Mammalian chromosomes fold into arrays of megabase‐sized topologically associating domains (TADs), which are arranged into compartments spanning multiple megabases of genomic DNA. TADs have internal substructures that are often cell type specific, but their higher‐order organization remains elusive. Here, we investigate TAD higher‐order interactions with Hi‐C through neuronal differentiation and show that they form a hierarchy of domains‐within‐domains (metaTADs) extending across genomic scales up to the range of entire chromosomes. We find that TAD interactions are well captured by tree‐like, hierarchical structures irrespective of cell type. metaTAD tree structures correlate with genetic, epigenomic and expression features, and structural tree rearrangements during differentiation are linked to transcriptional state changes. Using polymer modelling, we demonstrate that hierarchical folding promotes efficient chromatin packaging without the loss of contact specificity, highlighting a role far beyond the simple need for packing efficiency.

The Rfam database aims to catalogue non-coding RNAs through the use of sequence alignments and statistical profile models known as covariance models. In this contribution, we discuss the pros and cons of using the online encyclopedia, Wikipedia, as a source of community-derived annotation. We discuss the addition of groupings of related RNA families into clans and new developments to the website. Rfam is available on the Web at http://rfam.sanger.ac.uk.

Improvement of variant calling in next-generation sequence data requires a comprehensive, genome-wide catalog of highconfidence variants called in a set of genomes for use as a benchmark. We generated deep, whole-genome sequence data of 17 individuals in a three-generation pedigree and called variants in each genome using a range of currently available algorithms. We used haplotype transmission information to create a phased "Platinum" variant catalog of 4.7 million singlenucleotide variants (SNVs) plus 0.7 million small (1-50 bp) insertions and deletions (indels) that are consistent with the pattern of inheritance in the parents and 11 children of this pedigree. Platinum genotypes are highly concordant with the current catalog of the National Institute of Standards and Technology for both SNVs (>99.99%) and indels (99.92%) and add a validated truth catalog that has 26% more SNVs and 45% more indels. Analysis of 334,652 SNVs that were consistent between informatics pipelines yet inconsistent with haplotype transmission ("nonplatinum") revealed that the majority of these variants are de novo and cell-line mutations or reside within previously unidentified duplications and deletions. The reference materials from this study are a resource for objective assessment of the accuracy of variant calls throughout genomes.

Standardized benchmarking methods and tools are essential to robust accuracy assessment of NGS variant calling. Benchmarking variant calls requires careful attention to definitions of performance metrics, sophisticated comparison approaches, and stratification by variant type and genome context. To address these needs, the Global Alliance for Genomics and Health (GA4GH) Benchmarking Team convened representatives from sequencing technology developers, government agencies, academic bioinformatics researchers, clinical laboratories, and commercial technology and bioinformatics developers for whom benchmarking variant calls is essential to their work. This team addressed challenges in (1) matching variant calls with different representations, (2) defining standard performance metrics, (3) enabling stratification of performance by variant type and genome context, and (4) developing and describing limitations of high-confidence calls and regions that can be used as “truth”. Our methods are publicly available on GitHub (https://github.com/ga4gh/benchmarking-tools) and in a web-based app on precisionFDA, which allow users to compare their variant calls against truth sets and to obtain a standardized report on their variant calling performance. Our methods have been piloted in the precisionFDA variant calling challenges to identify the best-in-class variant calling methods within high-confidence regions. Finally, we recommend a set of best practices for using our tools and critically evaluating the results.