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Chromosome conformation capture data, particularly from high-throughput approaches such as Hi-C, are typically very complex to analyse. Existing analysis tools are often single-purpose, or limited in compatibility to a small number of data formats, frequently making Hi-C analyses tedious and time-consuming. Here, we present FAN-C, an easy-to-use command-line tool and powerful Python API with a broad feature set covering matrix generation, analysis, and visualisation for C-like data ( https://github.com/vaquerizaslab/fanc ). Due to its compatibility with the most prevalent Hi-C storage formats, FAN-C can be used in combination with a large number of existing analysis tools, thus greatly simplifying Hi-C matrix analysis.

Summary Guava (Psidium guajava) is an important fleshy‐fruited tree of the Myrtaceae family that is widely cultivated in tropical and subtropical areas of the world and has attracted considerable attention for the richness of ascorbic acid in its fruits. However, studies on the evolution and genetic breeding potential of guava are hindered by the lack of a reference genome. Here, we present a chromosome‐level genomic assembly of guava using PacBio sequencing and Hi‐C technology. We found that the genome assembly size was 443.8 Mb with a contig N50 of ~15.8 Mb. We annotated a total of 25 601 genes and 193.2 Mb of repetitive sequences for this genome. Comparative genomic analysis revealed that guava has undergone a recent whole‐genome duplication (WGD) event shared by all species in Myrtaceae. In addition, through metabolic analysis, we determined that the L‐galactose pathway plays a major role in ascorbic acid biosynthesis in guava fruits. Moreover, the softening of fruits of guava may result from both starch and cell wall degradation according to analyses of gene expression profiles and positively selected genes. Our data provide a foundational resource to support molecular breeding of guava and represent new insights into the evolution of soft, fleshy fruits in Myrtaceae.

Summary China is the origin and evolutionary centre of Oriental pears. Pyrus betuleafolia is a wild species native to China and distributed in the northern region, and it is widely used as rootstock. Here, we report the de novo assembly of the genome of P. betuleafolia‐Shanxi Duli using an integrated strategy that combines PacBio sequencing, BioNano mapping and chromosome conformation capture (Hi‐C) sequencing. The genome assembly size was 532.7 Mb, with a contig N50 of 1.57 Mb. A total of 59 552 protein‐coding genes and 247.4 Mb of repetitive sequences were annotated for this genome. The expansion genes in P. betuleafolia were significantly enriched in secondary metabolism, which may account for the organism's considerable environmental adaptability. An alignment analysis of orthologous genes showed that fruit size, sugar metabolism and transport, and photosynthetic efficiency were positively selected in Oriental pear during domestication. A total of 573 nucleotide‐binding site (NBS)‐type resistance gene analogues (RGAs) were identified in the P. betuleafolia genome, 150 of which are TIR‐NBS‐LRR (TNL)‐type genes, which represented the greatest number of TNL‐type genes among the published Rosaceae genomes and explained the strong disease resistance of this wild species. The study of flavour metabolism‐related genes showed that the anthocyanidin reductase (ANR) metabolic pathway affected the astringency of pear fruit and that sorbitol transporter (SOT) transmembrane transport may be the main factor affecting the accumulation of soluble organic matter. This high‐quality P. betuleafolia genome provides a valuable resource for the utilization of wild pear in fundamental pear studies and breeding.

Summary Allele‐specific expression (ASE) can lead to phenotypic diversity and evolution. However, the mechanisms regulating ASE are not well understood, particularly in woody perennial plants. In this study, we investigated ASE genes in the apple cultivar ‘Royal Gala’ (RG). A high quality chromosome‐level genome was assembled using a homozygous tetra‐haploid RG plant, derived from anther cultures. Using RNA‐sequencing (RNA‐seq) data from RG flower and fruit tissues, we identified 2091 ASE genes. Compared with the haploid genome of ‘Golden Delicious’ (GD), a parent of RG, we distinguished the genomic sequences between the two alleles of 817 ASE genes, and further identified allele‐specific presence of a transposable element (TE) in the upstream region of 354 ASE genes. These included MYB110a that encodes a transcription factor regulating anthocyanin biosynthesis. Interestingly, another ASE gene, MYB10 also showed an allele‐specific TE insertion and was identified using genome data of other apple cultivars. The presence of the TE insertion in both MYB genes was positively associated with ASE and anthocyanin accumulation in apple petals through analysis of 231 apple accessions, and thus underpins apple flower colour evolution. Our study demonstrated the importance of TEs in regulating ASE on a genome‐wide scale and presents a novel method for rapid identification of ASE genes and their regulatory elements in plants.

Fragaria nilgerrensis is a wild diploid strawberry species endemic to east and southeast region in Asia and provides a rich source of genetic variations for strawberry improvement. Here, we present a chromosome‐scale assembly of F. nilgerrensis using single‐molecule real‐time (SMRT) Pacific Biosciences sequencing and chromosome conformation capture (Hi‐C) genome scaffolding. The genome assembly size was 270.3 Mb, with a contig N50 of ∼8.5 Mb. A total of 28 780 genes and 117.2 Mb of transposable elements were annotated for this genome. Next, detailed comparative genomics with the high‐quality F. vesca reference genome was conducted to obtain the difference among transposable elements, SNPs, Indels, and so on. The genome size of F. nilgerrensis was enhanced by around 50 Mb relatively to F. vesca, which is mainly due to expansion of transposable elements. In comparison with the F. vesca genome, we identified 4 561 825 SNPs, 846 301 Indels, 4243 inversions, 35 498 translocations and 10 099 relocations. We also found a marked expansion of genes involved in phenylpropanoid biosynthesis, starch and sucrose metabolism, cyanoamino acid metabolism, plant–pathogen interaction, brassinosteroid biosynthesis and plant hormone signal transduction in F. nilgerrensis, which may account for its specific phenotypes and considerable environmental adaptability. Interestingly, we found sequence variations in the upstream regulatory region of FnMYB10, a core transcriptional activator of anthocyanin biosynthesis, resulted in the low expression level of the FnMYB10 gene, which is likely responsible for white fruit phenotype of F. nilgerrensis. The high‐quality F. nilgerrensis genome will be a valuable resource for biological research and comparative genomics research.

While colocalization within a bacterial operon enables coexpression of the constituent genes, the mechanistic logic of clustering of nonhomologous monocistronic genes in eukaryotes is not immediately obvious. Biosynthetic gene clusters that encode pathways for specialized metabolites are an exception to the classical eukaryote rule of random gene location and provide paradigmatic exemplars with which to understand eukaryotic cluster dynamics and regulation. Here, using 3C, Hi-C, and Capture Hi-C (CHi-C) organ-specific chromosome conformation capture techniques along with high-resolution microscopy, we investigate how chromosome topology relates to transcriptional activity of clustered biosynthetic pathway genes in Arabidopsis thaliana. Our analyses reveal that biosynthetic gene clusters are embedded in local hot spots of 3D contacts that segregate cluster regions from the surrounding chromosome environment. The spatial conformation of these cluster-associated domains differs between transcriptionally active and silenced clusters. We further show that silenced clusters associate with heterochromatic chromosomal domains toward the periphery of the nucleus, while transcriptionally active clusters relocate away from the nuclear periphery. Examination of chromosome structure at unrelated clusters in maize, rice, and tomato indicates that integration of clustered pathway genes into distinct topological domains is a common feature in plant genomes. Our results shed light on the potential mechanisms that constrain coexpression within clusters of nonhomologous eukaryotic genes and suggest that gene clustering in the one-dimensional chromosome is accompanied by compartmentalization of the 3D chromosome.

We present HiGlass, an open source visualization tool built on web technologies that provides a rich interface for rapid, multiplex, and multiscale navigation of 2D genomic maps alongside 1D genomic tracks, allowing users to combine various data types, synchronize multiple visualization modalities, and share fully customizable views with others. We demonstrate its utility in exploring different experimental conditions, comparing the results of analyses, and creating interactive snapshots to share with collaborators and the broader public. HiGlass is accessible online at http://higlass.io and is also available as a containerized application that can be run on any platform.

Hi-C exploits contact frequencies between pairs of loci to bridge and order contigs during genome assembly, resulting in chromosome-level assemblies. Because few robust programs are available for this type of data, we developed instaGRAAL, a complete overhaul of the GRAAL program, which has adapted the latter to allow efficient assembly of large genomes. instaGRAAL features a number of improvements over GRAAL, including a modular correction approach that optionally integrates independent data. We validate the program using data for two brown algae, and human, to generate near-complete assemblies with minimal human intervention.

Mammalian chromatin is spatially organized at many scales showing two prominent features in interphase: (i) alternating regions (1–10 Mb) of active and inactive chromatin that spatially segregate into different compartments, and (ii) domains (<1 Mb), that is, regions that preferentially interact internally [topologically associating domains (TADs)] and are central to gene regulation. There is growing evidence that TADs are formed by active extrusion of chromatin loops by cohesin, whereas compartmentalization is established according to local chromatin states. Here, we use polymer simulations to examine how loop extrusion and compartmental segregation work collectively and potentially interfere in shaping global chromosome organization. A model with differential attraction between euchromatin and heterochromatin leads to phase separation and reproduces compartmentalization as observed in Hi-C. Loop extrusion, essential for TAD formation, in turn, interferes with compartmentalization. Our integrated model faithfully reproduces Hi-C data from puzzling experimental observations where altering loop extrusion also led to changes in compartmentalization. Specifically, depletion of chromatin-associated cohesin reduced TADs and revealed finer compartments, while increased processivity of cohesin strengthened large TADs and reduced compartmentalization; and depletion of the TAD boundary protein CTCF weakened TADs while leaving compartments unaffected. We reveal that these experimental perturbations are special cases of a general polymer phenomenon of active mixing by loop extrusion. Our results suggest that chromatin organization on the megabase scale emerges from competition of nonequilibrium active loop extrusion and epigenetically defined compartment structure.

HiC-Pro is an optimized and flexible pipeline for processing Hi-C data from raw reads to normalized contact maps. HiC-Pro maps reads, detects valid ligation products, performs quality controls and generates intra- and inter-chromosomal contact maps. It includes a fast implementation of the iterative correction method and is based on a memory-efficient data format for Hi-C contact maps. In addition, HiC-Pro can use phased genotype data to build allele-specific contact maps. We applied HiC-Pro to different Hi-C datasets, demonstrating its ability to easily process large data in a reasonable time. Source code and documentation are available at http://github.com/nservant/HiC-Pro .