6 research outputs found

    Community-curated and standardised metadata of published ancient metagenomic samples with AncientMetagenomeDir

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    Ancient DNA and RNA are valuable data sources for a wide range of disciplines. Within the field of ancient metagenomics, the number of published genetic datasets has risen dramatically in recent years, and tracking this data for reuse is particularly important for large-scale ecological and evolutionary studies of individual taxa and communities of both microbes and eukaryotes. AncientMetagenomeDir (archived at https://doi.org/10.5281/zenodo.3980833) is a collection of annotated metagenomic sample lists derived from published studies that provide basic, standardised metadata and accession numbers to allow rapid data retrieval from online repositories. These tables are community-curated and span multiple sub-disciplines to ensure adequate breadth and consensus in metadata definitions, as well as longevity of the database. Internal guidelines and automated checks facilitate compatibility with established sequence-read archives and term-ontologies, and ensure consistency and interoperability for future meta-analyses. This collection will also assist in standardising metadata reporting for future ancient metagenomic studies

    Oral abstracts 3: RA Treatment and outcomesO13. Validation of jadas in all subtypes of juvenile idiopathic arthritis in a clinical setting

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    Background: Juvenile Arthritis Disease Activity Score (JADAS) is a 4 variable composite disease activity (DA) score for JIA (including active 10, 27 or 71 joint count (AJC), physician global (PGA), parent/child global (PGE) and ESR). The validity of JADAS for all ILAR subtypes in the routine clinical setting is unknown. We investigated the construct validity of JADAS in the clinical setting in all subtypes of JIA through application to a prospective inception cohort of UK children presenting with new onset inflammatory arthritis. Methods: JADAS 10, 27 and 71 were determined for all children in the Childhood Arthritis Prospective Study (CAPS) with complete data available at baseline. Correlation of JADAS 10, 27 and 71 with single DA markers was determined for all subtypes. All correlations were calculated using Spearman's rank statistic. Results: 262/1238 visits had sufficient data for calculation of JADAS (1028 (83%) AJC, 744 (60%) PGA, 843 (68%) PGE and 459 (37%) ESR). Median age at disease onset was 6.0 years (IQR 2.6-10.4) and 64% were female. Correlation between JADAS 10, 27 and 71 approached 1 for all subtypes. Median JADAS 71 was 5.3 (IQR 2.2-10.1) with a significant difference between median JADAS scores between subtypes (p < 0.01). Correlation of JADAS 71 with each single marker of DA was moderate to high in the total cohort (see Table 1). Overall, correlation with AJC, PGA and PGE was moderate to high and correlation with ESR, limited JC, parental pain and CHAQ was low to moderate in the individual subtypes. Correlation coefficients in the extended oligoarticular, rheumatoid factor negative and enthesitis related subtypes were interpreted with caution in view of low numbers. Conclusions: This study adds to the body of evidence supporting the construct validity of JADAS. JADAS correlates with other measures of DA in all ILAR subtypes in the routine clinical setting. Given the high frequency of missing ESR data, it would be useful to assess the validity of JADAS without inclusion of the ESR. Disclosure statement: All authors have declared no conflicts of interest. Table 1Spearman's correlation between JADAS 71 and single markers DA by ILAR subtype ILAR Subtype Systemic onset JIA Persistent oligo JIA Extended oligo JIA Rheumatoid factor neg JIA Rheumatoid factor pos JIA Enthesitis related JIA Psoriatic JIA Undifferentiated JIA Unknown subtype Total cohort Number of children 23 111 12 57 7 9 19 7 17 262 AJC 0.54 0.67 0.53 0.75 0.53 0.34 0.59 0.81 0.37 0.59 PGA 0.63 0.69 0.25 0.73 0.14 0.05 0.50 0.83 0.56 0.64 PGE 0.51 0.68 0.83 0.61 0.41 0.69 0.71 0.9 0.48 0.61 ESR 0.28 0.31 0.35 0.4 0.6 0.85 0.43 0.7 0.5 0.53 Limited 71 JC 0.29 0.51 0.23 0.37 0.14 -0.12 0.4 0.81 0.45 0.41 Parental pain 0.23 0.62 0.03 0.57 0.41 0.69 0.7 0.79 0.42 0.53 Childhood health assessment questionnaire 0.25 0.57 -0.07 0.36 -0.47 0.84 0.37 0.8 0.66 0.4

    Exploring signatures of positive selection in pigmentation candidate genes in populations of East Asian ancestry

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    Abstract Background Currently, there is very limited knowledge about the genes involved in normal pigmentation variation in East Asian populations. We carried out a genome-wide scan of signatures of positive selection using the 1000 Genomes Phase I dataset, in order to identify pigmentation genes showing putative signatures of selective sweeps in East Asia. We applied a broad range of methods to detect signatures of selection including: 1) Tests designed to identify deviations of the Site Frequency Spectrum (SFS) from neutral expectations (Tajima’s D, Fay and Wu’s H and Fu and Li’s D* and F*), 2) Tests focused on the identification of high-frequency haplotypes with extended linkage disequilibrium (iHS and Rsb) and 3) Tests based on genetic differentiation between populations (LSBL). Based on the results obtained from a genome wide analysis of 25 kb windows, we constructed an empirical distribution for each statistic across all windows, and identified pigmentation genes that are outliers in the distribution. Results Our tests identified twenty genes that are relevant for pigmentation biology. Of these, eight genes (ATRN, EDAR, KLHL7, MITF, OCA2, TH, TMEM33 and TRPM1,) were extreme outliers (top 0.1% of the empirical distribution) for at least one statistic, and twelve genes (ADAM17, BNC2, CTSD, DCT, EGFR, LYST, MC1R, MLPH, OPRM1, PDIA6, PMEL (SILV) and TYRP1) were in the top 1% of the empirical distribution for at least one statistic. Additionally, eight of these genes (BNC2, EGFR, LYST, MC1R, OCA2, OPRM1, PMEL (SILV) and TYRP1) have been associated with pigmentary traits in association studies. Conclusions We identified a number of putative pigmentation genes showing extremely unusual patterns of genetic variation in East Asia. Most of these genes are outliers for different tests and/or different populations, and have already been described in previous scans for positive selection, providing strong support to the hypothesis that recent selective sweeps left a signature in these regions. However, it will be necessary to carry out association and functional studies to demonstrate the implication of these genes in normal pigmentation variation

    Examining pathogen DNA recovery across the remains of a 14th century Italian friar (Blessed Sante) infected with Brucella melitensis

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    Objective To investigate variation in ancient DNA recovery of Brucella melitensis, the causative agent of brucellosis, from multiple tissues belonging to one individual Materials 14 samples were analyzed from the mummified remains of the Blessed Sante, a 14 th century Franciscan friar from central Italy, with macroscopic diagnosis of probable brucellosis. Methods Shotgun sequencing data from was examined to determine the presence of Brucella DNA. Results Three of the 14 samples contained authentic ancient DNA, identified as belonging to B. melitensis. A genome (23.81X depth coverage, 0.98 breadth coverage) was recovered from a kidney stone. Nine of the samples contained reads classified as B. melitensis (7−169), but for many the data quality was insufficient to withstand our identification and authentication criteria. Conclusions We identified significant variation in the preservation and abundance of B. melitensis DNA present across multiple tissues, with calcified nodules yielding the highest number of authenticated reads. This shows how greatly sample selection can impact pathogen identification. Significance Our results demonstrate variation in the preservation and recovery of pathogen DNA across tissues. This study highlights the importance of sample selection in the reconstruction of infectious disease burden and highlights the importance of a holistic approach to identifying disease. Limitations Study focuses on pathogen recovery in a single individual. Suggestions for further research Further analysis of how sampling impacts aDNA recovery will improve pathogen aDNA recovery and advance our understanding of disease in past people
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