School of Mathematics and Statistics - Research Publications

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    SSNIP-seq: A simple and rapid method for isolation of single-sperm nucleic acid for high-throughput sequencing
    Novakovic, S ; Tsui, V ; Semple, T ; Martelotto, L ; McCarthy, DJ ; Crismani, W ; Drevet, JR (PUBLIC LIBRARY SCIENCE, 2022-09-29)
    We developed a simple and reliable method for the isolation of haploid nuclei from fresh and frozen testes. The described protocol uses readily available reagents in combination with flow cytometry to separate haploid and diploid nuclei. The protocol can be completed within 1 hour and the resulting individual haploid nuclei have intact morphology. The isolated nuclei are suitable for library preparation for high-throughput DNA and RNA sequencing using bulk or single nuclei. The protocol was optimised with mouse testes and we anticipate that it can be applied for the isolation of mature sperm from other mammals including humans.
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    sgcocaller and comapr: personalised haplotype assembly and comparative crossover map analysis using single-gamete sequencing data
    Lyu, R ; Tsui, V ; Crismani, W ; Liu, R ; Shim, H ; McCarthy, DJ (OXFORD UNIV PRESS, 2022-11-11)
    Profiling gametes of an individual enables the construction of personalised haplotypes and meiotic crossover landscapes, now achievable at larger scale than ever through the availability of high-throughput single-cell sequencing technologies. However, high-throughput single-gamete data commonly have low depth of coverage per gamete, which challenges existing gamete-based haplotype phasing methods. In addition, haplotyping a large number of single gametes from high-throughput single-cell DNA sequencing data and constructing meiotic crossover profiles using existing methods requires intensive processing. Here, we introduce efficient software tools for the essential tasks of generating personalised haplotypes and calling crossovers in gametes from single-gamete DNA sequencing data (sgcocaller), and constructing, visualising, and comparing individualised crossover landscapes from single gametes (comapr). With additional data pre-possessing, the tools can also be applied to bulk-sequenced samples. We demonstrate that sgcocaller is able to generate impeccable phasing results for high-coverage datasets, on which it is more accurate and stable than existing methods, and also performs well on low-coverage single-gamete sequencing datasets for which current methods fail. Our tools achieve highly accurate results with user-friendly installation, comprehensive documentation, efficient computation times and minimal memory usage.
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    Personalized genome structure via single gamete sequencing
    Lyu, R ; Tsui, V ; McCarthy, DJ ; Crismani, W (BMC, 2021-04-19)
    Genetic maps have been fundamental to building our understanding of disease genetics and evolutionary processes. The gametes of an individual contain all of the information required to perform a de novo chromosome-scale assembly of an individual's genome, which historically has been performed with populations and pedigrees. Here, we discuss how single-cell gamete sequencing offers the potential to merge the advantages of short-read sequencing with the ability to build personalized genetic maps and open up an entirely new space in personalized genetics.