The ancestry and geographical origins of St Helena's liberated Africans

The island of St Helena played a crucial role in the suppression of the transatlantic slave trade. Strategically located in the middle of the South Atlantic, it served as a staging post for the Royal Navy and reception point for enslaved Africans who had been "liberated" from slave ships intercepted by the British. In total, St Helena received approximately 27,000 liberated Africans between 1840 and 1867. Written sources suggest that the majority of these individuals came from West Central Africa, but their precise origins are unknown. Here, we report the results of ancient DNA analyses that we conducted as part of a wider effort to commemorate St Helena's liberated Africans and to restore knowledge of their lives and experiences. We generated partial genomes (0.1-0.5×) for 20 individuals whose remains had been recovered during archaeological excavations on the island. We compared their genomes with genotype data for over 3,000 present-day individuals from 90 populations across sub-Saharan Africa and conclude that the individuals most likely originated from different source populations within the general area between northern Angola and Gabon. We also find that the majority (17/20) of the individuals were male, supporting a well-documented sex bias in the latter phase of the transatlantic slave trade. The study expands our understanding of St Helena's liberated African community and illustrates how ancient DNA analyses can be used to investigate the origins and identities of individuals whose lives were bound up in the story of slavery and its abolition.

Methods and Research Hotspots of Forensic Kinship Testing

Kinship testing is widely needed in forensic science practice. This paper reviews the definitions of common concepts, and summarizes the basic principles, advantages and disadvantages, and application scope of kinship analysis methods, including identity by state (IBS) method, likelihood ratio (LR) method, method of moment (MoM), and identity by descent (IBD) segment method. This paper also discusses the research hotspots of challenging kinship testing, complex kinship testing, forensic genetic genealogy analysis, and non-human biological samples.

Identification Strategy of Biological Half Sibling Relationship

OBJECTIVES

To compare the application value of the likelihood ratio (LR) method and identity by state (IBS) method in the identification involving half sibling relationships, and to provide a reference for the setting of relevant standards for identification of half sibling relationship.

METHODS

(1) Based on the same genetic marker combinations, the reliability of computer simulation method was verified by comparing the distributions of cumulated identity by state score (CIBS) and combined full sibling index in actual cases with the distributions in simulated cases. (2) In different numbers of three genetic marker combinations, the simulation of full sibling, half sibling and unrelated individual pairs, each 1 million pairs, was obtained; the CIBS, as well as the corresponding types of cumulative LR parameters, were calculated. (3) The application value of LR method was compared with that of IBS method, by comparing the best system efficiency provided by LR method and IBS method when genetic markers in different amounts and of different types and accuracy were applied to distinguish the above three relational individual pairs. (4) According to the existing simulation data, the minimum number of genetic markers required to distinguish half siblings from the other two relationships using different types of genetic markers was estimated by curve fitting.

RESULTS

(1) After the rank sum test, under the premise that the real relationship and the genetic marker combination tested were the same, there was no significant difference between the simulation method and the results obtained in the actual case. (2) In most cases, under the same conditions, the system effectiveness obtained by LR method was greater than that by IBS method. (3) According to the existing data, the number of genetic markers required for full-half siblings and half sibling identification could be obtained by curve fitting when the system effectiveness reached 0.95 or 0.99.

CONCLUSIONS

When distinguishing half sibling from full sibling pairs or unrelated pairs, it is recommended to give preference to the LR method, and estimate the required number of markers according to the identification types and the population data, to ensure the identification effect.

Genetic Diversity of Common Olive (Olea europaea L.) Cultivars from Nikita Botanical Gardens Collection Revealed Using RAD-Seq Method

In different countries, interest in the commercial cultivation of the olive has recently greatly increased, which has led to the expansion of its range. The Crimean Peninsula is the northern limit of the common olive (Olea europaea L.) range. A unique collection of common olive's cultivars and hybrids has been collected in the Nikitsky Botanical Gardens (NBG). The aim of this study was to assess the genetic diversity of 151 samples (total of several biological replicates of 46 olive cultivars including 29 introduced and 11 indigenous genotypes) using the ddRAD sequencing method. Structural analysis showed that the studied samples are divided into ten groups, each of which mainly includes cultivars of the same origin. Cultivars introduced to the Crimean Peninsula from different regions formed separate groups, while local cultivars joined different groups depending on their origin. Cultivars of Crimean origin contain admixtures of mainly Italian and Caucasian cultivars' genotypes. Our study showed that the significant number of Crimean cultivars contains an admixture of the Italian cultivar "Coreggiolo". Genetic analysis confirmed the synonymy for the cv. "Otur" and "Nikitskaya 2", but not for the other four putative synonyms. Our results revealed the genetic diversity of the olive collection of NBG and provided references for future research studies, especially in selection studies for breeding programs.

Genotype Value Decomposition: Simple Methods for the Computation of Kernel Statistics

Recent advances in sequencing technologies enable genome-wide analyses for thousands of individuals. The sequential kernel association test (SKAT) is a widely used method to test for associations between a phenotype and a set of rare variants. As the sample size of human genetics studies increases, the computational time required to calculate a kernel is becoming more and more problematic. In this study, a new method to obtain kernel statistics without calculating a kernel matrix is proposed. A simple method for the computation of two kernel statistics, namely, a kernel statistic based on a genetic relationship matrix (GRM) and one based on an identity by state (IBS) matrix, are proposed. By using this method, calculation of the kernel statistics can be conducted using vector calculation without matrix calculation. The proposed method enables one to conduct SKAT for large samples of human genetics.

The challenges of maintaining genetic privacy

Two studies suggest that a determined adversary may be able to obtain genetic information without permission from some genealogy databases.

Attacks on genetic privacy via uploads to genealogical databases

Direct-to-consumer (DTC) genetics services are increasingly popular, with tens of millions of customers. Several DTC genealogy services allow users to upload genetic data to search for relatives, identified as people with genomes that share identical by state (IBS) regions. Here, we describe methods by which an adversary can learn database genotypes by uploading multiple datasets. For example, an adversary who uploads approximately 900 genomes could recover at least one allele at SNP sites across up to 82% of the genome of a median person of European ancestries. In databases that detect IBS segments using unphased genotypes, approximately 100 falsified uploads can reveal enough genetic information to allow genome-wide genetic imputation. We provide a proof-of-concept demonstration in the GEDmatch database, and we suggest countermeasures that will prevent the exploits we describe.

A Log-Ratio Biplot Approach for Exploring Genetic Relatedness Based on Identity by State

The detection of cryptic relatedness in large population-based cohorts is of great importance in genome research. The usual approach for detecting closely related individuals is to plot allele sharing statistics, based on identity-by-state or identity-by-descent, in a two-dimensional scatterplot. This approach ignores that allele sharing data across individuals has in reality a higher dimensionality, and neither regards the compositional nature of the underlying counts of shared genotypes. In this paper we develop biplot methodology based on log-ratio principal component analysis that overcomes these restrictions. This leads to entirely new graphics that are essentially useful for exploring relatedness in genetic databases from homogeneous populations. The proposed method can be applied in an iterative manner, acting as a looking glass for more remote relationships that are harder to classify. Datasets from the 1,000 Genomes Project and the Genomes For Life-GCAT Project are used to illustrate the proposed method. The discriminatory power of the log-ratio biplot approach is compared with the classical plots in a simulation study. In a non-inbred homogeneous population the classification rate of the log-ratio principal component approach outperforms the classical graphics across the whole allele frequency spectrum, using only identity by state. In these circumstances, simulations show that with 35,000 independent bi-allelic variants, log-ratio principal component analysis, combined with discriminant analysis, can correctly classify relationships up to and including the fourth degree.

Formula Derivation for the Probability Distribution of IBS Score in Unrelated Individual Pairs

OBJECTIVES

To derive the probability equation given by STR allele frequencies of identity by state （IBS） score shared by unrelated individual pairs.

METHODS

By comparing the STR genotypes of two unrelated individuals, three mutually exclusive combinations could be obtained： （1） sharing 2 identical alleles, a₂=1, otherwise a₂=0; （2） sharing 1 identical allele, a₁=1, otherwise a₁=0; （3） sharing 0 identical allele, a₀=1, otherwise a₀=0. And the IBS score of the one STR locus in this unrelated individual pair could be given by the formula： ibs=2a₂+a₁. The probability of a₂=1 （p₂）, a₁=1 （p₁） and a₀=1 （p₀） were derived and expressed in powers of the allele frequencies. Subsequently, for a genotyping system including n independent STR loci, the characteristics of binomial distribution of IBS score shared by a pair of unrelated individuals could be given by p₂_l and p₁_l （l=1, 2, …, n）.

RESULTS

All the general equations of p₂, p₁ and p₀ were derived from the basic conceptions of a₂, a₁ and a₀, respectively. Given f_i （i=1, 2, …, m） as the ith allele frequency of a STR locus, the general equations of p₂, p₁ and p₀ could be respectively expressed in powers of f_i： [Formula: see text],[Formula: see text] and [Formula: see text]. The sum of p₂, p₁ and p₀ must be equal to 1. Then, the binomial distribution of IBS score shared by unrelated individual pairs genotyped with n independently STR loci could be written by： IBS~B（2n, π）, and the general probability, π, could be given by the formula： [Formula: see text].

CONCLUSIONS

In the biological full sibling identification, the probability of null hypothesis corresponding to any specific IBS score can be directly calculated by the general equations presented in this study, which is the basement of the evidence explanation.

The Effects of Both Recent and Long-Term Selection and Genetic Drift Are Readily Evident in North American Barley Breeding Populations

Barley was introduced to North America ∼400 yr ago but adaptation to modern production environments is more recent. Comparisons of allele frequencies among growth habits and spike (inflorescence) types in North America indicate that significant genetic differentiation has accumulated in a relatively short evolutionary time span. Allele frequency differentiation is greatest among barley with two-row vs. six-row spikes, followed by spring vs. winter growth habit. Large changes in allele frequency among breeding programs suggest a major contribution of genetic drift and linked selection on genetic variation. Despite this, comparisons of 3613 modern North American cultivated barley breeding lines that differ for spike-type and growth habit permit the discovery of 142 single nucleotide polymorphism (SNP) outliers putatively linked to targets of selection. For example, SNPs within the Cbf4, Ppd-H1, and Vrn-H1 loci, which have previously been associated with agronomically adaptive phenotypes, are identified as outliers. Analysis of extended haplotype sharing identifies genomic regions shared within and among breeding populations, suggestive of a number of genomic regions subject to recent selection. Finally, we are able to identify recent bouts of gene flow between breeding populations that could point to the sharing of agronomically adaptive variation. These results are supported by pedigrees and breeders’ understanding of germplasm sharing.

Estimating heritability of complex traits from genome-wide association studies using IBS-based Haseman-Elston regression

Exploring heritability of complex traits is a central focus of statistical genetics. Among various previously proposed methods to estimate heritability, variance component methods are advantageous when estimating heritability using markers. Due to the high-dimensional nature of data obtained from genome-wide association studies (GWAS) in which genetic architecture is often unknown, the most appropriate heritability estimator model is often unclear. The Haseman–Elston (HE) regression is a variance component method that was initially only proposed for linkage studies. However, this study presents a theoretical basis for a modified HE that models linkage disequilibrium for a quantitative trait, and consequently can be used for GWAS. After replacing identical by descent (IBD) scores with identity by state (IBS) scores, we applied the IBS-based HE regression to single-marker association studies (scenario I) and estimated the variance component using multiple markers (scenario II). In scenario II, we discuss the circumstances in which the HE regression and the mixed linear model are equivalent; the disparity between these two methods is observed when a covariance component exists for the additive variance. When we extended the IBS-based HE regression to case-control studies in a subsequent simulation study, we found that it provided a nearly unbiased estimate of heritability, more precise than that estimated via the mixed linear model. Thus, for the case-control scenario, the HE regression is preferable. GEnetic Analysis Repository (GEAR; http://sourceforge.net/p/gbchen/wiki/GEAR/) software implemented the HE regression method and is freely available.

Autosomal recessive disease in children of consanguineous parents: inferences from the proportion of compound heterozygotes

This short communication deals with the questions of how to calculate the expected proportion of compound heterozygous patients among affected offspring of consanguineous parents, and how, from an observed proportion of compound heterozygotes, to calculate both the proportion of homozygotes not identical by descent and the frequency of pathogenic alleles in the population. This estimate of allele frequency may be useful when dealing with populations with a considerable number of consanguineous matings.