Recent developments in third-gen long read sequencing and diploid-aware assemblers have resulted in the rapid release of numerous reference-quality assemblies for diploid genomes. However, assembly of highly heterozygous genomes is still problematic when regional heterogeneity is so high that haplotype homology is not recognised during assembly. This results in regional duplication rather than consolidation into allelic variants and can cause issues with downstream analysis, for example variant discovery, or haplotype reconstruction using the diploid assembly with unpaired allelic contigs. A new pipeline—Purge Haplotigs—was developed specifically for third-gen sequencing-based assemblies to automate the reassignment of allelic contigs, and to assist in the manual curation of genome assemblies. The pipeline uses a draft haplotype-fused assembly or a diploid assembly, read alignments, and repeat annotations to identify allelic variants in the primary assembly. The pipeline was tested on a simulated dataset and on four recent diploid (phased) de novo assemblies from third-generation long-read sequencing, and compared with a similar tool. After processing with Purge Haplotigs, haploid assemblies were less duplicated with minimal impact on genome completeness, and diploid assemblies had more pairings of allelic contigs. Purge Haplotigs improves the haploid and diploid representations of third-gen sequencing based genome assemblies by identifying and reassigning allelic contigs. The implementation is fast and scales well with large genomes, and it is less likely to over-purge repetitive or paralogous elements compared to alignment-only based methods. The software is available at https://bitbucket.org/mroachawri/purge_haplotigs under a permissive MIT licence.

Microorganisms found in natural environments are fundamental components of ecosystems and play vital roles in various ecological processes. Studying their genomes can provide valuable insights into the diversity, functionality, and evolution of microbial life, as well as their impacts on human health. Once the genetic material is extracted from environmental samples, it undergoes sequencing using technologies like whole genome sequencing (WGS). The raw sequence data is then analysed, and computational methods are applied to assemble the fragmented sequences and reconstruct the complete microbial genomes (Wick et al.,

Improvements in the accuracy and availability of long-read sequencing mean that complete bacterial genomes are now routinely reconstructed using hybrid (i.e. short- and long-reads) assembly approaches. Complete genomes allow a deeper understanding of bacterial evolution and genomic variation beyond single nucleotide variants. They are also crucial for identifying plasmids, which often carry medically significant antimicrobial resistance genes. However, small plasmids are often missed or misassembled by long-read assembly algorithms. Here, we present Hybracter which allows for the fast, automatic and scalable recovery of near-perfect complete bacterial genomes using a long-read first assembly approach. Hybracter can be run either as a hybrid assembler or as a long-read only assembler. We compared Hybracter to existing automated hybrid and long-read only assembly tools using a diverse panel of samples of varying levels of long-read accuracy with manually curated ground truth reference genomes. We demonstrate that Hybracter as a hybrid assembler is more accurate and faster than the existing gold standard automated hybrid assembler Unicycler. We also show that Hybracter with long-reads only is the most accurate long-read only assembler and is comparable to hybrid methods in accurately recovering small plasmids.

Chardonnay is the basis of some of the world’s most iconic wines and its success is underpinned by a historic program of clonal selection. There are numerous clones of Chardonnay available that exhibit differences in key viticultural and oenological traits that have arisen from the accumulation of somatic mutations during centuries of asexual propagation. However, the genetic variation that underlies these differences remains largely unknown. To address this knowledge gap, a high-quality, diploid-phased Chardonnay genome assembly was produced from single-molecule real time sequencing, and combined with re-sequencing data from 15 different Chardonnay clones. There were 1620 markers identified that distinguish the 15 clones. These markers were reliably used for clonal identification of independently sourced genomic material, as well as in identifying a potential genetic basis for some clonal phenotypic differences. The predicted parentage of the Chardonnay haplomes was elucidated by mapping sequence data from the predicted parents of Chardonnay (Gouais blanc and Pinot noir) against the Chardonnay reference genome. This enabled the detection of instances of heterosis, with differentially-expanded gene families being inherited from the parents of Chardonnay. Most surprisingly however, the patterns of nucleotide variation present in the Chardonnay genome indicate that Pinot noir and Gouais blanc share an extremely high degree of kinship that has resulted in the Chardonnay genome displaying characteristics that are indicative of inbreeding. Phenotypic variation within a grapevine cultivar arises from an accumulation of mutations from serial vegetative propagation. Old cultivars such as Chardonnay have been propagated for centuries resulting in hundreds of available ‘clones’ containing unique genetic mutations and a range of various phenotypic peculiarities. The genetic mutations can be leveraged as genetic markers and are useful in identifying specific clones for authenticity testing, or as breeding markers for new clonal selections where particular mutations are known to confer a phenotypic trait. We produced a high-quality genome assembly for Chardonnay, and using re-sequencing data for 15 popular clones, were able to identify a large selection of markers that are unique to at least one clone. We identified mutations that may confer phenotypic effects, and were able to identify clones from material independently sourced from nurseries and vineyards. The marker detection framework we describe for authenticity testing would be applicable to other grapevine cultivars or even other agriculturally important woody-plant crops that are vegetatively propagated such as fruit orchards. Finally, we show that the Chardonnay genome contains extensive evidence for parental inbreeding, such that its parents, Gouais blanc and Pinot noir, may even represent first-degree relatives.

Motivation: Microbial communities have a profound impact on both human health and various environments. Viruses infecting bacteria, known as bacteriophages or phages, play a key role in modulating bacterial communities within environments. High-quality phage genome sequences are essential for advancing our understanding of phage biology, enabling comparative genomics studies and developing phage-based diagnostic tools. Most available viral identification tools consider individual sequences to determine whether they are of viral origin. As a result of challenges in viral assembly, fragmentation of genomes can occur, and existing tools may recover incomplete genome fragments. Therefore, the identification and characterization of novel phage genomes remain a challenge, leading to the need of improved approaches for phage genome recovery. Results: We introduce Phables, a new computational method to resolve phage genomes from fragmented viral metagenome assemblies. Phables identifies phage-like components in the assembly graph, models each component as a flow network, and uses graph algorithms and flow decomposition techniques to identify genomic paths. Experimental results of viral metagenomic samples obtained from different environments show that Phables recovers on average over 49% more high-quality phage genomes compared to existing viral identification tools. Furthermore, Phables can resolve variant phage genomes with over 99% average nucleotide identity, a distinction that existing tools are unable to make. Availability and implementation: Phables is available on GitHub at https://github.com/Vini2/phables.

Formalin-fixed paraffin-embedded (FFPE) samples are valuable but underutilized in single-cell omics research due to their low RNA quality. In this study, leveraging a recent advance in single-cell genomic technology, we introduce snPATHO-seq, a versatile method to derive high-quality single-nucleus transcriptomic data from FFPE samples. We benchmarked the performance of the snPATHO-seq workflow against existing 10x 3’ and Flex assays designed for frozen or fresh samples and highlighted the consistency in snRNA-seq data produced by all workflows. The snPATHO-seq workflow also demonstrated high robustness when tested across a wide range of healthy and diseased FFPE tissue samples. When combined with FFPE spatial transcriptomic technologies such as FFPE Visium, the snPATHO-seq provides a multi-modal sampling approach for FFPE samples, allowing more comprehensive transcriptomic characterization.