Utilising Nanopore technology for interactive real-time metagenomics

Nanopore sequencing technology has the potential to revolutionise metagenomics by providing long reads, which can improve taxonomic classification and assembly contiguity, near real-time analysis, enabling rapid results and improved sequencing efficiency, and portability, allowing sequencing in the field. However, the full potential of these features is largely unrealised due to the lack of available tools and methods. In this thesis, we report on tools and analysis methods that facilitate the use of nanopore sequencing technology for metagenomics and real-time analysis. Applying metagenomics to samples containing a mix of eukaryote species, such as bee-collected pollen, is challenging due to lack of available reference genomes. This thesis presents a new method, RevMet (Reverse Metagenomics), for semi-quantitative characterisation of mixed eukaryote samples without the need for complete reference genomes. Instead, each reference species is represented by a low-cost genome skim. The short-read reference skims are mapped to the long nanopore query reads to individually classify them, which is the reverse of the standard metagenomic approach of mapping reads to (assembled) references. Recognising the need for an open-source software tool for real-time analysis and visualisation of metagenomic sequencing data, we developed MARTi (Metagenomic Analysis in Real-Time). MARTi provides a rapid, lightweight web interface that allows users to view community composition and identify antimicrobial resistance genes in real time. MARTi consists of two main parts, the Engine and the GUI, and can be configured in multiple ways to suit the needs of the user. We demonstrate MARTi on live nanopore sequencing runs - firstly, using a mock gut community and, secondly, using clinical faecal gut microbiome samples taken from patients suffering from liver disease

Semi‐quantitative characterisation of mixed pollen samples using MinION sequencing and Reverse Metagenomics (RevMet)

1. The ability to identify and quantify the constituent plant species that make up a mixed‐species sample of pollen has important applications in ecology, conservation, and agriculture. Recently, metabarcoding protocols have been developed for pollen that can identify constituent plant species, but there are strong reasons to doubt that metabarcoding can accurately quantify their relative abundances. A PCR‐free, shotgun metagenomics approach has greater potential for accurately quantifying species relative abundances, but applying metagenomics to eukaryotes is challenging due to low numbers of reference genomes. 2. We have developed a pipeline, RevMet (Reverse Metagenomics) that allows reliable and semi‐quantitative characterization of the species composition of mixed‐species eukaryote samples, such as bee‐collected pollen, without requiring reference genomes. Instead, reference species are represented only by ‘genome skims’: low‐cost, low‐coverage, short‐read sequence datasets. The skims are mapped to individual long reads sequenced from mixed‐species samples using the MinION, a portable nanopore sequencing device, and each long read is uniquely assigned to a plant species. 3. We genome‐skimmed 49 wild UK plant species, validated our pipeline with mock DNA mixtures of known composition, and then applied RevMet to pollen loads collected from wild bees. We demonstrate that RevMet can identify plant species present in mixed‐species samples at proportions of DNA ≥ 1%, with few false positives and false negatives, and reliably differentiate species represented by high versus low amounts of DNA in a sample. 4. RevMet could readily be adapted to generate semi‐quantitative datasets for a wide range of mixed eukaryote samples. Our per‐sample costs were £90 per genome skim and £60 per pollen sample, and new versions of sequencers available now will further reduce these costs

Metagenomic analysis of planktonic riverine microbial consortia using nanopore sequencing reveals insight into river microbe taxonomy and function

Background Riverine ecosystems are biogeochemical powerhouses driven largely by microbial communities that inhabit water columns and sediments. Because rivers are used extensively for anthropogenic purposes (drinking water, recreation, agriculture, and industry), it is essential to understand how these activities affect the composition of river microbial consortia. Recent studies have shown that river metagenomes vary considerably, suggesting that microbial community data should be included in broad-scale river ecosystem models. But such ecogenomic studies have not been applied on a broad “aquascape” scale, and few if any have applied the newest nanopore technology. Results We investigated the metagenomes of 11 rivers across 3 continents using MinION nanopore sequencing, a portable platform that could be useful for future global river monitoring. Up to 10 Gb of data per run were generated with average read lengths of 3.4 kb. Diversity and diagnosis of river function potential was accomplished with 0.5–1.0 ⋅ 106 long reads. Our observations for 7 of the 11 rivers conformed to other river-omic findings, and we exposed previously unrecognized microbial biodiversity in the other 4 rivers. Conclusions Deeper understanding that emerged is that river microbial consortia and the ecological functions they fulfil did not align with geographic location but instead implicated ecological responses of microbes to urban and other anthropogenic effects, and that changes in taxa manifested over a very short geographic space

An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations

Advances in genome sequencing and assembly technologies are generating many high-quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimized data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents >78% of the genome with a scaffold N50 of 88.8 kb that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNA-seq and Pacific Biosciences (PacBio) full-length cDNAs to identify 104,091 high-confidence protein-coding genes and 10,156 noncoding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop

Meiosis and beyond – understanding the mechanistic and evolutionary processes shaping the germline genome

The separation of germ cell populations from the soma is part of the evolutionary transition to multicellularity. Only genetic information present in the germ cells will be inherited by future generations, and any molecular processes affecting the germline genome are therefore likely to be passed on. Despite its prevalence across taxonomic kingdoms, we are only starting to understand details of the underlying micro‐evolutionary processes occurring at the germline genome level. These include segregation, recombination, mutation and selection and can occur at any stage during germline differentiation and mitotic germline proliferation to meiosis and post‐meiotic gamete maturation. Selection acting on germ cells at any stage from the diploid germ cell to the haploid gametes may cause significant deviations from Mendelian inheritance and may be more widespread than previously assumed. The mechanisms that affect and potentially alter the genomic sequence and allele frequencies in the germline are pivotal to our understanding of heritability. With the rise of new sequencing technologies, we are now able to address some of these unanswered questions. In this review, we comment on the most recent developments in this field and identify current gaps in our knowledge