Ancestry Estimation in Practice

The medicolegal system relies on forensic anthropologists to construct accurate biological profiles from skeletal remainsto narrow the pool of potential missing persons and provide support for positive identifications. The ancestry estimation component of theprofile offers physical descriptions of decedents through a combination of metric analysis and the interpretation of discrete traits believedto correlate with visible physical features. Forensic anthropologists employed in medical examiners’ offices in the United States regularlyconstruct these profiles in casework. However, ancestry estimation methods have been questioned in their ability to accurately describe theracial classification of the deceased. Although validation studies have documented the accuracy of ancestry estimation methods on skeletalcollections, it is unknown how well they operate in forensic casework and the assumption that methods mirror the results observed inacademic research studies remains unproven. In an effort to understand how well methods preform, this research was designed to evaluatethe accuracy ancestry estimation practices within three medical examiners’ offices in the United States. The results show an accuracy rateof 99% among 177 cases when both definitive and ambiguous ancestral and racial terminology was used to describe remains. Becauseunidentified cases lack antemortem information, it remains unknown if the ancestral assessments of the 280 unidentified individualsincluded in this study confer the same level of accuracy shown in resolved cases. The results presented here are informative not only forthe vital statistics obtained, but also for what this data reveals about the factors influencing ancestry estimation in practice.

Explanation of Ancestry Estimation in Forensic Anthropology Textbooks

The way we teach about race and racism can have profound impacts on undergraduate learners, both positive and negative. Textbooks represent a space in which hidden curriculum about race can cement misconceptions and biologically essentialist thinking, leading to the ongoing support of practices that harm racially minoritized populations. In this study, I critically examine five popular introductory level, undergraduate, forensic anthropology textbooks, with attention to chapters on ancestry estimation, and offer recommendations for supplementary or alternative content. Specific coverage of core concepts related to race and ancestry estimation practices in forensic anthropology are evaluated, as well as the order of presentation and consistency of key messages. Though each chapter focuses on distinct examples and approaches, none cover all of the concepts or present a consistent message about ancestry estimation as it pertains to the biological race concept. In particular, messaging within each chapter demonstrates some ambiguity in the distinction between race and ancestry, while also presenting a narrative through which racial typology practices are delineated as “in the past” and distinct from current ancestry estimation practices. These results demonstrate a need, at the undergraduate level, for a more explicit discussion of the biological race myth in lieu of traditional approaches that focus on demonstrating the practicality and validity of such methods. Finally, detailed presentations of ancestry estimation

ANINet: a deep neural network for skull ancestry estimation

Background Ancestry estimation of skulls is under a wide range of applications in forensic science, anthropology, and facial reconstruction. This study aims to avoid defects in traditional skull ancestry estimation methods, such as time-consuming and labor-intensive manual calibration of feature points, and subjective results. Results This paper uses the skull depth image as input, based on AlexNet, introduces the Wide module and SE-block to improve the network, designs and proposes ANINet, and realizes the ancestry classification. Such a unified model architecture of ANINet overcomes the subjectivity of manually calibrating feature points, of which the accuracy and efficiency are improved. We use depth projection to obtain the local depth image and the global depth image of the skull, take the skull depth image as the object, use global, local, and local + global methods respectively to experiment on the 95 cases of Han skull and 110 cases of Uyghur skull data sets, and perform cross-validation. The experimental results show that the accuracies of the three methods for skull ancestry estimation reached 98.21%, 98.04% and 99.03%, respectively. Compared with the classic networks AlexNet, Vgg-16, GoogLenet, ResNet-50, DenseNet-121, and SqueezeNet, the network proposed in this paper has the advantages of high accuracy and small parameters; compared with state-of-the-art methods, the method in this paper has a higher learning rate and better ability to estimate. Conclusions In summary, skull depth images have an excellent performance in estimation, and ANINet is an effective approach for skull ancestry estimation.

Terminology Used to Describe Human Variation in Forensic Anthropology

To understand the implications of the forensic anthropological practice of “ancestry” estimation, we explore terminology that has been employed in forensic anthropological research. The goal is to evaluate how such terms can often circulate within social contexts as a result, which may center forensic anthropologists as constituting “race” itself through analysis and categorization. This research evaluates terminology used in anthropological articles of the Journal of Forensic Sciences between 1972 and 2020 (n = 314). Terminology was placed into two categories: classifiers and descriptors. Classifiers were standardized into one of five options: “race,” “ancestry,” “population,” “ethnic,” or “other.” Descriptors included terms used to describe individuals within these classificatory systems. We also compared these terms to those in the NamUs database and the U.S. census. Our results found that the terms “ancestry” and “race” are often conflated and “ancestry” largely supplanted “race” in the 1990s without a similar change in research approach. The NamUs and census terminology are not the same as that used in forensic anthropological research; illustrating a disconnect in the terms used to identify the missing, unidentified, and in social contexts with those used in anthropological research. We provide histories of all of these terms and conclude with suggestions for how to use terminology in the future. It is important for forensic anthropologists to be cognizant of the terms they use in medicolegal contexts, publications, and in public and/or professional spaces. The continued use of misrepresentative and improper language further marginalizes groups and perpetuates oppression rooted in systemic racism.

Taurine and Indicine Haplotype Representation in Advanced Generation Individuals From Three American Breeds

Development of the American Breeds of beef cattle began in the 1920s as breeders and U. S. Experiment Station researchers began to create Bos taurus taurus × Bos taurus indicus hybrids using Brahman as the B. t. indicus source. By 1954, U.S. Breed Associations had been formed for Brangus (5/8 Angus × 3/8 Brahman), Beefmaster (½ Brahman × ¼ Shorthorn × ¼ Hereford), and Santa Gertrudis (5/8 Shorthorn × 3/8 Brahman). While these breeds were developed using mating designs expected to create base generation animals with the required genome contributions from progenitor breeds, each association has now registered advanced generation animals in which selection or drift may have caused the realized genome compositions to differ from initial expected proportions. The availability of high-density SNP genotypes for 9,161 Brangus, 3,762 Beefmaster, and 1,942 Santa Gertrudis animals allowed us to compare the realized genomic architectures of breed members to the base generation expectations. We used RFMix to estimate local ancestry and identify genomic regions in which the proportion of Brahman ancestry differed significantly from a priori expectations. For all three breeds, lower than expected levels of Brahman composition were found genome-wide, particularly in early-generation animals where we demonstrate that selection on beef production traits was likely responsible for the taurine enrichment. Using a proxy for generation number, we also contrasted the genomes of early- and advanced-generation animals and found that the indicine composition of the genome has increased with generation number likely due to selection on adaptive traits. Many of the most-highly differentiated genomic regions were breed specific, suggesting that differences in breeding objectives and selection intensities exist between the breeds. Global ancestry estimation is commonly performed in admixed animals to control for stratification in association studies. However, local ancestry estimation provides the opportunity to investigate the evolution of specific chromosomal segments and estimate haplotype effects on trait variation in admixed individuals. Investigating the genomic architecture of the American Breeds not only allows the estimation of indicine and taurine genome proportions genome-wide, but also the locations within the genome where either taurine or indicine alleles confer a selective advantage.

COPILOT: a Containerised wOrkflow for Processing ILlumina genOtyping daTa

Background: The Illumina genotyping microarrays generate data in image format, which is processed by the platform-specific software GenomeStudio, followed by an array of complex bioinformatics analyses. This process can be time-consuming, lead to reproducibility errors, and be a daunting task for novice bioinformaticians. Results: Here we introduce the COPILOT (Containerised wOrkflow for Processing ILlumina genOtyping daTa) protocol, which provides an in-depth and clear guide to process raw Illumina genotype data in GenomeStudio, followed by a containerised workflow to automate an array of complex bioinformatics analyses involved in a GWAS quality control (QC). The COPILOT protocol was applied to two independent cohorts consisting of 2791 and 479 samples genotyped on the Infinium Global Screening (GSA) array with Multi-disease (MD) drop-in (~750,000 markers) and the Infinium H3Africa consortium array (~2,200,000 markers) respectively. Following the COPILOT protocol, an average sample quality improvement of 1.24% was observed across sample call rates, with notable improvement for low-quality samples. For example, from the 3270 samples processed, 141 samples had an initial sample call rate below 98%, averaging 96.6% (95% CI 95.6-97.7%), which is considered below the acceptable sample call rate threshold for a typical GWAS analysis. However, following the COPILOT protocol, all 141 samples had a call rate above 98% after QC and averaged 99.6% (95% CI 99.5-99.7%). In addition, the COPILOT pipeline automatically identified potential data issues, including gender discrepancies, heterozygosity outliers, related individuals, and population outliers through ancestry estimation. Conclusions: The COPILOT protocol makes processing Illumina genotyping data transparent, effortless and reproducible. The container is deployable on multiple platforms, improves data quality, and the end product is analysis-ready PLINK formatted data, with a comprehensive and interactive summary report to guide the user for further data analyses.

Genetic Ancestry Inference and Its Application for the Genetic Mapping of Human Diseases

Admixed populations arise when two or more ancestral populations interbreed. As a result of this admixture, the genome of admixed populations is defined by tracts of variable size inherited from these parental groups and has particular genetic features that provide valuable information about their demographic history. Diverse methods can be used to derive the ancestry apportionment of admixed individuals, and such inferences can be leveraged for the discovery of genetic loci associated with diseases and traits, therefore having important biomedical implications. In this review article, we summarize the most common methods of global and local genetic ancestry estimation and discuss the use of admixture mapping studies in human diseases.

Morphology of Intersectionality

Forensic anthropologists operate within a medico-legal context, performing analyses to estimate a biological profile (ancestry, age, sex, stature) and make observations on trauma, pathological conditions, taphonomy, and other anomalies evident in skeletal remains. These findings are reported to the appropriate requesting agency to narrow down the possible identity of the unknown individual and to understand the death event. Boundaries of identity and the terminology used to describe and explain identity are dynamic and intersectional. Ancestry estimation is important because there is a bridge between ancestral categories and sociocultural labels. Yet, a lack of agreement between ancestry estimates and social identifiers exists for certain groups. To better understand why this disagreement exists, a three-component concept (bio-origin identity, public ancestral-racial identity, and self ancestral-racial identity) modeled after sociological frameworks is employed. This article explores the identity of a single individual within the study sample using the three-component concept. Results highlight that discordance exists between the identity approximated by ancestry estimation and the application of this identity to the sociocultural context. Understanding the importance of the intersectional nature of the terminology used in instances of forensic identification is imperative so as to not hinder identifications and marginalize groups.