Prehistoric human migration between Sundaland and South Asia was driven by sea-level rise.

Rapid sea-level rise between the Last Glacial Maximum (LGM) and the mid-Holocene transformed the Southeast Asian coastal landscape, but the impact on human demography remains unclear. Here, we create a paleogeographic map, focusing on sea-level changes during the period spanning the LGM to the present-day and infer the human population history in Southeast and South Asia using 763 high-coverage whole-genome sequencing datasets from 59 ethnic groups. We show that sea-level rise, in particular meltwater pulses 1 A (MWP1A, ~14,500-14,000 years ago) and 1B (MWP1B, ~11,500-11,000 years ago), reduced land area by over 50% since the LGM, resulting in segregation of local human populations. Following periods of rapid sea-level rises, population pressure drove the migration of Malaysian Negritos into South Asia. Integrated paleogeographic and population genomic analysis demonstrates the earliest documented instance of forced human migration driven by sea-level rise.

Population-specific positive selection on low CR1 expression in malaria-endemic regions.

Complement Receptor Type 1 (CR1) is a malaria-associated gene that encodes a transmembrane receptor of erythrocytes and is crucial for malaria parasite invasion. The expression of CR1 contributes to the rosetting of erythrocytes in the brain bloodstream, causing cerebral malaria, the most severe form of the disease. Here, we study the history of adaptation against malaria by analyzing selection signals in the CR1 gene. We used whole-genome sequencing datasets of 907 healthy individuals from malaria-endemic and non-endemic populations. We detected robust positive selection in populations from the hyperendemic regions of East India and Papua New Guinea. Importantly, we identified a new adaptive variant, rs12034598, which is associated with a slower rate of erythrocyte sedimentation and is linked with a variant associated with low levels of CR1 expression. The combination of the variants likely drives natural selection. In addition, we identified a variant rs3886100 under positive selection in West Africans, which is also related to a low level of CR1 expression in the brain. Our study shows the fine-resolution history of positive selection in the CR1 gene and suggests a population-specific history of CR1 adaptation to malaria. Notably, our novel approach using population genomic analyses allows the identification of protective variants that reduce the risk of malaria infection without the need for patient samples or malaria individual medical records. Our findings contribute to understanding of human adaptation against cerebral malaria.

Vertical stratification of the air microbiome in the lower troposphere.

The troposphere constitutes the final frontier of global ecosystem research due to technical challenges arising from its size, low biomass, and gaseous state. Using a vertical testing array comprising a meteorological tower and a research aircraft, we conducted synchronized measurements of meteorological parameters and airborne biomass (n = 480) in the vertical air column up to 3,500 m. The taxonomic analysis of metagenomic data revealed differing patterns of airborne microbial community composition with respect to time of day and height above ground. The temporal and spatial resolution of our study demonstrated that the diel cycle of airborne microorganisms is a ground-based phenomenon that is entirely absent at heights >1,000 m. In an integrated analysis combining meteorological and biological data, we demonstrate that atmospheric turbulence, identified by potential temperature and high-frequency three-component wind measurements, is the key driver of bioaerosol dynamics in the lower troposphere. Multivariate regression analysis shows that at least 50% of identified airborne microbial taxa (n = ∼10,000) are associated with either ground or height, allowing for an understanding of dispersal patterns of microbial taxa in the vertical air column. Due to the interconnectedness of atmospheric turbulence and temperature, the dynamics of microbial dispersal are likely to be impacted by rising global temperatures, thereby also affecting ecosystems on the planetary surface.

Who's afraid of genetic tests?: An assessment of Singapore's public attitudes and changes in attitudes after taking a genetic test.

BACKGROUND: As a consequence of precision medicine initiatives, genomic technologies have rapidly spread around the world, raising questions about genetic privacy and the ethics of data sharing. Previous scholarship in bioethics and science and technology studies has made clear that different nations have varying expectations about trust, transparency, and public reason in relation to emerging technologies and their governance. The key aims of this article are to assess genetic literacy, perceptions of genetic testing, privacy concerns, and governing norms amongst the Singapore population by collecting surveys. METHODS: This study investigated genetic literacy and broad public attitudes toward genetic tests in Singapore with an online public survey (n = 560). To assess potential changes in attitudes following receipt of results from a genetic test, we also surveyed undergraduate students who underwent a genetic screen as part of a university class before and after they received their test results (n = 25). RESULTS: Public participants showed broad support for the use of genetic tests; scored an average of 48.9% in genetic literacy; and expressed privacy concerns over data sharing and a desire for control over their genetic data. After taking a genetic test and receiving genetic test results, students reported less fear of genetic tests while other attitudes did not change significantly. CONCLUSION: These findings highlight the potential of genetic education and active engagement with genetic testing to increase support and participation in genomic projects, PM, and biobanking initiatives; and they suggest that data privacy protections could potentially reduce discrimination by giving participants control over who can access their data. More specifically, these findings and the dataset we provide may be helpful in formulating culturally sensitive education programs and regulations concerning genomic technologies and data privacy.

Population-specific adaptation in malaria-endemic regions of asia.

Evolutionary mechanisms of adaptation to malaria are understudied in Asian endemic regions despite a high prevalence of malaria in the region. In our research, we performed a genome-wide screening for footprints of natural selection against malaria by comparing eight Asian population groups from malaria-endemic regions with two non-endemic population groups from Europe and Mongolia. We identified 285 adaptive genes showing robust selection signals across three statistical methods, iHS, XP-EHH, and PBS. Interestingly, most of the identified genes (82%) were found to be under selection in a single population group, while adaptive genes shared across populations were rare. This is likely due to the independent adaptation history in different endemic populations. The gene ontology (GO) analysis for the 285 adaptive genes highlighted their functional processes linked to neuronal organizations or nervous system development. These genes could be related to cerebral malaria and may reduce the inflammatory response and the severity of malaria symptoms. Remarkably, our novel population genomic approach identified population-specific adaptive genes potentially against malaria infection without the need for patient samples or individual medical records.

Experimental parameters defining ultra-low biomass bioaerosol analysis.

Investigation of the microbial ecology of terrestrial, aquatic and atmospheric ecosystems requires specific sampling and analytical technologies, owing to vastly different biomass densities typically encountered. In particular, the ultra-low biomass nature of air presents an inherent analytical challenge that is confounded by temporal fluctuations in community structure. Our ultra-low biomass pipeline advances the field of bioaerosol research by significantly reducing sampling times from days/weeks/months to minutes/hours, while maintaining the ability to perform species-level identification through direct metagenomic sequencing. The study further addresses all experimental factors contributing to analysis outcome, such as amassment, storage and extraction, as well as factors that impact on nucleic acid analysis. Quantity and quality of nucleic acid extracts from each optimisation step are evaluated using fluorometry, qPCR and sequencing. Both metagenomics and marker gene amplification-based (16S and ITS) sequencing are assessed with regard to their taxonomic resolution and inter-comparability. The pipeline is robust across a wide range of climatic settings, ranging from arctic to desert to tropical environments. Ultimately, the pipeline can be adapted to environmental settings, such as dust and surfaces, which also require ultra-low biomass analytics.

Imputation Performance in Latin American Populations: Improving Rare Variants Representation With the Inclusion of Native American Genomes.

Current Genome-Wide Association Studies (GWAS) rely on genotype imputation to increase statistical power, improve fine-mapping of association signals, and facilitate meta-analyses. Due to the complex demographic history of Latin America and the lack of balanced representation of Native American genomes in current imputation panels, the discovery of locally relevant disease variants is likely to be missed, limiting the scope and impact of biomedical research in these populations. Therefore, the necessity of better diversity representation in genomic databases is a scientific imperative. Here, we expand the 1,000 Genomes reference panel (1KGP) with 134 Native American genomes (1KGP + NAT) to assess imputation performance in Latin American individuals of mixed ancestry. Our panel increased the number of SNPs above the GWAS quality threshold, thus improving statistical power for association studies in the region. It also increased imputation accuracy, particularly in low-frequency variants segregating in Native American ancestry tracts. The improvement is subtle but consistent across countries and proportional to the number of genomes added from local source populations. To project the potential improvement with a higher number of reference genomes, we performed simulations and found that at least 3,000 Native American genomes are needed to equal the imputation performance of variants in European ancestry tracts. This reflects the concerning imbalance of diversity in current references and highlights the contribution of our work to reducing it while complementing efforts to improve global equity in genomic research.

Complete genome of Enterobacter sichuanensis strain SGAir0282 isolated from air in Singapore.

BACKGROUND: Enterobacter cloacae complex (ECC) bacteria, such as E. cloacae, E. sichuanensis, E. kobei, and E. roggenkampii, have been emerging as nosocomial pathogens. Many strains isolated from medical clinics were found to be resistant to antibiotics, and in the worst cases, acquired multidrug resistance. We present the whole genome sequence of SGAir0282, isolated from the outdoor air in Singapore, and its relevance to other ECC bacteria by in silico genomic analysis. RESULTS: Complete genome assembly of E. sichuanensis strain SGAir0282 was generated using PacBio RSII and Illumina MiSeq platforms, and the datasets were used for de novo assembly using Hierarchical Genome Assembly Process (HGAP) and error corrected with Pilon. The genome assembly consisted of a single contig of 4.71 Mb and with a G+C content of 55.5%. No plasmid was detected in the assembly. The genome contained 4371 coding genes, 83 tRNA and 25 rRNA genes, as predicted by NCBI's Prokaryotic Genome Annotation Pipeline (PGAP). Among the genes, the antibiotic resistance related genes were included: Streptothricin acetdyltransferase (SatA), fosfomycin resistance protein (FosA) and metal-dependent hydrolases of the beta-lactamase superfamily I (BLI). CONCLUSION: Based on whole genome alignment and phylogenetic analysis, the strain SGAir0282 was identified to be Enterobacter sichuanensis. The strain possesses gene clusters for virulence, disease and defence, that can also be found in other multidrug resistant ECC type strains.

Microbial communities in the tropical air ecosystem follow a precise diel cycle.

The atmosphere is vastly underexplored as a habitable ecosystem for microbial organisms. In this study, we investigated 795 time-resolved metagenomes from tropical air, generating 2.27 terabases of data. Despite only 9 to 17% of the generated sequence data currently being assignable to taxa, the air harbored a microbial diversity that rivals the complexity of other planetary ecosystems. The airborne microbial organisms followed a clear diel cycle, possibly driven by environmental factors. Interday taxonomic diversity exceeded day-to-day and month-to-month variation. Environmental time series revealed the existence of a large core of microbial taxa that remained invariable over 13 mo, thereby underlining the long-term robustness of the airborne community structure. Unlike terrestrial or aquatic environments, where prokaryotes are prevalent, the tropical airborne biomass was dominated by DNA from eukaryotic phyla. Specific fungal and bacterial species were strongly correlated with temperature, humidity, and CO2 concentration, making them suitable biomarkers for studying the bioaerosol dynamics of the atmosphere.

NARD: whole-genome reference panel of 1779 Northeast Asians improves imputation accuracy of rare and low-frequency variants.

Here, we present the Northeast Asian Reference Database (NARD), including whole-genome sequencing data of 1779 individuals from Korea, Mongolia, Japan, China, and Hong Kong. NARD provides the genetic diversity of Korean (n = 850) and Mongolian (n = 384) ancestries that were not present in the 1000 Genomes Project Phase 3 (1KGP3). We combined and re-phased the genotypes from NARD and 1KGP3 to construct a union set of haplotypes. This approach established a robust imputation reference panel for Northeast Asians, which yields the greatest imputation accuracy of rare and low-frequency variants compared with the existing panels. NARD imputation panel is available at https://nard.macrogen.com/ .

Mitogenomes reveal diversity of the European Lyme borreliosis vector Ixodes ricinus in Italy.

In Europe, the Ixodes ricinus tick is the most important vector of the etiological agents of Lyme borreliosis and several other emerging tick-borne diseases. Because tick-borne pathogens are dependent on their vectors for transmission, understanding the vector population structure is crucial to inform public health research of pathogen dynamics and spread. However, the population structure and dynamics of this important vector species are not well understood as most genetic studies utilize short mitochondrial and nuclear sequences with little diversity. Herein we obtained and analyzed complete mitochondrial genome (hereafter "mitogenome") sequences to better understand the genetic diversity and the population structure of I. ricinus from two long-standing tick-borne disease foci in northern Italy. Complete mitogenomes of 23 I. ricinus ticks were sequenced at high coverage. Out of 23 mitogenome sequences we identified 17 unique haplotypes composed of 244 segregating sites. Phylogenetic reconstruction using 18 complete mitogenome sequences revealed the coexistence of four highly divergent I. ricinus maternal lineages despite the narrow spatial scale over which these samples were obtained (100km). Notably, the estimated coalescence time of the 18 mitogenome haplotypes is ∼427 thousand years ago (95% HPD 330, 540). This divergence between I. ricinus lineages is consistent with the mitochondrial diversity of other arthropod vector species and indicates that long-term I. ricinus populations may have been less structured and larger than previously thought. Thus, this study suggests that a rapid and accurate retrieval of full mitochondrial genomes from this disease vector enables fine-resolution studies of tick intraspecies genetic relationships, population differentiation, and demographic history.

Khoisan hunter-gatherers have been the largest population throughout most of modern-human demographic history.

The Khoisan people from Southern Africa maintained ancient lifestyles as hunter-gatherers or pastoralists up to modern times, though little else is known about their early history. Here we infer early demographic histories of modern humans using whole-genome sequences of five Khoisan individuals and one Bantu speaker. Comparison with a 420 K SNP data set from worldwide individuals demonstrates that two of the Khoisan genomes from the Ju/'hoansi population contain exclusive Khoisan ancestry. Coalescent analysis shows that the Khoisan and their ancestors have been the largest populations since their split with the non-Khoisan population ~100-150 kyr ago. In contrast, the ancestors of the non-Khoisan groups, including Bantu-speakers and non-Africans, experienced population declines after the split and lost more than half of their genetic diversity. Paleoclimate records indicate that the precipitation in southern Africa increased ~80-100 kyr ago while west-central Africa became drier. We hypothesize that these climate differences might be related to the divergent-ancient histories among human populations.

Poor Man's 1000 Genome Project: Recent Human Population Expansion Confounds the Detection of Disease Alleles in 7,098 Complete Mitochondrial Genomes.

Rapid growth of the human population has caused the accumulation of rare genetic variants that may play a role in the origin of genetic diseases. However, it is challenging to identify those rare variants responsible for specific diseases without genetic data from an extraordinarily large population sample. Here we focused on the accumulated data from the human mitochondrial (mt) genome sequences because this data provided 7,098 whole genomes for analysis. In this dataset we identified 6,110 single nucleotide variants (SNVs) and their frequency and determined that the best-fit demographic model for the 7,098 genomes included severe population bottlenecks and exponential expansions of the non-African population. Using this model, we simulated the evolution of mt genomes in order to ascertain the behavior of deleterious mutations. We found that such deleterious mutations barely survived during population expansion. We derived the threshold frequency of a deleterious mutation in separate African, Asian, and European populations and used it to identify pathogenic mutations in our dataset. Although threshold frequency was very low, the proportion of variants showing a lower frequency than that threshold was 82, 83, and 91% of the total variants for the African, Asian, and European populations, respectively. Within these variants, only 18 known pathogenic mutations were detected in the 7,098 genomes. This result showed the difficulty of detecting a pathogenic mutation within an abundance of rare variants in the human population, even with a large number of genomes available for study.

Galaxy tools to study genome diversity.

BACKGROUND: Intra-species genetic variation can be used to investigate population structure, selection, and gene flow in non-model vertebrates; and due to the plummeting costs for genome sequencing, it is now possible for small labs to obtain full-genome variation data from their species of interest. However, those labs may not have easy access to, and familiarity with, computational tools to analyze those data. RESULTS: We have created a suite of tools for the Galaxy web server aimed at handling nucleotide and amino-acid polymorphisms discovered by full-genome sequencing of several individuals of the same species, or using a SNP genotyping microarray. In addition to providing user-friendly tools, a main goal is to make published analyses reproducible. While most of the examples discussed in this paper deal with nuclear-genome diversity in non-human vertebrates, we also illustrate the application of the tools to fungal genomes, human biomedical data, and mitochondrial sequences. CONCLUSIONS: This project illustrates that a small group can design, implement, test, document, and distribute a Galaxy tool collection to meet the needs of a particular community of biologists.

Sequencing and analysis of a South Asian-Indian personal genome.

BACKGROUND: With over 1.3 billion people, India is estimated to contain three times more genetic diversity than does Europe. Next-generation sequencing technologies have facilitated the understanding of diversity by enabling whole genome sequencing at greater speed and lower cost. While genomes from people of European and Asian descent have been sequenced, only recently has a single male genome from the Indian subcontinent been published at sufficient depth and coverage. In this study we have sequenced and analyzed the genome of a South Asian Indian female (SAIF) from the Indian state of Kerala. RESULTS: We identified over 3.4 million SNPs in this genome including over 89,873 private variations. Comparison of the SAIF genome with several published personal genomes revealed that this individual shared ~50% of the SNPs with each of these genomes. Analysis of the SAIF mitochondrial genome showed that it was closely related to the U1 haplogroup which has been previously observed in Kerala. We assessed the SAIF genome for SNPs with health and disease consequences and found that the individual was at a higher risk for multiple sclerosis and a few other diseases. In analyzing SNPs that modulate drug response, we found a variation that predicts a favorable response to metformin, a drug used to treat diabetes. SNPs predictive of adverse reaction to warfarin indicated that the SAIF individual is not at risk for bleeding if treated with typical doses of warfarin. In addition, we report the presence of several additional SNPs of medical relevance. CONCLUSIONS: This is the first study to report the complete whole genome sequence of a female from the state of Kerala in India. The availability of this complete genome and variants will further aid studies aimed at understanding genetic diversity, identifying clinically relevant changes and assessing disease burden in the Indian population.

Genomic structure and evolution of multigene families: "flowers" on the human genome.

We report the results of an extensive investigation of genomic structures in the human genome, with a particular focus on relatively large repeats (>50 kb) in adjacent chromosomal regions. We named such structures "Flowers" because the pattern observed on dot plots resembles a flower. We detected a total of 291 Flowers in the human genome. They were predominantly located in euchromatic regions. Flowers are gene-rich compared to the average gene density of the genome. Genes involved in systems receiving environmental information, such as immunity and detoxification, were overrepresented in Flowers. Within a Flower, the mean number of duplication units was approximately four. The maximum and minimum identities between homologs in a Flower showed different distributions; the maximum identity was often concentrated to 100% identity, while the minimum identity was evenly distributed in the range of 78% to 100%. Using a gene conversion detection test, we found frequent and/or recent gene conversion events within the tested Flowers. Interestingly, many of those converted regions contained protein-coding genes. Computer simulation studies suggest that one role of such frequent gene conversions is the elongation of the life span of gene families in a Flower by the resurrection of pseudogenes.

Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change.

Polar bears (PBs) are superbly adapted to the extreme Arctic environment and have become emblematic of the threat to biodiversity from global climate change. Their divergence from the lower-latitude brown bear provides a textbook example of rapid evolution of distinct phenotypes. However, limited mitochondrial and nuclear DNA evidence conflicts in the timing of PB origin as well as placement of the species within versus sister to the brown bear lineage. We gathered extensive genomic sequence data from contemporary polar, brown, and American black bear samples, in addition to a 130,000- to 110,000-y old PB, to examine this problem from a genome-wide perspective. Nuclear DNA markers reflect a species tree consistent with expectation, showing polar and brown bears to be sister species. However, for the enigmatic brown bears native to Alaska's Alexander Archipelago, we estimate that not only their mitochondrial genome, but also 5-10% of their nuclear genome, is most closely related to PBs, indicating ancient admixture between the two species. Explicit admixture analyses are consistent with ancient splits among PBs, brown bears and black bears that were later followed by occasional admixture. We also provide paleodemographic estimates that suggest bear evolution has tracked key climate events, and that PB in particular experienced a prolonged and dramatic decline in its effective population size during the last ca. 500,000 years. We demonstrate that brown bears and PBs have had sufficiently independent evolutionary histories over the last 4-5 million years to leave imprints in the PB nuclear genome that likely are associated with ecological adaptation to the Arctic environment.

Revealing mammalian evolutionary relationships by comparative analysis of gene clusters.

Many software tools for comparative analysis of genomic sequence data have been released in recent decades. Despite this, it remains challenging to determine evolutionary relationships in gene clusters due to their complex histories involving duplications, deletions, inversions, and conversions. One concept describing these relationships is orthology. Orthologs derive from a common ancestor by speciation, in contrast to paralogs, which derive from duplication. Discriminating orthologs from paralogs is a necessary step in most multispecies sequence analyses, but doing so accurately is impeded by the occurrence of gene conversion events. We propose a refined method of orthology assignment based on two paradigms for interpreting its definition: by genomic context or by sequence content. X-orthology (based on context) traces orthology resulting from speciation and duplication only, while N-orthology (based on content) includes the influence of conversion events. We developed a computational method for automatically mapping both types of orthology on a per-nucleotide basis in gene cluster regions studied by comparative sequencing, and we make this mapping accessible by visualizing the output. All of these steps are incorporated into our newly extended CHAP 2 package. We evaluate our method using both simulated data and real gene clusters (including the well-characterized α-globin and ß-globin clusters). We also illustrate use of CHAP 2 by analyzing four more loci: CCL (chemokine ligand), IFN (interferon), CYP2abf (part of cytochrome P450 family 2), and KIR (killer cell immunoglobulin-like receptors). These new methods facilitate and extend our understanding of evolution at these and other loci by adding automated accurate evolutionary inference to the biologist's toolkit. The CHAP 2 package is freely available from http://www.bx.psu.edu/miller_lab.

Conversion events in gene clusters.

BACKGROUND: Gene clusters containing multiple similar genomic regions in close proximity are of great interest for biomedical studies because of their associations with inherited diseases. However, such regions are difficult to analyze due to their structural complexity and their complicated evolutionary histories, reflecting a variety of large-scale mutational events. In particular, conversion events can mislead inferences about the relationships among these regions, as traced by traditional methods such as construction of phylogenetic trees or multi-species alignments. RESULTS: To correct the distorted information generated by such methods, we have developed an automated pipeline called CHAP (Cluster History Analysis Package) for detecting conversion events. We used this pipeline to analyze the conversion events that affected two well-studied gene clusters (α-globin and ß-globin) and three gene clusters for which comparative sequence data were generated from seven primate species: CCL (chemokine ligand), IFN (interferon), and CYP2abf (part of cytochrome P450 family 2). CHAP is freely available at http://www.bx.psu.edu/miller_lab. CONCLUSIONS: These studies reveal the value of characterizing conversion events in the context of studying gene clusters in complex genomes.

Divergence, demography and gene loss along the human lineage.

Genomic DNA sequences are an irreplaceable source for reconstructing the vanished past of living organisms. Based on updated sequence data, this paper summarizes our studies on species divergence time, ancient population size and functional loss of genes in the primate lineage leading to modern humans (Homo sapiens sapiens). The inter- and intraspecific comparisons of DNA sequences suggest that the human lineage experienced a rather severe bottleneck in the Middle Pleistocene, throughout which period the subdivided African population played a predominant role in shaping the genetic architecture of modern humans. Also, published and newly identified human-specific pseudogenes (HSPs) are enumerated in order to infer their significance for human evolution. Of the 121 candidate genes obtained, authentic HSPs turn out to comprise only 25 olfactory receptor genes, four T cell receptor genes and nine other genes. The fixation of HSPs has been too rare over the past 6-7 Myr to account for species differences between humans and chimpanzees.