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Pierre Taberlet, Eva Bellemain, Aurélie Bonin, François Pompanon

Genotyping errors. Pierre Taberlet, Eva Bellemain, Aurélie Bonin, François Pompanon Laboratoire d'Ecologie Alpine, CNRS UMR 5553, Université Joseph Fourier, Grenoble, France. Genotyping errors.

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Pierre Taberlet, Eva Bellemain, Aurélie Bonin, François Pompanon

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  1. Genotyping errors Pierre Taberlet, Eva Bellemain, Aurélie Bonin, François Pompanon Laboratoire d'Ecologie Alpine, CNRS UMR 5553, Université Joseph Fourier, Grenoble, France

  2. Genotyping errors • Bonin A, Bellemain E, Bronken Eidesen P, Pompanon F, Brochmann C, Taberlet P (2004) How to track and assess genotyping errors in population genetics studies. Molecular Ecology, 13, 3261-3273. • Pompanon F, Bonin A, Bellemain E, Taberlet P (2005) Genotyping errors: causes, consequences and solutions. Nature Reviews Genetics, in press.

  3. Genotyping errors • Definition • Non-invasive sampling and genotyping errors • Causes of genotyping errors • Quantifying genotyping errors • Consequences of genotyping errors • How to limit genotyping errors and their impact?

  4. Genotyping errors • Definition • Non-invasive sampling and genotyping errors • Causes of genotyping errors • Quantifying genotyping errors • Consequences of genotyping errors • How to limit genotyping errors and their impact?

  5. Definition • A genotyping error occurs when the observed genotype of an individual does not correspond to the true genotype. • Genotyping errors can have strong consequences on the biological message that can be deduced from the data.

  6. Distribution of papers on "genotyping errors" according to their publication year • Apparently, more and more attention is paid to genotyping errors.

  7. Distribution of papers on "genotyping errors" according to their subject • Genotyping errors are a concern for some research field only (linkage analyses, non-invasive methods). • What about the other fields using genetic tools? (population genetics/genomics?)

  8. Genotyping errors • Definition • Non-invasive sampling and genotyping errors • Causes of genotyping errors • Quantifying genotyping errors • Consequences of genotyping errors • How to limit genotyping errors and their impact?

  9. Non-invasive sampling and genotyping errors • Historical aspects • Solutions to limit genotyping errors • Towards a quality index • Practicals: estimation of the quality index

  10. Questions about the Pyrenean bear population Papillon, Photo J.-J. Camarra, ONC, Août 1995 Geographic distribution of the brown bear in Europe

  11. Questions about the Pyrenean bear population • Where to take bears to reinforce the endangered Pyrenean population? • How many bears are left in the Pyrenees? • How many males and females?

  12. The three different sampling methods • Destructive sampling • Non-destructive sampling • Non-invasive sampling

  13. Destructive sampling • The animal is killed in order to obtain the tissues necessary for genetic analysis. • This sampling strategy has been used extensively for isozyme studies, and for mtDNA analysis before PCR was discovered. • It has been abandoned by many researchers.

  14. Non-destructive sampling • The animal is often captured, and a biopsy or a blood sample is taken invasively. • However, some invasive sampling strategies do not require catching the animal. • For example tissues can be obtained from whales and some other large mammals by using biopsy dart guns.

  15. Non-invasive sampling • This term should be restricted to situation where the source of DNA is left behind and is collected without having to catch or disturb the animal. • In the literature, non-destructive sampling is often improperly considered as non-invasive. • Catching a mammal (or a bird) and plucking a few hairs (or feathers) should not be considered as non-invasive, but rather as non-destructive.

  16. Non-invasive genetic sampling: only possible via PCR • Mullis KB, Faloona FA (1987) Specific synthesis of DNA invitro via a polymerase-catalysed chain reaction. Methods in Enzymology, 155, 335-350. • Saiki RK, Gelfand DH, Stoffel S, Scharf SJ, Higuchi R, Horn GT, Mullis KB, Erlich HA (1988) Primer-directed enzymatic amplification of DNA with a thermostable DNA polymerase. Science, 239, 487-491.

  17. Problematic results about the census of the Pyrenean bear population (in 1994) • More bears than expected! • No success when trying to replicate the results. • Two years to understand and solve the problem.

  18. Potential of non-invasive genetic sampling: two opposing point of view • Non-invasive sampling can exploit the full potential of DNA analysis. • True for mtDNA • Dominant opinion ten years ago • Non-invasive sampling has serious limitations. • Many technical problems • Possibility of genotyping errors

  19. Non-invasive sampling can exploit the full potential of DNA analysis • Morin PA, Moore JJ, Chakraborty R, Jin L, Goodall J, Woodruff DS (1994) Kin selection, social structure, gene flow, and the evolution of chimpanzees. Science, 265, 1193-1201. • Microsatellite study using hairs as a source of DNA. • Males are more homozygous than females in general. • Males are staying in their group more than    females. • Wrong results due to more genotyping errors in males (mainly allelic dropout).

  20. Non-invasive sampling has serious limitations • Gerloff U, Schlötterer C, Rassmann K, Rambold I, Hohmann G, Fruth B, Tautz D (1995) Amplification of hypervariable simple sequence repeats (microsatellites) from excremental DNA of wild living bonobos (Panpaniscus). Molecular Ecology, 4, 515-518. • Taberlet P, Griffin S, Goossens B, Questiau S, Manceau V, Escaravage N, Waits LP, Bouvet J (1996) Reliable genotyping of samples with very low DNA quantities using PCR. Nucleic Acids Research, 26, 3189-3194. • Gagneux P, Boesch C, Woodruff DS (1997) Microsatellite scoring errors associated with noninvasive genotyping based on nuclear DNA amplified from shed hair. Molecular Ecology, 6, 861-868.

  21. Gagneux P, Woodruff DS, Boesch C (1997) Furtive mating in female chimpanzees. Nature, 387 (22 May 1997), 358-359.

  22. Gagneux P, Woodruff DS, Boesch C (1997) Furtive mating in female chimpanzees. Nature, 387 (22 May 1997), 358-359. • Paternity study of the offspring of a chimpanze community. • Half of the offspring did not display any allele inherited from an intragroup father. • Conclusion: these offspring had an extragroup father. • The dataset contained allelic dropouts (paper retraction in 2001).

  23. Scan of the Gagneux paper in Mol Ecol

  24. Genotyping errors: main difficulties in non-invasive sampling • Contamination • Allelic dropout • False alleles

  25. Contamination • Behind the possibility of detecting a single target molecule, there is also a possibility of detecting a single contaminant molecule. • Working with non-invasive genetic sampling is similar to ancient DNA studies.

  26. Genotyping errors: allelic dropout • For a heterozygous individual, only one allele is present in the template and/or is amplified in the PCR reaction. • This error produces a false homozygote.

  27. Genotyping errors: false alleles • Artifacts can be generated during the first cycles of the PCR reaction, and can be misinterpreted as true alleles. • Very difficult to discern from sporadic contamination.

  28. Genotyping errors: example Five independent genetic typing using the same DNA extract (from feces). Allele A Brown bear Locus G10B Allele B

  29. Genotyping errors: example Fifty independent genotyping experiments using the same DNA extract (from a bear feces); locus G10B. Allele A Allele B

  30. 1 2 3 4 5 6 7 Genotyping errors: example Seven independent experiments using the same DNA extract from a bear feces.

  31. 1 2 3 4 5 6 7 Genotyping errors: example Seven independent experiments using the same DNA extract from a single marmot hair.

  32. 1 marmot hair 3 marmot hairs 10 marmot hairs Influence of the amount of template DNA From Goossens et al., 1998

  33. Allelic dropout: mathematical model • The model is restricted to the genotyping of an individual bearing alleles A and B at an autosomal locus. • Many assumptions have been made.

  34. Allelic dropout: mathematical model assumptions • The DNA extract contains equal numbers of the alleles A and B. • A single target molecule can be amplified and detected. • Each single target molecule has the same probability of being amplified. • 100 PCRs and be performed using the DNA extract, and the target DNA molecules are distributed randomly among the 100 PCR tubes. • If the initial proportion between alleles A and B (A/B or B/A) in the PCR tube is greater than or equal to five, then only the most common allele will be detected.

  35. 3.5 pg of template DNA per reaction 14 pg of template DNA per reaction 3.5 pg of template DNA per reaction 14 pg of template DNA per reaction tube 1: AABAB tube 13: AAAAB tube 1: B tube 13: - tube 1: B tube 13: - tube 2: BB tube 14: B tube 2: B tube 14: BA tube 2: B tube 14: BA tube 3: ABBBBB tube 15: AAAA tube 3: - tube 15: BABB tube 3: - tube 15: BABB tube 4: AABA tube 16: BBAAAB tube 4: - tube 16: BB tube 4: - tube 16: BB tube 5: BBAAABA tube 17: BABB tube 5: A tube 17: - tube 5: BBAAABA tube 17: BABB tube 5: A tube 17: - tube 6: BBBB tube 18: BAABAA tube 6: A tube 18: B tube 6: BBBB tube 18: BAABAA tube 6: A tube 18: B tube 7: BAAB tube 19: ABBBA tube 7: A tube 19: A tube 7: BAAB tube 19: ABBBA tube 7: A tube 19: A tube 8: BAAA tube 20: BBABA tube 8: A tube 20: A tube 8: BAAA tube 20: BBABA tube 8: A tube 20: A tube 9: - tube 21: BAB tube 9: - tube 21: B tube 9: - tube 21: BAB tube 9: - tube 21: B tube 10: AAB tube 22: BBA tube 10: - tube 22: A tube 10: AAB tube 22: BBA tube 10: - tube 22: A tube 11: BBB tube 23: - tube 11: ABB tube 23: - tube 11: BBB tube 23: - tube 11: ABB tube 23: - tube 12: AABABBAB tube 24: AAAA tube 12: AA tube 24: - tube 12: AABABBAB tube 24: AAAA tube 12: AA tube 24: - The problem of very small DNA samples: simulations Simulations for a heterozygote individual with alleles A and B Simulations for a heterozygote individual with alleles A and B. correct genotyping correct genotyping

  36. 100 80 60 40 20 0 0 5 10 15 20 25 30 35 40 45 50 55 ! Results of the simulations PCR product % (at least one allele) correct genotyping (both alleles) one cell contains about 7 picograms of DNA template DNA per amplification (picograms) Probability of correct genotyping at a heterozygote microsatellite locus using very mall DNA samples DNA samples

  37. Guidelines for genotyping very small DNA samples • Multiple-tube approach. • Navidi W, Arnheim N, Waterman MS (1992) A multiple-tube approach for accurate genotyping of very small DNA samples by using PCR: statistical considerations. American Journal of Human Genetics, 50, 347-359. • Taberlet P, Griffin S, Goossens B, Questiau S, Manceau V, Escaravage N, Waits LP, Bouvet J (1996) Reliable genotyping of samples with very low DNA quantities using PCR. Nucleic Acids Research, 26, 3189-3194.

  38. Guidelines for genotyping very small DNA samples • The guidelines are only valid under the following conditions. • A single target molecule can be detected. • The amount of template DNA is very low, in the picogram range, but is not accurately know.

  39. Guidelines for genotyping very small DNA samples • Confidence of 99%. • Multiple-tube approach. • Heterozygotes: an allele can be recorded only if it has been found at least twice. • Homozygotes: an individual can be considered as homozygous only if eight independent experiments have shown the same allele.

  40. Guidelines for genotyping very small DNA samples • How to avoid or to limit the impact of the multiple-tube approach? • By estimating the amount of template DNA • Miller C, Joyce P, Waits L (2002) Assessing allelic dropout and genotype reliability using maximum likelihood. Genetics, 160, 357-366. • Morin P, Chambers K, Boesh C, Vigilant L (2001) Quantitative polymerase chain reaction analysis of DNA from noninvasive samples for accurate microsatellite genotyping of wild chimpanzees (Pan troglodytes verus). Molecular Ecology, 10, 1835-1844.

  41. Quantitative PCR (from Morin et al., 2001) Relationship between the initial amount of template DNA in the PCR and both the proportion of PCRs with amplification product (grey squares) and the proportion of PCRs with allelic dropout (black circles).

  42. Towards a quality index • Goal: estimate a quality index associated to each sample. • This quality index should allow comparisons among samples, loci, and studies. • Restricted to the situation where the multiple-tube approach is used.

  43. Towards a quality index • The estimation of the quality index (QI) is based on the analysis of the whole set of electropherograms produced when using the multiple-tube approach. • For each locus of a given sample, a QI is estimated using the following steps: • Step 1: estimation of the most likely consensus genotype • Step 2: estimation of the score for each repeat • Step 3: estimation of the quality index for the locus

  44. Towards a quality index • Step 1: estimation of the most likely consensus genotype after simultaneous observation of the electropherograms corresponding to the different repeats of this locus. An allele is considered only if it is present at least twice among the different repeats. • Step 2: estimation of the score for each repeat. If the electropherogram at one repeat corresponds to the consensus genotype, the score "1" is assigned, otherwise the score "0" is assigned, whetever the differences. • Step 3: estimation of the QI for the locus. The scores assigned to each repeat are summed, and divided by the number of repeats. • Step 4: estimation of the mean QI per locus and per individual.

  45. Additional rules • No signal is scored as "0". • Electropherograms with an additional allele are scored as "0". • If the less intense allele is less than 20% of the most intense allele, a score of "0" is given.

  46. 1 1 1 2 1 3 1 4 Step 2: score for each repeat 1 5 1 6 1 7 1 8 Step 3: quality index 1.00 Step 1: consensus genotype Quality index: example 1 Multiple-tube approach, 8 repeats

  47. 1 2 3 4 5 6 7 8 Step 3: quality index 0.25 Step 1: consensus genotype Quality index: example 2 Multiple-tube approach, 8 repeats 0 1 0 0 Step 2: score for each repeat 1 0 0 0

  48. 1 2 3 4 5 6 7 8 Step 3: quality index 0.62 Step 1: consensus genotype Quality index: example 3 Multiple-tube approach, 8 repeats 1 1 0 1 Step 2: score for each repeat 1 0 0 1

  49. Quality indexes for loci, samples, and study

  50. Quality indexes for loci, samples, and study

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