Literature DB >> 33664303

Uncertainty in estimating the number of contributors from simulated DNA mixture profiles, with and without allele dropout, from Chinese, Malay, Indian, and Caucasian ethnic populations.

Kevin Wai Yin Chong1, Christopher Kiu-Choong Syn2.   

Abstract

Determining the number of contributors (NOC) accurately in a forensic DNA mixture profile can be challenging. To address this issue, there have been various studies that examined the uncertainty in estimating the NOC in a DNA mixture profile. However, the focus of these studies lies primarily on dominant populations residing within Europe and North America. Thus, there is limited representation of Asian populations in these studies. Further, the effects of allele dropout on the NOC estimation has not been explored. As such, this study assesses the uncertainty of NOC in simulated DNA mixture profiles of Chinese, Malay, and Indian populations, which are the predominant ethnic populations in Asia. The Caucasian ethnic population was also included to provide a basis of comparison with other similar studies. Our results showed that without considering allele dropout, the NOC from DNA mixture profiles derived from up to four contributors of the same ethnic population could be estimated with confidence in the Chinese, Malay, Indian and Caucasian populations. The same results can be observed on DNA mixture profiles originating from a combination of differing ethnic populations. The inclusion of an overall 30% allele dropout rate increased the probability (risk) of underestimating the NOC in a DNA mixture profile; even a 3-person DNA mixture profile has a > 99% risk of underestimating the NOC as two or fewer contributors. However, such risks could be mitigated when the highly polymorphic SE33 locus was included in the dataset. Lastly there was a negligible level of risk in misinterpreting the NOC in a mixture profile as deriving from a single source profile. In summary, our studies showcased novel results representative of the Chinese, Malay, and Indian ethnic populations when examining the uncertainty in NOC estimation in a DNA mixture profile. Our results would be useful in the estimation of NOC in a DNA mixture profile in the Asian context.

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Year:  2021        PMID: 33664303      PMCID: PMC7933404          DOI: 10.1038/s41598-021-84580-4

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.996


  18 in total

1.  Uncertainty in the number of contributors in the proposed new CODIS set.

Authors:  Michael D Coble; Jo-Anne Bright; John S Buckleton; James M Curran
Journal:  Forensic Sci Int Genet       Date:  2015-07-17       Impact factor: 4.882

2.  Estimating the probability of allelic drop-out of STR alleles in forensic genetics.

Authors:  Torben Tvedebrink; Poul Svante Eriksen; Helle Smidt Mogensen; Niels Morling
Journal:  Forensic Sci Int Genet       Date:  2009-03-13       Impact factor: 4.882

3.  Allelic drop-out probabilities estimated by logistic regression--further considerations and practical implementation.

Authors:  Torben Tvedebrink; Poul Svante Eriksen; Maria Asplund; Helle Smidt Mogensen; Niels Morling
Journal:  Forensic Sci Int Genet       Date:  2011-07-05       Impact factor: 4.882

Review 4.  Probabilistic genotyping software: An overview.

Authors:  Michael D Coble; Jo-Anne Bright
Journal:  Forensic Sci Int Genet       Date:  2018-11-11       Impact factor: 4.882

5.  STRmix™ collaborative exercise on DNA mixture interpretation.

Authors:  Jo-Anne Bright; Kevin Cheng; Zane Kerr; Catherine McGovern; Hannah Kelly; Tamyra R Moretti; Michael A Smith; Frederick R Bieber; Bruce Budowle; Michael D Coble; Rashed Alghafri; Paul Stafford Allen; Amy Barber; Vickie Beamer; Christina Buettner; Melanie Russell; Christian Gehrig; Tacha Hicks; Jessica Charak; Kate Cheong-Wing; Anne Ciecko; Christie T Davis; Michael Donley; Natalie Pedersen; Bill Gartside; Dominic Granger; MaryMargaret Greer-Ritzheimer; Erick Reisinger; Jarrah Kennedy; Erin Grammer; Marla Kaplan; David Hansen; Hans J Larsen; Alanna Laureano; Christina Li; Eugene Lien; Emilia Lindberg; Ciara Kelly; Ben Mallinder; Simon Malsom; Alyse Yacovone-Margetts; Andrew McWhorter; Sapana M Prajapati; Tamar Powell; Gary Shutler; Kate Stevenson; April R Stonehouse; Lindsey Smith; Julie Murakami; Eric Halsing; Darren Wright; Leigh Clark; Duncan A Taylor; John Buckleton
Journal:  Forensic Sci Int Genet       Date:  2019-01-15       Impact factor: 4.882

6.  U.S. population data for 29 autosomal STR loci.

Authors:  Carolyn R Hill; David L Duewer; Margaret C Kline; Michael D Coble; John M Butler
Journal:  Forensic Sci Int Genet       Date:  2013-01-11       Impact factor: 4.882

7.  Uncertainty in the number of contributors for the European Standard Set of loci.

Authors:  James M Curran; John Buckleton
Journal:  Forensic Sci Int Genet       Date:  2014-04-03       Impact factor: 4.882

8.  Analysis of allelic drop-out using the Identifiler(®) and PowerPlex(®) 16 forensic STR typing systems.

Authors:  Kirk E Lohmueller; Norah Rudin; Keith Inman
Journal:  Forensic Sci Int Genet       Date:  2014-04-18       Impact factor: 4.882

9.  Determining the number of contributors to DNA mixtures in the low-template regime: Exploring the impacts of sampling and detection effects.

Authors:  Sarah Norsworthy; Desmond S Lun; Catherine M Grgicak
Journal:  Leg Med (Tokyo)       Date:  2018-02-08       Impact factor: 1.376

10.  Evaluation of forensic DNA mixture evidence: protocol for evaluation, interpretation, and statistical calculations using the combined probability of inclusion.

Authors:  Frederick R Bieber; John S Buckleton; Bruce Budowle; John M Butler; Michael D Coble
Journal:  BMC Genet       Date:  2016-08-31       Impact factor: 2.797

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