An efficient method to identify, date, and describe admixture events using haplotype information.

We present fastGLOBETROTTER, an efficient new haplotype-based technique to identify, date, and describe admixture events using genome-wide autosomal data. With simulations, we show how fastGLOBETROTTER reduces computation time by an order of magnitude relative to the related technique GLOBETROTTER without suffering loss of accuracy. We apply fastGLOBETROTTER to a cohort of more than 6000 Europeans from 10 countries, revealing previously unreported admixture signals. In particular, we infer multiple periods of admixture related to East Asian or Siberian-like sources, starting >2000 yr ago, in people living in countries north of the Baltic Sea. In contrast, we infer admixture related to West Asian, North African, and/or Southern European sources in populations south of the Baltic Sea, including admixture dated to ∼300-700 CE, overlapping the fall of the Roman Empire, in people from Belgium, France, and parts of Germany. Our new approach scales to analyzing hundreds to thousands of individuals from a putatively admixed population and, hence, is applicable to emerging large-scale cohorts of genetically homogeneous populations.

The Thai reference exome (T-REx) variant database.

To maximize the potential of genomics in medicine, it is essential to establish databases of genomic variants for ethno-geographic groups that can be used for filtering and prioritizing candidate pathogenic variants. Populations with non-European ancestry are poorly represented among current genomic variant databases. Here, we report the first high-density survey of genomic variants for the Thai population, the Thai Reference Exome (T-REx) variant database. T-REx comprises exome sequencing data of 1092 unrelated Thai individuals. The targeted exome regions common among four capture platforms cover 30.04 Mbp on autosomes and chromosome X. 345 681 short variants (18.27% of which are novel) and 34 907 copy number variations were found. Principal component analysis on 38 469 single nucleotide variants present worldwide showed that the Thai population is most genetically similar to East and Southeast Asian populations. Moreover, unsupervised clustering revealed six Thai subpopulations consistent with the evidence of gene flow from neighboring populations. The prevalence of common pathogenic variants in T-REx was investigated in detail, which revealed subpopulation-specific patterns, in particular variants associated with erythrocyte disorders such as the HbE variant in HBB and the Viangchan variant in G6PD. T-REx serves as a pivotal addition to the current databases for genomic medicine.

Ancestry-informative marker (AIM) SNP panel for the Malay population.

Ancestry-informative markers (AIMs) can be used to infer the ancestry of an individual to minimize the inaccuracy of self-reported ethnicity in biomedical research. In this study, we describe three methods for selecting AIM SNPs for the Malay population (Malay AIM panel) using different approaches based on pairwise FST, informativeness for assignment (In), and PCA-correlated SNPs (PCAIMs). These Malay AIM panels were extracted from genotype data stored in SNP arrays hosted by the Malaysian node of the Human Variome Project (MyHVP) and the Singapore Genome Variation Project (SGVP). In particular, genotype data from a total of 165 Malay individuals were analyzed, comprising data on 117 individual genotypes from the Affymetrix SNP-6 SNP array platform and data on 48 individual genotypes from the OMNI 2.5 Illumina SNP array platform. The HapMap phase 3 database (1397 individuals from 11 populations) was used as a reference for comparison with the Malay genotype data. The accuracy of each resulting Malay AIM panel was evaluated using a machine learning "ancestry-predictive model" constructed by using WEKA, a comprehensive machine learning platform written in Java. A total of 1250 SNPs were finally selected, which successfully identified Malay individuals from other world populations with an accuracy of 90%, but the accuracy decreased to 80% using 157 SNPs according to the pairwise FST method, while a panel of 200 SNPs selected using In and PCAIMs could be used to identify Malay individuals with an accuracy of approximately 80%.

Comprehensive genome assembly reveals genetic diversity and carcass consumption insights in critically endangered Asian king vultures.

The Asian king vulture (AKV), a vital forest scavenger, is facing globally critical endangerment. This study aimed to construct a reference genome to unveil the mechanisms underlying its scavenger abilities and to assess the genetic relatedness of the captive population in Thailand. A reference genome of a female AKV was assembled from sequencing reads obtained from both PacBio long-read and MGI short-read sequencing platforms. Comparative genomics with New World vultures (NWVs) and other birds in the Family Accipitridae revealed unique gene families in AKV associated with retroviral genome integration and feather keratin, contrasting with NWVs' genes related to olfactory reception. Expanded gene families in AKV were linked to inflammatory response, iron regulation and spermatogenesis. Positively selected genes included those associated with anti-apoptosis, immune response and muscle cell development, shedding light on adaptations for carcass consumption and high-altitude soaring. Using restriction site-associated DNA sequencing (RADseq)-based genome-wide single nucleotide polymorphisms (SNPs), genetic relatedness and inbreeding status of five captive AKVs were determined, revealing high genomic inbreeding in two females. In conclusion, the AKV reference genome was established, providing insights into its unique characteristics. Additionally, the potential of RADseq-based genome-wide SNPs for selecting AKV breeders was demonstrated.

Fine-scale subpopulation detection via an SNP-based unsupervised method: A case study on the 1000 Genomes Project resources.

SNP-based information is used in several existing clustering methods to detect shared genetic ancestry or to identify population substructure. Here, we present a methodology, called IPCAPS for unsupervised population analysis using iterative pruning. Our method, which can capture fine-level structure in populations, supports ordinal data, and thus can readily be applied to SNP data. Although haplotypes may be more informative than SNPs, especially in fine-level substructure detection contexts, the haplotype inference process often remains too computationally intensive. In this work, we investigate the scale of the structure we can detect in populations without knowledge about haplotypes; our simulated data do not assume the availability of haplotype information while comparing our method to existing tools for detecting fine-level population substructures. We demonstrate experimentally that IPCAPS can achieve high accuracy and can outperform existing tools in several simulated scenarios. The fine-level structure detected by IPCAPS on an application to the 1000 Genomes Project data underlines its subject heterogeneity.

Comparative genomics and genome-wide SNPs of endangered Eld's deer provide breeder selection for inbreeding avoidance.

Eld's deer, a conserved wildlife species of Thailand, is facing inbreeding depression, particularly in the captive Siamese Eld's deer (SED) subspecies. In this study, we constructed genomes of a male SED and a male Burmese Eld's deer (BED), and used genome-wide single nucleotide polymorphisms to evaluate the genetic purity and the inbreeding status of 35 SED and 49 BED with limited pedigree information. The results show that these subspecies diverged approximately 1.26 million years ago. All SED were found to be purebred. A low proportion of admixed SED genetic material was observed in some BED individuals. Six potential breeders from male SED with no genetic relation to any female SED and three purebred male BED with no relation to more than 10 purebred female BED were identified. This study provides valuable insights about Eld's deer populations and appropriate breeder selection in efforts to repopulate this endangered species while avoiding inbreeding.

Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and structure.

BACKGROUND: The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used for detecting structure. However, it has not been adequately investigated whether the TW statistic is susceptible to type I error, especially in large, complex datasets. Non-parametric, Principal Component Analysis (PCA) based methods for resolving structure have been developed which rely on the TW test. Although PCA-based methods can resolve structure, they cannot infer ancestry. Model-based methods are still needed for ancestry analysis, but they are not suitable for large datasets. We propose a new structure analysis framework for large datasets. This includes a new heuristic for detecting structure and incorporation of the structure patterns inferred by a PCA method to complement STRUCTURE analysis. RESULTS: A new heuristic called EigenDev for detecting population structure is presented. When tested on simulated data, this heuristic is robust to sample size. In contrast, the TW statistic was found to be susceptible to type I error, especially for large population samples. EigenDev is thus better-suited for analysis of large datasets containing many individuals, in which spurious patterns are likely to exist and could be incorrectly interpreted as population stratification. EigenDev was applied to the iterative pruning PCA (ipPCA) method, which resolves the underlying subpopulations. This subpopulation information was used to supervise STRUCTURE analysis to infer patterns of ancestry at an unprecedented level of resolution. To validate the new approach, a bovine and a large human genetic dataset (3945 individuals) were analyzed. We found new ancestry patterns consistent with the subpopulations resolved by ipPCA. CONCLUSIONS: The EigenDev heuristic is robust to sampling and is thus superior for detecting structure in large datasets. The application of EigenDev to the ipPCA algorithm improves the estimation of the number of subpopulations and the individual assignment accuracy, especially for very large and complex datasets. Furthermore, we have demonstrated that the structure resolved by this approach complements parametric analysis, allowing a much more comprehensive account of population structure. The new version of the ipPCA software with EigenDev incorporated can be downloaded from http://www4a.biotec.or.th/GI/tools/ippca.

Predictive SNPs for ß0-thalassemia/HbE disease severity.

ß-Thalassemia/HbE disease has a wide spectrum of clinical phenotypes ranging from asymptomatic to dependent on regular blood transfusions. Ability to predict disease severity is helpful for clinical management and treatment decision making. A thalassemia severity score has been developed from Mediterranean ß-thalassemia patients. However, different ethnic groups may have different allele frequency and linkage disequilibrium structures. Here, Thai ß0-thalassemia/HbE disease genome-wild association studies (GWAS) data of 487 patients were analyzed by SNP interaction prioritization algorithm, interacting Loci (iLoci), to find predictive SNPs for disease severity. Three SNPs from two SNP interaction pairs associated with disease severity were identifies. The three-SNP disease severity risk score composed of rs766432 in BCL11A, rs9399137 in HBS1L-MYB and rs72872548 in HBE1 showed more than 85% specificity and 75% accuracy. The three-SNP predictive score was then validated in two independent cohorts of Thai and Malaysian ß0-thalassemia/HbE patients with comparable specificity and accuracy. The SNP risk score could be used for prediction of clinical severity for Southeast Asia ß0-thalassemia/HbE population.

Iterative pruning PCA improves resolution of highly structured populations.

BACKGROUND: Non-random patterns of genetic variation exist among individuals in a population owing to a variety of evolutionary factors. Therefore, populations are structured into genetically distinct subpopulations. As genotypic datasets become ever larger, it is increasingly difficult to correctly estimate the number of subpopulations and assign individuals to them. The computationally efficient non-parametric, chiefly Principal Components Analysis (PCA)-based methods are thus becoming increasingly relied upon for population structure analysis. Current PCA-based methods can accurately detect structure; however, the accuracy in resolving subpopulations and assigning individuals to them is wanting. When subpopulations are closely related to one another, they overlap in PCA space and appear as a conglomerate. This problem is exacerbated when some subpopulations in the dataset are genetically far removed from others. We propose a novel PCA-based framework which addresses this shortcoming. RESULTS: A novel population structure analysis algorithm called iterative pruning PCA (ipPCA) was developed which assigns individuals to subpopulations and infers the total number of subpopulations present. Genotypic data from simulated and real population datasets with different degrees of structure were analyzed. For datasets with simple structures, the subpopulation assignments of individuals made by ipPCA were largely consistent with the STRUCTURE, BAPS and AWclust algorithms. On the other hand, highly structured populations containing many closely related subpopulations could be accurately resolved only by ipPCA, and not by other methods. CONCLUSION: The algorithm is computationally efficient and not constrained by the dataset complexity. This systematic subpopulation assignment approach removes the need for prior population labels, which could be advantageous when cryptic stratification is encountered in datasets containing individuals otherwise assumed to belong to a homogenous population.

RExPrimer: an integrated primer designing tool increases PCR effectiveness by avoiding 3' SNP-in-primer and mis-priming from structural variation.

BACKGROUND: Polymerase chain reaction (PCR) is very useful in many areas of molecular biology research. It is commonly observed that PCR success is critically dependent on design of an effective primer pair. Current tools for primer design do not adequately address the problem of PCR failure due to mis-priming on target-related sequences and structural variations in the genome. METHODS: We have developed an integrated graphical web-based application for primer design, called RExPrimer, which was written in Python language. The software uses Primer3 as the primer designing core algorithm. Locally stored sequence information and genomic variant information were hosted on MySQLv5.0 and were incorporated into RExPrimer. RESULTS: RExPrimer provides many functionalities for improved PCR primer design. Several databases, namely annotated human SNP databases, insertion/deletion (indel) polymorphisms database, pseudogene database, and structural genomic variation databases were integrated into RExPrimer, enabling an effective without-leaving-the-website validation of the resulting primers. By incorporating these databases, the primers reported by RExPrimer avoid mis-priming to related sequences (e.g. pseudogene, segmental duplication) as well as possible PCR failure because of structural polymorphisms (SNP, indel, and copy number variation (CNV)). To prevent mismatching caused by unexpected SNPs in the designed primers, in particular the 3' end (SNP-in-Primer), several SNP databases covering the broad range of population-specific SNP information are utilized to report SNPs present in the primer sequences. Population-specific SNP information also helps customize primer design for a specific population. Furthermore, RExPrimer offers a graphical user-friendly interface through the use of scalable vector graphic image that intuitively presents resulting primers along with the corresponding gene structure. In this study, we demonstrated the program effectiveness in successfully generating primers for strong homologous sequences. CONCLUSION: The improvements for primer design incorporated into RExPrimer were demonstrated to be effective in designing primers for challenging PCR experiments. Integration of SNP and structural variation databases allows for robust primer design for a variety of PCR applications, irrespective of the sequence complexity in the region of interest. This software is freely available at http://www4a.biotec.or.th/rexprimer.

The Genomic Impact of European Colonization of the Americas.

The human genetic diversity of the Americas has been affected by several events of gene flow that have continued since the colonial era and the Atlantic slave trade. Moreover, multiple waves of migration followed by local admixture occurred in the last two centuries, the impact of which has been largely unexplored. Here, we compiled a genome-wide dataset of ∼12,000 individuals from twelve American countries and ∼6,000 individuals from worldwide populations and applied haplotype-based methods to investigate how historical movements from outside the New World affected (1) the genetic structure, (2) the admixture profile, (3) the demographic history, and (4) sex-biased gene-flow dynamics of the Americas. We revealed a high degree of complexity underlying the genetic contribution of European and African populations in North and South America, from both geographic and temporal perspectives, identifying previously unreported sources related to Italy, the Middle East, and to specific regions of Africa.

Statistical methods for detecting admixture.

The increasing availability of large-scale autosomal genetic variation data sampled from world-wide geographic areas, coupled with advances in the statistical methodology to analyse these data, is showcasing the power of DNA as a major tool to gain insights into the demographic history of humans and other organisms. Here we review statistical techniques that shed light on a specific aspect of demography: the detection and description of admixture events where two or more genetically distinct groups intermixed at one or more times in the past. In particular we give an overview of some of the widely used methods to identify and describe admixture events using autosomal DNA from unrelated individuals, with a particular focus on analysing biallelic Single-Nucleotide-Polymorphsim (SNP) markers.

WASP: a Web-based Allele-Specific PCR assay designing tool for detecting SNPs and mutations.

BACKGROUND: Allele-specific (AS) Polymerase Chain Reaction is a convenient and inexpensive method for genotyping Single Nucleotide Polymorphisms (SNPs) and mutations. It is applied in many recent studies including population genetics, molecular genetics and pharmacogenomics. Using known AS primer design tools to create primers leads to cumbersome process to inexperience users since information about SNP/mutation must be acquired from public databases prior to the design. Furthermore, most of these tools do not offer the mismatch enhancement to designed primers. The available web applications do not provide user-friendly graphical input interface and intuitive visualization of their primer results. RESULTS: This work presents a web-based AS primer design application called WASP. This tool can efficiently design AS primers for human SNPs as well as mutations. To assist scientists with collecting necessary information about target polymorphisms, this tool provides a local SNP database containing over 10 million SNPs of various populations from public domain databases, namely NCBI dbSNP, HapMap and JSNP respectively. This database is tightly integrated with the tool so that users can perform the design for existing SNPs without going off the site. To guarantee specificity of AS primers, the proposed system incorporates a primer specificity enhancement technique widely used in experiment protocol. In particular, WASP makes use of different destabilizing effects by introducing one deliberate 'mismatch' at the penultimate (second to last of the 3'-end) base of AS primers to improve the resulting AS primers. Furthermore, WASP offers graphical user interface through scalable vector graphic (SVG) draw that allow users to select SNPs and graphically visualize designed primers and their conditions. CONCLUSION: WASP offers a tool for designing AS primers for both SNPs and mutations. By integrating the database for known SNPs (using gene ID or rs number), this tool facilitates the awkward process of getting flanking sequences and other related information from public SNP databases. It takes into account the underlying destabilizing effect to ensure the effectiveness of designed primers. With user-friendly SVG interface, WASP intuitively presents resulting designed primers, which assist users to export or to make further adjustment to the design. This software can be freely accessed at http://bioinfo.biotec.or.th/WASP.

Analysis of the genetic structure of the Malay population: Ancestry-informative marker SNPs in the Malay of Peninsular Malaysia.

Malay, the main ethnic group in Peninsular Malaysia, is represented by various sub-ethnic groups such as Melayu Banjar, Melayu Bugis, Melayu Champa, Melayu Java, Melayu Kedah Melayu Kelantan, Melayu Minang and Melayu Patani. Using data retrieved from the MyHVP (Malaysian Human Variome Project) database, a total of 135 individuals from these sub-ethnic groups were profiled using the Affymetrix GeneChip Mapping Xba 50-K single nucleotide polymorphism (SNP) array to identify SNPs that were ancestry-informative markers (AIMs) for Malays of Peninsular Malaysia. Prior to selecting the AIMs, the genetic structure of Malays was explored with reference to 11 other populations obtained from the Pan-Asian SNP Consortium database using principal component analysis (PCA) and ADMIXTURE. Iterative pruning principal component analysis (ipPCA) was further used to identify sub-groups of Malays. Subsequently, we constructed an AIMs panel for Malays using the informativeness for assignment (In) of genetic markers, and the K-nearest neighbor classifier (KNN) was used to teach the classification models. A model of 250 SNPs ranked by In, correctly classified Malay individuals with an accuracy of up to 90%. The identified panel of SNPs could be utilized as a panel of AIMs to ascertain the specific ancestry of Malays, which may be useful in disease association studies, biomedical research or forensic investigation purposes.

Characterising private and shared signatures of positive selection in 37 Asian populations.

The Asian Diversity Project (ADP) assembled 37 cosmopolitan and ethnic minority populations in Asia that have been densely genotyped across over half a million markers to study patterns of genetic diversity and positive natural selection. We performed population structure analyses of the ADP populations and divided these populations into four major groups based on their genographic information. By applying a highly sensitive algorithm haploPS to locate genomic signatures of positive selection, 140 distinct genomic regions exhibiting evidence of positive selection in at least one population were identified. We examined the extent of signal sharing for regions that were selected in multiple populations and observed that populations clustered in a similar fashion to that of how the ancestry clades were phylogenetically defined. In particular, populations predominantly located in South Asia underwent considerably different adaptation as compared with populations from the other geographical regions. Signatures of positive selection present in multiple geographical regions were predicted to be older and have emerged prior to the separation of the populations in the different regions. In contrast, selection signals present in a single population group tended to be of lower frequencies and thus can be attributed to recent evolutionary events.

Genetic analysis of Thai cattle reveals a Southeast Asian indicine ancestry.

Cattle commonly raised in Thailand have characteristics of Bos indicus (zebu). We do not know when or how cattle domestication in Thailand occurred, and so questions remain regarding their origins and relationships to other breeds. We obtained genome-wide SNP genotypic data of 28 bovine individuals sampled from four regions: North (Kho-Khaolampoon), Northeast (Kho-Isaan), Central (Kho-Lan) and South (Kho-Chon) Thailand. These regional varieties have distinctive traits suggestive of breed-like genetic variations. From these data, we confirmed that all four Thai varieties are Bos indicus and that they are distinct from other indicine breeds. Among these Thai cattle, a distinctive ancestry pattern is apparent, which is the purest within Kho-Chon individuals. This ancestral component is only present outside of Thailand among other indicine breeds in Southeast Asia. From this pattern, we conclude that a unique Bos indicus ancestor originated in Southeast Asia, and native Kho-Chon Thai cattle retain the signal of this ancestry with limited admixture of other bovine ancestors.

Insight into the peopling of Mainland Southeast Asia from Thai population genetic structure.

There is considerable ethno-linguistic and genetic variation among human populations in Asia, although tracing the origins of this diversity is complicated by migration events. Thailand is at the center of Mainland Southeast Asia (MSEA), a region within Asia that has not been extensively studied. Genetic substructure may exist in the Thai population, since waves of migration from southern China throughout its recent history may have contributed to substantial gene flow. Autosomal SNP data were collated for 438,503 markers from 992 Thai individuals. Using the available self-reported regional origin, four Thai subpopulations genetically distinct from each other and from other Asian populations were resolved by Neighbor-Joining analysis using a 41,569 marker subset. Using an independent Principal Components-based unsupervised clustering approach, four major MSEA subpopulations were resolved in which regional bias was apparent. A major ancestry component was common to these MSEA subpopulations and distinguishes them from other Asian subpopulations. On the other hand, these MSEA subpopulations were admixed with other ancestries, in particular one shared with Chinese. Subpopulation clustering using only Thai individuals and the complete marker set resolved four subpopulations, which are distributed differently across Thailand. A Sino-Thai subpopulation was concentrated in the Central region of Thailand, although this constituted a minority in an otherwise diverse region. Among the most highly differentiated markers which distinguish the Thai subpopulations, several map to regions known to affect phenotypic traits such as skin pigmentation and susceptibility to common diseases. The subpopulation patterns elucidated have important implications for evolutionary and medical genetics. The subpopulation structure within Thailand may reflect the contributions of different migrants throughout the history of MSEA. The information will also be important for genetic association studies to account for population-structure confounding effects.