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Background Hi-C experiments couple DNA-DNA proximity with next-generation sequencing to yield an unbiased description of genome-wide interactions. Previous methods describing Hi-C experiments have focused on the industry-standard Illumina sequencing. With new next-generation sequencing platforms such as BGISEQ-500 becoming more widely available, protocol adaptations to fit platform-specific requirements are useful to give increased choice to researchers who routinely generate sequencing data. Results We describe an in situ Hi-C protocol adapted to be compatible with the BGISEQ-500 high-throughput sequencing platform. Using zebra finch (Taeniopygia guttata) as a biological sample, we demonstrate how Hi-C libraries can be constructed to generate informative data using the BGISEQ-500 platform, following circularization and DNA nanoball generation. Our protocol is a modification of an Illumina-compatible method, based around blunt-end ligations in library construction, using un-barcoded, distally overhanging double-stranded adapters, followed by amplification using indexed primers. The resulting libraries are ready for circularization and subsequent sequencing on the BGISEQ series of platforms and yield data similar to what can be expected using Illumina-compatible approaches. Conclusions Our straightforward modification to an Illumina-compatible in situ Hi-C protocol enables data generation on the BGISEQ series of platforms, thus expanding the options available for researchers who wish to utilize the powerful Hi-C techniques in their research. [ABSTRACT FROM AUTHOR]

T47D rep2 and b1913e6c1 51720e9cf were 2 Hi-C samples. They were born and processed at the same time, yet their fates were very different. The life of b1913e6c1 51720e9cf was simple and fruitful, while that of T47D rep2 was full of accidents and sorrow. At the heart of these differences lies the fact that b1913e6c1 51720e9cf was born under a lab culture of Documentation, Automation, Traceability, and Autonomy and compliance with the FAIR Principles. Their lives are a lesson for those who wish to embark on the journey of managing high-throughput sequencing data. [ABSTRACT FROM AUTHOR]

Motivation: Aligning RNAs is useful to search for homologous genes, study evolutionary relationships, detect conserved regions and identify any patterns that may be of biological relevance. Poor levels of conservation among homologs, however, make it difficult to compare RNA sequences, even when considering closely evolutionary related sequences.Results: We describe SARA-Coffee, a tertiary structure-based multiple RNA aligner, which has been validated using BRAliDARTS, a new benchmark framework designed for evaluating tertiary structure–based multiple RNA aligners. We provide two methods to measure the capacity of alignments to match corresponding secondary and tertiary structure features. On this benchmark, SARA-Coffee outperforms both regular aligners and those using secondary structure information. Furthermore, we show that on sequences in which <60% of the nucleotides form base pairs, primary sequence methods usually perform better than secondary-structure aware aligners.Availability and implementation: The package and the datasets are available from http://www.tcoffee.org/Projects/saracoffee and http://structure.biofold.org/sara/.Contact: cedric.notredame@crg.esSupplementary information: Supplementary data are available at Bioinformatics online [ABSTRACT FROM AUTHOR]

Motivation: Over the recent years, the vision that RNA simply serves as information transfer molecule has dramatically changed. The study of the sequence/structure/function relationships in RNA is becoming more important. As a direct consequence, the total number of experimentally solved RNA structures has dramatically increased and new computer tools for predicting RNA structure from sequence are rapidly emerging. Therefore, new and accurate methods for assessing the accuracy of RNA structure models are clearly needed.Results: Here, we introduce an all-atom knowledge-based potential for the assessment of RNA three-dimensional (3D) structures. We have benchmarked our new potential, called Ribonucleic Acids Statistical Potential (RASP), with two different decoy datasets composed of near-native RNA structures. In one of the benchmark sets, RASP was able to rank the closest model to the X-ray structure as the best and within the top 10 models for ∼93 and ∼95% of decoys, respectively. The average correlation coefficient between model accuracy, calculated as the root mean square deviation and global distance test-total score (GDT-TS) measures of C3′ atoms, and the RASP score was 0.85 and 0.89, respectively. Based on a recently released benchmark dataset that contains hundreds of 3D models for 32 RNA motifs with non-canonical base pairs, RASP scoring function compared favorably to ROSETTA FARFAR force field in the selection of accurate models. Finally, using the self-splicing group I intron and the stem-loop IIIc from hepatitis C virus internal ribosome entry site as test cases, we show that RASP is able to discriminate between known structure-destabilizing mutations and compensatory mutations.Availability: RASP can be readily applied to assess all-atom or coarse-grained RNA structures and thus should be of interest to both developers and end-users of RNA structure prediction methods. The computer software and knowledge-based potentials are freely available at http://melolab.org/supmat.html.Contact: fmelo@bio.puc.cl; mmarti@cipf.esSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Comparing the structures of proteins is crucial to gaining insight into protein evolution and function. Here, we align the sequences of multiple protein structures by a dynamic programming optimization of a scoring function that is a sum of an affine gap penalty and terms dependent on various sequence and structure features (SALIGN). The features include amino acid residue type, residue position, residue accessible surface area, residue secondary structure state and the conformation of a short segment centered on the residue. The multiple alignment is built by following the ‘guide’ tree constructed from the matrix of all pairwise protein alignment scores. Importantly, the method does not depend on the exact values of various parameters, such as feature weights and gap penalties, because the optimal alignment across a range of parameter values is found. Using multiple structure alignments in the HOMSTRAD database, SALIGN was benchmarked against MUSTANG for multiple alignments as well as against TM-align and CE for pairwise alignments. On the average, SALIGN produces a 15% improvement in structural overlap over HOMSTRAD and 14% over MUSTANG, and yields more equivalent structural positions than TM-align and CE in 90% and 95% of cases, respectively. The utility of accurate multiple structure alignment is illustrated by its application to comparative protein structure modeling. [ABSTRACT FROM PUBLISHER]

The three-dimensional (3D) organization of chromosomes can influence transcription. However, the frequency and magnitude of these effects remain debated. To determine how changes in chromosome positioning affect transcription across thousands of genes with minimal perturbation, we characterized nuclear organization and global gene expression in budding yeast containing chromosome fusions. We used computational modeling and single-cell imaging to determine chromosome positions, and integrated these data with genome-wide transcriptional profiles from RNA sequencing. We find that chromosome fusions dramatically alter 3D nuclear organization without leading to strong genome-wide changes in transcription. However, we observe a mild but significant and reproducible increase in the expression of genes displaced away from the periphery. The increase in transcription is inversely proportional to the propensity of a given locus to be at the nuclear periphery; for example, a 10% decrease in the propensity of a gene to reside at the nuclear envelope is accompanied by a 10% increase in gene expression. Modeling suggests that this is due to both deletion of telomeres and to displacement of genes relative to the nuclear periphery. These data suggest that basal transcriptional activity is sensitive to radial changes in gene position, and provide insight into the functional relevance of budding yeast chromosome-level 3D organization in gene expression. [ABSTRACT FROM AUTHOR]