Cis-regulatory determinants of MyoD function.

Muscle-specific transcription factor MyoD orchestrates the myogenic gene expression program by binding to short DNA motifs called E-boxes within myogenic cis-regulatory elements (CREs). Genome-wide analyses of MyoD cistrome by chromatin immnunoprecipitation sequencing shows that MyoD-bound CREs contain multiple E-boxes of various sequences. However, how E-box numbers, sequences and their spatial arrangement within CREs collectively regulate the binding affinity and transcriptional activity of MyoD remain largely unknown. Here, by an integrative analysis of MyoD cistrome combined with genome-wide analysis of key regulatory histones and gene expression data we show that the affinity landscape of MyoD is driven by multiple E-boxes, and that the overall binding affinity-and associated nucleosome positioning and epigenetic features of the CREs-crucially depend on the variant sequences and positioning of the E-boxes within the CREs. By comparative genomic analysis of single nucleotide polymorphism (SNPs) across publicly available data from 17 strains of laboratory mice, we show that variant sequences within the MyoD-bound motifs, but not their genome-wide counterparts, are under selection. At last, we show that the quantitative regulatory effect of MyoD binding on the nearby genes can, in part, be predicted by the motif composition of the CREs to which it binds. Taken together, our data suggest that motif numbers, sequences and their spatial arrangement within the myogenic CREs are important determinants of the cis-regulatory code of myogenic CREs.

MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data.

MOTIVATION: Reliable estimation of the mean fragment length for next-generation short-read sequencing data is an important step in next-generation sequencing analysis pipelines, most notably because of its impact on the accuracy of the enriched regions identified by peak-calling algorithms. Although many peak-calling algorithms include a fragment-length estimation subroutine, the problem has not been adequately solved, as demonstrated by the variability of the estimates returned by different algorithms. RESULTS: In this article, we investigate the use of strand cross-correlation to estimate mean fragment length of single-end data and show that traditional estimation approaches have mixed reliability. We observe that the mappability of different parts of the genome can introduce an artificial bias into cross-correlation computations, resulting in incorrect fragment-length estimates. We propose a new approach, called mappability-sensitive cross-correlation (MaSC), which removes this bias and allows for accurate and reliable fragment-length estimation. We analyze the computational complexity of this approach, and evaluate its performance on a test suite of NGS datasets, demonstrating its superiority to traditional cross-correlation analysis. AVAILABILITY: An open-source Perl implementation of our approach is available at http://www.perkinslab.ca/Software.html.

Costs of Next-Generation Sequencing Assays in Non-Small Cell Lung Cancer: A Micro-Costing Study.

Background: Next-generation sequencing (NGS) of tumor genomes has changed and improved cancer treatment over the past few decades. It can inform clinicians on the optimal therapeutic approach in many of the solid and hematologic cancers, including non-small lung cancer (NSCLC). Our study aimed to determine the costs of NGS assays for NSCLC diagnostics. Methods: We performed a micro-costing study of four NGS assays (Trusight Tumor 170 Kit (Illumina), Oncomine Focus (Thermo Fisher), QIAseq Targeted DNA Custom Panel and QIASeq Targeted RNAscan Custom Panel (Qiagen), and KAPA HyperPlus/SeqCap EZ (Roche)) at the StemCore Laboratories, the Ottawa Hospital, Canada. We used a time-and-motion approach to measure personnel time and a pre-defined questionnaire to collect resource utilization. The unit costs were based on market prices. The cost data were reported in 2019 Canadian dollars. Results: Based on a case throughput of 500 cases per year, the per-sample cost for TruSight Tumor 170 Kit, QIASeq Targeted DNA Custom Panel and QIASeq Targeted RNAscan Custom Panel, Oncomine Focus, and HyperPlus/SeqCap EZ were CAD 1778, CAD 599, CAD 1100 and CAD 1270, respectively. The key cost drivers were library preparation (34-60%) and sequencing (31-51%), followed by data analysis (6-13%) and administrative support (2-7%). Conclusions: Trusight Tumor 170 Kit was the most expensive NGS assay for NSCLC diagnostics; however, an economic evaluation is required to identify the most cost-effective NGS assay. Our study results could help inform decisions to select a robust platform for NSCLC diagnostics from fine needle aspirates, and future economic evaluations of the NGS platforms to guide treatment selections for NSCLC patients.

A genome-wide strategy to identify causes and consequences of retrotransposon expression finds activation by BRCA1 in ovarian cancer.

It is challenging to identify the causes and consequences of retrotransposon expression in human disease due to the hundreds of active genomic copies and their poor conservation across species. We profiled genomic insertions of retrotransposons in ovarian cancer. In addition, in ovarian and breast cancer we analyzed RNAs exhibiting Bayesian correlation with retrotransposon RNA to identify causes and consequences of retrotransposon expression. This strategy finds divergent inflammatory responses associated with retrotransposon expression in ovarian and breast cancer and identifies new factors inducing expression of endogenous retrotransposons including anti-viral responses and the common tumor suppressor BRCA1. In cell lines, mouse ovarian epithelial cells and patient-derived tumor spheroids, BRCA1 promotes accumulation of retrotransposon RNA. BRCA1 promotes transcription of active families of retrotransposons and their insertion into the genome. Intriguingly, elevated retrotransposon expression predicts survival in ovarian cancer patients. Retrotransposons are part of a complex regulatory network in ovarian cancer including BRCA1 that contributes to patient survival. The described strategy can be used to identify the regulators and impacts of retrotransposons in various contexts of biology and disease in humans.

Detection of alpha-rod protein repeats using a neural network and application to huntingtin.

A growing number of solved protein structures display an elongated structural domain, denoted here as alpha-rod, composed of stacked pairs of anti-parallel alpha-helices. Alpha-rods are flexible and expose a large surface, which makes them suitable for protein interaction. Although most likely originating by tandem duplication of a two-helix unit, their detection using sequence similarity between repeats is poor. Here, we show that alpha-rod repeats can be detected using a neural network. The network detects more repeats than are identified by domain databases using multiple profiles, with a low level of false positives (<10%). We identify alpha-rod repeats in approximately 0.4% of proteins in eukaryotic genomes. We then investigate the results for all human proteins, identifying alpha-rod repeats for the first time in six protein families, including proteins STAG1-3, SERAC1, and PSMD1-2 & 5. We also characterize a short version of these repeats in eight protein families of Archaeal, Bacterial, and Fungal species. Finally, we demonstrate the utility of these predictions in directing experimental work to demarcate three alpha-rods in huntingtin, a protein mutated in Huntington's disease. Using yeast two hybrid analysis and an immunoprecipitation technique, we show that the huntingtin fragments containing alpha-rods associate with each other. This is the first definition of domains in huntingtin and the first validation of predicted interactions between fragments of huntingtin, which sets up directions toward functional characterization of this protein. An implementation of the repeat detection algorithm is available as a Web server with a simple graphical output: http://www.ogic.ca/projects/ard. This can be further visualized using BiasViz, a graphic tool for representation of multiple sequence alignments.

Accuracy and reproducibility of somatic point mutation calling in clinical-type targeted sequencing data.

BACKGROUND: Treating cancer depends in part on identifying the mutations driving each patient's disease. Many clinical laboratories are adopting high-throughput sequencing for assaying patients' tumours, applying targeted panels to formalin-fixed paraffin-embedded tumour tissues to detect clinically-relevant mutations. While there have been some benchmarking and best practices studies of this scenario, much variant calling work focuses on whole-genome or whole-exome studies, with fresh or fresh-frozen tissue. Thus, definitive guidance on best choices for sequencing platforms, sequencing strategies, and variant calling for clinical variant detection is still being developed. METHODS: Because ground truth for clinical specimens is rarely known, we used the well-characterized Coriell cell lines GM12878 and GM12877 to generate data. We prepared samples to mimic as closely as possible clinical biopsies, including formalin fixation and paraffin embedding. We evaluated two well-known targeted sequencing panels, Illumina's TruSight 170 hybrid-capture panel and the amplification-based Oncomine Focus panel. Sequencing was performed on an Illumina NextSeq500 and an Ion Torrent PGM respectively. We performed multiple replicates of each assay, to test reproducibility. Finally, we applied four different freely-available somatic single-nucleotide variant (SNV) callers to the data, along with the vendor-recommended callers for each sequencing platform. RESULTS: We did not observe major differences in variant calling success within the regions that each panel covers, but there were substantial differences between callers. All had high sensitivity for true SNVs, but numerous and non-overlapping false positives. Overriding certain default parameters to make them consistent between callers substantially reduced discrepancies, but still resulted in high false positive rates. Intersecting results from multiple replicates or from different variant callers eliminated most false positives, while maintaining sensitivity. CONCLUSIONS: Reproducibility and accuracy of targeted clinical sequencing results depend less on sequencing platform and panel than on variability between replicates and downstream bioinformatics. Differences in variant callers' default parameters are a greater influence on algorithm disagreement than other differences between the algorithms. Contrary to typical clinical practice, we recommend employing multiple variant calling pipelines and/or analyzing replicate samples, as this greatly decreases false positive calls.

An OTX2-PAX3 signaling axis regulates Group 3 medulloblastoma cell fate.

OTX2 is a potent oncogene that promotes tumor growth in Group 3 medulloblastoma. However, the mechanisms by which OTX2 represses neural differentiation are not well characterized. Here, we perform extensive multiomic analyses to identify an OTX2 regulatory network that controls Group 3 medulloblastoma cell fate. OTX2 silencing modulates the repressive chromatin landscape, decreases levels of PRC2 complex genes and increases the expression of neurodevelopmental transcription factors including PAX3 and PAX6. Expression of PAX3 and PAX6 is significantly lower in Group 3 medulloblastoma patients and is correlated with reduced survival, yet only PAX3 inhibits self-renewal in vitro and increases survival in vivo. Single cell RNA sequencing of Group 3 medulloblastoma tumorspheres demonstrates expression of an undifferentiated progenitor program observed in primary tumors and characterized by translation/elongation factor genes. Identification of mTORC1 signaling as a downstream effector of OTX2-PAX3 reveals roles for protein synthesis pathways in regulating Group 3 medulloblastoma pathogenesis.

A complex of C9ORF72 and p62 uses arginine methylation to eliminate stress granules by autophagy.

Mutations in proteins like FUS which cause Amyotrophic Lateral Sclerosis (ALS) result in the aberrant formation of stress granules while ALS-linked mutations in other proteins impede elimination of stress granules. Repeat expansions in C9ORF72, the major cause of ALS, reduce C9ORF72 levels but how this impacts stress granules is uncertain. Here, we demonstrate that C9ORF72 associates with the autophagy receptor p62 and controls elimination of stress granules by autophagy. This requires p62 to associate via the Tudor protein SMN with proteins, including FUS, that are symmetrically methylated on arginines. Mice lacking p62 accumulate arginine-methylated proteins and alterations in FUS-dependent splicing. Patients with C9ORF72 repeat expansions accumulate symmetric arginine dimethylated proteins which co-localize with p62. This suggests that C9ORF72 initiates a cascade of ALS-linked proteins (C9ORF72, p62, SMN, FUS) to recognize stress granules for degradation by autophagy and hallmarks of a defect in this process are observable in ALS patients.

Characterization of a novel OTX2-driven stem cell program in Group 3 and Group 4 medulloblastoma.

Medulloblastoma (MB) is the most common malignant primary pediatric brain cancer. Among the most aggressive subtypes, Group 3 and Group 4 originate from stem/progenitor cells, frequently metastasize, and often display the worst prognosis, yet we know the least about the molecular mechanisms driving their progression. Here, we show that the transcription factor orthodenticle homeobox 2 (OTX2) promotes self-renewal while inhibiting differentiation in vitro and increases tumor initiation from MB stem/progenitor cells in vivo. To determine how OTX2 contributes to these processes, we employed complementary bioinformatic approaches to characterize the OTX2 regulatory network and identified novel relationships between OTX2 and genes associated with neuronal differentiation and axon guidance signaling in Group 3 and Group 4 MB stem/progenitor cells. In particular, OTX2 levels were negatively correlated with semaphorin (SEMA) signaling, as expression of 9 SEMA pathway genes is upregulated following OTX2 knockdown with some being potential direct OTX2 targets. Importantly, this negative correlation was also observed in patient samples, with lower expression of SEMA4D associated with poor outcome specifically in Group 4 tumors. Functional proof-of-principle studies demonstrated that increased levels of select SEMA pathway genes are associated with decreased self-renewal and growth in vitro and in vivo and that RHO signaling, known to mediate the effects of SEMA genes, is contributing to the OTX2 KD phenotype. Our study provides mechanistic insight into the networks controlled by OTX2 in MB stem/progenitor cells and reveals novel roles for axon guidance genes and their downstream effectors as putative tumor suppressors in MB.

Mtf2-PRC2 control of canonical Wnt signaling is required for definitive erythropoiesis.

Polycomb repressive complex 2 (PRC2) accessory proteins play substoichiometric, tissue-specific roles to recruit PRC2 to specific genomic loci or increase enzymatic activity, while PRC2 core proteins are required for complex stability and global levels of trimethylation of histone 3 at lysine 27 (H3K27me3). Here, we demonstrate a role for the classical PRC2 accessory protein Mtf2/Pcl2 in the hematopoietic system that is more akin to that of a core PRC2 protein. Mtf2-/- erythroid progenitors demonstrate markedly decreased core PRC2 protein levels and a global loss of H3K27me3 at promoter-proximal regions. The resulting de-repression of transcriptional and signaling networks blocks definitive erythroid development, culminating in Mtf2-/- embryos dying by e15.5 due to severe anemia. Gene regulatory network (GRN) analysis demonstrated Mtf2 directly regulates Wnt signaling in erythroblasts, leading to activated canonical Wnt signaling in Mtf2-deficient erythroblasts, while chemical inhibition of canonical Wnt signaling rescued Mtf2-deficient erythroblast differentiation in vitro. Using a combination of in vitro, in vivo and systems analyses, we demonstrate that Mtf2 is a critical epigenetic regulator of Wnt signaling during erythropoiesis and recast the role of polycomb accessory proteins in a tissue-specific context.

Gene function in early mouse embryonic stem cell differentiation.

BACKGROUND: Little is known about the genes that drive embryonic stem cell differentiation. However, such knowledge is necessary if we are to exploit the therapeutic potential of stem cells. To uncover the genetic determinants of mouse embryonic stem cell (mESC) differentiation, we have generated and analyzed 11-point time-series of DNA microarray data for three biologically equivalent but genetically distinct mESC lines (R1, J1, and V6.5) undergoing undirected differentiation into embryoid bodies (EBs) over a period of two weeks. RESULTS: We identified the initial 12 hour period as reflecting the early stages of mESC differentiation and studied probe sets showing consistent changes of gene expression in that period. Gene function analysis indicated significant up-regulation of genes related to regulation of transcription and mRNA splicing, and down-regulation of genes related to intracellular signaling. Phylogenetic analysis indicated that the genes showing the largest expression changes were more likely to have originated in metazoans. The probe sets with the most consistent gene changes in the three cell lines represented 24 down-regulated and 12 up-regulated genes, all with closely related human homologues. Whereas some of these genes are known to be involved in embryonic developmental processes (e.g. Klf4, Otx2, Smn1, Socs3, Tagln, Tdgf1), our analysis points to others (such as transcription factor Phf21a, extracellular matrix related Lama1 and Cyr61, or endoplasmic reticulum related Sc4mol and Scd2) that have not been previously related to mESC function. The majority of identified functions were related to transcriptional regulation, intracellular signaling, and cytoskeleton. Genes involved in other cellular functions important in ESC differentiation such as chromatin remodeling and transmembrane receptors were not observed in this set. CONCLUSION: Our analysis profiles for the first time gene expression at a very early stage of mESC differentiation, and identifies a functional and phylogenetic signature for the genes involved. The data generated constitute a valuable resource for further studies. All DNA microarray data used in this study are available in the StemBase database of stem cell gene expression data 1 and in the NCBI's GEO database.

ChIP on SNP-chip for genome-wide analysis of human histone H4 hyperacetylation.

BACKGROUND: SNP microarrays are designed to genotype Single Nucleotide Polymorphisms (SNPs). These microarrays report hybridization of DNA fragments and therefore can be used for the purpose of detecting genomic fragments. RESULTS: Here, we demonstrate that a SNP microarray can be effectively used in this way to perform chromatin immunoprecipitation (ChIP) on chip as an alternative to tiling microarrays. We illustrate this novel application by mapping whole genome histone H4 hyperacetylation in human myoblasts and myotubes. We detect clusters of hyperacetylated histone H4, often spanning across up to 300 kilobases of genomic sequence. Using complementary genome-wide analyses of gene expression by DNA microarray we demonstrate that these clusters of hyperacetylated histone H4 tend to be associated with expressed genes. CONCLUSION: The use of a SNP array for a ChIP-on-chip application (ChIP on SNP-chip) will be of great value to laboratories whose interest is the determination of general rules regarding the relationship of specific chromatin modifications to transcriptional status throughout the genome and to examine the asymmetric modification of chromatin at heterozygous loci.

StemBase: a resource for the analysis of stem cell gene expression data.

StemBase is a database of gene expression data obtained from stem cells and derivatives mainly from mouse and human using DNA microarrays and Serial Analysis of Gene Expression. Here, we describe this database and indicate ways to use it for the study the expression of particular genes in stem cells or to search for genes with particular expression profiles in stem cells, which could be associated to stem cell function or used as stem cell markers.

Reprogramming progeria fibroblasts re-establishes a normal epigenetic landscape.

Ideally, disease modeling using patient-derived induced pluripotent stem cells (iPSCs) enables analysis of disease initiation and progression. This requires any pathological features of the patient cells used for reprogramming to be eliminated during iPSC generation. Hutchinson-Gilford progeria syndrome (HGPS) is a segmental premature aging disorder caused by the accumulation of the truncated form of Lamin A known as Progerin within the nuclear lamina. Cellular hallmarks of HGPS include nuclear blebbing, loss of peripheral heterochromatin, defective epigenetic inheritance, altered gene expression, and senescence. To model HGPS using iPSCs, detailed genome-wide and structural analysis of the epigenetic landscape is required to assess the initiation and progression of the disease. We generated a library of iPSC lines from fibroblasts of patients with HGPS and controls, including one family trio. HGPS patient-derived iPSCs are nearly indistinguishable from controls in terms of pluripotency, nuclear membrane integrity, as well as transcriptional and epigenetic profiles, and can differentiate into affected cell lineages recapitulating disease progression, despite the nuclear aberrations, altered gene expression, and epigenetic landscape inherent to the donor fibroblasts. These analyses demonstrate the power of iPSC reprogramming to reset the epigenetic landscape to a revitalized pluripotent state in the face of widespread epigenetic defects, validating their use to model the initiation and progression of disease in affected cell lineages.

Taxonomic colouring of phylogenetic trees of protein sequences.

BACKGROUND: Phylogenetic analyses of protein families are used to define the evolutionary relationships between homologous proteins. The interpretation of protein-sequence phylogenetic trees requires the examination of the taxonomic properties of the species associated to those sequences. However, there is no online tool to facilitate this interpretation, for example, by automatically attaching taxonomic information to the nodes of a tree, or by interactively colouring the branches of a tree according to any combination of taxonomic divisions. This is especially problematic if the tree contains on the order of hundreds of sequences, which, given the accelerated increase in the size of the protein sequence databases, is a situation that is becoming common. RESULTS: We have developed PhyloView, a web based tool for colouring phylogenetic trees upon arbitrary taxonomic properties of the species represented in a protein sequence phylogenetic tree. Provided that the tree contains SwissProt, SpTrembl, or GenBank protein identifiers, the tool retrieves the taxonomic information from the corresponding database. A colour picker displays a summary of the findings and allows the user to associate colours to the leaves of the tree according to any number of taxonomic partitions. Then, the colours are propagated to the branches of the tree. CONCLUSION: PhyloView can be used at http://www.ogic.ca/projects/phyloview/. A tutorial, the software with documentation, and GPL licensed source code, can be accessed at the same web address.

Study of stem cell function using microarray experiments.

DNA Microarrays are used to simultaneously measure the levels of thousands of mRNAs in a sample. We illustrate here that a collection of such measurements in different cell types and states is a sound source of functional predictions, provided the microarray experiments are analogous and the cell samples are appropriately diverse. We have used this approach to study stem cells, whose identity and mechanisms of control are not well understood, generating Affymetrix microarray data from more than 200 samples, including stem cells and their derivatives, from human and mouse. The data can be accessed online (StemBase; http://www.scgp.ca:8080/StemBase/).

Genomic adaptation to acidic environment: evidence from Helicobacter pylori.

The origin of new functions is fundamental in understanding evolution, and three processes known as adaptation, preadaptation, and exaptation have been proposed as possible evolutionary pathways leading to the origin of new functions. Here we examine the origin of an acid resistance mechanism in the mammalian gastric pathogen Helicobacter pylori, with reference to these three evolutionary pathways. The mechanism involved is that H. pylori, when exposed to the acidic environment in mammalian stomach, restricts the acute proton entry across its membrane by its increased usage of positively charged amino acids in the inner and outer membrane proteins. The results of our comparative genomic analysis between H. pylori, the two closely related species Helicobacter hepaticus and Campylobacter jejuni, and other relevant proteobacterial species are incompatible with the hypotheses invoking preadaptation or exaptation. The acid resistance mechanism most likely arose by selection favoring an increased usage of positively charged lysine in membrane proteins.

BIDCHIPS: bias decomposition and removal from ChIP-seq data clarifies true binding signal and its functional correlates.

BACKGROUND: Unraveling transcriptional regulatory networks is a central problem in molecular biology and, in this quest, chromatin immunoprecipitation and sequencing (ChIP-seq) technology has given us the unprecedented ability to identify sites of protein-DNA binding and histone modification genome wide. However, multiple systemic and procedural biases hinder harnessing the full potential of this technology. Previous studies have addressed this problem, but a thorough characterization of different, interacting biases on ChIP-seq signals is still lacking. RESULTS: Here, we present a novel framework where the genome-wide ChIP-seq signal is viewed as being quantifiably influenced by different, measurable sources of bias, which can then be computationally subtracted away. We use a compendium of 123 human ENCODE ChIP-seq datasets to build regression models that tell us how much of a ChIP-seq signal can be attributed to mappability, GC-content, chromatin accessibility, and factors represented in input DNA and IgG controls. When we use the model to separate out these non-binding influences from the ChIP-seq signal, we obtain a purified signal that associates better to TF-DNA-binding motifs than do other measures of peak significance. We also carry out a multiscale analysis that reveals how ChIP-seq signal biases differ across different scales. Finally, we investigate previously reported associations between gene expression and ChIP-seq signals at transcription start sites. We show that our model can be used to discriminate ChIP-seq signals that are truly related to gene expression from those that are merely correlated by virtue of bias-in particular, chromatin accessibility bias, which shows up in ChIP-seq signals and also relates to gene expression. CONCLUSIONS: Our study provides new insights into the behavior of ChIP-seq signal biases and proposes a novel mitigation framework that improves results compared to existing techniques. With ChIP-seq now being the central technology for studying transcriptional regulation, it is most crucial to accurately characterize, quantify, and adjust for the genome-wide effects of biases affecting ChIP-seq. Our study also emphasizes that properly accounting for confounders in ChIP-seq data is of paramount importance for obtaining biologically accurate insights into the workings of the complex regulatory mechanisms in living organisms. R and MATLAB packages implementing the framework can be obtained from http://www.perkinslab.ca/Software.html.

Chromatin tandem affinity purification sequencing.

Chromatin immunoprecipitation coupled with ultra-high-throughput sequencing (ChIP-seq) is a widely used method for mapping the interactions of proteins with DNA. However, the requirements for ChIP-grade antibodies impede wider application of this method, and variations in results can be high owing to differences in affinity and cross-reactivity of antibodies. Therefore, we developed chromatin tandem affinity purification (ChTAP) as an effective alternative to ChIP. Through the use of affinity tags and reagents that are identical for all proteins investigated, ChTAP enables one to directly compare the binding between different transcription factors and to directly assess the background in control experiments. Thus, ChTAP-seq can be used to rapidly map the genome-wide binding of multiple DNA-binding proteins in a wide range of cell types. ChTAP can be completed in 3-4 d, starting from cross-linking of chromatin to purification of ChIP DNA.

Functional and genomic analyses of alpha-solenoid proteins.

Alpha-solenoids are flexible protein structural domains formed by ensembles of alpha-helical repeats (Armadillo and HEAT repeats among others). While homology can be used to detect many of these repeats, some alpha-solenoids have very little sequence homology to proteins of known structure and we expect that many remain undetected. We previously developed a method for detection of alpha-helical repeats based on a neural network trained on a dataset of protein structures. Here we improved the detection algorithm and updated the training dataset using recently solved structures of alpha-solenoids. Unexpectedly, we identified occurrences of alpha-solenoids in solved protein structures that escaped attention, for example within the core of the catalytic subunit of PI3KC. Our results expand the current set of known alpha-solenoids. Application of our tool to the protein universe allowed us to detect their significant enrichment in proteins interacting with many proteins, confirming that alpha-solenoids are generally involved in protein-protein interactions. We then studied the taxonomic distribution of alpha-solenoids to discuss an evolutionary scenario for the emergence of this type of domain, speculating that alpha-solenoids have emerged in multiple taxa in independent events by convergent evolution. We observe a higher rate of alpha-solenoids in eukaryotic genomes and in some prokaryotic families, such as Cyanobacteria and Planctomycetes, which could be associated to increased cellular complexity. The method is available at http://cbdm.mdc-berlin.de/~ard2/.