TY - JOUR
T1 - Comparing genomic variant identification protocols for Candida auris
AU - Li, Xiao
AU - Muñoz, José F
AU - Gade, Lalitha
AU - Argimon, Silvia
AU - Bougnoux, Marie-Elisabeth
AU - Bowers, Jolene R
AU - Chow, Nancy A
AU - Cuesta, Isabel
AU - Farrer, Rhys A
AU - Maufrais, Corinne
AU - Monroy-Nieto, Juan
AU - Pradhan, Dibyabhaba
AU - Uehling, Jessie
AU - Vu, Duong
AU - Yeats, Corin A
AU - Aanensen, David M
AU - d'Enfert, Christophe
AU - Engelthaler, David M
AU - Eyre, David W
AU - Fisher, Matthew C
AU - Hagen, Ferry
AU - Meyer, Wieland
AU - Singh, Gagandeep
AU - Alastruey-Izquierdo, Ana
AU - Litvintseva, Anastasia P
AU - Cuomo, Christina A
PY - 2023/4/13
Y1 - 2023/4/13
N2 - Genomic analyses are widely applied to epidemiological, population genetic and experimental studies of pathogenic fungi. A wide range of methods are employed to carry out these analyses, typically without including controls that gauge the accuracy of variant prediction. The importance of tracking outbreaks at a global scale has raised the urgency of establishing high-accuracy pipelines that generate consistent results between research groups. To evaluate currently employed methods for whole-genome variant detection and elaborate best practices for fungal pathogens, we compared how 14 independent variant calling pipelines performed across 35 Candida auris isolates from 4 distinct clades and evaluated the performance of variant calling, single-nucleotide polymorphism (SNP) counts and phylogenetic inference results. Although these pipelines used different variant callers and filtering criteria, we found high overall agreement of SNPs from each pipeline. This concordance correlated with site quality, as SNPs discovered by a few pipelines tended to show lower mapping quality scores and depth of coverage than those recovered by all pipelines. We observed that the major differences between pipelines were due to variation in read trimming strategies, SNP calling methods and parameters, and downstream filtration criteria. We calculated specificity and sensitivity for each pipeline by aligning three isolates with chromosomal level assemblies and found that the GATK-based pipelines were well balanced between these metrics. Selection of trimming methods had a greater impact on SAMtools-based pipelines than those using GATK. Phylogenetic trees inferred by each pipeline showed high consistency at the clade level, but there was more variability between isolates from a single outbreak, with pipelines that used more stringent cutoffs having lower resolution. This project generated two truth datasets useful for routine benchmarking of C. auris variant calling, a consensus VCF of genotypes discovered by 10 or more pipelines across these 35 diverse isolates and variants for 2 samples identified from whole-genome alignments. This study provides a foundation for evaluating SNP calling pipelines and developing best practices for future fungal genomic studies.
AB - Genomic analyses are widely applied to epidemiological, population genetic and experimental studies of pathogenic fungi. A wide range of methods are employed to carry out these analyses, typically without including controls that gauge the accuracy of variant prediction. The importance of tracking outbreaks at a global scale has raised the urgency of establishing high-accuracy pipelines that generate consistent results between research groups. To evaluate currently employed methods for whole-genome variant detection and elaborate best practices for fungal pathogens, we compared how 14 independent variant calling pipelines performed across 35 Candida auris isolates from 4 distinct clades and evaluated the performance of variant calling, single-nucleotide polymorphism (SNP) counts and phylogenetic inference results. Although these pipelines used different variant callers and filtering criteria, we found high overall agreement of SNPs from each pipeline. This concordance correlated with site quality, as SNPs discovered by a few pipelines tended to show lower mapping quality scores and depth of coverage than those recovered by all pipelines. We observed that the major differences between pipelines were due to variation in read trimming strategies, SNP calling methods and parameters, and downstream filtration criteria. We calculated specificity and sensitivity for each pipeline by aligning three isolates with chromosomal level assemblies and found that the GATK-based pipelines were well balanced between these metrics. Selection of trimming methods had a greater impact on SAMtools-based pipelines than those using GATK. Phylogenetic trees inferred by each pipeline showed high consistency at the clade level, but there was more variability between isolates from a single outbreak, with pipelines that used more stringent cutoffs having lower resolution. This project generated two truth datasets useful for routine benchmarking of C. auris variant calling, a consensus VCF of genotypes discovered by 10 or more pipelines across these 35 diverse isolates and variants for 2 samples identified from whole-genome alignments. This study provides a foundation for evaluating SNP calling pipelines and developing best practices for future fungal genomic studies.
KW - Candida auris
KW - Phylogeny
KW - High-Throughput Nucleotide Sequencing/methods
KW - Polymorphism, Single Nucleotide
KW - Genomics
U2 - 10.1099/mgen.0.000979
DO - 10.1099/mgen.0.000979
M3 - Article
C2 - 37043380
SN - 2057-5858
VL - 9
JO - Microbial genomics
JF - Microbial genomics
IS - 4
ER -