10,306 research outputs found

    Discovering cellular mitochondrial heteroplasmy heterogeneity with single cell RNA and ATAC sequencing

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    Next generation sequencing technologies have revolutionised the study of biological systems by enabling the examination of a broad range of tissues. Its application to single cell genomics has generated a dynamic and evolving field with a vast amount of research highlighting heterogeneity in transcriptional, genetic and epigenomic state between cells. However, compared to these aspects of cellular heterogeneity, relatively little has been gleaned from the single cell datasets regarding cellular mitochondrial heterogeneity. Single cell sequencing techniques can provide coverage of the mitochondrial genome which allows researchers to probe heteroplasmies 0at the level of the single cell, and observe interactions with cellular function. In this review we give an overview of two popular single cell modalities — single cell RNA sequencing and single cell ATAC sequencing — whose throughput and widespread usage offers researchers the chance to probe heteroplasmy combined with cell state in detailed resolution across thousands of cells. After summarising these technologies in the context of mitochondrial research, we give an overview of recent methods which have used these approaches for discovering mitochondrial heterogeneity. We conclude by highlighting current limitations of these approaches and open problems for future consideration

    Immunoglobulin variable-region gene mutational lineage tree analysis: application to autoimmune diseases

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    Lineage trees have frequently been drawn to illustrate diversification, via somatic hypermutation (SHM), of immunoglobulin variable-region (IGV) genes. In order to extract more information from IGV sequences, we developed a novel mathematical method for analyzing the graphical properties of IgV gene lineage trees, allowing quantification of the differences between the dynamics of SHM and antigen-driven selection in different lymphoid tissues, species, and disease situations. Here, we investigated trees generated from published IGV sequence data from B cell clones participating in autoimmune responses in patients with Myasthenia Gravis (MG), Rheumatoid Arthritis (RA), and Sjögren's Syndrome (SS). At present, as no standards exist for cell sampling and sequence extraction methods, data obtained by different research groups from two studies of the same disease often vary considerably. Nevertheless, based on comparisons of data groups within individual studies, we show here that lineage trees from different individual patients are often similar and can be grouped together, as can trees from two different tissues in the same patient, and even from IgG- and IgA-expressing B cell clones. Additionally, lineage trees from most studies reflect the chronic character of autoimmune diseases

    A new multi locus variable number of tandem repeat analysis scheme for epidemiological surveillance of Xanthomonas vasicola pv. musacearum, the plant pathogen causing bacterial wilt on banana and enset

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    Xanthomonas vasicola pv. musacearum (Xvm) which causes Xanthomonas wilt (XW) on banana (Musa accuminata x balbisiana) and enset (Ensete ventricosum), is closely related to the species Xanthomonas vasicola that contains the pathovars vasculorum (Xvv) and holcicola (Xvh), respectively pathogenic to sugarcane and sorghum. Xvm is considered a monomorphic bacterium whose intra-pathovar diversity remains poorly understood. With the sudden emergence of Xvm within east and central Africa coupled with the unknown origin of one of the two sublineages suggested for Xvm, attention has shifted to adapting technologies that focus on identifying the origin and distribution of the genetic diversity within this pathogen. Although microbiological and conventional molecular diagnostics have been useful in pathogen identification. Recent advances have ushered in an era of genomic epidemiology that aids in characterizing monomorphic pathogens. To unravel the origin and pathways of the recent emergence of XW in Eastern and Central Africa, there was a need for a genotyping tool adapted for molecular epidemiology. Multi-Locus Variable Number of Tandem Repeat Analysis (MLVA) is able to resolve the evolutionary patterns and invasion routes of a pathogen. In this study, we identified microsatellite loci from nine published Xvm genome sequences. Of the 36 detected microsatellite loci, 21 were selected for primer design and 19 determined to be highly typeable, specific, reproducible and polymorphic with two- to four- alleles per locus on a sub-collection. The 19 markers were multiplexed and applied to genotype 335 Xvm strains isolated from seven countries over several years. The microsatellite markers grouped the Xvm collection into three clusters; with two similar to the SNP-based sublineages 1 and 2 and a new cluster 3, revealing an unknown diversity in Ethiopia. Five of the 19 markers had alleles present in both Xvm and Xanthomonas vasicola pathovars holcicola and vasculorum, supporting the phylogenetic closeliness of these three pathovars. Thank to the public availability of the haplotypes on the MLVABank database, this highly reliable and polymorphic genotyping tool can be further used in a transnational surveillance network to monitor the spread and evolution of XW throughout Africa.. It will inform and guide management of Xvm both in banana-based and enset-based cropping systems. Due to the suitability of MLVA-19 markers for population genetic analyses, this genotyping tool will also be used in future microevolution studies

    How research can support efforts to control avian flu in developing countries: first steps towards a research action plan

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    Report of an international consultation — The Research Community’s Response to Avian Influenza, with Special Reference to the Needs of Developing Countries, held 14-16 June 2006 in Nairobi, Kenya — organised by the International Food Policy Research Institute (IFPRI) and the International Livestock Research Institute (ILRI)
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