGFR isoforms bind the epidermal growth factor (EGF). Although EGFR is an essential target of long-established and successful tumor therapeutics, the exact function and biomarker potential of alternative EGFR isoforms II-IV are unclear, motivating more in-depth analyses. Hence, we analyzed transcriptome data from glioblastoma cell line SF767 to predict target genes regulated by EGFR isoforms II-IV, but not by EGFR isoform I nor other receptors such as HER2, HER3, or HER4. RESULTS: We analyzed the differential expression of potential target genes in a glioblastoma cell line in two nested RNAi experimental conditions and one negative control, contrasting expression with EGF stimulation against expression without EGF stimulation. In one RNAi experiment, we selectively knocked down EGFR splice variant I, while in the other we knocked down all four EGFR splice variants, so the associated effects of EGFR II-IV knock-down can only be inferred indirectly. For this type of nested experimental design, we developed a two-step bioinformatics approach based on the Bayesian Information Criterion for predicting putative target genes of EGFR isoforms II-IV. Finally, we experimentally validated a set of six putative target genes, and we found that qPCR validations confirmed the predictions in all cases. CONCLUSIONS: By performing RNAi experiments for three poorly investigated EGFR isoforms, we were able to successfully predict 1140 putative target genes specifically regulated by EGFR isoforms II-IV using the developed Bayesian Gene Selection Criterion (BGSC) approach. This approach is easily utilizable for the analysis of data of other nested experimental designs, and we provide an implementation in R that is easily adaptable to similar data or experimental designs together with all raw datasets used in this study in the BGSC repository, https://github.com/GrosseLab/BGSC .

RNA-Seq analysis of soft rush (Juncus effusus): transcriptome sequencing, de novo assembly, annotation, and polymorphism identification.

BACKGROUND: Juncus effusus L. (family: Juncaceae; order: Poales) is a helophytic rush growing in temperate damp or wet terrestrial habitats and is of almost cosmopolitan distribution. The species has been studied intensively with respect to its interaction with co-occurring plants as well as microbes being involved in major biogeochemical cycles. J. effusus has biotechnological value as component of Constructed Wetlands where the plant has been employed in phytoremediation of contaminated water. Its genome has not been sequenced. RESULTS: In this study we carried out functional annotation and polymorphism analysis of de novo assembled RNA-Seq data from 18 genotypes using 249 million paired-end Illumina HiSeq reads and 2.8 million 454 Titanium reads. The assembly comprised 158,591 contigs with a mean contig length of 780 bp. The assembly was annotated using the dammit! annotation pipeline, which queries the databases OrthoDB, Pfam-A, Rfam, and runs BUSCO (Benchmarking Single-Copy Ortholog genes). In total, 111,567 contigs (70.3%) were annotated with functional descriptions, assigned gene ontology terms, and conserved protein domains, which resulted in 30,932 non-redundant gene sequences. Results of BUSCO and KEGG pathway analyses were similar for J. effusus as for the well-studied members of the Poales, Oryza sativa and Sorghum bicolor. A total of 566,433 polymorphisms were identified in transcribed regions with an average frequency of 1 polymorphism in every 171 bases. CONCLUSIONS: The transcriptome assembly was of high quality and genome coverage was sufficient for global analyses. This annotated knowledge resource can be utilized for future gene expression analysis, genomic feature comparisons, genotyping, primer design, and functional genomics in J. effusus.

myTAI: evolutionary transcriptomics with R.

Motivation: Next Generation Sequencing (NGS) technologies generate a large amount of high quality transcriptome datasets enabling the investigation of molecular processes on a genomic and metagenomic scale. These transcriptomics studies aim to quantify and compare the molecular phenotypes of the biological processes at hand. Despite the vast increase of available transcriptome datasets, little is known about the evolutionary conservation of those characterized transcriptomes. Results: The myTAI package implements exploratory analysis functions to infer transcriptome conservation patterns in any transcriptome dataset. Comprehensive documentation of myTAI functions and tutorial vignettes provide step-by-step instructions on how to use the package in an exploratory and computationally reproducible manner. Availability and implementation: The open source myTAI package is available at https://github.com/HajkD/myTAI and https://cran.r-project.org/web/packages/myTAI/index.html. Contact: hgd23@cam.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.

EFFECTOR OF TRANSCRIPTION factors are novel plant-specific regulators associated with genomic DNA methylation in Arabidopsis.

Plant-specific EFFECTORS OF TRANSCRIPTION (ET) are characterised by a variable number of highly conserved ET repeats, which are involved in zinc and DNA binding. In addition, ETs share a GIY-YIG domain, involved in DNA nicking activity. It was hypothesised that ETs might act as epigenetic regulators. Here, methylome, transcriptome and phenotypic analyses were performed to investigate the role of ET factors and their involvement in DNA methylation in Arabidopsis thaliana. Comparative DNA methylation and transcriptome analyses in flowers and seedlings of et mutants revealed ET-specific differentially expressed genes and mostly independently characteristic, ET-specific differentially methylated regions. Loss of ET function results in pleiotropic developmental defects. The accumulation of cyclobutane pyrimidine dimers after ultraviolet stress in et mutants suggests an ET function in DNA repair.

Time resolved gene expression analysis during tamoxifen adaption of MCF-7 cells identifies long non-coding RNAs with prognostic impact.

Acquired tamoxifen resistance is a persistent problem for the treatment of estrogen receptor positive, premenopausal breast cancer patients and predictive biomarkers are still elusive. We here analyzed gene expression changes in a cellular model to identify early and late changes upon tamoxifen exposure and thereby novel prognostic biomarkers. Estrogen receptor positive MCF-7 cells were incubated with 4OH-tamoxifen (10 nM) and gene expression analyzed by array hybridization during 12 weeks. Array results were confirmed by nCounter- and qRT-PCR technique. Pathway enrichment analysis revealed that early responses concerned mainly amine synthesis and NRF2-related signaling and evolved into a stable gene expression pattern within 4 weeks characterized by changes in glucuronidation-, estrogen metabolism-, nuclear receptor- and interferon signaling pathways. As a large number of long non coding RNAs was subject to regulation, we investigated 5 of these (linc01213, linc00632 linc0992, LOC101929547 and XR_133213) in more detail. From these, only linc01213 was upregulated but all were less abundant in estrogen-receptor negative cell lines (MDA-MB 231, SKBR-3 and UACC3199). In a web-based survival analysis linc01213 and linc00632 turned out to have prognostic impact. Linc01213 was investigated further by plasmid-mediated over-expression as well as siRNA down-regulation in MCF-7 cells. Nevertheless, this had no effect on proliferation or expression of tamoxifen regulated genes, but migration was increased. In conclusion, the cellular model identified a set of lincRNAs with prognostic relevance for breast cancer. One of these, linc01213 although regulated by 4OH-tamoxifen, is not a central regulator of tamoxifen adaption, but interferes with the regulation of migration.

Causes and Consequences of A Glutamine Induced Normoxic HIF1 Activity for the Tumor Metabolism.

The transcription factor hypoxia-inducible factor 1 (HIF1) is the crucial regulator of genes that are involved in metabolism under hypoxic conditions, but information regarding the transcriptional activity of HIF1 in normoxic metabolism is limited. Different tumor cells were treated under normoxic and hypoxic conditions with various drugs that affect cellular metabolism. HIF1α was silenced by siRNA in normoxic/hypoxic tumor cells, before RNA sequencing and bioinformatics analyses were performed while using the breast cancer cell line MDA-MB-231 as a model. Differentially expressed genes were further analyzed and validated by qPCR, while the activity of the metabolites was determined by enzyme assays. Under normoxic conditions, HIF1 activity was significantly increased by (i) glutamine metabolism, which was associated with the release of ammonium, and it was decreased by (ii) acetylation via acetyl CoA synthetase (ACSS2) or ATP citrate lyase (ACLY), respectively, and (iii) the presence of L-ascorbic acid, citrate, or acetyl-CoA. Interestingly, acetylsalicylic acid, ibuprofen, L-ascorbic acid, and citrate each significantly destabilized HIF1α only under normoxia. The results from the deep sequence analyses indicated that, in HIF1-siRNA silenced MDA-MB-231 cells, 231 genes under normoxia and 1384 genes under hypoxia were transcriptionally significant deregulated in a HIF1-dependent manner. Focusing on glycolysis genes, it was confirmed that HIF1 significantly regulated six normoxic and 16 hypoxic glycolysis-associated gene transcripts. However, the results from the targeted metabolome analyses revealed that HIF1 activity affected neither the consumption of glucose nor the release of ammonium or lactate; however, it significantly inhibited the release of the amino acid alanine. This study comprehensively investigated, for the first time, how normoxic HIF1 is stabilized, and it analyzed the possible function of normoxic HIF1 in the transcriptome and metabolic processes of tumor cells in a breast cancer cell model. Furthermore, these data imply that HIF1 compensates for the metabolic outcomes of glutaminolysis and, subsequently, the Warburg effect might be a direct consequence of the altered amino acid metabolism in tumor cells.

Genome-wide single nucleotide polymorphism scan suggests adaptation to urbanization in an important pollinator, the red-tailed bumblebee (Bombus lapidarius L.).

Urbanization is considered a global threat to biodiversity; the growth of cities results in an increase in impervious surfaces, soil and air pollution, fragmentation of natural vegetation and invasion of non-native species, along with numerous environmental changes, including the heat island phenomenon. The combination of these effects constitutes a challenge for both the survival and persistence of many native species, while also imposing altered selective regimes. Here, using 110 314 single nucleotide polymorphisms generated by restriction-site-associated DNA sequencing, we investigated the genome-wide effects of urbanization on putative neutral and adaptive genomic diversity in a major insect pollinator, Bombus lapidarius, collected from nine German cities and nine paired rural sites. Overall, genetic differentiation among sites was low and there was no obvious genome-wide genetic structuring, suggesting the absence of strong effects of urbanization on gene flow. We nevertheless identified several loci under directional selection, a subset of which was associated with urban land use, including the percentage of impervious surface surrounding each sampling site. Overall, our results provide evidence of local adaptation to urbanization in the face of gene flow in a highly mobile insect pollinator.

InMoDe: tools for learning and visualizing intra-motif dependencies of DNA binding sites.

Summary: Recent studies have shown that the traditional position weight matrix model is often insufficient for modeling transcription factor binding sites, as intra-motif dependencies play a significant role for an accurate description of binding motifs. Here, we present the Java application InMoDe, a collection of tools for learning, leveraging and visualizing such dependencies of putative higher order. The distinguishing feature of InMoDe is a robust model selection from a class of parsimonious models, taking into account dependencies only if justified by the data while choosing for simplicity otherwise. Availability and Implementation: InMoDe is implemented in Java and is available as command line application, as application with a graphical user-interface, and as an integration into Galaxy on the project website at http://www.jstacs.de/index.php/InMoDe . Contact: ralf.eggeling@cs.helsinki.fi.

Unrealistic phylogenetic trees may improve phylogenetic footprinting.

MOTIVATION: The computational investigation of DNA binding motifs from binding sites is one of the classic tasks in bioinformatics and a prerequisite for understanding gene regulation as a whole. Due to the development of sequencing technologies and the increasing number of available genomes, approaches based on phylogenetic footprinting become increasingly attractive. Phylogenetic footprinting requires phylogenetic trees with attached substitution probabilities for quantifying the evolution of binding sites, but these trees and substitution probabilities are typically not known and cannot be estimated easily. RESULTS: Here, we investigate the influence of phylogenetic trees with different substitution probabilities on the classification performance of phylogenetic footprinting using synthetic and real data. For synthetic data we find that the classification performance is highest when the substitution probability used for phylogenetic footprinting is similar to that used for data generation. For real data, however, we typically find that the classification performance of phylogenetic footprinting surprisingly increases with increasing substitution probabilities and is often highest for unrealistically high substitution probabilities close to one. This finding suggests that choosing realistic model assumptions might not always yield optimal predictions in general and that choosing unrealistically high substitution probabilities close to one might actually improve the classification performance of phylogenetic footprinting. AVAILABILITY AND IMPLEMENTATION: The proposed PF is implemented in JAVA and can be downloaded from https://github.com/mgledi/PhyFoo. CONTACT: : martin.nettling@informatik.uni-halle.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Whole-transcriptome analysis reveals genetic factors underlying flowering time regulation in rapeseed (Brassica napus L.).

Rapeseed (Brassica napus L.), one of the most important sources of vegetable oil and protein-rich meals worldwide, is adapted to different geographical regions by modification of flowering time. Rapeseed cultivars have different day length and vernalization requirements, which categorize them into winter, spring, and semiwinter ecotypes. To gain a deeper insight into genetic factors controlling floral transition in B. napus, we performed RNA sequencing (RNA-seq) in the semiwinter doubled haploid line, Ningyou7, at different developmental stages and temperature regimes. The expression profiles of more than 54,000 gene models were compared between different treatments and developmental stages, and the differentially expressed genes were considered as targets for association analysis and genetic mapping to confirm their role in floral transition. Consequently, 36 genes with association to flowering time, seed yield, or both were identified. We found novel indications for neofunctionalization in homologs of known flowering time regulators like VIN3 and FUL. Our study proved the potential of RNA-seq along with association analysis and genetic mapping to identify candidate genes for floral transition in rapeseed. The candidate genes identified in this study could be subjected to genetic modification or targeted mutagenesis and genotype building to breed rapeseed adapted to certain environments.

Diversity of cis-regulatory elements associated with auxin response in Arabidopsis thaliana.

The phytohormone auxin regulates virtually every developmental process in land plants. This regulation is mediated via de-repression of DNA-binding auxin response factors (ARFs). ARFs bind TGTC-containing auxin response cis-elements (AuxREs), but there is growing evidence that additional cis-elements occur in auxin-responsive regulatory regions. The repertoire of auxin-related cis-elements and their involvement in different modes of auxin response are not yet known. Here we analyze the enrichment of nucleotide hexamers in upstream regions of auxin-responsive genes associated with auxin up- or down-regulation, with early or late response, ARF-binding domains, and with different chromatin states. Intriguingly, hexamers potentially bound by basic helix-loop-helix (bHLH) and basic leucine zipper (bZIP) factors as well as a family of A/T-rich hexamers are more highly enriched in auxin-responsive regions than canonical TGTC-containing AuxREs. We classify and annotate the whole spectrum of enriched hexamers and discuss their patterns of enrichment related to different modes of auxin response.

A transcriptomic hourglass in plant embryogenesis.

Animal and plant development starts with a constituting phase called embryogenesis, which evolved independently in both lineages. Comparative anatomy of vertebrate development--based on the Meckel-Serrès law and von Baer's laws of embryology from the early nineteenth century--shows that embryos from various taxa appear different in early stages, converge to a similar form during mid-embryogenesis, and again diverge in later stages. This morphogenetic series is known as the embryonic 'hourglass', and its bottleneck of high conservation in mid-embryogenesis is referred to as the phylotypic stage. Recent analyses in zebrafish and Drosophila embryos provided convincing molecular support for the hourglass model, because during the phylotypic stage the transcriptome was dominated by ancient genes and global gene expression profiles were reported to be most conserved. Although extensively explored in animals, an embryonic hourglass has not been reported in plants, which represent the second major kingdom in the tree of life that evolved embryogenesis. Here we provide phylotranscriptomic evidence for a molecular embryonic hourglass in Arabidopsis thaliana, using two complementary approaches. This is particularly significant because the possible absence of an hourglass based on morphological features in plants suggests that morphological and molecular patterns might be uncoupled. Together with the reported developmental hourglass patterns in animals, these findings indicate convergent evolution of the molecular hourglass and a conserved logic of embryogenesis across kingdoms.

Age- and Diabetes-Related Changes in the Free Fatty Acid Composition of the Human Stratum Corneum.

Of particular importance for Stratum corneum (SC) lipids are the free fatty acids (FFAs). Age-related changes of the SC structure lead to diminished capacity for barrier compensation. The aims of this cross-sectional study were to identify even-numbered especially odd-numbered FFAs within the intercorneocytic lamellar lipid structures of the SC and to explore age- and diabetes-related changes in FFAs. Gas chromatography - flame ionisation detection was used to qualitatively and quantitatively assess FFAs extracted from the SC. 110 subjects aged over 60 years (elderly/healthy), 110 subjects aged 18-40 (young/healthy) and 38 subjects with diabetes mellitus aged 18-40 (young/diabetic) were investigated. Overall, odd-numbered FFAs comprised about 21, 23 and 24% of total FFAs in subgroups elderly/healthy, young/healthy and young/diabetic. The most abundant short-chain FFAs were C16: 0 and C18: 0 and long-chain FFAs were C24: 0 and C26: 0. Only levels of C15: 0 and C17: 0 decreased with age. In contrast, levels of C18: 2 and C19 were significantly decreased and levels of C15, C17, C18: 1 and C23 were significantly increased in young diabetic subjects. In general, compared with younger healthy subjects, FFA composition was only partly significantly altered in older healthy subjects but was significantly altered in younger diabetic subjects.

Combining phylogenetic footprinting with motif models incorporating intra-motif dependencies.

BACKGROUND: Transcriptional gene regulation is a fundamental process in nature, and the experimental and computational investigation of DNA binding motifs and their binding sites is a prerequisite for elucidating this process. Approaches for de-novo motif discovery can be subdivided in phylogenetic footprinting that takes into account phylogenetic dependencies in aligned sequences of more than one species and non-phylogenetic approaches based on sequences from only one species that typically take into account intra-motif dependencies. It has been shown that modeling (i) phylogenetic dependencies as well as (ii) intra-motif dependencies separately improves de-novo motif discovery, but there is no approach capable of modeling both (i) and (ii) simultaneously. RESULTS: Here, we present an approach for de-novo motif discovery that combines phylogenetic footprinting with motif models capable of taking into account intra-motif dependencies. We study the degree of intra-motif dependencies inferred by this approach from ChIP-seq data of 35 transcription factors. We find that significant intra-motif dependencies of orders 1 and 2 are present in all 35 datasets and that intra-motif dependencies of order 2 are typically stronger than those of order 1. We also find that the presented approach improves the classification performance of phylogenetic footprinting in all 35 datasets and that incorporating intra-motif dependencies of order 2 yields a higher classification performance than incorporating such dependencies of only order 1. CONCLUSION: Combining phylogenetic footprinting with motif models incorporating intra-motif dependencies leads to an improved performance in the classification of transcription factor binding sites. This may advance our understanding of transcriptional gene regulation and its evolution.