CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts

Motivation Characterization of the coding sequences (CDSs) is an essential step in transcriptome annotation. Incorrect identification of CDSs can lead to the prediction of non-existent proteins that can eventually compromise knowledge if databases are populated with similar incorrect predictions made in different genomes. Also, the correct identification of CDSs is important for the characterization of the untranslated regions (UTRs), which are known to be important regulators of the mRNA translation process. Considering this, we present CodAn (Coding sequence Annotator), a new approach to predict confident CDS and UTR regions in full or partial transcriptome sequences in eukaryote species. Results Our analysis revealed that CodAn performs confident predictions on full-length and partial transcripts with the strand sense of the CDS known or unknown. The comparative analysis showed that CodAn presents better overall performance than other approaches, mainly when considering the correct identification of the full CDS (i.e. correct identification of the start and stop codons). In this sense, CodAn is the best tool to be used in projects involving transcriptomic data. Availability CodAn is freely available at https://github.com/pedronachtigall/CodAn.

Sequence motif finder using memetic algorithm.

BACKGROUND: De novo prediction of Transcription Factor Binding Sites (TFBS) using computational methods is a difficult task and it is an important problem in Bioinformatics. The correct recognition of TFBS plays an important role in understanding the mechanisms of gene regulation and helps to develop new drugs. RESULTS: We here present Memetic Framework for Motif Discovery (MFMD), an algorithm that uses semi-greedy constructive heuristics as a local optimizer. In addition, we used a hybridization of the classic genetic algorithm as a global optimizer to refine the solutions initially found. MFMD can find and classify overrepresented patterns in DNA sequences and predict their respective initial positions. MFMD performance was assessed using ChIP-seq data retrieved from the JASPAR site, promoter sequences extracted from the ABS site, and artificially generated synthetic data. The MFMD was evaluated and compared with well-known approaches in the literature, called MEME and Gibbs Motif Sampler, achieving a higher f-score in the most datasets used in this work. CONCLUSIONS: We have developed an approach for detecting motifs in biopolymers sequences. MFMD is a freely available software that can be promising as an alternative to the development of new tools for de novo motif discovery. Its open-source software can be downloaded at https://github.com/jadermcg/mfmd .

Epigenetic signature of differentially methylated genes in cutaneous melanoma

Background: Cutaneous melanoma (CM) is the most aggressive subtype of skin cancer, with increasing incidence over the past several decades. DNA methylation is a key element of several biological processes such as genomic imprinting, cell differentiation and senescence, and deregulation of this mechanism has been implicated in several diseases, including cancer. In order to understand the relationship of DNA methylation in CMs, we searched for an epigenetic signature of cutaneous melanomas by comparing the DNA methylation profiles between tumours and benign melanocytes, the precursor cells of CM. Methods: We used 20 primary CMs and three primary cell cultures of melanocytes as a discovery cohort. The tumours mutational background was collected as previously reported. Methylomes were obtained using the HM450K DNA methylation assay, and differential methylation analysis was performed. DNA methylation data of CMs from TCGA were recovered to validate our findings. Results: A signature of 514 differentially methylated genes (DMGs) was evident in CMs compared to melanocytes, which was independent of the presence of driver mutations. Pathway analysis of this CM signature revealed an enrichment of proteins involved in the binding of DNA regulatory regions (hypermethylated sites), and related to transmembrane signal transducer activities (hypomethylated sites). The methylation signature was validated in an independent dataset of primary CMs, as well as in lymph node and distant metastases (correlation of DNA methylation level: r > 0,95; Pearson's test: p < 2.2e-16). Conclusions: CMs exhibited a DMGs signature, which was independent of the mutational background and possibly established prior to genetic alterations. This signature provides important insights into how epigenetic deregulation contributes to melanomagenesis in general (AU)

DNA Methylation Levels of Melanoma Risk Genes Are Associated with Clinical Characteristics of Melanoma Patients.

In melanoma development, oncogenic process is mediated by genetic and epigenetic mutations, and few studies have so far explored the role of DNA methylation either as predisposition factor or biomarker. We tested patient samples for germline CDKN2A methylation status and found no evidence of inactivation by promoter hypermethylation. We have also investigated the association of clinical characteristics of samples with the DNA methylation pattern of twelve genes relevant for melanomagenesis. Five genes (BAP1, MGMT, MITF, PALB2, and POT1) presented statistical association between blood DNA methylation levels and either CDKN2A-mutation status, number of lesions, or Breslow thickness. In tumors, five genes (KIT, MGMT, MITF, TERT, and TNF) exhibited methylation levels significantly different between tumor groups including acral compared to nonacral melanomas and matched primary lesions and metastases. Our data pinpoint that the methylation level of eight melanoma-associated genes could potentially represent markers for this disease both in peripheral blood and in tumor samples.

LINE-1 hypermethylation in peripheral blood of cutaneous melanoma patients is associated with metastasis.

Aberrant DNA methylation pattern is a well-known epigenetic marker of cancer cells. Recently, aberrant methylation was also reported in the peripheral blood of cancer patients and it could potentially serve as a biomarker for cancer risk. We investigated the methylation pattern of LINE-1 and other repetitive DNA elements in peripheral blood of cutaneous melanoma patients in order to search for an association with clinical characteristics. The patient cohort was composed by 69 unrelated melanoma patients, 28 of whom were hereditary cases (with or without CDKN2A mutations) and 41 were isolated (sporadic) melanoma cases. Methylation of LINE-1 was evaluated by pyrosequencing, whereas additional repetitive DNA sequences were assessed using Illumina 450K methylation microarray. Melanoma patients exhibited a higher, albeit heterogeneous, LINE-1 methylation level compared with controls. Hereditary melanoma patients carrying CDKN2A mutations showed a hypermethylated pattern of both LINE-1 and repetitive DNA elements compared with other patients. In particular, the methylation level at one specific CpG of LINE-1 was found to be correlated with the occurrence of metastasis. Our data suggest that LINE-1 hypermethylation in peripheral blood of melanoma patients is a potential epigenetic biomarker for metastasis occurrence.

EGene: a configurable pipeline generation system for automated sequence analysis.

UNLABELLED: EGene is a generic, flexible and modular pipeline generation system that makes pipeline construction a modular job. EGene allows for third-party programs to be used and integrated according to the needs of distinct projects and without any previous programming or formal language experience being required. EGene comes with CoEd, a visual tool to facilitate pipeline construction and documentation. A series of components to build pipelines for sequence processing is provided. AVAILABILITY: http://www.lbm.fmvz.usp.br/egene/ CONTACT: alan@ime.usp.br; argruber@usp.br SUPPLEMENTARY INFORMATION: http://www.lbm.fmvz.usp.br/egene/

Characterization of SCAR markers of Eimeria spp. of domestic fowl and construction of a public relational database (The Eimeria SCARdb).

This study reports the development and characterization of 151 sequence characterized amplified region (SCAR) markers for the seven Eimeria species that infect the domestic fowl. From this set, 84 markers are species-specific and 67 present partial specificity. The complete nucleotide sequence was derived for all markers, revealing the presence of micro- and minisatellite repetitive units in 22 SCARs, with up to five distinct repeat units being observed per marker. Only 15 markers showed significant hits in similarity searches against public sequence databases, thus confirming their anonymous and non-coding character. Finally, a relational database of the markers (the Eimeria SCARdb) was developed and made available on the Internet, providing a valuable resource of SCAR markers that can be useful for molecular diagnosis, and also for epizootiological, genetic variability and genome mapping studies.