Narrow Results

A turning point in cancer research is the introduction of massively parallel sequencing technology which greatly reduced the cost and time for genome sequencing. This enhanced the scope for detecting and analyzing the role of structural alterations in cancer. However, certain bias exists in NGS-based approaches, which badly affects the CNV identification process. Moreover, DNA repeats existing in CNV regions need special attention as they will degrade the performance of majority of the existing CNV detection tools, even after applying generalized bias correction method. This motivated this work, where a novel method has been designed to address the issue of DNA repeats and thereby mappability bias existing in regions of CNV. The method consists of three phases, where the first phase computes the alignment information of uniquely mapped DNA reads, considering the base quality and base mismatch parameters at nucleotide level precision. The second and the third phase use a novel approach to allocate the non-uniquely mapped reads to an optimal region of the DNA repeats based on a probabilistic membership model. The proposed method is capable of identifying CNVs present in coding, as well as non-coding region of the DNA, and is also capable of detecting CNVs existing in DNA repeat regions. The methodology achieves a sensitivity greater than $0.99$ during the performed simulations, and on real data, the detected variants are validated with the database of genomic variants, where the percentage overlap is also greater than 95%, and has achieved much better breakpoint prediction, as compared with other popular bias correction CNV detection methods.

Despite extensive experimental investigations of human amnesia, the basic nature of this vivid syndrome remains surrounded by controversy. The dynamics of amnesia, the rapid, selective and long-lasting plasticity of hippocampal synapses, and the connections between the hippocampal formation and association neocortex. all suggest that amnesia may result from damage to the medial temporal site where the recent declarative memory trace is temporarily laid down. Alternatively, amnesics' preserved capacity for procedural learning on indirect memory tests suggests that their deficit may rather be in intentional, sustained and directed (i.e., active) encoding/retrieval processes. It has been difficult to distinguish between these possibilities because amnesics are most impaired on direct memory tasks that involve both a new integrative trace and active processes. It is possible that different amnesics may have a relatively greater defect either in the memory trace, or in active memory processes, or both, and these differences could correspond to differences in their anatomical lesions. Specifically, hippocampal formation lesions may disrupt all recent declarative memory traces, whereas brainstem lesions could produce amnesia by impairing modulatory processes essential for encoding/retrieval or for storage. In this model, the different areas of association neocortex with bidirectional hippocampal connections would contribute specificity to encoding/retrieval, with posterior areas encoding the sensory/semantic aspects of events, and prefrontal cortex the ongoing context. Active modulatory processes arising in the brainstem would then function to integrate this extensive declarative memory system. The cognitive correlates and neural substrates of the evoked potentials recorded during declarative memory tasks suggest that they may embody such modulatory processes. Finally, since the prefrontal cortex and the medial temporal lobe appear to control the onset, intensity and duration of the ascending neuromodulation, lesions of these structures may impair aspects of both the trace and of the processes supporting declarative memory. In summary, a model is proposed in which the association neocortex (encoding/retrieval) and hippocampus (trace) are integrated by the brainstem (modulation) to produce the psychological properties of declarative memory.

We present a genome-wide analysis of splicing patterns of 282 kidney renal clear cell carcinoma patients in which we integrate data from whole-exome sequencing of tumor and normal samples, RNA-seq and copy number variation. We proposed a scoring mechanism to compare splicing patterns in tumor samples to normal samples in order to rank and detect tumor-specific isoforms that have a potential for new biomarkers. We identified a subset of genes that show introns only observable in tumor but not in normal samples, ENCODE and GEUVADIS samples. In order to improve our understanding of the underlying genetic mechanisms of splicing variation we performed a large-scale association analysis to find links between somatic or germline variants with alternative splicing events. We identified 915 cis- and trans-splicing quantitative trait loci (sQTL) associated with changes in splicing patterns. Some of these sQTL have previously been associated with being susceptibility loci for cancer and other diseases. Our analysis also allowed us to identify the function of several COSMIC variants showing significant association with changes in alternative splicing. This demonstrates the potential significance of variants affecting alternative splicing events and yields insights into the mechanisms related to an array of disease phenotypes.