Acute Q fever is a worldwide zoonotic infection due to C. burnetii that may be associated with hepatitis. Nonspecific clinical and biological manifestations may accompany liver involvement, including hepatomegaly and elevated liver biological tests. However, the presence of jaundice is rare. Therefore, making a diagnosis of Q fever hepatitis may be difficult in an afebrile patient with jaundice of recent onset, altered liver function tests, excessive alcohol intake and no reported contact with animals. We report here the diagnostic work-up and complex clinical management of a patient presenting with acute hepatitis resulting from both C. burnetii infection and severe alcoholic steatohepatitis. Positive serology together with a detailed examination of the liver biopsy was able to reveal the coexistence of both Q fever hepatitis with typical fibrin-ring granulomas as well as florid lesions of alcoholic steatohepatitis. A combination of antibiotics, hydroxychloroquine and steroids, guided by the helpful description of changes in histological alterations on repeated liver biopsies during the course of the disease contributed to the slow but favorable outcome.

Array comparative genomic hybridization (array CGH) is a method for detecting gains and losses of DNA segments or gene dosage in the genome 1. Recent advances in this technology have enabled high resolution comparison of whole genomes for the identification of genetic alterations in cancer and other genetic diseases 2. The Sub-Megabase Resolution Tiling-set array (or SMRT) array is comprised of a set of approximately thirty thousand overlapping bacterial artificial chromosome (BAC) clones that span the human genome in ~100 kilobase pair (kb) segments 2. These BAC targets are individually synthesized and spotted in duplicate on a single glass slide 2-4. Array CGH is based on the principle of competitive hybridization. Sample and reference DNA are differentially labeled with Cyanine-3 and Cyanine-5 fluorescent dyes, and co-hybridized to the array. After an incubation period the unbound samples are washed from the slide and the array is imaged. A freely available custom software package called SeeGH (www.flintbox.ca) is used to process the large volume of data collected - a single experiment generates 53,892 data points. SeeGH visualizes the log2 signal intensity ratio between the 2 samples at each BAC target which is vertically aligned with chromosomal position 5,6. The SMRT array can detect alterations as small as 50 kb in size 7. The SMRT array can detect a variety of DNA rearrangement events including DNA gains, losses, amplifications and homozygous deletions. A unique advantage of the SMRT array is that one can use DNA isolated from formalin fixed paraffin embedded samples. When combined with the low input requirements of unamplified DNA (25-100ng) this allows profiling of precious samples such as those produced by microdissection 7,8. This is attributed to the large size of each BAC hybridization target that allows the binding of sufficient labeled samples to produce signals for detection. Another advantage of this platform is the tolerance of tissue heterogeneity, decreasing the need for tedious tissue microdissection 8. This video protocol is a step-by-step tutorial from labeling the input DNA through to signal acquisition for the whole genome tiling path SMRT array.

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its application in a clinical diagnostic service laboratory. DNA extracted from a patient’s sample (blood, saliva or other tissue types) is labeled with a fluorochrome (either cyanine 5 or cyanine 3). A reference DNA sample is labeled with the opposite fluorochrome. There follows a cleanup step to remove unincorporated nucleotides before the labeled DNAs are mixed and resuspended in a hybridization buffer and applied to an array comprising ~60,000 oligonucleotide probes from loci across the genome, with high probe density in clinically important areas. Following hybridization, the arrays are washed, then scanned and the resulting images are analyzed to measure the red and green fluorescence for each probe. Software is used to assess the quality of each probe measurement, calculate the ratio of red to green fluorescence and detect potential copy number variants.

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its application in a clinical diagnostic service laboratory. DNA extracted from a patient’s sample (blood, saliva or other tissue types) is labeled with a fluorochrome (either cyanine 5 or cyanine 3). A reference DNA sample is labeled with the opposite fluorochrome. There follows a cleanup step to remove unincorporated nucleotides before the labeled DNAs are mixed and resuspended in a hybridization buffer and applied to an array comprising ~60,000 oligonucleotide probes from loci across the genome, with high probe density in clinically important areas. Following hybridization, the arrays are washed, then scanned and the resulting images are analyzed to measure the red and green fluorescence for each probe. Software is used to assess the quality of each probe measurement, calculate the ratio of red to green fluorescence and detect potential copy number variants.

In the current issue Mertzanidou et al. (2012) report a detailed chromosome study of cleavage-stage embryos using a version of the array comparative genomic hybridization (aCGH) technique. The aCGH technique is widely used in the genetics field and this study provides an opportunity to offer some guidance to the journal reader on its scope and limitations when applied to early human embryos, and the interpretation of the complex results sometimes obtained.

Numerical chromosomal abnormalities cause a broad spectrum of clinical symptoms for children, including congenital malformations, developmental delay, and epilepsy. The combinations and significance of such symptoms are associated with specific chromosome regions. Prognosis of developmental delay and epilepsy also depends on the chromosomal regions affected. Many distinctive chromosomal deletion syndromes have been clinically recognized. Miller–Dieker syndrome, due to the subtelomeric deletion of the short arm of chromosome 17, is one of the most characteristic chromosomal aberrations. Because patients with 17p monosomy show typical lissencephaly and distinctive facial features, they are easily recognized by the combinatory findings of clinical manifestations. Patients with 17p monosomy show variable deletion sizes. Accumulated genetic information regarding the size of 17p deletions and patients' clinical information led to the establishment of genotype–phenotype relationships and narrowed the causative chromosomal regions for each clinical finding.[1] The genes responsible for each clinical finding have been identified; LIS1 and YWHAE are the causative genes for lissencephaly and distinctive facial features, respectively.[2] Such genotype–phenotype correlation studies have been accelerated by the development of genetic technologies. Microarray-based comparative genomic hybridization (aCGH) is one of such technologies. aCGH can accurately identify small chromosomal deletions at the molecular level.[3] Therefore, the resolution of genotype–phenotype correlation studies has been improved, and causative genes for clinical findings are more easily identified. In this special issue, we provide reviews focused on various chromosome regions that are related to epilepsy, including 1p36 deletion syndrome, 2q24 deletions, Wolf–Hirschhorn syndrome (4p-), 9q34 deletions, Angelman syndrome (15q11.2), 16p11.2 deletion/duplication syndrome, ring(20) syndrome, and Xq28 duplication syndrome (MECP2). The 1p36 deletion syndrome is the most common among the subtelomeric deletion syndromes.[4] On the other hand, the Xq28 duplication syndrome is the most common among the chromosomal duplication syndromes.[5] The 16p11.2 deletion/duplication syndrome is newly established based on aCGH studies.[6] The 16p11.2 deletion of ∼600 kb is common among patients with neuropsychiatric disorders. However, clinical features are often nonspecific. Chromosomal deletions of the 2q24.3 region have also been identified using aCGH.[7] Sodium channel genes including SCN1A are located in this region as a clustering. Small deletions in this region have been identified in patients with intractable epilepsy. Chromosomal deletions of the 9q34.11 region are symbolic, because the causative gene for Ohtahara syndrome, STXBP1, was first identified in this region.[8] Both the 15q11.2 deletion and ring(20) syndrome are well-known chromosome aberrations. Recent progress related to these particular deletions has been reviewed. As an invited editor of this special issue, I encouraged specialists from around the world to contribute reviews. However, all of the authors who agreed my proposals were from Japan. I am grateful to all of the contributing authors for their excellent reviews and timely submissions. The review process was kindly supported by the deputy editor, Professor Okumura, Aichi Medical University, Japan. I hope that the reviews provide a better understanding of chromosomal aberrations related to childhood epilepsy for the readers of this journal.

This review reports main progresses in various pediatric issues published in Italian Journal of Pediatrics and in international journals in 2016. New insights in clinical features or complications of several disorders may be useful for our better understanding. They comprise severe asthma, changing features of lupus erythematosus from birth to adolescence, celiac disease, functional gastrointestinal disorders, Moebius syndrome, recurrent pneumonia. Risk factors for congenital heart defects, Kawasaki disease have been widely investigated. New diagnostic tools are available for ascertaining brucellosis, celiac disease and viral infections. The usefulness of aCGH as first-tier test is confirmed in patients with neurodevelopmental disorders. Novel information have been provided on the safety of milk for infants. Recent advances in the treatment of common disorders, including neonatal respiratory distress syndrome, hypo-glycemia in newborns, atopic dermatitis, constipation, cyclic vomiting syndrome, nephrotic syndrome, diabetes mellitus, regurgitation, short stature, secretions in children with cerebral palsy have been reported. Antipyretics treatment has been updated by national guidelines and studies have excluded side effects (e.g. asthma risk during acetaminophen therapy). Vaccinations are a painful event and several options are reported to prevent this pain. Adverse effects due to metabolic abnormalities are reported for second generation antipsychotic drugs.

The initiating somatic genetic events in chordoma development have not yet been identified. Most cytogenetically investigated chordomas have displayed near-diploid or moderately hypodiploid karyotypes, with several numerical and structural rearrangements. However, no consistent structural chromosome aberration has been reported. This is the first array-based study characterising DNA copy number changes in chordoma. Array comparative genomic hybridisation (aCGH) identified copy number alterations in all samples and imbalances affecting 5 or more out of the 21 investigated tumours were seen on all chromosomes. In general, deletions were more common than gains and no high-level amplification was found, supporting previous findings of primarily losses of large chromosomal regions as an important mechanism in chordoma development. Although small imbalances were commonly found, the vast majority of these were detected in single cases; no small deletion affecting all tumours could be discerned. However, the CDKN2A and CDKN2B loci in 9p21 were homo- or heterozygously lost in 70% of the tumours, a finding corroborated by fluorescence in situ hybridisation, suggesting that inactivation of these genes constitute an important step in chordoma development.British Journal of Cancer (2008) 98, 434-442. doi:10.1038/sj.bjc.6604130 www.bjcancer.com Published online 11 December 2007

In this era of explosive high throughput (HT) genomics data generation, there is a growing need for accessible software solutions that can help unlock biological/clinical characteristics from such data. With the biomedical researcher (with limited or no bioinformatics skills) in mind, we developed a comprehensive web-based system called R2 (http://r2.amc.nl). R2 aids in the analysis and visualization of private/shielded as well as public high throughput data and their associated annotated features. The R2 platform consists of a database storing both publicly accessible as well as shielded datasets with unified gene annotation, supplemented with a large suite of tools that can be used on these data, and their associated annotation. As such the user experiences the same look & feel throughout the mining process. In the public section, R2 hosts over 60,000 HT samples. Next to gene expression (microarray and RNA-seq), the platform is also being employed in the integration, analysis and visualization of other data types, such as aCGH, SNP, ChIP, methylation, miRNA, and NGS whole genome sequencing information. R2 contains an expanding set of interactive analyses which are heavily inter-connected, allowing users to quickly hop from one view (representation of the data) to another. Analyses include, correlation, differential expression, gene sets, gene ontology, transcription factor binding sites, PCA, kmeans, Kaplan Meier scans, signature creation etc. Visualizations include, various gene oriented plots, heatmaps, circos, embedded genome browser, Venn, etc. Many parts of the R2 platform are publicly accessible through the http://r2.amc.nl portal. The R2 gene expression analysis tools have thus far been used in more than 180 peer-reviewed scientific publications including journals as Nature, Nature Genetics and Cell. R2 also supports restricted / shielded use and is used in many (inter)national collaborative efforts involving unpublished datasets. The webservers have been serving over 900.000 pages over the past 12 months (Nov 2014). Citation Format: Jan Koster, Jan J. Molenaar, Rogier Versteeg. R2: Accessible web-based genomics analysis and visualization platform for biomedical researchers. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-05.

In this era of explosive high throughput (HT) genomics data generation, there is a growing need for accessible software solutions that can help unlock biological/clinical characteristics from such data. With the biomedical researcher (with limited or no bioinformatics skills) in mind, we developed a comprehensive web-based system called R2 (http://r2.amc.nl). R2 aids in the analysis and visualization of private/shielded as well as public high throughput data and their associated annotated features. The R2 platform consists of a database storing both publicly accessible as well as shielded datasets with unified gene annotation, supplemented with a large suite of tools that can be used on these data, and their associated annotation. As such the user experiences the same look & feel throughout the mining process. In the public section, R2 hosts over 60,000 HT samples. Next to gene expression (microarray and RNA-seq), the platform is also being employed in the integration, analysis and visualization of other data types, such as aCGH, SNP, ChIP, methylation, miRNA, and NGS whole genome sequencing information. R2 contains an expanding set of interactive analyses which are heavily inter-connected, allowing users to quickly hop from one view (representation of the data) to another. Analyses include, correlation, differential expression, gene sets, gene ontology, transcription factor binding sites, PCA, kmeans, Kaplan Meier scans, signature creation etc. Visualizations include, various gene oriented plots, heatmaps, circos, embedded genome browser, Venn, etc. Many parts of the R2 platform are publicly accessible through the http://r2.amc.nl portal. The R2 gene expression analysis tools have thus far been used in more than 180 peer-reviewed scientific publications including journals as Nature, Nature Genetics and Cell. R2 also supports restricted / shielded use and is used in many (inter)national collaborative efforts involving unpublished datasets. The webservers have been serving over 900.000 pages over the past 12 months (Nov 2014). Citation Format: Jan Koster, Jan J. Molenaar, Rogier Versteeg. R2: Accessible web-based genomics analysis and visualization platform for biomedical researchers. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-45.

Introduction: 9p24 contains genes that are critical for immune evasion and propagating cell division. The loci for PD-L1, PD-L2, JAK2, and the histone demethylases KDM4C/JMJD2C are linked on 9p24 (Van Roosbroeck et al. Genes, Chromosomes and Cancer 2016). Amplification or rearrangements of this region have been described in the pathogenesis of classical Hodgkin lymphoma (cHL) and primary mediastinal large B-cell lymphoma (Ansell et al. New England Journal of Medicine 2015). Additionally, JAK2 amplification up-regulates PD-L1 and L2, which leads to increased T-cell inactivation and suggests synergy between these drug targets. The recent success of PD-1 blockade in numerous malignancies has led to the development and approval of PD-1 inhibitors in cHL as well as other cancers. Targeted therapies are approved for JAK2 inhibition, such as ruxolitinib, and are in development for histone demethylases, which illustrates the utility of identifying the 9p24 amplicon in hematologic malignancies (HM) (Van Roosbroeck et al. Genes, Chromsomes and Cancer 2016). The goal of this analysis is to better understand the distribution of 9p24 abnormalities across a broader range of leukemias and lymphomas in order to facilitate future studies of targeted therapy. Methods: The National Cancer Institute's Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer was queried for 9p24 breakpoint abnormalities within HM. Incidence of additions and rearrangements in chromosome 9p24 for all subtypes of HM listed in the Mitelman Database were calculated. Individual references were manually reviewed and pathologic data was extracted as available from the primary sources. Diffuse large B-cell lymphoma (DLBCL) cases were further assessed for co-incident rearrangement of MYC (8q24), BCL2 (18q21) and BCL6 (3q27) with 9p24. All subtypes with greater than 2% incidence of additions and/or rearrangements in chromosome 9p24 were reported. Results: 48,761 patients (pts) with HM across 74 lymphoid and myeloid subtypes were identified. 361 ( Conclusion: Amplifications and rearrangement of 9p24 are rare in HM within the Mitelman database. Our study suggests that patients with DLBCL, adult T-cell leukemia/lymphoma, extranodal NK/T cell lymphoma, intravascular B cell lymphoma, peripheral T-cell lymphoma, and extranodal marginal zone B-cell may be considered for further studies with FISH and aCGH to further define the incidence of 9p24 alterations and potentially for targeted clinical trials. 9p24 abnormalities did not correlate with previously described phenotypic subtypes of DLBCL. Disclosures No relevant conflicts of interest to declare.

Childhood cancer has been a global public health scourge with considerably escalating incidence each year [1]. Although the incidence is relatively lower compared to adult malignancies, it remains the leading cause of disease-related death in children. The most frequent childhood cancer is acute lymphoblastic leukemia (ALL) with an annual incidence of 3.5 per 100,000 children in the United States [2]. Similarly, in Indonesia, ALL has the highest number of cancer cases in children [3]. The total incidence of ALL in Indonesia reaches 2.5-4.0 per 100,000 children with an estimated 2,000-3,200 annually [4]. Because of its high incidence and curability, ALL is a logical initial objective for childhood cancer program developments in Indonesia. As an indicator of successful treatment of childhood ALL, the 5-year survival rate shows contrasting figures between high-income (HIC) and lower-middle-income countries (LMIC). In the United States and most European countries, the survival rates are approximately 90% and 85% respectively. However, in Southeast Asian countries, the highest 5-year survival rate for children aged 0 to 14 was reported in Malaysia (69.4%), followed by Thailand (55.1%) [5]. Furthermore, more unfavorable results were reported in Indonesia. Studies from Dharmais Cancer Hospital and Dr. Sardjito Hospital reported the 5-year survival rate of 28.9% and 31.8% respectively [6,7]. The outcome difference between Indonesia and other countries is probably due to the high rate of relapse occurrence and toxic death during the treatment. Some studies revealed the factors that affecting the worst outcome of childhood ALL in LMIC include inadequate and delayed diagnosis, limited healthcare access, treatment abandonment, and suboptimal supportive care [8]. As pediatric oncologists in HIC have become more effective at treating childhood ALL, much of the research attempts concentrated on the risk stratification of the patients. The term “risk stratification” is used to allocate the patients into various risk groups based on the notable prognostic features for specific treatment administration. Patients with a high-risk assessment could be targeted for more aggressive treatments, while patients with lower risk could be treated less intensively to avoid the side effects and toxicities [9]. In Indonesia, risk stratification strategy encompasses clinical-hematologic parameters (age, leukocyte count, extramedullary involvement), and conventional morphological examination. These assessments represent the first step in the diagnostic pathway of ALL. Though helpful, in certain cases, the residual leukemic cells might be undetectable under bone marrow morphology examination. This led to more underdiagnosed cases, thus more patients were subjected to inadequate treatment. Fortunately, immunophenotyping is currently applied to improve the diagnosis of childhood ALL by grouping the patients based on the aberrant expression of leukemic cell antigen, even though its application is only available in several centers including Dharmais Cancer Hospital. The BCR-ABL1 fusion gene examination by PCR-based techniques has also routinely been implemented to predict the poor outcome since it was detected in 12% of childhood ALL patients [10]. However, the current above-mentioned strategy is insufficient to solve the accuracy of risk stratification of childhood ALL. In HIC, childhood ALL are classified by more comprehensive examination involving morphology, immunophenotyping, cytogenetics, and molecular techniques. The approach to classifying prognosis and to personalize treatment based on the underlying genetic biology has already implemented for understanding the pathogenesis of childhood ALL. According to studies, the molecular features of childhood ALL have been shown to have a significant prognostic value [11], and the survival rate was improved when genetic examinations are applied [12]. In recent years, high-resolution array-based genomic technologies have revolutionized the understanding of the genetic basis of childhood ALL. Several biomarkers have successfully been identified that are provenly associated with poor prognosis in childhood ALL, including the deletion/mutation of IKZF1 (IKAROS), CDKN2A, ETV6, EBF1, JAK2, and many more [13]. The majority of these genetic changes were originally identified by sophisticated methods such as single nucleotide polymorphism (SNP) arrays, gene expression profiling (GEP), array-based comparative genomic hybridization (aCGH), and more recently next-generation sequencing (NGS) [14]. Despite being highly sensitive for detection of multiple copy number changes, these approaches are not feasible for routine diagnostic use in LMIC which requires significant EDITORIAL Indonesian Journal of Cancer, Vol 14(4), 115–116, December 2020 DOI: http://dx.doi.org/10.33371/ijoc.v14i4.818 www.indonesianjournalofcancer.or.id P-ISSN: 1978-3744 E-ISSN: 2355-6811 116 | financial investment. Therefore, molecular techniques that suit available resources and infrastructure should be developed in LMIC, and most importantly the cost should be affordable for patients. One feasible method is Multiplex Ligation-dependent Probe Amplification (MLPA). MLPA is a rapid multiplex PCR-based technique that enables the comparative analysis of multiple mutation spots [15]. MLPA provides a low-cost, simple alternative to array-based techniques for much routine clinical practice, even though it is unsuitable for whole-genome analysis. Furthermore, one benefit compared to other quantitative PCR-based techniques is that MLPA allows 50 or more different genomic DNA to be analyzed in a single tube reaction. Several studies have demonstrated the implementation of specific MLPA probe mixes for hematological malignancies, including ALL, chronic lymphocytic leukemia (CLL), and myelodysplastic syndrome (MDS). These studies have also shown the sensitive and accurate identification of clinically...

The Editorial on the Research TopicRepetitive Structures in Biological Sequences: Algorithms and Applications Repetitive structures in biological sequences are emerging as an active focus of research and the unifying concept of “repeatome” (the ensemble of knowledge associated with repeating structures in genomic/proteomic data) has been recently proposed in order to highlight several converging trends. One main trend is the ongoing discovery that genomic repetitions are often linked to biologically significant events and functions. For example, an abnormal number of tandem repeating units both in coding and regulatory parts of the genome have been found to cause a series of diseases, including Huntington disease (MacDonald et al., 1993). There are indications of a link between tandem repeat expansion and certain forms of Amyotrophic Lateral Sclerosis (Renton et al., 2011). Copy Number Variations and alterations (CNV/CNA), not necessarily in tandem, have been demonstrated to be one of the main sources of genomic variation in humans. These participate to phenotypic variation and adaptation and contribute to causing various diseases, including cancer, cardiovascular diseases, HIV acquisition and progression, autoimmune diseases, and Alzheimer’s and Parkinson’s diseases (Zhang et al., 2009). Genome-wide identification of CNVs can be performed with array-based comparative genomic hybridization (aCGH), SNP arrays, and next generation sequencing (NGS). Although the experimental nature of these technologies is very different, the genomic profiles that they generate for CNVs identification are mathematically very similar. Several computational methods have been published in the last 10 years for segmenting these genomic profiles; however, much work still needs to be done, in particular for discovering CNV in low frequency subclones of cancer samples. Intragenic tandem repeats polymorphisms may be involved in mis-regulations leading to protein toxicity through multiple pathways. Tandem repeats and CNV in Next Generation Sequencing (NGS) data are, however, difficult to detect and analyze, and devising effective detection algorithms is still a very open area of research (Treangen and Salzberg, 2012). Repeating structures abound also in human proteins and they are a possible key to exploring sequence, structure, and function relationships. Inverted repeats are fingerprints of DNA hairpins and have been shown to contribute to chromosomal fragility in the human genome. A second converging trend has been the emergence of many different models and algorithms for detecting non-obvious repeating patterns in strings with applications to genomic data collected in Hight Throughput assays (e.g., reads from NGS sequencing, or assembled genomes). A challenging aspect still to be explored is the full impact of evolutionary sequence divergence, and evolutionary selection over the origin and functional significance of repeating substructure. High divergence repetitions are harder to detect from the genomic background; however, they may give us more insight into the evolution of functional units in the genome. New modeling and algorithmic schemes are emerging to tackle these issues, focusing on the computational characterization of the individual entities involved in the repeatome. Borrowing methodologies from combinatorial pattern matching, string algorithms, data structures, data mining, machine learning, probability, and statistics, these new approaches overcome the limitations of the current approaches and offer an example of trans-disciplinary research. In this Research Topic, we have collected four original research articles and six reviews spanning the full scope of the Topic. NGS data are a common theme of three of the contributions. Tattini et al. give an overview of the challenges and the several approaches in the literature for detecting structural variants in the human genome using whole genome and whole exome sequencing data, pointing at major advantages and drawbacks of each approach. Narzisi and Schatz analyze the impact of small-scale repetitive sequences, in particular near-tandem repeats, on the discovery of DNA structural variations with the micro-assembly approach. Manconi et al. describe a GPU-based efficient pipeline for filtering reads obtained from Next Generation sequencing, in conjunction with read depth CNV detection methods. Repetitive sequences both within a single genome and across multiple genomes cause several problems in building effective genomic databases that support efficient data mining on genomic data. Gagie and Puglisi survey advances in algorithmic techniques for taking advantage of repetitive sequences in indexing and searching genomic databases. The study of tandem repeats in DNA sequences has been a very active area of research in the last decade. Anisimova et al. survey both computational and statistical approaches for TR detection and their application to sequence alignment, phylogenetic analysis, and benchmarking. Régnier and Chassignet develop new models for predicting the statistics of repetitions and show that the proposed model fits nicely data from a biological case study. Pellegrini gives an overview on the multi-faceted aspects of research on protein tandem repeats (PTR), including prediction algorithms, databases, early classification efforts, mechanisms of PTR formation and evolution, and synthetic PTR design, embracing both sequence and 3-dimensional structural aspects. Transposable Elements (TE) are DNA subsequences that can replicate themselves via a series of biochemical mechanisms and are particularly abundant in mammalian genomes. Kannan et al. investigate the correlations between TE and long intergenic non-coding RNA genes (lincRNA), corroborating the hypothesis that TE have substantially contributed to the origin, evolution, and functional diversification of lincRNA genes. Nigita et al. investigate computational aspects of RNA editing, which is a post-transcriptional alteration of expressed RNA sequences eventually affecting protein and ncRNA structure and function. This phenomenon is mostly associated with repetitive regions of RNA sequences. Besides sequence and 3-dimensional structures, biological data are increasingly available in graphical form. Micale et al. describe a web-based tool (SPECTRA) to build and analyze PPI networks that capture tumor and tissue-specific interactions via integration of a variety of heterogeneous data repositories, thus allowing the comparative exploration of similarities/differences in tissue-specific processes. This series of papers provides a glance into the rich emerging area of repeatome research, addressing some of its pressing challenges. We believe that these contributions are valuable resources for repeatome research and will stimulate further research from bioinformatic, statistical, and biological points of view. The authors contributed equally to this work. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Work supported by Italian Ministry of Education, Universities and Research (MIUR) and by the National Research Council of Italy (CNR) within the Flagship Project InterOmics PB.P05. MacDonald, M. E., Ambrose, C. M., Duyao, M. P., Myers, R. H., Lin, C., Srinidhi, L., et al. (1993). A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington’s disease chromosomes. Cell 72, 971–983. doi: 10.1016/0092-8674(93)90585-E CrossRef Full Text | Google Scholar Renton, A., Majounie, E., Waite, A., Simon-Sanchez, J., Rollinson, S., Gibbs, J., et al. (2011). A hexanucleotide repeat expansion in C9ORF72 is the cause of chromosome 9p21-linked ALS-FTD. Neuron 72, 257–268. doi:10.1016/j.neuron.2011.09.010 PubMed Abstract | CrossRef Full Text | Google Scholar Treangen, T. J., and Salzberg, S. L. (2012). Repetitive DNA and next-generation sequencing: computational challenges and solutions. Nat. Rev. Genet. 13, 36–46. doi:10.1038/nrg3117 CrossRef Full Text | Google Scholar Zhang, F., Gu, W., Hurles, M. E., and Lupski, J. R. (2009). Copy number variation in human health, disease, and evolution. Annu. Rev. Genomics Hum. Genet. 10, 451. doi:10.1146/annurev.genom.9.081307.164217 PubMed Abstract | CrossRef Full Text | Google Scholar Keywords: repetitive structures, algorithms, tandem repeats, next generation sequencing, transposable elements Citation: Pellegrini M, Magi A and Iliopoulos CS (2016) Editorial: Repetitive Structures in Biological Sequences: Algorithms and Applications. Front. Bioeng. Biotechnol. 4:66. doi: 10.3389/fbioe.2016.00066 Received: 27 June 2016; Accepted: 25 July 2016; Published: 04 August 2016 Edited and Reviewed by: Richard D. Emes, University of Nottingham, UK Copyright: © 2016 Pellegrini, Magi and Iliopoulos. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Marco Pellegrini, [email protected]