Evidence map›Paper›PMID 31227725›Full record

ArticleScientific reports2019

Estimating Y-Str Mutation Rates and Tmrca Through Deep-Rooting Italian Pedigrees.

Alessio Boattini, Stefania Sarno, Alessandra M Mazzarisi, Cinzia Viroli, Sara De Fanti, Carla Bini, Maarten H D Larmuseau, Susi Pelotti, Donata Luiselli

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Alessio BoattiniDipartimento di Scienze Biologiche, Geologiche e Ambientali (BiGeA), Università di Bologna, 40126, Bologna, Italy. alessio.boattini2@unibo.it.
Stefania SarnoDipartimento di Scienze Biologiche, Geologiche e Ambientali (BiGeA), Università di Bologna, 40126, Bologna, Italy.
Alessandra M MazzarisiDipartimento di Scienze Biologiche, Geologiche e Ambientali (BiGeA), Università di Bologna, 40126, Bologna, Italy.
Cinzia ViroliDipartimento di Scienze Statistiche "Paolo Fortunati", Università di Bologna, 40126, Bologna, Italy.
Sara De FantiDipartimento di Scienze Biologiche, Geologiche e Ambientali (BiGeA), Università di Bologna, 40126, Bologna, Italy.
Carla BiniDipartimento di Scienze Mediche e Chirurgiche, Università di Bologna, 40126, Bologna, Italy.
Maarten H D LarmuseauLaboratory of Forensic Genetics and Molecular Archaeology, Forensic Biomedical Sciences, KU Leuven, B-3000, Leuven, Belgium.
Susi PelottiDipartimento di Scienze Mediche e Chirurgiche, Università di Bologna, 40126, Bologna, Italy.
Donata LuiselliDipartimento di Beni Culturali, Università di Bologna, 48121, Ravenna, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the population genomics era, the study of Y-chromosome variability is still of the greatest interest for several fields ranging from molecular anthropology to forensics and genetic genealogy. In particular, mutation rates of Y-chromosomal Short Tandem Repeats markers (Y-STRs) are key parameters for different interdisciplinary applications. Among them, testing the patrilineal relatedness between individuals and calculating their Time of Most Recent Common Ancestors (TMRCAs) are of the utmost importance. To provide new valuable estimates and to address these issues, we typed 47 Y-STRs (comprising Yfiler, PowerPlex23 and YfilerPlus loci, the recently defined Rapidly Mutating [RM] panel and 11 additional markers often used in genetic genealogical applications) in 135 individuals belonging to 66 deep-rooting paternal genealogies from Northern Italy. Our results confirmed that the genealogy approach is an effective way to obtain reliable Y-STR mutation rate estimates even with a limited number of samples. Moreover, they showed that the impact of multi-step mutations and backmutations is negligible within the temporal scale usually adopted by forensic and genetic genealogy analyses. We then detected a significant association between the number of mutations within genealogies and observed TMRCAs. Therefore, we compared observed and expected TMRCAs by implementing a Bayesian procedure originally designed by Walsh (2001) and showed that the method yields a good performance (up to 96.72%), especially when using the Infinite Alleles Model (IAM).

Indexed as

Chromosomes, Human, YMutation RateAllelesHumansItalyMeiosisMicrosatellite RepeatsPedigree

Identifiers

PMID31227725
PMCPMC6588691

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.