190 research outputs found

    Cross-tissue immune cell analysis reveals tissue-specific adaptations and clonal architecture in humans

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    Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. Here, we surveyed the immune compartment of 15 tissues of six deceased adult donors by single-cell RNA sequencing and paired VDJ sequencing. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of 45 finely phenotyped immune cell types and states, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. In summary, our multi-tissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis and antigen receptor sequencing. One Sentence Summary We provide an immune cell atlas, including antigen receptor repertoire profiling, across lymphoid and non-lymphoid human tissues

    Analysis of the association between spawning time QTL markers and the biannual spawning behavior in rainbow trout (Oncorhynchus mykiss)

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    The rainbow trout is a salmonid fish that occasionally exhibits broodstocks with biannual spawning behavior, a phenomenon known as a double annual reproductive cycle (DARC). Spawning time quantitative trait loci (SPT-QTLs) affect the time of the year that female rainbow trout spawn and may influence expression of the DARC trait. In this study, microsatellite markers linked and unlinked to SPT-QTLs were genotyped to investigate the underlying genetics of this trait. SPT-QTLs influenced the DARC trait since in two case-control comparisons three linked markers (OmyFGT12TUF, One3ASC and One19ASC) had significant levels of allelic frequency differentiation and marker-character association. Furthermore, alleles of One3ASC and One19ASC had significantly higher frequencies in populations that carried the DARC trait

    Herd-level risk factors associated with Leptospira Hardjo seroprevalence in Beef/Suckler herds in the Republic of Ireland

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    <p>Abstract</p> <p>Background</p> <p>The aim of the present study was to investigate risk factors for herd seropositivity to <it>Leptospira </it>Hardjo in Irish suckler herds. Herds were considered eligible for the study if they were unvaccinated and contained ≥ 9 breeding animals of beef breed which were ≥ 12 months of age. The country was divided into six regions using county boundaries. Herd and individual animal prevalence data were available from the results of a concurrent seroprevalence study. Herds were classified as either "Free from Infection" or "Infected" based on a minimum expected 40% within-herd prevalence.</p> <p>Questionnaires were posted to 320 farmers chosen randomly from 6 regions, encompassing 25 counties, of the Republic of Ireland. The questionnaire was designed to obtain information about vaccination; reproductive disease; breeding herd details; the presence of recognized risk factors from previous studies; and husbandry on each farm. Data collected from 128 eligible herds were subjected to statistical analysis.</p> <p>Results</p> <p>Following the use of Pearson's Chi-Square Test, those variables associated with a herd being "infected" with a significance level of P < 0.2 were considered as candidates for multivariable logistic regression modelling. Breeding herd size was found to be a statistically significant risk factor after multivariable logistic regression. The odds of a herd being positive for leptospiral infection were 5.47 times higher (P = 0.032) in herds with 14 to 23 breeding animals compared with herds with ≤ 13 breeding animals, adjusting for Region, and 7.08 times higher (P = 0.033) in herds with 32.6 to 142 breeding animals.</p> <p>Conclusions</p> <p>Breeding herd size was identified as a significant risk factor for leptospiral infection in Irish suckler herds, which was similar to findings of previous studies of leptospirosis in dairy herds.</p

    Association mapping of stigma and spikelet characteristics in rice (Oryza sativa L.)

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    Stigma and spikelet characteristics play an essential role in hybrid seed production. A mini-core of 90 accessions developed from USDA rice core collection was phenotyped in field grown for nine traits of stigma and spikelet and genotyped with 109 DNA markers, 108 SSRs plus an indel. Three major clusters were built upon Rogers’ genetic distance, indicative of indicas, and temperate and tropical japonicas. A mixed linear model combining PC-matrix and K-matrix was adapted for mapping marker-trait associations. Resulting associations were adjusted using false discovery rate technique. We identified 34 marker-trait associations involving 22 SSR markers for eight traits. Four markers were associated with single stigma exsertion (SStgE), six with dual exsertion (DStgE) and five with total exsertion. RM5_Chr1 played major role indicative of high regression with not only DStgE but also SStgE. Four markers were associated with spikelet length, three with width and seven with L/W ratio. Numerous markers were co-associated with multiple traits that were phenotypically correlated, i.e. RM12521_Chr2 associated with all three correlated spikelet traits. The co-association should improve breeding efficiency because single marker could be used to assist breeding for multiple traits. Indica entry 1032 (cultivar 50638) and japonica entry 671 (cultivar Linia 84 Icar) with 80.65 and 75.17% of TStgE, respectively are recommended to breeder for improving stigma exsertion

    Cells of the human intestinal tract mapped across space and time

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    The cellular landscape of the human intestinal tract is dynamic throughout life, developing in utero and changing in response to functional requirements and environmental exposures. Here, to comprehensively map cell lineages, we use single-cell RNA sequencing and antigen receptor analysis of almost half a million cells from up to 5 anatomical regions in the developing and up to 11 distinct anatomical regions in the healthy paediatric and adult human gut. This reveals the existence of transcriptionally distinct BEST4 epithelial cells throughout the human intestinal tract. Furthermore, we implicate IgG sensing as a function of intestinal tuft cells. We describe neural cell populations in the developing enteric nervous system, and predict cell-type-specific expression of genes associated with Hirschsprung’s disease. Finally, using a systems approach, we identify key cell players that drive the formation of secondary lymphoid tissue in early human development. We show that these programs are adopted in inflammatory bowel disease to recruit and retain immune cells at the site of inflammation. This catalogue of intestinal cells will provide new insights into cellular programs in development, homeostasis and disease

    Calcineurin Inhibition at the Clinical Phase of Prion Disease Reduces Neurodegeneration, Improves Behavioral Alterations and Increases Animal Survival

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    Prion diseases are fatal neurodegenerative disorders characterized by a long pre-symptomatic phase followed by rapid and progressive clinical phase. Although rare in humans, the unconventional infectious nature of the disease raises the potential for an epidemic. Unfortunately, no treatment is currently available. The hallmark event in prion diseases is the accumulation of a misfolded and infectious form of the prion protein (PrPSc). Previous reports have shown that PrPSc induces endoplasmic reticulum stress and changes in calcium homeostasis in the brain of affected individuals. In this study we show that the calcium-dependent phosphatase Calcineurin (CaN) is hyperactivated both in vitro and in vivo as a result of PrPSc formation. CaN activation mediates prion-induced neurodegeneration, suggesting that inhibition of this phosphatase could be a target for therapy. To test this hypothesis, prion infected wild type mice were treated intra-peritoneally with the CaN inhibitor FK506 at the clinical phase of the disease. Treated animals exhibited reduced severity of the clinical abnormalities and increased survival time compared to vehicle treated controls. Treatment also led to a significant increase in the brain levels of the CaN downstream targets pCREB and pBAD, which paralleled the decrease of CaN activity. Importantly, we observed a lower degree of neurodegeneration in animals treated with the drug as revealed by a higher number of neurons and a lower quantity of degenerating nerve cells. These changes were not dependent on PrPSc formation, since the protein accumulated in the brain to the same levels as in the untreated mice. Our findings contribute to an understanding of the mechanism of neurodegeneration in prion diseases and more importantly may provide a novel strategy for therapy that is beneficial at the clinical phase of the disease

    Association mapping for yield and grain quality traits in rice (Oryza sativa L.)

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    Association analysis was applied to a panel of accessions of Embrapa Rice Core Collection (ERiCC) with 86 SSR and field data from two experiments. A clear subdivision between lowland and upland accessions was apparent, thereby indicating the presence of population structure. Thirty-two accessions with admixed ancestry were identified through structure analysis, these being discarded from association analysis, thus leaving 210 accessions subdivided into two panels. The association of yield and grain-quality traits with SSR was undertaken with a mixed linear model, with markers and subpopulation as fixed factors, and kinship matrix as a random factor. Eight markers from the two appraised panels showed significant association with four different traits, although only one (RM190) maintained the marker-trait association across years and cultivation. The significant association detected between amylose content and RM190 was in agreement with previous QTL analyses in the literature. Herein, the feasibility of undertaking association analysis in conjunction with germplasm characterization was demonstrated, even when considering low marker density. The high linkage disequilibrium expected in rice lines and cultivars facilitates the detection of marker-trait associations for implementing marker assisted selection, and the mining of alleles related to important traits in germplasm

    Is Replication the Gold Standard for Validating Genome-Wide Association Findings?

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    With the advent of genome-wide association (GWA) studies, researchers are hoping that reliable genetic association of common human complex diseases/traits can be detected. Currently, there is an increasing enthusiasm about GWA and a number of GWA studies have been published. In the field a common practice is that replication should be used as the gold standard to validate an association finding. In this article, based on empirical and theoretical data, we emphasize that replication of GWA findings can be quite difficult, and should not always be expected, even when true variants are identified. The probability of replication becomes smaller with the increasing number of independent GWA studies if the power of individual replication studies is less than 100% (which is usually the case), and even a finding that is replicated may not necessarily be true. We argue that the field may have unreasonably high expectations on success of replication. We also wish to raise the question whether it is sufficient or necessary to treat replication as the ultimate and gold standard for defining true variants. We finally discuss the usefulness of integrating evidence from multiple levels/sources such as genetic epidemiological studies (at the DNA level), gene expression studies (at the RNA level), proteomics (at the protein level), and follow-up molecular and cellular studies for eventual validation and illumination of the functional relevance of the genes uncovered

    High-Resolution Mapping of Gene Expression Using Association in an Outbred Mouse Stock

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    Quantitative trait locus (QTL) analysis is a powerful tool for mapping genes for complex traits in mice, but its utility is limited by poor resolution. A promising mapping approach is association analysis in outbred stocks or different inbred strains. As a proof of concept for the association approach, we applied whole-genome association analysis to hepatic gene expression traits in an outbred mouse population, the MF1 stock, and replicated expression QTL (eQTL) identified in previous studies of F2 intercross mice. We found that the mapping resolution of these eQTL was significantly greater in the outbred population. Through an example, we also showed how this precise mapping can be used to resolve previously identified loci (in intercross studies), which affect many different transcript levels (known as eQTL “hotspots”), into distinct regions. Our results also highlight the importance of correcting for population structure in whole-genome association studies in the outbred stock
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