Hi-C for mosquito genomes: Most genomes sequenced today are determined through the generation of short sequenced bits of DNA that are computationally pieced together like a jigsaw puzzle. This has resulted in the need for funds and additional data to fill in gaps in order to fully assemble the many chromosomes that make up a eukaryotic genome. Dudchenko et al. used the Hi-C method, which measures the distance between contact points within and between chromosomes for scaffold validation, together with correction and ordering to more completely determine the arrangement of short sequencing reads for genome mapping. They validated their approach through the de novo generation of a complete human genome. A comparative analysis of mosquito genomes was made possible by improving the Culex quinquefasciatus genome assembly and generating the genome of Aedes aegypti , the vector of Zika virus. Science , this issue p. 92

Like many other crops, the cultivated peanut (Arachis hypogaea L.) is of hybrid origin and has a polyploid genome that contains essentially complete sets of chromosomes from two ancestral species. Here we report the genome sequence of peanut and show that after its polyploid origin, the genome has evolved through mobile-element activity, deletions and by the flow of genetic information between corresponding ancestral chromosomes (that is, homeologous recombination). Uniformity of patterns of homeologous recombination at the ends of chromosomes favors a single origin for cultivated peanut and its wild counterpart A. monticola. However, through much of the genome, homeologous recombination has created diversity. Using new polyploid hybrids made from the ancestral species, we show how this can generate phenotypic changes such as spontaneous changes in the color of the flowers. We suggest that diversity generated by these genetic mechanisms helped to favor the domestication of the polyploid A. hypogaea over other diploid Arachis species cultivated by humans.

Hi-C contact maps are valuable for genome assembly (Lieberman-Aiden, van Berkum et al. 2009; Burton et al. 2013; Dudchenko et al. 2017). Recently, we developed Juicebox, a system for the visual exploration of Hi-C data (Durand, Robinson et al. 2016), and 3D-DNA, an automated pipeline for using Hi-C data to assemble genomes (Dudchenko et al. 2017). Here, we introduce “Assembly Tools,” a new module for Juicebox, which provides a point-and-click interface for using Hi-C heatmaps to identify and correct errors in a genome assembly. Together, 3D-DNA and the Juicebox Assembly Tools greatly reduce the cost of accurately assembling complex eukaryotic genomes. To illustrate, we generated de novo assemblies with chromosome-length scaffolds for three mammals: the wombat, Vombatus ursinus (3.3Gb), the Virginia opossum, Didelphis virginiana (3.3Gb), and the raccoon, Procyon lotor (2.5Gb). The only inputs for each assembly were Illumina reads from a short insert DNA-Seq library (300 million Illumina reads, maximum length 2x150 bases) and an in situ Hi-C library (100 million Illumina reads, maximum read length 2x150 bases), which cost <$1000.

Organismal evolution of the 3D genome: The conformation of chromosomes within the nucleus can reflect a cell's type or state. However, studies of the conservation and evolutionary history of the mechanisms regulating genome structure across species are lacking. Hoencamp et al. mapped three-dimensional (3D) genome organization in 24 eukaryote species, including animals, fungi, and plants. At interphase, species' telomeres and centromeres either clustered across chromosomes or oriented in a polarized state maintaining individual chromosomal territories within the cell, a difference attributed to condensin II. An experimental loss of condensin II in human cells promotes the formation of centromere clusters but has no effect on loop or compartment formation. Whether the structure of the 3D genome varies across species may thus depend on whether they carry a functional condensin II gene. Science , abe2218, this issue p. 984

Nuclear compartments are prominent features of 3D chromatin organization, but sequencing depth limitations have impeded investigation at ultra fine-scale. CTCF loops are generally studied at a finer scale, but the impact of looping on proximal interactions remains enigmatic. Here, we critically examine nuclear compartments and CTCF loop-proximal interactions using a combination of in situ Hi-C at unparalleled depth, algorithm development, and biophysical modeling. Producing a large Hi-C map with 33 billion contacts in conjunction with an algorithm for performing principal component analysis on sparse, super massive matrices (POSSUMM), we resolve compartments to 500 bp. Our results demonstrate that essentially all active promoters and distal enhancers localize in the A compartment, even when flanking sequences do not. Furthermore, we find that the TSS and TTS of paused genes are often segregated into separate compartments. We then identify diffuse interactions that radiate from CTCF loop anchors, which correlate with strong enhancer-promoter interactions and proximal transcription. We also find that these diffuse interactions depend on CTCF’s RNA binding domains. In this work, we demonstrate features of fine-scale chromatin organization consistent with a revised model in which compartments are more precise than commonly thought while CTCF loops are more protracted.

The Encyclopedia of DNA elements (ENCODE) project is a collaborative effort to create a comprehensive catalog of functional elements in the human genome. The current database comprises more than 19000 functional genomics experiments across more than 1000 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the Homo sapiens and Mus musculus genomes. All experimental data, metadata, and associated computational analyses created by the ENCODE consortium are submitted to the Data Coordination Center (DCC) for validation, tracking, storage, and distribution to community resources and the scientific community. The ENCODE project has engineered and distributed uniform processing pipelines in order to promote data provenance and reproducibility as well as allow interoperability between genomic resources and other consortia. All data files, reference genome versions, software versions, and parameters used by the pipelines are captured and available via the ENCODE Portal. The pipeline code, developed using Docker and Workflow Description Language (WDL; https://openwdl.org/ ) is publicly available in GitHub, with images available on Dockerhub ( https://hub.docker.com ), enabling access to a diverse range of biomedical researchers. ENCODE pipelines maintained and used by the DCC can be installed to run on personal computers, local HPC clusters, or in cloud computing environments via Cromwell. Access to the pipelines and data via the cloud allows small labs the ability to use the data or software without access to institutional compute clusters. Standardization of the computational methodologies for analysis and quality control leads to comparable results from different ENCODE collections - a prerequisite for successful integrative analyses. Database URL: https://www.encodeproject.org/