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Capturing and sequencing only the coding regions of the human genome leverages resources in the pursuit of rare disease-causing mutations. Clark et al. compare the performance of three leading exome-capture methods and their advantages over whole-genome sequencing.
Identification of genomic structural variation from short-read sequencing data is typically accomplished by mapping reads to a reference genome. Li et al. show that de novo assembly of the reads followed by whole-genome alignment to the reference is a more comprehensive method that can also resolve complex rearrangements.
Widely applicable methods for mapping protein-RNA interactions by crosslinking achieve a resolution of ∼30–60 nucleotides. Zhang and Darnell analyze sites of mutation induced by the crosslinking to map binding at single-nucleotide resolution.
Magtanong et al. describe the first study to systematically analyze dosage suppression, a type of genetic interaction in which increased dosage of one gene compensates for mutation in another. The authors also develop reagents for future large-scale studies of dosage suppression.
When embarking on a microarray-based study of genomic copy number variation, what's helpful for navigating the myriad of available array platforms and data analysis approaches? Pinto et al. evaluate six samples from healthy controls in triplicate on commonly used combinations of commercial arrays and analytic tools, providing realistic comparisons of performance.
The experiences of patients who try drugs that aren't approved for their disease have the potential to be mined for insights into drug efficacy. Wicks et al. rapidly monitored the efficacy of lithium treatment for 149 patients with amyotrophic lateral sclerosis using an online data collection tool and a patient-matching algorithm.
The metabolism of tissues often involves interactions between several types of cell. Lewis et al. model metabolism within and between neurons in the human brain, gaining insight into energy metabolism and Alzheimer's disease.
Methods for profiling DNA methylation differ in the physical principles used to detect modified cytosines. Harris et al. compare the performances of four sequencing-based technologies for genome-wide analysis of DNA methylation and combine two methods to enable detection of allelic differences in epigenetic marks.
Comparison of the methylation patterns of cells in different developmental or disease states can help to elucidate both normal and pathological regulatory mechanisms. Bock et al. evaluate the ability of three sequencing-based methods and one microarray-based technology to detect differentially methylated regions on a genome-wide scale.
Label-free methods for assaying GPCR signaling promise to illuminate the effects of drugs in therapeutically relevant primary cells. Kostenis and colleagues demonstrate the utility of one such method, dynamic mass redistribution, in comparison with traditional second messenger–based assays.
Which of the possible combinations of epigenetic marks have biological significance is a major question in epigenetics. Analyzing data from human T-cells, Ernst and Kellis discover 51 distinct, recurring combinations of histone modifications that can be correlated with the functional annotations of the underlying DNA sequences.
Mining information from genomes often begins by aligning the sequences to identify evolutionarily conserved regions. Chen et al. assess the performance of four commonly used multiple sequence alignment tools.
ChIP-Seq data are usually analyzed with approaches developed for microarrays, which only consider binding events within a few kilobases of a gene. McLean et al. present an algorithm that takes into account more distant events, thereby improving functional annotation of regulatory regions.
With a flood of cancer genome sequences expected soon, distinguishing 'driver' from 'passenger' mutations will be an important task. Wang et al. describe a bioinformatic method for identifying cancer-associated fusions and apply it to discover a recurrent rearrangement in lung cancer.
Modulatory proteins ensure that transcription factors are active when and where they should be. Wang et al. describe an algorithm for identifying modulators from a compendium of gene expression profiles and experimentally validate four diverse modulators of the MYC oncogene in human B cells.
Although multiple reaction monitoring (MRM) mass spectrometry holds considerable promise for quantifying candidate protein biomarkers in blood, transferability of MRM assays between laboratories has never been shown. Addona et al. assess the reproducibility, dynamic range and limits of detection and quantification of MRM across multiple sites.
Transfection of siRNAs and miRNAs into cells has been observed to generate unexpected effects in the form of gene upregulation. By statistically analyzing published transfection experiments, Khan et al. explain these effects with a model that the transfected RNAs compete with miRNAs naturally expressed by the cell.
The physical properties that determine the propensity of a protein to form a well-ordered crystal suitable for structure determination are poorly understood. An analysis of large-scale crystallization results generated by a structural genomics consortium highlights the importance of low-entropy surface features capable of mediating protein-protein interactions.
Critical considerations in the design and analysis of ChIP-seq experiments include how to align sequenced tags to the genome, how to detect binding sites and how to estimate the number of tags needed to confidently determine where a protein binds DNA. Using data set for three transcription factors, Kharchenko et al. address these considerations by comparing three novel algorithms with published computational methods.