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The SALL2 transcription factor, an evolutionarily conserved gene through vertebrates, is involved in normal development and neuronal differentiation. In disease, SALL2 is associated with eye, kidney, and brain disorders, but mainly is related to cancer. Some studies support a tumor suppressor role and others an oncogenic role for SALL2, which seems to depend on the cancer type. An additional consideration is tissue-dependent expression of different SALL2 isoforms. Human and mouse SALL2 gene loci contain two promoters, each controlling the expression of a different protein isoform (E1 and E1A). Also, several improvements on the human genome assembly and gene annotation through next-generation sequencing technologies reveal correction and annotation of additional isoforms, obscuring dissection of SALL2 isoform-specific transcriptional targets and functions. We here integrated current data of normal/tumor gene expression databases along with ChIP-seq binding profiles to analyze SALL2 isoforms expression distribution and infer isoform-specific SALL2 targets. We found that the canonical SALL2 E1 isoform is one of the lowest expressed, while the E1A isoform is highly predominant across cell types. To dissect SALL2 isoform-specific targets, we analyzed publicly available ChIP-seq data from Glioblastoma tumor-propagating cells and in-house ChIP-seq datasets performed in SALL2 wild-type and E1A isoform knockout HEK293 cells. Another available ChIP-seq data in HEK293 cells (ENCODE Consortium Phase III) overexpressing a non-canonical SALL2 isoform (short_E1A) was also analyzed. Regardless of cell type, our analysis indicates that the SALL2 long E1 and E1A isoforms, but not short_E1A, are mostly contributing to transcriptional control, and reveals a highly conserved network of brain-specific transcription factors (i.e., SALL3, POU3F2, and NPAS3). Our data integration identified a conserved molecular network in which SALL2 regulates genes associated with neural function, cell differentiation, development, and cell adhesion between others. Also, we identified PODXL as a gene that is likely regulated by SALL2 across tissues. Our study encourages the validation of publicly available ChIP-seq datasets to assess a specific gene/isoform's transcriptional targets. The knowledge of SALL2 isoforms expression and function in different tissue contexts is relevant to understanding its role in disease.

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BACKGROUND: Noncoding sequences have been demonstrated to possess regulatory functions. Its classification is challenging because they do not show well-defined nucleotide patterns that can correlate with their biological functions. Genomic signal processing techniques like Fourier transform have been employed to characterize coding and noncoding sequences. This transformation in a systematic whole-genome noncoding library, such as the ENCODE database, can provide evidence of a periodic behaviour in the noncoding sequences that correlates with their regulatory functions. OBJECTIVE: The objective of this study was to classify different noncoding regulatory regions through their frequency spectra. METHODS: We computed machine learning algorithms to classify the noncoding regulatory sequences frequency spectra. RESULTS: The sequences from different regulatory regions, cell lines, and chromosomes possessed distinct frequency spectra, and that machine learning classifiers (such as those of the support vector machine type) could successfully discriminate among regulatory regions, thus correlating the frequency spectra with their biological functions CONCLUSION: Our work supports the idea that there are patterns in the noncoding sequences of the genome.

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RESUMEN En la actualidad, nuevas bases de datos genómicos (secuencias de ADN) son puestas al alcance del dominio público para su análisis. La bioinformática ha desarrollado algoritmos para extraer información y características de dichas secuencias. Sin embargo, estos algoritmos bioinformáticos tienen limitaciones. Una alternativa es utilizar herramientas propias del procesamiento digital de señales (DSP) adaptadas a secuencias genómicas (procesamiento de señales genómicas - GSP). El presente trabajo versa sobre el análisis de los cuatro primeros momentos centrales (media, desviación estándar, asimetría y curtosis) y dos momentos estadísticos (mediana y varianza) de los espectros frecuenciales de las 15 Regiones Reguladoras (RRs) de la base de datos ENCODE con el objetivo de estudiar diferencias estadísticas y frecuencias características. La base de datos seleccionada es "mapeada". Luego, la FFT es calculada a estas señales genómicas y finalmente los momentos estadísticos son implementados. Los resultados mues tran la existencia de 3 grupos de RRs utilizando la media, mediana y curtosis. La desviación estándar y la varianza, parecen no resaltar información importante. Finalmente, la asimetría revela un comportamiento homogéneo ante la presencia de valores atípicos en algunas RRs. Estas observaciones permiten inferir que la periodicidad dentro de la secuencia está relacionada o podría determinar la función biológica que desempeña la misma secuencia.

ABSTRACT Nowadays, new genomic databases (DNA sequences) are available to the whole scientist community for its analysis. The bioinformatics has developed algorithms to extract information and features of the sequences. However, the bioinformatics algorithms have restrictions. An alternative is the use of digital signal processing (DSP) tools adapted to genomic sequences (genomic signal processing - GSP). This work analyzes the first four statistics moments (mean, standard deviation, skewness and kurtosis) and other two moments (median and variance) of the frequency spectra of 15 regulatory regions (RRs) in ENCODE database with the main objective of studying the statistics di fferences and frequency features. The selected database is mapped. Then, the FFT is calculated to these genomic signals and finally the statistic moments implemented. The results show a three-group behavior in the RRs with the mean, median and kurtosis. The deviations standard and the variance do not show important behavior. Finally, the skewness shows a homogeneous behavior with the lack of atypical values in some RRs. These observations support the idea of the presence of periodicities in a sequence that may be related or may determine the biological function that a sequence may perform.

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Several studies of the behavior in the voltage and frequency fluctuations of the neural electrical activity have been performed. Here, we explored the particular association between behavior of the voltage fluctuations in the inter-spike segment (VFIS) and the inter-spike intervals (ISI) of F1 pacemaker neurons from H. aspersa, by disturbing the intracellular calcium handling with cadmium and caffeine. The scaling exponent α of the VFIS, as provided by detrended fluctuations analysis, in conjunction with the corresponding duration of ISI to estimate the determination coefficient R 2 (48-50 intervals per neuron, N = 5) were all evaluated. The time-varying scaling exponent α(t) of VFIS was also studied (20 segments per neuron, N = 11). The R 2 obtained in control conditions was 0.683 ([0.647 0.776] lower and upper quartiles), 0.405 [0.381 0.495] by using cadmium, and 0.151 [0.118 0.222] with caffeine (P < 0.05). A non-uniform scaling exponent α(t) showing a profile throughout the duration of the VFIS was further identified. A significant reduction of long-term correlations by cadmium was confirmed in the first part of this profile (P = 0.0001), but no significant reductions were detected by using caffeine. Our findings endorse that the behavior of the VFIS appears associated to the activation of different populations of ionic channels, which establish the neural membrane potential and are mediated by the intracellular calcium handling. Thus, we provide evidence to consider that the behavior of the VFIS, as determined by the scaling exponent α, conveys insights into mechanisms regulating the excitability of pacemaker neurons.

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The Human Genome Project (HGP) was initiated in 1990 and completed in 2003. It aimed to sequence the whole human genome. Although it represented an advance in understanding the human genome and its complexity, many questions remained unanswered. Other projects were launched in order to unravel the mysteries of our genome, including the ENCyclopedia of DNA Elements (ENCODE). This review aims to analyze the evolution of scientific knowledge related to both the HGP and ENCODE projects. Data were retrieved from scientific articles published in 1990-2014, a period comprising the development and the 10 years following the HGP completion. The fact that only 20,000 genes are protein and RNA-coding is one of the most striking HGP results. A new concept about the organization of genome arose. The ENCODE project was initiated in 2003 and targeted to map the functional elements of the human genome. This project revealed that the human genome is pervasively transcribed. Therefore, it was determined that a large part of the non-protein coding regions are functional. Finally, a more sophisticated view of chromatin structure emerged. The mechanistic functioning of the genome has been redrafted, revealing a much more complex picture. Besides, a gene-centric conception of the organism has to be reviewed. A number of criticisms have emerged against the ENCODE project approaches, raising the question of whether non-conserved but biochemically active regions are truly functional. Thus, HGP and ENCODE projects accomplished a great map of the human genome, but the data generated still requires further in depth analysis. © 2016 by The International Union of Biochemistry and Molecular Biology, 44:215-223, 2016.

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Aberrant mucin O-glycosylation often occurs in different cancers and is characterized by immature expression of simple mucin-type carbohydrates. At present, there are some controversial reports about the Tn antigen (GalNAcα-O-Ser/Thr) expression and there is a great lack of information about the [UDP-N-acetyl-α-d-galactosamine:polypeptide N-acetylgalactosaminyltransferase (GalNAc-Ts)] expression in chronic lymphocytic leukemia (CLL). To gain insight in these issues we evaluated the Tn antigen expression in CLL patient samples using two Tn binding proteins with different fine specificity. We also studied the expression from 14 GalNAc-Ts genes in CLL patients by RT-PCR. Our results have provided additional information about the expression level of the Tn antigen, suggesting that a low density of Tn residues is expressed in CLL cells. We also found that GALNT11 was expressed in CLL cells and normal T cell whereas little or no expression was found in normal B cells. Based on these results, GALNT11 expression was assessed by qPCR in a cohort of 50 CLL patients. We found significant over-expression of GALNT11 in 96% of B-CLL cells when compared to normal B cells. Moreover, we confirmed the expression of this enzyme at the protein level. Finally we found that GALNT11 expression was significantly associated with the mutational status of the immunoglobulin heavy chain variable region (IGHV), [א(2)(1)=18.26; P<0.0001], lipoprotein lipase expression [א(2)(1)=13.72; P=0.0002] and disease prognosis [א(2)(1)=15.49; P<0.0001]. Our evidence suggests that CLL patient samples harbor aberrant O-glycosylation highlighted by Tn antigen expression and that the over-expression of GALNT11 constitutes a new molecular marker for CLL.

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