The revolution of genome sequencing is continuing after the successful second-generation sequencing (SGS) technology. The third-generation sequencing (TGS) technology, led by Pacific Biosciences (PacBio), is progressing rapidly, moving from a technology once only capable of providing data for small genome analysis, or for performing targeted screening, to one that promises high quality de novo assembly and structural variation detection for human-sized genomes. In 2014, the MinION, the first commercial sequencer using nanopore technology, was released by Oxford Nanopore Technologies (ONT). MinION identifies DNA bases by measuring the changes in electrical conductivity generated as DNA strands pass through a biological pore. Its portability, affordability, and speed in data production makes it suitable for real-time applications, the release of the long read sequencer MinION has thus generated much excitement and interest in the genomics community. While de novo genome assemblies can be cheaply produced from SGS data, assembly continuity is often relatively poor, due to the limited ability of short reads to handle long repeats. Assembly quality can be greatly improved by using TGS long reads, since repetitive regions can be easily expanded into using longer sequencing lengths, despite having higher error rates at the base level. The potential of nanopore sequencing has been demonstrated by various studies in genome surveillance at locations where rapid and reliable sequencing is needed, but where resources are limited.

Long-read sequencing technologies such as Pacific Biosciences and Oxford Nanopore MinION are capable of producing long sequencing reads with average fragment lengths of over 10,000 base-pairs and maximum lengths reaching 100,000 base- pairs. Compared with short reads, the assemblies obtained from long-read sequencing platforms have much higher contig continuity and genome completeness as long fragments are able to extend paths into problematic or repetitive regions. Many successful assembly applications of the Pacific Biosciences technology have been reported ranging from small bacterial genomes to large plant and animal genomes. Recently, genome assemblies using Oxford Nanopore MinION data have attracted much attention due to the portability and low cost of this novel sequencing instrument. In this paper, we re-sequenced a well characterized genome, the Saccharomyces cerevisiae S288C strain using three different platforms: MinION, PacBio and MiSeq. We present a comprehensive metric comparison of assemblies generated by various pipelines and discuss how the platform associated data characteristics affect the assembly quality. With a given read depth of 31X, the assemblies from both Pacific Biosciences and Oxford Nanopore MinION show excellent continuity and completeness for the 16 nuclear chromosomes, but not for the mitochondrial genome, whose reconstruction still represents a significant challenge.

Although diet is a substantial determinant of the human gut microbiome, the interplay between specific foods and microbial community structure remains poorly understood. Coffee is a habitually consumed beverage with established metabolic and health benefits. We previously found that coffee is, among >150 items, the food showing the highest correlation with microbiome components. Here we conducted a multi-cohort, multi-omic analysis of US and UK populations with detailed dietary information from a total of 22,867 participants, which we then integrated with public data from 211 cohorts (N = 54,198). The link between coffee consumption and microbiome was highly reproducible across different populations (area under the curve of 0.89), largely driven by the presence and abundance of the species Lawsonibacter asaccharolyticus. Using in vitro experiments, we show that coffee can stimulate growth of L. asaccharolyticus. Plasma metabolomics on 438 samples identified several metabolites enriched among coffee consumers, with quinic acid and its potential derivatives associated with coffee and L. asaccharolyticus. This study reveals a metabolic link between a specific gut microorganism and a specific food item, providing a framework for the understanding of microbial dietary responses at the biochemical level.

The incidence of cardiometabolic diseases is increasing globally, and both poor diet and the human gut microbiome have been implicated ¹ . However, the field lacks large-scale, comprehensive studies exploring these links in diverse populations ² . Here, in over 34,000 US and UK participants with metagenomic, diet, anthropometric and host health data, we identified known and yet-to-be-cultured gut microbiome species associated significantly with different diets and risk factors. We developed a ranking of species most favourably and unfavourably associated with human health markers, called the ‘ZOE Microbiome Health Ranking 2025’. This system showed strong and reproducible associations between the ranking of microbial species and both body mass index and host disease conditions on more than 7,800 additional public samples. In an additional 746 people from two dietary interventional clinical trials, favourably ranked species increased in abundance and prevalence, and unfavourably ranked species reduced over time. In conclusion, these analyses provide strong support for the association of both diet and microbiome with health markers, and the summary system can be used to inform the basis for future causal and mechanistic studies. It should be emphasized, however, that causal inference is not possible without prospective cohort studies and interventional clinical trials.

The recent technological advances in genome sequencing techniques have resulted in an exponential increase in the number of sequenced human and non-human genomes. The ever increasing number of assemblies generated by novel de novo pipelines and strategies demands the development of new software to evaluate assembly quality and completeness. One way to determine the completeness of an assembly is by detecting its Presence–Absence variations (PAV) with respect to a reference, where PAVs between two assemblies are defined as the sequences present in one assembly but entirely missing in the other one. Beyond assembly error or technology bias, PAVs can also reveal real genome polymorphism, consequence of species or individual evolution, or horizontal transfer from viruses and bacteria. We present scanPAV, a pipeline for pairwise assembly comparison to identify and extract sequences present in one assembly but not the other. In this note, we use the GRCh38 reference assembly to assess the completeness of six human genome assemblies from various assembly strategies and sequencing technologies including Illumina short reads, 10× genomics linked-reads, PacBio and Oxford Nanopore long reads, and Bionano optical maps. We also discuss the PAV polymorphism of seven Tasmanian devil whole genome assemblies of normal animal tissues and devil facial tumour 1 (DFT1) and 2 (DFT2) samples, and the identification of bacterial sequences as contamination in some of the tumorous assemblies. The pipeline is available under the MIT License at https://github.com/wtsi-hpag/scanPAV. Supplementary data are available at Bioinformatics online.