The Experts below are selected from a list of 30 Experts worldwide ranked by ideXlab platform
Thierry De Meeus - One of the best experts on this subject based on the ideXlab platform.
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null allele Allelic Dropouts or rare sex detection in clonal organisms simulations and application to real data sets of pathogenic microbes
Parasites & Vectors, 2014Co-Authors: Modou Sere, Jacques Kabore, Vincent Jamonneau, Adrien Marie Gaston Belem, Francisco J Ayala, Thierry De MeeusAbstract:Background Pathogens and their vectors are organisms whose ecology is often only accessible through population genetics tools based on spatio-temporal variability of molecular markers. However, molecular tools may present technical difficulties due to the masking of some alleles (Allelic Dropouts and/or null alleles), which tends to bias the estimation of heterozygosity and thus the inferences concerning the breeding system of the organism under study. This is especially critical in clonal organisms in which deviation from panmixia, as measured by Wright’s FIS, can, in principle, be used to infer both the extent of clonality and structure in a given population. In particular, null alleles and Allelic Dropouts are locus specific and likely produce high variance of Wright’s FIS across loci, as rare sex is expected to do. In this paper we propose a tool enabling to discriminate between consequences of these technical problems and those of rare sex.
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null allele Allelic Dropouts or rare sex detection in clonal organisms simulations and application to real data sets of pathogenic microbes
Parasites & Vectors, 2014Co-Authors: Modou Sere, Jacques Kabore, Vincent Jamonneau, Adrien Marie Gaston Belem, Francisco J Ayala, Thierry De MeeusAbstract:Pathogens and their vectors are organisms whose ecology is often only accessible through population genetics tools based on spatio-temporal variability of molecular markers. However, molecular tools may present technical difficulties due to the masking of some alleles (Allelic Dropouts and/or null alleles), which tends to bias the estimation of heterozygosity and thus the inferences concerning the breeding system of the organism under study. This is especially critical in clonal organisms in which deviation from panmixia, as measured by Wright’s FIS, can, in principle, be used to infer both the extent of clonality and structure in a given population. In particular, null alleles and Allelic Dropouts are locus specific and likely produce high variance of Wright’s FIS across loci, as rare sex is expected to do. In this paper we propose a tool enabling to discriminate between consequences of these technical problems and those of rare sex. We have performed various simulations of clonal and partially clonal populations. We introduce Allelic Dropouts and null alleles in clonal data sets and compare the results with those that exhibit increasing rates of sexual recombination. We use the narrow relationship that links Wright’s FIS to genetic diversity in purely clonal populations as assessment criterion, since this relationship disappears faster with sexual recombination than with amplification problems of certain alleles. We show that the relevance of our criterion for detecting poorly amplified alleles depends partly on the population structure, the level of homoplasy and/or mutation rate. However, the interpretation of data becomes difficult when the number of poorly amplified alleles is above 50%. The application of this method to reinterpret published data sets of pathogenic clonal microbes (yeast and trypanosomes) confirms its usefulness and allows refining previous estimates concerning important pathogenic agents. Our criterion of superimposing between the FIS expected under clonality and the observed FIS, is effective when amplification difficulties occur in low to moderate frequencies (20-30%).
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a protocol to improve genotyping of problematic microsatellite loci of trypanosoma brucei gambiense from body fluids
Infection Genetics and Evolution, 2013Co-Authors: Jacques Kabore, Adrien Marie Gaston Belem, Thierry De Meeus, Annette Macleod, Hamidou Ilboudo, Paul Capewell, Mamadou Camara, Bruno Bucheton, Vincent JamonneauAbstract:Microsatellite genotyping of Trypanosoma brucei gambiense, the causative agent of human African trypanosomiasis or sleeping sickness, and population genetics tools, are useful for inferring population parameters such as population size and dispersal. Amplifying parasite DNA directly from body fluids (i.e., blood, lymph or cerebrospinal fluid) allows avoiding costly and tedious isolation phases. It is however associated to increased frequencies of amplification failures (Allelic Dropouts and/or null alleles) at some loci. In this paper, we present a study focused on three T. brucei gambiense microsatellite loci suspected to present amplification problems when amplified from body fluids sampled in Guinean sleeping sickness foci. We checked for the real nature of blank and apparent homozygous genotypes of parasite DNA directly amplified from body fluids and tested the effect of three different DNA quantities of trypanosomes. Our results show that some initially blank and homozygous genotypes happen to be actual heterozygous genotypes. In Guinea, lymph from the cervical nymph nodes, known to contain the highest concentrations of parasites, appeared to provide the best amplification results. Simply repeating the PCR may be enough to retrieve the correct genotype, but we also show that increasing initial DNA content provides better results while undertaking first amplification. We finally propose an optimal protocol for amplifying trypanosome’s DNA directly from body fluids that should be adapted to local characteristics and/or constraints.
Anni Aggerholm - One of the best experts on this subject based on the ideXlab platform.
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systematic evaluation of signal to noise ratio in variant detection from single cell genome multiple displacement amplification and exome sequencing
BMC Genomics, 2018Co-Authors: Anita Tranberg Simonsen, Marcus Celik Hansen, Eigil Kjeldsen, Peter L Moller, Johnny Juhl Hindkjaer, Peter Hokland, Anni AggerholmAbstract:The current literature on single cell genomic analyses on the DNA level is conflicting regarding requirements for cell quality, amplification success rates, Allelic Dropouts and resolution, lacking a systematic comparison of multiple cell input down to the single cell. We hypothesized that such a correlation assay would provide an approach to address the latter issues, utilizing the leukemic cell line OCI-AML3 with a known set of genetic aberrations. By analyzing single and multiple cell replicates (2 to 50 cells) purified by micromanipulation and serial dilution we stringently assessed the signal-to-noise ratio (SNR) from single as well as a discrete number of cells based on a multiple displacement amplification method, with whole exome sequencing as signal readout. In this setting, known OCI-AML3 mutations as well as large copy number alterations could be identified, adding to the current knowledge of cytogenetic status. The presence of DNMT3A R882C, NPM1 W288 fs and NRAS Q61L was consistent, in spite of uneven Allelic read depths. In contrast, at the level of single cells, we observed that one-third to half of all variants were not reproduced in the replicate sample, and this Allelic mismatch displayed an exponential function of cell input. Large signature duplications were discernible from 5 cells, whereas deletions were visible down to the single cell. Thus, even under highly optimized conditions, single cell whole genome amplification and interpretation must be taken with considerable caution, given that Allelic change is frequent and displays low SNR. Allelic noise is rapidly alleviated with increased cell input, and the SNR is doubled from 2 to 50 cells. In conclusion, we demonstrate noisy allele distributions, when analyzing genetic aberrations within single cells relative to multiple cells. Based on the presented data we recommend that single cell analyses should include replicate cell dilution assays for a given setup for relative assessment of procedure-specific SNR to ensure that the resolution supports the specific hypotheses.
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Systematic evaluation of signal-to-noise ratio in variant detection from single cell genome multiple displacement amplification and exome sequencing
BMC, 2018Co-Authors: Anita Tranberg Simonsen, Marcus Celik Hansen, Eigil Kjeldsen, Peter L Moller, Johnny Juhl Hindkjaer, Peter Hokland, Anni AggerholmAbstract:Abstract Background The current literature on single cell genomic analyses on the DNA level is conflicting regarding requirements for cell quality, amplification success rates, Allelic Dropouts and resolution, lacking a systematic comparison of multiple cell input down to the single cell. We hypothesized that such a correlation assay would provide an approach to address the latter issues, utilizing the leukemic cell line OCI-AML3 with a known set of genetic aberrations. Results By analyzing single and multiple cell replicates (2 to 50 cells) purified by micromanipulation and serial dilution we stringently assessed the signal-to-noise ratio (SNR) from single as well as a discrete number of cells based on a multiple displacement amplification method, with whole exome sequencing as signal readout. In this setting, known OCI-AML3 mutations as well as large copy number alterations could be identified, adding to the current knowledge of cytogenetic status. The presence of DNMT3A R882C, NPM1 W288 fs and NRAS Q61L was consistent, in spite of uneven Allelic read depths. In contrast, at the level of single cells, we observed that one-third to half of all variants were not reproduced in the replicate sample, and this Allelic mismatch displayed an exponential function of cell input. Large signature duplications were discernible from 5 cells, whereas deletions were visible down to the single cell. Thus, even under highly optimized conditions, single cell whole genome amplification and interpretation must be taken with considerable caution, given that Allelic change is frequent and displays low SNR. Allelic noise is rapidly alleviated with increased cell input, and the SNR is doubled from 2 to 50 cells. Conclusions In conclusion, we demonstrate noisy allele distributions, when analyzing genetic aberrations within single cells relative to multiple cells. Based on the presented data we recommend that single cell analyses should include replicate cell dilution assays for a given setup for relative assessment of procedure-specific SNR to ensure that the resolution supports the specific hypotheses
Vincent Jamonneau - One of the best experts on this subject based on the ideXlab platform.
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null allele Allelic Dropouts or rare sex detection in clonal organisms simulations and application to real data sets of pathogenic microbes
Parasites & Vectors, 2014Co-Authors: Modou Sere, Jacques Kabore, Vincent Jamonneau, Adrien Marie Gaston Belem, Francisco J Ayala, Thierry De MeeusAbstract:Background Pathogens and their vectors are organisms whose ecology is often only accessible through population genetics tools based on spatio-temporal variability of molecular markers. However, molecular tools may present technical difficulties due to the masking of some alleles (Allelic Dropouts and/or null alleles), which tends to bias the estimation of heterozygosity and thus the inferences concerning the breeding system of the organism under study. This is especially critical in clonal organisms in which deviation from panmixia, as measured by Wright’s FIS, can, in principle, be used to infer both the extent of clonality and structure in a given population. In particular, null alleles and Allelic Dropouts are locus specific and likely produce high variance of Wright’s FIS across loci, as rare sex is expected to do. In this paper we propose a tool enabling to discriminate between consequences of these technical problems and those of rare sex.
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null allele Allelic Dropouts or rare sex detection in clonal organisms simulations and application to real data sets of pathogenic microbes
Parasites & Vectors, 2014Co-Authors: Modou Sere, Jacques Kabore, Vincent Jamonneau, Adrien Marie Gaston Belem, Francisco J Ayala, Thierry De MeeusAbstract:Pathogens and their vectors are organisms whose ecology is often only accessible through population genetics tools based on spatio-temporal variability of molecular markers. However, molecular tools may present technical difficulties due to the masking of some alleles (Allelic Dropouts and/or null alleles), which tends to bias the estimation of heterozygosity and thus the inferences concerning the breeding system of the organism under study. This is especially critical in clonal organisms in which deviation from panmixia, as measured by Wright’s FIS, can, in principle, be used to infer both the extent of clonality and structure in a given population. In particular, null alleles and Allelic Dropouts are locus specific and likely produce high variance of Wright’s FIS across loci, as rare sex is expected to do. In this paper we propose a tool enabling to discriminate between consequences of these technical problems and those of rare sex. We have performed various simulations of clonal and partially clonal populations. We introduce Allelic Dropouts and null alleles in clonal data sets and compare the results with those that exhibit increasing rates of sexual recombination. We use the narrow relationship that links Wright’s FIS to genetic diversity in purely clonal populations as assessment criterion, since this relationship disappears faster with sexual recombination than with amplification problems of certain alleles. We show that the relevance of our criterion for detecting poorly amplified alleles depends partly on the population structure, the level of homoplasy and/or mutation rate. However, the interpretation of data becomes difficult when the number of poorly amplified alleles is above 50%. The application of this method to reinterpret published data sets of pathogenic clonal microbes (yeast and trypanosomes) confirms its usefulness and allows refining previous estimates concerning important pathogenic agents. Our criterion of superimposing between the FIS expected under clonality and the observed FIS, is effective when amplification difficulties occur in low to moderate frequencies (20-30%).
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a protocol to improve genotyping of problematic microsatellite loci of trypanosoma brucei gambiense from body fluids
Infection Genetics and Evolution, 2013Co-Authors: Jacques Kabore, Adrien Marie Gaston Belem, Thierry De Meeus, Annette Macleod, Hamidou Ilboudo, Paul Capewell, Mamadou Camara, Bruno Bucheton, Vincent JamonneauAbstract:Microsatellite genotyping of Trypanosoma brucei gambiense, the causative agent of human African trypanosomiasis or sleeping sickness, and population genetics tools, are useful for inferring population parameters such as population size and dispersal. Amplifying parasite DNA directly from body fluids (i.e., blood, lymph or cerebrospinal fluid) allows avoiding costly and tedious isolation phases. It is however associated to increased frequencies of amplification failures (Allelic Dropouts and/or null alleles) at some loci. In this paper, we present a study focused on three T. brucei gambiense microsatellite loci suspected to present amplification problems when amplified from body fluids sampled in Guinean sleeping sickness foci. We checked for the real nature of blank and apparent homozygous genotypes of parasite DNA directly amplified from body fluids and tested the effect of three different DNA quantities of trypanosomes. Our results show that some initially blank and homozygous genotypes happen to be actual heterozygous genotypes. In Guinea, lymph from the cervical nymph nodes, known to contain the highest concentrations of parasites, appeared to provide the best amplification results. Simply repeating the PCR may be enough to retrieve the correct genotype, but we also show that increasing initial DNA content provides better results while undertaking first amplification. We finally propose an optimal protocol for amplifying trypanosome’s DNA directly from body fluids that should be adapted to local characteristics and/or constraints.
Modou Sere - One of the best experts on this subject based on the ideXlab platform.
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null allele Allelic Dropouts or rare sex detection in clonal organisms simulations and application to real data sets of pathogenic microbes
Parasites & Vectors, 2014Co-Authors: Modou Sere, Jacques Kabore, Vincent Jamonneau, Adrien Marie Gaston Belem, Francisco J Ayala, Thierry De MeeusAbstract:Background Pathogens and their vectors are organisms whose ecology is often only accessible through population genetics tools based on spatio-temporal variability of molecular markers. However, molecular tools may present technical difficulties due to the masking of some alleles (Allelic Dropouts and/or null alleles), which tends to bias the estimation of heterozygosity and thus the inferences concerning the breeding system of the organism under study. This is especially critical in clonal organisms in which deviation from panmixia, as measured by Wright’s FIS, can, in principle, be used to infer both the extent of clonality and structure in a given population. In particular, null alleles and Allelic Dropouts are locus specific and likely produce high variance of Wright’s FIS across loci, as rare sex is expected to do. In this paper we propose a tool enabling to discriminate between consequences of these technical problems and those of rare sex.
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null allele Allelic Dropouts or rare sex detection in clonal organisms simulations and application to real data sets of pathogenic microbes
Parasites & Vectors, 2014Co-Authors: Modou Sere, Jacques Kabore, Vincent Jamonneau, Adrien Marie Gaston Belem, Francisco J Ayala, Thierry De MeeusAbstract:Pathogens and their vectors are organisms whose ecology is often only accessible through population genetics tools based on spatio-temporal variability of molecular markers. However, molecular tools may present technical difficulties due to the masking of some alleles (Allelic Dropouts and/or null alleles), which tends to bias the estimation of heterozygosity and thus the inferences concerning the breeding system of the organism under study. This is especially critical in clonal organisms in which deviation from panmixia, as measured by Wright’s FIS, can, in principle, be used to infer both the extent of clonality and structure in a given population. In particular, null alleles and Allelic Dropouts are locus specific and likely produce high variance of Wright’s FIS across loci, as rare sex is expected to do. In this paper we propose a tool enabling to discriminate between consequences of these technical problems and those of rare sex. We have performed various simulations of clonal and partially clonal populations. We introduce Allelic Dropouts and null alleles in clonal data sets and compare the results with those that exhibit increasing rates of sexual recombination. We use the narrow relationship that links Wright’s FIS to genetic diversity in purely clonal populations as assessment criterion, since this relationship disappears faster with sexual recombination than with amplification problems of certain alleles. We show that the relevance of our criterion for detecting poorly amplified alleles depends partly on the population structure, the level of homoplasy and/or mutation rate. However, the interpretation of data becomes difficult when the number of poorly amplified alleles is above 50%. The application of this method to reinterpret published data sets of pathogenic clonal microbes (yeast and trypanosomes) confirms its usefulness and allows refining previous estimates concerning important pathogenic agents. Our criterion of superimposing between the FIS expected under clonality and the observed FIS, is effective when amplification difficulties occur in low to moderate frequencies (20-30%).
Jacques Kabore - One of the best experts on this subject based on the ideXlab platform.
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null allele Allelic Dropouts or rare sex detection in clonal organisms simulations and application to real data sets of pathogenic microbes
Parasites & Vectors, 2014Co-Authors: Modou Sere, Jacques Kabore, Vincent Jamonneau, Adrien Marie Gaston Belem, Francisco J Ayala, Thierry De MeeusAbstract:Background Pathogens and their vectors are organisms whose ecology is often only accessible through population genetics tools based on spatio-temporal variability of molecular markers. However, molecular tools may present technical difficulties due to the masking of some alleles (Allelic Dropouts and/or null alleles), which tends to bias the estimation of heterozygosity and thus the inferences concerning the breeding system of the organism under study. This is especially critical in clonal organisms in which deviation from panmixia, as measured by Wright’s FIS, can, in principle, be used to infer both the extent of clonality and structure in a given population. In particular, null alleles and Allelic Dropouts are locus specific and likely produce high variance of Wright’s FIS across loci, as rare sex is expected to do. In this paper we propose a tool enabling to discriminate between consequences of these technical problems and those of rare sex.
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null allele Allelic Dropouts or rare sex detection in clonal organisms simulations and application to real data sets of pathogenic microbes
Parasites & Vectors, 2014Co-Authors: Modou Sere, Jacques Kabore, Vincent Jamonneau, Adrien Marie Gaston Belem, Francisco J Ayala, Thierry De MeeusAbstract:Pathogens and their vectors are organisms whose ecology is often only accessible through population genetics tools based on spatio-temporal variability of molecular markers. However, molecular tools may present technical difficulties due to the masking of some alleles (Allelic Dropouts and/or null alleles), which tends to bias the estimation of heterozygosity and thus the inferences concerning the breeding system of the organism under study. This is especially critical in clonal organisms in which deviation from panmixia, as measured by Wright’s FIS, can, in principle, be used to infer both the extent of clonality and structure in a given population. In particular, null alleles and Allelic Dropouts are locus specific and likely produce high variance of Wright’s FIS across loci, as rare sex is expected to do. In this paper we propose a tool enabling to discriminate between consequences of these technical problems and those of rare sex. We have performed various simulations of clonal and partially clonal populations. We introduce Allelic Dropouts and null alleles in clonal data sets and compare the results with those that exhibit increasing rates of sexual recombination. We use the narrow relationship that links Wright’s FIS to genetic diversity in purely clonal populations as assessment criterion, since this relationship disappears faster with sexual recombination than with amplification problems of certain alleles. We show that the relevance of our criterion for detecting poorly amplified alleles depends partly on the population structure, the level of homoplasy and/or mutation rate. However, the interpretation of data becomes difficult when the number of poorly amplified alleles is above 50%. The application of this method to reinterpret published data sets of pathogenic clonal microbes (yeast and trypanosomes) confirms its usefulness and allows refining previous estimates concerning important pathogenic agents. Our criterion of superimposing between the FIS expected under clonality and the observed FIS, is effective when amplification difficulties occur in low to moderate frequencies (20-30%).
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a protocol to improve genotyping of problematic microsatellite loci of trypanosoma brucei gambiense from body fluids
Infection Genetics and Evolution, 2013Co-Authors: Jacques Kabore, Adrien Marie Gaston Belem, Thierry De Meeus, Annette Macleod, Hamidou Ilboudo, Paul Capewell, Mamadou Camara, Bruno Bucheton, Vincent JamonneauAbstract:Microsatellite genotyping of Trypanosoma brucei gambiense, the causative agent of human African trypanosomiasis or sleeping sickness, and population genetics tools, are useful for inferring population parameters such as population size and dispersal. Amplifying parasite DNA directly from body fluids (i.e., blood, lymph or cerebrospinal fluid) allows avoiding costly and tedious isolation phases. It is however associated to increased frequencies of amplification failures (Allelic Dropouts and/or null alleles) at some loci. In this paper, we present a study focused on three T. brucei gambiense microsatellite loci suspected to present amplification problems when amplified from body fluids sampled in Guinean sleeping sickness foci. We checked for the real nature of blank and apparent homozygous genotypes of parasite DNA directly amplified from body fluids and tested the effect of three different DNA quantities of trypanosomes. Our results show that some initially blank and homozygous genotypes happen to be actual heterozygous genotypes. In Guinea, lymph from the cervical nymph nodes, known to contain the highest concentrations of parasites, appeared to provide the best amplification results. Simply repeating the PCR may be enough to retrieve the correct genotype, but we also show that increasing initial DNA content provides better results while undertaking first amplification. We finally propose an optimal protocol for amplifying trypanosome’s DNA directly from body fluids that should be adapted to local characteristics and/or constraints.