Desempeño de competencia matemática en contextos de la Educación Física en primaria

El objetivo de la investigación fue valorar en qué grado el recurso didáctico diseñado en el marco de la Educación Física de 4º de Primaria impulsaba el desempeño de la Competencia Matemática. La intervención didáctica estaba conformada por situaciones-problema contextualizadas en entornos de Educación Física. 68 estudiantes, a través del trabajo cooperativo tenían el reto de elaborar e implementar un plan en el que utilizando sus conocimientos matemáticos resolvieran las situaciones planteadas. Se diseñó un estudio de casos cuyos resultados fueron de naturaleza cuantitativa-cualitativa. Se recogieron datos mediante la observación participante, notas de campo, cuestionarios y entrevistas. Los resultados mostraron que el alumnado ejecutó habilidades matemáticas competenciales en niveles de desempeño medio-alto. Refuerzan estas evidencias de aprendizaje que el alumnado reconociera los contenidos matemáticos aprendidos y el papel de las matemáticas en la Educación Física. Además, el profesorado de matemáticas observó un dominio de contenidos no trabajados en el aula.

Subclone Eradication Analysis Identifies Targets for Enhanced Cancer Therapy and Reveals L1 Retrotransposition as a Dynamic Source of Cancer Heterogeneity

Treatment-eradicated cancer subclones have been reported in leukemia and have recently been detected in solid tumors. Here we introduce Differential Subclone Eradication and Resistance (DSER) analysis, a method developed to identify molecular targets for improved therapy by direct comparison of genomic features of eradicated and resistant subclones in pre- and posttreatment samples from a patient with BRCA2-deficient metastatic prostate cancer. FANCI and EYA4 were identified as candidate DNA repair-related targets for converting subclones from resistant to eradicable, and RNAi-mediated depletion of FANCI confirmed it as a potential target. The EYA4 alteration was associated with adjacent L1 transposon insertion during cancer evolution upon treatment, raising questions surrounding the role of therapy in L1 activation. Both carboplatin and enzalutamide turned on L1 transposon machinery in LNCaP and VCaP but not in PC3 and 22Rv1 prostate cancer cell lines. L1 activation in LNCaP and VCaP was inhibited by the antiretroviral drug azidothymidine. L1 activation was also detected postcastration in LuCaP 77 and LuCaP 105 xenograft models and postchemotherapy in previously published time-series transcriptomic data from SCC25 head and neck cancer cells. In conclusion, DSER provides an informative intermediate step toward effective precision cancer medicine and should be tested in future studies, especially those including dramatic but temporary metastatic tumor regression. L1 transposon activation may be a modifiable source of cancer genomic heterogeneity, suggesting the potential of leveraging newly discovered triggers and blockers of L1 activity to overcome therapy resistance. SIGNIFICANCE: Differential analysis of eradicated and resistant subclones following cancer treatment identifies that L1 activity associated with resistance is induced by current therapies and blocked by the antiretroviral drug azidothymidine.

Characterizing Mutational Signatures in Human Cancer Cell Lines Reveals Episodic APOBEC Mutagenesis

Multiple signatures of somatic mutations have been identified in cancer genomes. Exome sequences of 1,001 human cancer cell lines and 577 xenografts revealed most common mutational signatures, indicating past activity of the underlying processes, usually in appropriate cancer types. To investigate ongoing patterns of mutational-signature generation, cell lines were cultured for extended periods and subsequently DNA sequenced. Signatures of discontinued exposures, including tobacco smoke and ultraviolet light, were not generated in vitro. Signatures of normal and defective DNA repair and replication continued to be generated at roughly stable mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing exhibited substantial fluctuations in mutation rate over time with episodic bursts of mutations. The initiating factors for the bursts are unclear, although retrotransposon mobilization may contribute. The examined cell lines constitute a resource of live experimental models of mutational processes, which potentially retain patterns of activity and regulation operative in primary human cancers.

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Annotation of mutational signatures across 1,001 cancer cell lines and 577 PDXs

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Activities of mutational processes determined over time in cancer cell lines

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APOBEC-associated mutagenesis is often ongoing and can be episodic

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Detection of mutational signatures by single-cell sequencing

ChimPipe: accurate detection of fusion genes and transcription-induced chimeras from RNA-seq data

Background

Chimeric transcripts are commonly defined as transcripts linking two or more different genes in the genome, and can be explained by various biological mechanisms such as genomic rearrangement, read-through or trans-splicing, but also by technical or biological artefacts. Several studies have shown their importance in cancer, cell pluripotency and motility. Many programs have recently been developed to identify chimeras from Illumina RNA-seq data (mostly fusion genes in cancer). However outputs of different programs on the same dataset can be widely inconsistent, and tend to include many false positives. Other issues relate to simulated datasets restricted to fusion genes, real datasets with limited numbers of validated cases, result inconsistencies between simulated and real datasets, and gene rather than junction level assessment.

Results

Here we present ChimPipe, a modular and easy-to-use method to reliably identify fusion genes and transcription-induced chimeras from paired-end Illumina RNA-seq data. We have also produced realistic simulated datasets for three different read lengths, and enhanced two gold-standard cancer datasets by associating exact junction points to validated gene fusions. Benchmarking ChimPipe together with four other state-of-the-art tools on this data showed ChimPipe to be the top program at identifying exact junction coordinates for both kinds of datasets, and the one showing the best trade-off between sensitivity and precision. Applied to 106 ENCODE human RNA-seq datasets, ChimPipe identified 137 high confidence chimeras connecting the protein coding sequence of their parent genes. In subsequent experiments, three out of four predicted chimeras, two of which recurrently expressed in a large majority of the samples, could be validated. Cloning and sequencing of the three cases revealed several new chimeric transcript structures, 3 of which with the potential to encode a chimeric protein for which we hypothesized a new role. Applying ChimPipe to human and mouse ENCODE RNA-seq data led to the identification of 131 recurrent chimeras common to both species, and therefore potentially conserved.

Conclusions

ChimPipe combines discordant paired-end reads and split-reads to detect any kind of chimeras, including those originating from polymerase read-through, and shows an excellent trade-off between sensitivity and precision. The chimeras found by ChimPipe can be validated in-vitro with high accuracy.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3404-9) contains supplementary material, which is available to authorized users.