Effects of sample selection bias on the accuracy of population structure and ancestry inference

Comparative analysis of allele variation using allele frequencies according to sample size in Korean population

Background

Allele frequency using short tandem repeats (STRs) is used to calculate likelihood ratio for database match, to interpret DNA mixture and to estimate ethnic groups in forensic genetics. In Korea, three population studies for 23 STR loci have been conducted with different sample size for forensic purposes.

Objective

We performed comparative analysis to determine how the difference of sample size affects the allele frequency and allele variation within same ethnic population (i.e. Korean). Furthermore, this study was conducted to check how the sampling group and multiplex kit also affect allele variation such as rare alleles and population specific alleles.

Methods

To compare allele variation, we used allele frequencies of three population data published from three Korean forensic research groups. Allele frequencies were calculated using different sample sizes and multiplex kits: 526, 1000, and 2000 individuals, respectively.

Results

The results showed the different distribution of allele frequencies in some loci. There was also a difference in the number of rare alleles observed by the sample size and sampling bias. In particular, an allele of 9.1 in the D2S441 locus was not observed in population study with 526 individuals due to multiplex kits.

Conclusion

Because the allele frequencies play an important role in forensic genetics, even if the samples are derived from the same population, it is important to consider the effects of sample size, sampling bias, and selection of multiplex kits in population studies.

Dating genomic variants and shared ancestry in population-scale sequencing data

The origin and fate of new mutations within species is the fundamental process underlying evolution. However, while much attention has been focused on characterizing the presence, frequency, and phenotypic impact of genetic variation, the evolutionary histories of most variants are largely unexplored. We have developed a nonparametric approach for estimating the date of origin of genetic variants in large-scale sequencing data sets. The accuracy and robustness of the approach is demonstrated through simulation. Using data from two publicly available human genomic diversity resources, we estimated the age of more than 45 million single-nucleotide polymorphisms (SNPs) in the human genome and release the Atlas of Variant Age as a public online database. We characterize the relationship between variant age and frequency in different geographical regions and demonstrate the value of age information in interpreting variants of functional and selective importance. Finally, we use allele age estimates to power a rapid approach for inferring the ancestry shared between individual genomes and to quantify genealogical relationships at different points in the past, as well as to describe and explore the evolutionary history of modern human populations.

Factors influencing participation in controlled human infection models: a pooled analysis from six enteric fever studies

Background: Enteric fever is an acute febrile-illness caused by infection with the human-restricted Salmonella serovars Typhi and Paratyphi. Controlled human infection models (CHIM) of S. Typhi and Paratyphi infection are used to accelerate vaccine development and to better understand host-pathogen interactions. The primary motivations for participants to take part in these studies are unknown. We studied participant motivations, attitudes and the factors influencing CHIM study participation. Methods: Participant surveys were nested in six enteric fever CHIM studies conducted at a single centre in Oxford, UK, between 2011 and 2017. All eligible participants received one invitation to complete an anonymous, self-administered paper or online survey on either day 28 or 60 after challenge. A descriptive analysis was performed on these pooled data. All studies were included, to minimize selection bias. Results: Survey response rates varied from 33.0%-86.1%, yielding 201 participants. In the cohort, 113/198(57.0%) were educated to bachelor’s level, 61.6% were employed, 30.3% were students and 4.6% were unemployed. The most commonly cited motivations for CHIM study participation were a desire to contribute to the progression of medicine (170/201; 84.6%); the prospect of financial reimbursement (166/201; 82.6%) and curiosity about clinical trials (117/201; 57.2%). The majority of respondents (139/197; 70.6%) reported that most people advised them against participation. Conclusion: Motivation to participate in a CHIM study was multi-factorial and heavily influenced by internal drivers beyond monetary reimbursement alone. High educational attainment and employment may be protective factors against financial inducement; however, further research is needed, particularly with CHIM studies expanding to low-income and middle-income countries.

Genetic diversity patterns and domestication origin of soybean

KEY MESSAGE

Genotyping data of a comprehensive Korean soybean collection obtained using a large SNP array were used to clarify global distribution patterns of soybean and address the evolutionary history of soybean. Understanding diversity and evolution of a crop is an essential step to implement a strategy to expand its germplasm base for crop improvement research. Accessions intensively collected from Korea, which is a small but central region in the distribution geography of soybean, were genotyped to provide sufficient data to underpin population genetic questions. After removing natural hybrids and duplicated or redundant accessions, we obtained a non-redundant set comprising 1957 domesticated and 1079 wild accessions to perform population structure analyses. Our analysis demonstrates that while wild soybean germplasm will require additional sampling from diverse indigenous areas to expand the germplasm base, the current domesticated soybean germplasm is saturated in terms of genetic diversity. We then showed that our genome-wide polymorphism map enabled us to detect genetic loci underlying flower color, seed-coat color, and domestication syndrome. A representative soybean set consisting of 194 accessions was divided into one domesticated subpopulation and four wild subpopulations that could be traced back to their geographic collection areas. Population genomics analyses suggested that the monophyletic group of domesticated soybeans was likely originated at a Japanese region. The results were further substantiated by a phylogenetic tree constructed from domestication-associated single nucleotide polymorphisms identified in this study.

MS4A2-rs573790 Is Associated With Aspirin-Exacerbated Respiratory Disease: Replicative Study Using a Candidate Gene Strategy

Aspirin exacerbated respiratory disease (AERD) is a set of diseases of the unified airway, and its physiopathology is related to disruption of the metabolism of arachidonic acid (AA). Genetic association studies in AERD had explored single nucleotide polymorphism (SNPs) in several genes related to many mechanisms (AA metabolism, inflammation, drug metabolism, etc.) but most lack validation stages in second populations. Our aim is to evaluated whether contribution to susceptibility of SNPs reported in other populations are associated with AERD in Mexican Mestizo patients. We developed a replicative study in two stages. In the first, 381 SNPs selected by fine mapping of associated genes, (previously reported in the literature), were integrated into a microarray and tested in three groups (AERD, asthma and healthy controls -HC-) using the GoldenGate array. Results associated to risk based on genetic models [comparing: AERD vs. HC (comparison 1, C1), AERD vs. asthma (C2), and asthma vs. HC (C3)] were validated in the second stage in other population groups using qPCR. In the first stage, we identified 11 SNPs associated with risk in C1.The top SNPs were ACE-rs4309C (p = 0.0001) and MS4A2-rs573790C (p = 0.0002). In C2, we detected 14 SNPs, including ACE-rs4309C (p = 0.0001). In C3, we found MS4A2-rs573790C (p = 0.001). Using genetic models, C1 MS4A2-rs57370 CC (p = 0.001), and ACE-rs4309 CC (p = 0.002) had associations. In C2 ACE-rs4309 CC (p = 0.0001) and C3 MS4A2-rs573790 CC (p = 0.001) were also associate with risk. In the second stage, only MS4A2-rs573790 CC had significance in C1 and C3 (p = 0.008 and p = 0.03). We concluded that rs573790 in the MS4A2 gene is the only SNP that supports an association with AERD in Mexican Mestizo patients in both stages of the study.

New ABCC2 rs3740066 and rs2273697 Polymorphisms Identified in a Healthy Colombian Cohort

Multidrug resistance-associated proteins (MRP) 1 and 2 belong to the ABC (ATP-Binding Cassette) transporters. These transport proteins are involved in the removal of various drugs and xenobiotics, as well as in multiple physiological, pathological, and pharmacological processes. There is a strong correlation between different polymorphisms and their clinical implication in resistance to antiepileptic drugs, anticancer, and anti-infective agents. In our study, we evaluated exon regions of MRP1 (ABCC1)/MRP2 (ABCC2) in a Colombian cohort of healthy subjects to determine single nucleotide polymorphisms (SNPs) and to determine the allelic and genomic frequency. Results showed there are SNPs in our population that have been previously reported for both MRP1/ABCC1 (rs200647436, rs200624910, rs150214567) and MRP2/ABCC2 (rs2273697, rs3740066, rs142573385, rs17216212). Additionally, 13 new SNPs were identified. Evidence also shows a significant clinical correlation for polymorphisms rs3740066 and rs2273697 in the transport of multiple drugs, which suggests a genetic variability in regards to that reported in other populations.

Population Structure and Phylogenetic Relationships in a Diverse Panel of Brassica rapa L

The crop species Brassica rapa L. has significant economic importance around the world. However, the global distribution and complex evolutionary history of the species has made investigating its genetic population structure difficult. Crop domestication and improvement has resulted in extreme phenotypic diversity and subspecies that are used for oilseed, food for human consumption, and fodder for livestock. These subspecies include the oilseed morphotypes. oleifera (turnip rape), ssp. dichotoma (brown sarson/toria), ssp. trilocularis (yellow sarson); ssp. rapa (turnip); and Asian leafy vegetables ssp. pekinensis (Chinese cabbage), ssp. chinensis (bok choy), ssp. nipposinica (mizuna/mibuna), ssp. rapifera (rapini/broccoli rabe), ssp. narinosa (tatsoi), ssp parachinensis (choy sum), and ssp. perviridis (komatsuna). To date, studies have had insufficient sampling to determine the relationship of all morphotypes, especially oilseed morphotypes, and questions remain over the contribution of morphotype and geographic origin to population structure. We used genotyping-by-sequencing to score 18,272 single nucleotide polymorphism markers in a globally diverse panel of 333 B. rapa National Plant Germplasm System accessions that included 10 recognized subspecies. Our population genetic and phylogenetic analyses were broadly congruent and revealed five subpopulations that were largely reflective of morphotype and geography. These subpopulations were 1. European turnips/oilseed, 2. Asian turnips/oilseed, 3. yellow/brown sarson (ssp. trilocularis and ssp. dichotoma), 4. Chinese cabbage (ssp. pekinensis), and 5. bok choy, choy sum, and tatsoi (ssp. chinensis, ssp. parachinensis, ssp. narinosa). Additionally, we found evidence of polyphyly and/or paraphyly, particularly for oilseed morphotypes (ssp. oleifera and ssp. dichotoma) and turnips. The results of this study have provided improved resolution to the genetic and phylogenetic relationships of subspecies within the species B. rapa. Understanding of these relationships is key to the future genetic study and improvement of this globally important crop species.

Genetic Programming of Hypertension

The heritability of hypertension (HTN) is widely recognized and as a result, extensive studies ranging from genetic linkage analyses to genome-wide association studies are actively ongoing to elucidate the etiology of both monogenic and polygenic forms of HTN. Due to the complex nature of essential HTN, however, single genes affecting blood pressure (BP) variability remain difficult to isolate and identify and have rendered the development of single-gene targeted therapies challenging. The roles of other causative factors in modulating BP, such as gene-environment interactions and epigenetic factors, are increasingly being brought to the forefront. In this review, we discuss the various monogenic HTN syndromes and corresponding pathophysiologic mechanisms, the different methodologies employed in genetic studies of essential HTN, the mechanisms for epigenetic modulation of essential HTN, pharmacogenomics and HTN, and finally, recent advances in genetic studies of essential HTN in the pediatric population.

Efficient analysis of large datasets and sex bias with ADMIXTURE

BACKGROUND

A number of large genomic datasets are being generated for studies of human ancestry and diseases. The ADMIXTURE program is commonly used to infer individual ancestry from genomic data.

RESULTS

We describe two improvements to the ADMIXTURE software. The first enables ADMIXTURE to infer ancestry for a new set of individuals using cluster allele frequencies from a reference set of individuals. Using data from the 1000 Genomes Project, we show that this allows ADMIXTURE to infer ancestry for 10,920 individuals in a few hours (a 5 × speedup). This mode also allows ADMIXTURE to correctly estimate individual ancestry and allele frequencies from a set of related individuals. The second modification allows ADMIXTURE to correctly handle X-chromosome (and other haploid) data from both males and females. We demonstrate increased power to detect sex-biased admixture in African-American individuals from the 1000 Genomes project using this extension.

CONCLUSIONS

These modifications make ADMIXTURE more efficient and versatile, allowing users to extract more information from large genomic datasets.

The conservation status of the Galápagos marine iguanas, Amblyrhynchus cristatus: a molecular perspective

Traditionally, conservation management focuses efforts on taxonomic units. However, when the taxa used do not reflect biologically meaningful units, such methods should be reconsidered to avoid the loss of irreplaceable biodiversity. The Galápagos marine iguana (Amblyrhynchus cristatus) is listed as Vulnerable on the IUCN Red List of Threatened Species and is facing growing anthropogenic threats. Currently, management is based on a taxonomy which is questionable in the light of recent molecular data. As such, there is a danger that evolutionarily significant populations may be left vulnerable to extirpation. Herein, we apply molecular data to elucidate the population structure of this species across the Galápagos archipelago, and thus advise conservation management in the absence of a revised taxonomy. Applying a wealth of molecular data including 12 microsatellite loci and 1181 bp of the mitochondrial control region in over 1200 individuals, we delineate distinct populations and prioritize their management. Bayesian population structure analysis revealed 10 distinct population clusters, which we propose as management units (MUs). All MUs are significantly differentiated, with one unit on San Cristóbal Island being particularly distinct in terms of both microsatellite loci and mitochondrial data. Based on estimates of the genetic effective population size (Ne), we find the MUs comprised of populations occurring on Floreana, Española, Marchena, and San Cristóbal to be alarmingly small. In consideration of both Neand anthropogenic threats, we recommend that conservation practitioners focus efforts on Floreana and San Cristóbal islands, and argue that better census size estimates of populations are urgently needed.

Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach

This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447-2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8-30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics.