Imputation approach for deducing a complete mitogenome sequence from low-depth-coverage next-generation sequencing data: application to ancient remains from the Moon Pyramid, Mexico

Missing data in bioarchaeology II: A test of ordinal and continuous data imputation

OBJECTIVES

Previous research has shown that while missing data are common in bioarchaeological studies, they are seldom handled using statistically rigorous methods. The primary objective of this article is to evaluate the ability of imputation to manage missing data and encourage the use of advanced statistical methods in bioarchaeology and paleopathology. An overview of missing data management in biological anthropology is provided, followed by a test of imputation and deletion methods for handling missing data.

MATERIALS AND METHODS

Missing data were simulated on complete datasets of ordinal (n = 287) and continuous (n = 369) bioarchaeological data. Missing values were imputed using five imputation methods (mean, predictive mean matching, random forest, expectation maximization, and stochastic regression) and the success of each at obtaining the parameters of the original dataset compared with pairwise and listwise deletion.

RESULTS

In all instances, listwise deletion was least successful at approximating the original parameters. Imputation of continuous data was more effective than ordinal data. Overall, no one method performed best and the amount of missing data proved a stronger predictor of imputation success.

DISCUSSION

These findings support the use of imputation methods over deletion for handling missing bioarchaeological and paleopathology data, especially when the data are continuous. Whereas deletion methods reduce sample size, imputation maintains sample size, improving statistical power and preventing bias from being introduced into the dataset.

Recovery of mitogenomes from whole genome sequences to infer maternal diversity in 1883 modern taurine and indicine cattle

Maternal diversity based on a sub-region of mitochondrial genome or variants were commonly used to understand past demographic events in livestock. Additionally, there is growing evidence of direct association of mitochondrial genetic variants with a range of phenotypes. Therefore, this study used complete bovine mitogenomes from a large sequence database to explore the full spectrum of maternal diversity. Mitogenome diversity was evaluated among 1883 animals representing 156 globally important cattle breeds. Overall, the mitogenomes were diverse: presenting 11 major haplogroups, expanding to 1309 unique haplotypes, with nucleotide diversity 0.011 and haplotype diversity 0.999. A small proportion of African taurine (3.5%) and indicine (1.3%) haplogroups were found among the European taurine breeds and composites. The haplogrouping was largely consistent with the population structure derived from alternate clustering methods (e.g. PCA and hierarchical clustering). Further, we present evidence confirming a new indicine subgroup (I1a, 64 animals) mainly consisting of breeds originating from China and characterised by two private mutations within the I1 haplogroup. The total genetic variation was attributed mainly to within-breed variance (96.9%). The accuracy of the imputation of missing genotypes was high (99.8%) except for the relatively rare heteroplasmic genotypes, suggesting the potential for trait association studies within a breed.

The Mitochondrial DNA Landscape of Modern Mexico

Mexico is a rich source for anthropological and population genetic studies with high diversity in ethnic and linguistic groups. The country witnessed the rise and fall of major civilizations, including the Maya and Aztec, but resulting from European colonization, the population landscape has dramatically changed. Today, the majority of Mexicans do not identify themselves as Indigenous but as admixed, and appear to have very little in common with their pre-Columbian predecessors. However, when the maternally inherited mitochondrial (mt)DNA is investigated in the modern Mexican population, this is not the case. Control region sequences of 2021 samples deriving from all over the country revealed an overwhelming Indigenous American legacy, with almost 90% of mtDNAs belonging to the four major pan-American haplogroups A2, B2, C1, and D1. This finding supports a very low European contribution to the Mexican gene pool by female colonizers and confirms the effectiveness of employing uniparental markers as a tool to reconstruct a country’s history. In addition, the distinct frequency and dispersal patterns of Indigenous American and West Eurasian clades highlight the benefit such large and country-wide databases provide for studying the impact of colonialism from a female perspective and population stratification. The importance of geographical database subsets not only for forensic application is clearly demonstrated.

Species Diversity and Phylogenetic Relationships of Olive Lace Bugs (Hemiptera: Tingidae) Found in South Africa

Olive lace bugs (Hemiptera: Tingidae) are small sap-sucking insects that feed on wild and cultivated Olea europaea. The diversity of olive lace bug species in South Africa, the most important olive producer on the continent, has been incompletely surveyed. Adult specimens were collected in the Western Cape province for morphological and DNA-based species identification, and sequencing of complete mitogenomes. Cysteochila lineata, Plerochila australis, Neoplerochila paliatseasi and Neoplerochila sp. were found at 12 sites. Intra- and interspecific genetic divergences and phylogenetic clustering in 30 species in 18 genera of Tingidae using new and publicly available DNA barcodes showed high levels of congruity between taxonomic and genetic data. The phylogenetic position of the four species found in South Africa was inferred using new and available mitogenomes of Tingidae. Notably, olive lace bugs formed a cluster of closely related species. However, Cysteochila was non-monophyletic as C. lineata was recovered as a sister species to P. australis whereas Cysteochila chiniana, the other representative of the genus, was grouped with Trachypeplus jacobsoni and Tingis cardui in a different cluster. This result suggests that feeding on O. europaea may have a common origin in Tingidae and warrants future research on potential evolutionary adaptations of olive lace bugs to this plant host.

Ancient DNA Studies in Pre-Columbian Mesoamerica

Mesoamerica is a historically and culturally defined geographic area comprising current central and south Mexico, Belize, Guatemala, El Salvador, and border regions of Honduras, western Nicaragua, and northwestern Costa Rica. The permanent settling of Mesoamerica was accompanied by the development of agriculture and pottery manufacturing (2500 BCE-150 CE), which led to the rise of several cultures connected by commerce and farming. Hence, Mesoamericans probably carried an invaluable genetic diversity partly lost during the Spanish conquest and the subsequent colonial period. Mesoamerican ancient DNA (aDNA) research has mainly focused on the study of mitochondrial DNA in the Basin of Mexico and the Yucatán Peninsula and its nearby territories, particularly during the Postclassic period (900-1519 CE). Despite limitations associated with the poor preservation of samples in tropical areas, recent methodological improvements pave the way for a deeper analysis of Mesoamerica. Here, we review how aDNA research has helped discern population dynamics patterns in the pre-Columbian Mesoamerican context, how it supports archaeological, linguistic, and anthropological conclusions, and finally, how it offers new working hypotheses.

MitoIMP: A Computational Framework for Imputation of Missing Data in Low-Coverage Human Mitochondrial Genome

The incompleteness of partial human mitochondrial genome sequences makes it difficult to perform relevant comparisons among multiple resources. To deal with this issue, we propose a computational framework for deducing missing nucleotides in the human mitochondrial genome. We applied it to worldwide mitochondrial haplogroup lineages and assessed its performance. Our approach can deduce the missing nucleotides with a precision of 0.99 or higher in most human mitochondrial DNA lineages. Furthermore, although low-coverage mitochondrial genome sequences often lead to a blurred relationship in the multidimensional scaling analysis, our approach can correct this positional arrangement according to the corresponding mitochondrial DNA lineages. Therefore, our framework will provide a practical solution to compensate for the lack of genome coverage in partial and fragmented human mitochondrial genome sequences. In this study, we developed an open-source computer program, MitoIMP, implementing our imputation procedure. MitoIMP is freely available from https://github.com/omics-tools/mitoimp.