Finding the right coverage: the impact of coverage and sequence quality on single nucleotide polymorphism genotyping error rates

Restriction‐enzyme‐based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in nonmodel organisms. However, in contrast to traditional genetic markers, genotyping error rates in SNPs derived from restriction‐enzyme‐based methods remain largely unknown....

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Vydáno v:Molecular ecology resources Ročník 16; číslo 4; s. 966 - 978
Hlavní autoři: Fountain, Emily D., Pauli, Jonathan N., Reid, Brendan N., Palsbøll, Per J., Peery, M. Zachariah
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Blackwell Publishing Ltd 01.07.2016
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Abstract Restriction‐enzyme‐based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in nonmodel organisms. However, in contrast to traditional genetic markers, genotyping error rates in SNPs derived from restriction‐enzyme‐based methods remain largely unknown. Here, we estimated genotyping error rates in SNPs genotyped with double digest RAD sequencing from Mendelian incompatibilities in known mother–offspring dyads of Hoffman's two‐toed sloth (Choloepus hoffmanni) across a range of coverage and sequence quality criteria, for both reference‐aligned and de novo‐assembled data sets. Genotyping error rates were more sensitive to coverage than sequence quality and low coverage yielded high error rates, particularly in de novo‐assembled data sets. For example, coverage ≥5 yielded median genotyping error rates of ≥0.03 and ≥0.11 in reference‐aligned and de novo‐assembled data sets, respectively. Genotyping error rates declined to ≤0.01 in reference‐aligned data sets with a coverage ≥30, but remained ≥0.04 in the de novo‐assembled data sets. We observed approximately 10‐ and 13‐fold declines in the number of loci sampled in the reference‐aligned and de novo‐assembled data sets when coverage was increased from ≥5 to ≥30 at quality score ≥30, respectively. Finally, we assessed the effects of genotyping coverage on a common population genetic application, parentage assignments, and showed that the proportion of incorrectly assigned maternities was relatively high at low coverage. Overall, our results suggest that the trade‐off between sample size and genotyping error rates be considered prior to building sequencing libraries, reporting genotyping error rates become standard practice, and that effects of genotyping errors on inference be evaluated in restriction‐enzyme‐based SNP studies.
AbstractList Restriction-enzyme-based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in nonmodel organisms. However, in contrast to traditional genetic markers, genotyping error rates in SNPs derived from restriction-enzyme-based methods remain largely unknown. Here, we estimated genotyping error rates in SNPs genotyped with double digest RAD sequencing from Mendelian incompatibilities in known mother-offspring dyads of Hoffman's two-toed sloth (Choloepus hoffmanni) across a range of coverage and sequence quality criteria, for both reference-aligned and de novo-assembled data sets. Genotyping error rates were more sensitive to coverage than sequence quality and low coverage yielded high error rates, particularly in de novo-assembled data sets. For example, coverage greater than or equal to 5 yielded median genotyping error rates of greater than or equal to 0.03 and greater than or equal to 0.11 in reference-aligned and de novo-assembled data sets, respectively. Genotyping error rates declined to less than or equal to 0.01 in reference-aligned data sets with a coverage greater than or equal to 30, but remained greater than or equal to 0.04 in the de novo-assembled data sets. We observed approximately 10- and 13-fold declines in the number of loci sampled in the reference-aligned and de novo-assembled data sets when coverage was increased from greater than or equal to 5 to greater than or equal to 30 at quality score greater than or equal to 30, respectively. Finally, we assessed the effects of genotyping coverage on a common population genetic application, parentage assignments, and showed that the proportion of incorrectly assigned maternities was relatively high at low coverage. Overall, our results suggest that the trade-off between sample size and genotyping error rates be considered prior to building sequencing libraries, reporting genotyping error rates become standard practice, and that effects of genotyping errors on inference be evaluated in restriction-enzyme-based SNP studies.
Restriction-enzyme-based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in nonmodel organisms. However, in contrast to traditional genetic markers, genotyping error rates in SNPs derived from restriction-enzyme-based methods remain largely unknown. Here, we estimated genotyping error rates in SNPs genotyped with double digest RAD sequencing from Mendelian incompatibilities in known mother-offspring dyads of Hoffman's two-toed sloth (Choloepus hoffmanni) across a range of coverage and sequence quality criteria, for both reference-aligned and de novo-assembled data sets. Genotyping error rates were more sensitive to coverage than sequence quality and low coverage yielded high error rates, particularly in de novo-assembled data sets. For example, coverage ≥5 yielded median genotyping error rates of ≥0.03 and ≥0.11 in reference-aligned and de novo-assembled data sets, respectively. Genotyping error rates declined to ≤0.01 in reference-aligned data sets with a coverage ≥30, but remained ≥0.04 in the de novo-assembled data sets. We observed approximately 10- and 13-fold declines in the number of loci sampled in the reference-aligned and de novo-assembled data sets when coverage was increased from ≥5 to ≥30 at quality score ≥30, respectively. Finally, we assessed the effects of genotyping coverage on a common population genetic application, parentage assignments, and showed that the proportion of incorrectly assigned maternities was relatively high at low coverage. Overall, our results suggest that the trade-off between sample size and genotyping error rates be considered prior to building sequencing libraries, reporting genotyping error rates become standard practice, and that effects of genotyping errors on inference be evaluated in restriction-enzyme-based SNP studies.
Restriction‐enzyme‐based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism ( SNP ) loci in nonmodel organisms. However, in contrast to traditional genetic markers, genotyping error rates in SNP s derived from restriction‐enzyme‐based methods remain largely unknown. Here, we estimated genotyping error rates in SNP s genotyped with double digest RAD sequencing from Mendelian incompatibilities in known mother–offspring dyads of Hoffman's two‐toed sloth ( Choloepus hoffmanni ) across a range of coverage and sequence quality criteria, for both reference‐aligned and de novo ‐assembled data sets. Genotyping error rates were more sensitive to coverage than sequence quality and low coverage yielded high error rates, particularly in de novo ‐assembled data sets. For example, coverage ≥5 yielded median genotyping error rates of ≥0.03 and ≥0.11 in reference‐aligned and de novo ‐assembled data sets, respectively. Genotyping error rates declined to ≤0.01 in reference‐aligned data sets with a coverage ≥30, but remained ≥0.04 in the de novo‐ assembled data sets. We observed approximately 10‐ and 13‐fold declines in the number of loci sampled in the reference‐aligned and de novo ‐assembled data sets when coverage was increased from ≥5 to ≥30 at quality score ≥30, respectively. Finally, we assessed the effects of genotyping coverage on a common population genetic application, parentage assignments, and showed that the proportion of incorrectly assigned maternities was relatively high at low coverage. Overall, our results suggest that the trade‐off between sample size and genotyping error rates be considered prior to building sequencing libraries, reporting genotyping error rates become standard practice, and that effects of genotyping errors on inference be evaluated in restriction‐enzyme‐based SNP studies.
Author Pauli, Jonathan N.
Palsbøll, Per J.
Peery, M. Zachariah
Reid, Brendan N.
Fountain, Emily D.
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Issue 4
Keywords ddRAD
genotyping error
next-generation sequencing
single nucleotide polymorphism
Mendelian incompatibility
Language English
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2016 John Wiley & Sons Ltd.
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Table S1 Total number of raw and retained reads by individuals, sample quality and the sequencing library for quality score ≥10. Table S2 Total number of raw and retained reads by individuals, sample quality and the sequencing library for quality score ≥20. Table S3 Total number of raw and retained reads by individuals, sample quality and the sequencing library for quality score ≥30. Fig. S1 Figure of median genotyping error for reference-aligned full reads using all 16 dyads vs. dataset with the three low-quality dyads removed. Fig. S2 Reference-aligned full dataset changes relative to that observed at minimum coverage (≥5) and quality score (≥10). Fig. S3de novo-assembled dataset changes relative to that observed at minimum coverage (≥5) and quality score (≥10). Fig. S4 Figure of median genotyping error for de novo-assembled dataset using all 16 dyads vs. dataset with the three low-quality dyads removed. Fig. S5 rxstacks corrected dataset changes relative to that observed at minimum coverage (≥5) and quality score (≥10) for reference-aligned full and de novo-assembled datasets.Appendix S1 Detailed methods for laboratory protocols, de novo assembly parameter tests and parentage assignments.
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Saunders IW, Brohede J, Hannan GN (2007) Estimating genotyping error rates from Mendelian errors in SNP array genotypes and their impact on inference. Genomics, 90, 291-296.
Larson WA, Seeb JE, Pascal CE, Templin WD, Seeb LW (2014) Single-nucleotide polymorphisms (SNPs) identified through genotyping-by-sequencing improve genetic stock identification of Chinook salmon (Oncorhynchus tshawytscha) from western Alaska. Canadian Journal of Fisheries and Aquatic Sciences, 71, 698-708.
Malhis N, Jones SJM (2010) High quality SNP calling using Illumina data at shallow coverage. Bioinformatics, 26, 1029-1035.
Gnerre S, MacCallum I, Przybylski D et al. (2011) High-quality draft assemblies of mammalian genomes from massively parallel sequence data. Proceedings of the National Academy of Sciences, USA, 108, 1513-1518.
Jezkova T, Riddle BR, Card DC et al. (2015) Genetic consequences of post-glacial range expansion in two co-distributed rodents (genus Dipodomys) depend on ecology and genetic locus. Molecular Ecology, 24, 83-97.
Pompanon F, Bonin A, Bellemain E, Taberlet P (2005) Genotyping errors: causes, consequences and solutions. Nature Reviews Genetics, 6, 847-859.
Palti Y, Gao G, Liu S et al. (2015) The development and characterization of a 57K single nucleotide polymorphism array for rainbow trout. Molecular Ecology Resources, 15, 662-672.
Funk WC, McKay JK, Hohenlohe PA, Allendorf FW (2012) Harnessing genomics for delineating conservation units. Trends in Ecology & Evolution, 27, 489-496.
Zhang J, Chiodini R, Badr A, Zhang G (2011) The impact of next-generation sequencing on genomics. Journal of Genetics and Genomics, 38, 95-109.
Davey JW, Hohenlohe PA, Etter PD, et al. (2011) Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nature Reviews Genetics, 12, 499-510.
R Core Team (2013) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
Mastretta-Yanes A, Arrigo N, Alvarez N et al. (2015) Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference. Molecular Ecology Resources, 15, 28-41.
Buerkle AC, Gompert Z (2013) Population genomics based on low coverage sequencing: how low should we go? Molecular Ecology, 22, 3028-3035.
Peterson BK, Weber JN, Kay EH, Fisher HS, Hoekstra HE (2012) Double Digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLoS ONE, 7, e37135.
Jones JC, Fan S, Franchini P, Schartl M, Meyer A (2013) The evolutionary history of Xiphophorus fish and their sexually selected sword: a genome-wide approach using restriction site-associated DNA sequencing. Molecular Ecology, 22, 2986-3001.
Baird NA, Etter PD, Atwood TS, et al. (2008) Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS ONE, 3, e3376.
Lozier JD (2014) Revisiting comparisons of genetic diversity in stable and declining species: assessing genome-wide polymorphism in North American bumble bees using RAD sequencing. Molecular Ecology, 23, 788-801.
Chen N, Van Hout CV, Gottipati S, Clark AG (2014) Using Mendelian Inheritance to improve high throughput SNP discovery. Genetics, 198, 847-857.
Corrales C, Höglund J (2012) Maintenance of gene flow by female-biased dispersal of Black Grouse Tetrao tetrix in northern Sweden. Journal of Ornithology, 153, 1127-1139.
Le SQ, Durbin R (2011) SNP detection and genotyping from low-coverage sequencing data on multiple diploid samples. Genome Research, 21, 952-960.
Li H, Ruan J, Durbin R (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Research, 18, 1851-1858.
Hohenlohe PA, Bassham S, Etter PD, et al. (2010) Population genomics of parallel adaptation in threespine stickleback using sequenced RAD tags. PLoS Genetics, 6, e1000862.
Schmid CW, Deininger PL (1975) Sequence organization of the human genome. Cell, 6, 345-358.
Zhou X, Xia Y, Ren X et al. (2014) Construction of a SNP-based genetic linkage map in cultivated peanut based on large scale marker development using next-generation double-digest restriction-site-associated DNA sequencing (ddRADseq). BMC Genomics, 15, 351.
Davey JW, Cezard T, Fuentes-Utrilla P et al. (2013) Special features of RAD Sequencing data: implications for genotyping. Molecular Ecology, 22, 3151-3164.
Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program cervus accommodates genotyping error increases success in paternity assignment. Molecular Ecology, 16, 1099-1106.
Chain PSG, Grafham DV, Fulton RS et al. (2009) Genome project standards in a new era of sequencing. Science (New York, N.Y.), 326, 236-237.
Nielsen R, Korneliussen T, Albrechtsen A, Li Y, Wang J (2012) SNP calling, genotype calling, and sample allele frequency estimation from new-generation sequencing data. PLoS ONE, 7, e37558.
Kai W, Nomura K, Fujiwara A et al. (2014) A ddRAD-based genetic map and its integration with the genome assembly of Japanese eel (Anguilla japonica) provides insights into genome evolution after the teleost-specific genome duplication. BMC Genomics, 15, 233.
Franchini P, Fruciano C, Spreitzer ML et al. (2014) Genomic architecture of ecologically divergent body shape in a pair of sympatric Crater Lake cichlid fishes. Molecular Ecology, 23, 1828-1845.
Lamichhaney S, Barrio AM, Rafati N et al. (2012) Population-scale sequencing reveals genetic differentiation due to local adaptation in Atlantic herring. Proceedings of the National Academy of Sciences, USA, 109, 19345-19350.
Kang SJ, Gordon D, Finch SJ (2004) What SNP genotyping errors are most costly for genetic association studies? Genetic Epidemiology, 26, 132-141.
Hao K, Li C, Rosenow C, Hung Wong W (2004) Estimation of genotype error rate using samples with pedigree information-an application on the GeneChip Mapping 10K array. Genomics, 84, 623-630.
DaCosta JM, Sorenson MD (2014) Amplification biases and consistent recovery of loci in a double-digest RAD-seq protocol. PLoS ONE, 9, e106713.
Li R, Yu C, Li Y et al. (2009) SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics, 25, 1966-1967.
Wagner CE, Keller I, Wittwer S et al. (2013) Genome-wide RAD sequence data provide unprecedented resolution of species boundaries and relationships in the Lake Victoria cichlid adaptive radiation. Molecular Ecology, 22, 787-798.
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Haaland ØA, Skaug HJ (2013) Estimating genotyping error rates from parent-offspring dyads. Statistics & Probability Letters, 83, 812-819.
Johnson PLF, Slatkin M (2008) Accounting for bias from sequencing error in population genetic estimates. Molecular Biology and Evolution, 25, 199-206.
Catchen JM, Amores A, Hohenlohe P, Cresko W, Postlethwait JH (2011) Stacks: building and genotyping loci de novo from short-read sequences. G3: Genes Genomes, Genetics, 1, 171-182.
Douglas JA, Skol AD, Boehnke M (2002) Probability of detection of genotyping errors and mutations as inheritance inconsistencies in nuclear-family data. American Journal of Human Genetics, 70, 487-495.
2009; 25
2015; 15
2013; 3
2004; 84
2011; 1
2013; 22
2010; 19
2008; 18
2013; 83
2004; 26
2007; 90
2011; 13
2011; 12
2008; 3
2014; 198
2011; 38
2011; 6
2014; 23
2012; 109
2007; 16
2015; 24
2012; 153
2010; 26
2011; 108
2013; 14
2009; 10
2013; 77
2013; 13
2013; 30
2008; 25
2014; 15
2011; 21
2005; 6
2002; 70
2012; 27
2013
2014; 9
1998; 7
2012; 7
2014; 71
2010; 6
1975; 6
2009; 326
2012; 84
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Snippet Restriction‐enzyme‐based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in nonmodel organisms. However, in...
Restriction‐enzyme‐based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism ( SNP ) loci in nonmodel organisms. However,...
Restriction-enzyme-based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in nonmodel organisms. However, in...
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StartPage 966
SubjectTerms Animals
Choloepus
Choloepus hoffmanni
data collection
Datasets
ddRAD
Diagnostic Errors
DNA libraries
DNA Restriction Enzymes - metabolism
Economic models
Enzymes
Genetic markers
genotyping error
genotyping errors
Genotyping Techniques - methods
High-Throughput Nucleotide Sequencing
loci
Mendelian incompatibility
next-generation sequencing
Offspring
parentage
Polymorphism, Single Nucleotide
Quality
Sequence Analysis, DNA
single nucleotide polymorphism
Xenarthra - classification
Xenarthra - genetics
Title Finding the right coverage: the impact of coverage and sequence quality on single nucleotide polymorphism genotyping error rates
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Volume 16
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