Microbiology & Immunology - Research Publications

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    Unicycler: resolving bacterial genome assemblies from short and long sequencing reads
    Wick, R ; Judd, L ; Gorrie, C ; Holt, K ( 2016-12-22)
    The Illumina DNA sequencing platform generates accurate but short reads, which can be used to produce accurate but fragmented genome assemblies. Pacific Biosciences and Oxford Nanopore Technologies DNA sequencing platforms generate long reads that can produce more complete genome assemblies, but the sequencing is more expensive and error prone. There is significant interest in combining data from these complementary sequencing technologies to generate more accurate “hybrid” assemblies. However, few tools exist that truly leverage the benefits of both types of data, namely the accuracy of short reads and the structural resolving power of long reads. Here we present Unicycler, a new tool for assembling bacterial genomes from a combination of short and long reads, which produces assemblies that are accurate, complete and cost-effective. Unicycler builds an initial assembly graph from short reads using the de novo assembler SPAdes and then simplifies the graph using information from short and long reads. Unicycler utilises a novel semi-global aligner, which is used to align long reads to the assembly graph. Tests on both synthetic and real reads show Unicycler can assemble larger contigs with fewer misassemblies than other hybrid assemblers, even when long read depth and accuracy are low. Unicycler is open source (GPLv3) and available at github.com/rrwick/Unicycler .
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    Temporal mixture modelling of single-cell RNA-seq data resolves a CD4+ T cell fate bifurcation
    Lönnberg, T ; Svensson, V ; James, K ; Fernandez-Ruiz, D ; Sebina, I ; Montandon, R ; Soon, M ; Fogg, L ; Stubbington, M ; Otzen Bagger, F ; Zwiessele, M ; Lawrence, N ; Souza-Fonseca-Guimaraes, F ; Heath, W ; Billker, O ; Stegle, O ; Haque, A ; Teichmann, S ( 2016)
    Differentiation of naïve CD4 + T cells into functionally distinct T helper subsets is crucial for the orchestration of immune responses. Due to multiple levels of heterogeneity and multiple overlapping transcriptional programs in differentiating T cell populations, this process has remained a challenge for systematic dissection in vivo . By using single-cell RNA transcriptomics and computational modelling of temporal mixtures, we reconstructed the developmental trajectories of Th1 and Tfh cell populations during Plasmodium infection in mice at single-cell resolution. These cell fates emerged from a common, highly proliferative and metabolically active precursor. Moreover, by tracking clonality from T cell receptor sequences, we infer that ancestors derived from the same naïve CD4 + T cell can concurrently populate both Th1 and Tfh subsets. We further found that precursor T cells were coached towards a Th1 but not a Tfh fate by monocytes/macrophages. The integrated genomic and computational approach we describe is applicable for analysis of any cellular system characterized by differentiation towards multiple fates.

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    Using single-cell RNA sequencing and a novel unsupervised computational approach, we resolve the developmental trajectories of two CD4 + T cell fates in vivo , and show that uncommitted T cells are externally influenced towards one fate by inflammatory monocytes.