Predicting foodborne pathogens and probiotics taxa within poultry-related microbiomes using a machine learning approach.

BACKGROUND: Microbiomes that can serve as an indicator of gut, intestinal, and general health of humans and animals are largely influenced by food consumed and contaminant bioagents. Microbiome studies usually focus on estimating the alpha (within sample) and beta (similarity/dissimilarity among samples) diversities. This study took a combinatorial approach and applied machine learning to microbiome data to predict the presence of disease-causing pathogens and their association with known/potential probiotic taxa. Probiotics are beneficial living microorganisms capable of improving the host organism's digestive system, immune function and ultimately overall health. Here, 16 S rRNA gene high-throughput Illumina sequencing of temporal pre-harvest (feces, soil) samples of 42 pastured poultry flocks (poultry in this entire work solely refers to chickens) from southeastern U.S. farms was used to generate the relative abundance of operational taxonomic units (OTUs) as machine learning input. Unique genera from the OTUs were used as predictors of the prevalence of foodborne pathogens (Salmonella, Campylobacter and Listeria) at different stages of poultry growth (START (2-4 weeks old), MID (5-7 weeks old), END (8-11 weeks old)), association with farm management practices and physicochemical properties. RESULT: While we did not see any significant associations between known probiotics and Salmonella or Listeria, we observed significant negative correlations between known probiotics (Bacillus and Clostridium) and Campylobacter at the mid-time point of sample collection. Our data indicates a negative correlation between potential probiotics and Campylobacter at both early and end-time points of sample collection. Furthermore, our model prediction shows that changes in farm operations such as how often the houses are moved on the pasture, age at which chickens are introduced to the pasture, diet composition and presence of other animals on the farm could favorably increase the abundance and activity of probiotics that could reduce Campylobacter prevalence. CONCLUSION: Integration of microbiome data with farm management practices using machine learning provided insights on how to reduce Campylobacter prevalence and transmission along the farm-to-fork continuum. Altering management practices to support proliferation of beneficial probiotics to reduce pathogen prevalence identified here could constitute a complementary method to the existing but ineffective interventions such as vaccination and bacteriophage cocktails usage. Study findings also corroborate the presence of bacterial genera such as Caloramator, DA101, Parabacteroides and Faecalibacterium as potential probiotics.

PEGylation of a shell over core-shell MOFs-a novel strategy for preventing agglomeration and synergism in terms of physicochemical and biological properties.

We demonstrate a new strategy of PEGylation over core-shell MOFs of HKUST-1 and Cu-MOF-2 by a solvothermal method. The novel synthesized PEGylated core-shell MOFs has synergistic enhancement in terms of physicochemical and biological properties. FTIR spectroscopy and XRD analysis described the bonding characteristics of the double-shelled-core MOFs PEG@HKUST-1@CuMOF-2 and PEG@CuMOF-2@HKUST-1. XPS and EDAX spectroscopy confirmed the structural features of the PEG@core-shell MOFs. The as-synthesized PEG-modified core-shell MOFs showed a readily identifiable morphology with a reduction in particle size. The significant observation from SEM and TEM was that agglomeration disappeared completely, and the morphology of individual core-shell MOFs was clearly revealed. BET analysis provided the surface characteristics of MOF compounds. The chemical states of frameworks were established by XPS. The designed PEG-modified copper MOFs were evaluated for their activity against Gram-positive (Staphylococcus aureus, Enterococcus faecalis), Gram-negative (Escherichia coli and Klebsiella pneumoniae) bacterial species and activity against fungal species (Aspergillus niger and Candida albicans). This research work highlights a facile and synergistic approach to design promising biocompatible nano-dimensional core-shell MOFs for biological applications.

Demographics and Trends of Hypertrophic Cardiomyopathy-Related Mortality in the United States, 1999-2020.

There are limited data on the mortality trends of HCM in the United States. To study the demographics and trends of mortality in patients with HCM, a retrospective cohort analysis was done with mortality data of patients with HCM listed as an underlying cause of death in the US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database (CDC-WONDER) from January 1999 to December 2020. The analysis took place in February 2022. First, we measured HCM-related age-adjusted mortality rate (AAMR) per 100,000 US population stratified by sex, race, ethnicity, and geographic area. We then calculated the Annual Percentage Change (APC) for AAMR for each. A total of 24,655 HCM-related deaths occurred between 1999 and 2020. The AAMR for HCM-related deaths declined from 0.5/100,000 patients in 1999 to 0.2 in 2020. The APC changes are as follows: -6.8 (95% CI: -11.8 to -1.5) from 2002 to 2009, -1.23 (95% CI -13.8 to 13.2) from 2009 to 2014, -6.71 (95% CI -46.2 to 61.7) from 2014 to 2017 and remained at 2.07 (95% CI -26.1 to 41.1) from 2017 to 2020. Men had consistently higher AAMR than women. Overall, AAMR in men was 0.4 (95% CI: 0.4-0.5), and in women was 0.3 (95% CI: 0.3-0.3). A similar trend was noticed in men and women over the years, starting from 1999 (AAMR men: 0.7 and women: 0.4) to 2020 (AAMR men: 0.3 and women: 0.2). AAMRs were highest among black or African American patients 0.6 (95% CI: 0.5-0.6), followed by non-Hispanic and Hispanic white 0.3 (95% CI 0.3-0.3) and Asian or Pacific Islander 0.2 (95% CI 0.2-0.2). There was substantial variation in each region in the US. States such as California, Ohio, Michigan, Oregon, and Wyoming had the highest AAMR. Large metropolitan cities had higher AAMR than non-metropolitan cities. During the study period from 1999 to 2020, HCM-related mortality steadily decreased. The highest AAMR was observed among men, black patients, and residents of metropolitan areas. States such as California, Ohio, Michigan, Oregon, and Wyoming had the highest AAMR.

No-boundary thinking for artificial intelligence in bioinformatics and education.

No-boundary thinking enables the scientific community to reflect in a thoughtful manner and discover new opportunities, create innovative solutions, and break through barriers that might have otherwise constrained their progress. This concept encourages thinking without being confined by traditional rules, limitations, or established norms, and a mindset that is not limited by previous work, leading to fresh perspectives and innovative outcomes. So, where do we see the field of artificial intelligence (AI) in bioinformatics going in the next 30 years? That was the theme of a "No-Boundary Thinking" Session as part of the Mid-South Computational Bioinformatics Society's (MCBIOS) 19th annual meeting in Irving, Texas. This session addressed various areas of AI in an open discussion and raised some perspectives on how popular tools like ChatGPT can be integrated into bioinformatics, communicating with scientists in different fields to properly utilize the potential of these algorithms, and how to continue educational outreach to further interest of data science and informatics to the next-generation of scientists.

An ensemble learning approach to identify pastured poultry farm practice variables and soil constituents that promote Salmonella prevalence.

Animal sourced foods including contaminated poultry meat and eggs contribute to human non-typhoidal salmonellosis, a foodborne zoonosis. Prevalence of Salmonella in pastured poultry production systems can lead to contamination of the final product. Identification of farm practices that affect Salmonella prevalence is critical for implementing control measures to ensure the safety of these products. In this study, we developed predictive models based predominantly on deep learning approaches to identify key pre-harvest management variables (using soil and feces samples) in pastured poultry farms that contribute to Salmonella prevalence. Our ensemble approach utilizing five different machine learning techniques predicts that physicochemical parameters of the soil and feces (elements such as sodium (Na), zinc (Zn), potassium (K), copper (Cu)), electrical conductivity (EC), the number of years that the farms have been in use, and flock size significantly influence pre-harvest Salmonella prevalence. Egg source, feed type, breed, and manganese (Mn) levels in the soil/feces are other important variables identified to contribute to Salmonella prevalence on larger (≥3 flocks reared per year) farms, while pasture feed and soil carbon-to-nitrogen ratio are predicted to be important for smaller/hobby (<3 flocks reared per year) farms. Predictive models such as the ones described here are important for developing science-based control measures for Salmonella to reduce the environmental, animal, and public health impacts from these types of poultry production systems.

Artificial Intelligence Models for Zoonotic Pathogens: A Survey.

Zoonotic diseases or zoonoses are infections due to the natural transmission of pathogens between species (animals and humans). More than 70% of emerging infectious diseases are attributed to animal origin. Artificial Intelligence (AI) models have been used for studying zoonotic pathogens and the factors that contribute to their spread. The aim of this literature survey is to synthesize and analyze machine learning, and deep learning approaches applied to study zoonotic diseases to understand predictive models to help researchers identify the risk factors, and develop mitigation strategies. Based on our survey findings, machine learning and deep learning are commonly used for the prediction of both foodborne and zoonotic pathogens as well as the factors associated with the presence of the pathogens.

Preharvest Environmental and Management Drivers of Multidrug Resistance in Major Bacterial Zoonotic Pathogens in Pastured Poultry Flocks.

Due to nutritional benefits and perceived humane ways of treating the animals, the demand for antibiotic-free pastured poultry chicken has continued to be steadily rise. Despite the non-usage of antibiotics in pastured poultry broiler production, antibiotic resistance (AR) is reported in zoonotic poultry pathogens. However, factors that drive multidrug resistance (MDR) in pastured poultry are not well understood. In this study, we used machine learning and deep learning approaches to predict farm management practices and physicochemical properties of feces and soil that drive MDR in zoonotic poultry pathogens. Antibiotic use in agroecosystems is known to contribute to resistance. Evaluation of the development of resistance in environments that are free of antibiotics such as the all-natural, antibiotic-free, pastured poultry production systems described here is critical to understand the background AR in the absence of any selection pressure, i.e., basal levels of resistance. We analyzed 1635 preharvest (feces and soil) samples collected from forty-two pastured poultry flocks and eleven farms in the Southeastern United States. CDC National Antimicrobial Resistance Monitoring System guidelines were used to determine antimicrobial/multidrug resistance profiles of Salmonella, Listeria, and Campylobacter. A combination of two traditional machine learning (RandomForest and XGBoost) and three deep learning (Multi-layer Perceptron, Generative Adversarial Network, and Auto-Encoder) approaches identified critical farm management practices and environmental variables that drive multidrug resistance in poultry pathogens in broiler production systems that represents background resistance. This study enumerates management practices that contribute to AR and makes recommendations to potentially mitigate multidrug resistance and the prevalence of Salmonella and Listeria in pastured poultry.

Reconstruction of proto-vertebrate, proto-cyclostome and proto-gnathostome genomes provides new insights into early vertebrate evolution.

Ancient polyploidization events have had a lasting impact on vertebrate genome structure, organization and function. Some key questions regarding the number of ancient polyploidization events and their timing in relation to the cyclostome-gnathostome divergence have remained contentious. Here we generate de novo long-read-based chromosome-scale genome assemblies for the Japanese lamprey and elephant shark. Using these and other representative genomes and developing algorithms for the probabilistic macrosynteny model, we reconstruct high-resolution proto-vertebrate, proto-cyclostome and proto-gnathostome genomes. Our reconstructions resolve key questions regarding the early evolutionary history of vertebrates. First, cyclostomes diverged from the lineage leading to gnathostomes after a shared tetraploidization (1R) but before a gnathostome-specific tetraploidization (2R). Second, the cyclostome lineage experienced an additional hexaploidization. Third, 2R in the gnathostome lineage was an allotetraploidization event, and biased gene loss from one of the subgenomes shaped the gnathostome genome by giving rise to remarkably conserved microchromosomes. Thus, our reconstructions reveal the major evolutionary events and offer new insights into the origin and evolution of vertebrate genomes.

Antigen receptor repertoires of one of the smallest known vertebrates.

The rules underlying the structure of antigen receptor repertoires are not yet fully defined, despite their enormous importance for the understanding of adaptive immunity. With current technology, the large antigen receptor repertoires of mice and humans cannot be comprehensively studied. To circumvent the problems associated with incomplete sampling, we have studied the immunogenetic features of one of the smallest known vertebrates, the cyprinid fish Paedocypris sp. "Singkep" ("minifish"). Despite its small size, minifish has the key genetic facilities characterizing the principal vertebrate lymphocyte lineages. As described for mammals, the frequency distributions of immunoglobulin and T cell receptor clonotypes exhibit the features of fractal systems, demonstrating that self-similarity is a fundamental property of antigen receptor repertoires of vertebrates, irrespective of body size. Hence, minifish achieve immunocompetence via a few thousand lymphocytes organized in robust scale-free networks, thereby ensuring immune reactivity even when cells are lost or clone sizes fluctuate during immune responses.

Transcriptional activation of elephant shark mineralocorticoid receptor by corticosteroids, progesterone, and spironolactone.

The mineralocorticoid receptor (MR) is a nuclear receptor and part of a large and diverse family of transcription factors that also includes receptors for glucocorticoids, progesterone, androgens, and estrogens. The corticosteroid aldosterone is the physiological activator of the MR in humans and other terrestrial vertebrates; however, its activator is not known in cartilaginous fish, the oldest group of extant jawed vertebrates. Here, we analyzed the ability of corticosteroids and progesterone to activate the full-length MR from the elephant shark (Callorhinchus milii). On the basis of their measured activities, aldosterone, cortisol, 11-deoxycorticosterone, corticosterone, 11-deoxcortisol, progesterone, and 19-norprogesterone are potential physiological mineralocorticoids. However, aldosterone, the physiological mineralocorticoid in humans and other terrestrial vertebrates, is not found in cartilaginous or ray-finned fish. Although progesterone activates MRs in ray-finned fish, progesterone does not activate MRs in humans, amphibians, or alligator, suggesting that during the transition to terrestrial vertebrates, progesterone lost the ability to activate the MR. Both elephant shark MR and human MR are expressed in the brain, heart, ovary, testis, and other nonepithelial tissues, suggesting that MR expression in diverse tissues evolved in the common ancestor of jawed vertebrates. Our data suggest that 19-norprogesterone- and progesterone-activated MR may have unappreciated functions in reproductive physiology.

Voltage-gated sodium channel gene repertoire of lampreys: gene duplications, tissue-specific expression and discovery of a long-lost gene.

Studies of the voltage-gated sodium (Nav) channels of extant gnathostomes have made it possible to deduce that ancestral gnathostomes possessed four voltage-gated sodium channel genes derived from a single ancestral chordate gene following two rounds of genome duplication early in vertebrates. We investigated the Nav gene family in two species of lampreys (the Japanese lamprey Lethenteron japonicum and sea lamprey Petromyzon marinus) (jawless vertebrates-agnatha) and compared them with those of basal vertebrates to better understand the origin of Nav genes in vertebrates. We noted six Nav genes in both lamprey species, but orthology with gnathostome (jawed vertebrate) channels was inconclusive. Surprisingly, the Nav2 gene, ubiquitously found in invertebrates and believed to have been lost in vertebrates, is present in lampreys, elephant shark (Callorhinchus milii) and coelacanth (Latimeria chalumnae). Despite repeated duplication of the Nav1 family in vertebrates, Nav2 is only in single copy in those vertebrates in which it is retained, and was independently lost in ray-finned fishes and tetrapods. Of the other five Nav channel genes, most were expressed in brain, one in brain and heart, and one exclusively in skeletal muscle. Invertebrates do not express Nav channel genes in muscle. Thus, early in the vertebrate lineage Nav channels began to diversify and different genes began to express in heart and muscle.

Establishing multiple omics baselines for three Southeast Asian populations in the Singapore Integrative Omics Study.

The Singapore Integrative Omics Study provides valuable insights on establishing population reference measurement in 364 Chinese, Malay, and Indian individuals. These measurements include > 2.5 millions genetic variants, 21,649 transcripts expression, 282 lipid species quantification, and 284 clinical, lifestyle, and dietary variables. This concept paper introduces the depth of the data resource, and investigates the extent of ethnic variation at these omics and non-omics biomarkers. It is evident that there are specific biomarkers in each of these platforms to differentiate between the ethnicities, and intra-population analyses suggest that Chinese and Indians are the most biologically homogeneous and heterogeneous, respectively, of the three groups. Consistent patterns of correlations between lipid species also suggest the possibility of lipid tagging to simplify future lipidomics assays. The Singapore Integrative Omics Study is expected to allow the characterization of intra-omic and inter-omic correlations within and across all three ethnic groups through a systems biology approach.The Singapore Genome Variation projects characterized the genetics of Singapore's Chinese, Malay, and Indian populations. The Singapore Integrative Omics Study introduced here goes further in providing multi-omic measurements in individuals from these populations, including genetic, transcriptome, lipidome, and lifestyle data, and will facilitate the study of common diseases in Asian communities.

Lampreys, the jawless vertebrates, contain only two ParaHox gene clusters.

ParaHox genes (Gsx, Pdx, and Cdx) are an ancient family of developmental genes closely related to the Hox genes. They play critical roles in the patterning of brain and gut. The basal chordate, amphioxus, contains a single ParaHox cluster comprising one member of each family, whereas nonteleost jawed vertebrates contain four ParaHox genomic loci with six or seven ParaHox genes. Teleosts, which have experienced an additional whole-genome duplication, contain six ParaHox genomic loci with six ParaHox genes. Jawless vertebrates, represented by lampreys and hagfish, are the most ancient group of vertebrates and are crucial for understanding the origin and evolution of vertebrate gene families. We have previously shown that lampreys contain six Hox gene loci. Here we report that lampreys contain only two ParaHox gene clusters (designated as α- and ß-clusters) bearing five ParaHox genes (Gsxα, Pdxα, Cdxα, Gsxß, and Cdxß). The order and orientation of the three genes in the α-cluster are identical to that of the single cluster in amphioxus. However, the orientation of Gsxß in the ß-cluster is inverted. Interestingly, Gsxß is expressed in the eye, unlike its homologs in jawed vertebrates, which are expressed mainly in the brain. The lamprey Pdxα is expressed in the pancreas similar to jawed vertebrate Pdx genes, indicating that the pancreatic expression of Pdx was acquired before the divergence of jawless and jawed vertebrate lineages. It is likely that the lamprey Pdxα plays a crucial role in pancreas specification and insulin production similar to the Pdx of jawed vertebrates.

Cyclostomes Lack Clustered Protocadherins.

The brain, comprising billions of neurons and intricate neural networks, is arguably the most complex organ in vertebrates. The diversity of individual neurons is fundamental to the neuronal network complexity and the overall function of the vertebrate brain. In jawed vertebrates, clustered protocadherins provide the molecular basis for this neuronal diversity, through stochastic and combinatorial expression of their various isoforms in individual neurons. Based on analyses of transcriptomes from the Japanese lamprey brain and sea lamprey embryos, genome assemblies of the two lampreys, and brain expressed sequence tags of the inshore hagfish, we show that extant jawless vertebrates (cyclostomes) lack the clustered protocadherins. Our findings indicate that the clustered protocadherins originated from a nonclustered protocadherin in the jawed vertebrate ancestor, after the two rounds of whole-genome duplication. In the absence of clustered protocadherins, cyclostomes might have evolved novel molecules or mechanisms for generating neuronal diversity which remains to be discovered.

Early Evolution of Vertebrate Mybs: An Integrative Perspective Combining Synteny, Phylogenetic, and Gene Expression Analyses.

The genes in the Myb superfamily encode for three related transcription factors in most vertebrates, A-, B-, and c-Myb, with functionally distinct roles, whereas most invertebrates have a single Myb. B-Myb plays an essential role in cell division and cell cycle progression, c-Myb is involved in hematopoiesis, and A-Myb is involved in spermatogenesis and regulating expression of pachytene PIWI interacting RNAs, a class of small RNAs involved in posttranscriptional gene regulation and the maintenance of reproductive tissues. Comparisons between teleost fish and tetrapods suggest that the emergence and functional divergence of the Myb genes were linked to the two rounds of whole-genome duplication early in vertebrate evolution. We combined phylogenetic, synteny, structural, and gene expression analyses of the Myb paralogs from elephant shark and lampreys with data from 12 bony vertebrates to reconstruct the early evolution of vertebrate Mybs. Phylogenetic and synteny analyses suggest that the elephant shark and Japanese lamprey have copies of the A-, B-, and c-Myb genes, implying their origin could be traced back to the common ancestor of lampreys and gnathostomes. However, structural and gene expression analyses suggest that their functional roles diverged between gnathostomes and cyclostomes. In particular, we did not detect A-Myb expression in testis suggesting that the involvement of A-Myb in the pachytene PIWI interacting RNA pathway is probably a gnathostome-specific innovation. We speculate that the secondary loss of a central domain in lamprey A-Myb underlies the functional differences between the cyclostome and gnathostome A-Myb proteins.

Risk for ACPA-positive rheumatoid arthritis is driven by shared HLA amino acid polymorphisms in Asian and European populations.

Previous studies have emphasized ethnically heterogeneous human leukocyte antigen (HLA) classical allele associations to rheumatoid arthritis (RA) risk. We fine-mapped RA risk alleles within the major histocompatibility complex (MHC) in 2782 seropositive RA cases and 4315 controls of Asian descent. We applied imputation to determine genotypes for eight class I and II HLA genes to Asian populations for the first time using a newly constructed pan-Asian reference panel. First, we empirically measured high imputation accuracy in Asian samples. Then we observed the most significant association in HLA-DRß1 at amino acid position 13, located outside the classical shared epitope (Pomnibus = 6.9 × 10(-135)). The individual residues at position 13 have relative effects that are consistent with published effects in European populations (His > Phe > Arg > Tyr ≅ Gly > Ser)--but the observed effects in Asians are generally smaller. Applying stepwise conditional analysis, we identified additional independent associations at positions 57 (conditional Pomnibus = 2.2 × 10(-33)) and 74 (conditional Pomnibus = 1.1 × 10(-8)). Outside of HLA-DRß1, we observed independent effects for amino acid polymorphisms within HLA-B (Asp9, conditional P = 3.8 × 10(-6)) and HLA-DPß1 (Phe9, conditional P = 3.0 × 10(-5)) concordant with European populations. Our trans-ethnic HLA fine-mapping study reveals that (i) a common set of amino acid residues confer shared effects in European and Asian populations and (ii) these same effects can explain ethnically heterogeneous classical allelic associations (e.g. HLA-DRB1*09:01) due to allele frequency differences between populations. Our study illustrates the value of high-resolution imputation for fine-mapping causal variants in the MHC.

Insights into the genetic structure and diversity of 38 South Asian Indians from deep whole-genome sequencing.

South Asia possesses a significant amount of genetic diversity due to considerable intergroup differences in culture and language. There have been numerous reports on the genetic structure of Asian Indians, although these have mostly relied on genotyping microarrays or targeted sequencing of the mitochondria and Y chromosomes. Asian Indians in Singapore are primarily descendants of immigrants from Dravidian-language-speaking states in south India, and 38 individuals from the general population underwent deep whole-genome sequencing with a target coverage of 30X as part of the Singapore Sequencing Indian Project (SSIP). The genetic structure and diversity of these samples were compared against samples from the Singapore Sequencing Malay Project and populations in Phase 1 of the 1,000 Genomes Project (1 KGP). SSIP samples exhibited greater intra-population genetic diversity and possessed higher heterozygous-to-homozygous genotype ratio than other Asian populations. When compared against a panel of well-defined Asian Indians, the genetic makeup of the SSIP samples was closely related to South Indians. However, even though the SSIP samples clustered distinctly from the Europeans in the global population structure analysis with autosomal SNPs, eight samples were assigned to mitochondrial haplogroups that were predominantly present in Europeans and possessed higher European admixture than the remaining samples. An analysis of the relative relatedness between SSIP with two archaic hominins (Denisovan, Neanderthal) identified higher ancient admixture in East Asian populations than in SSIP. The data resource for these samples is publicly available and is expected to serve as a valuable complement to the South Asian samples in Phase 3 of 1 KGP.

Predicting HLA alleles from high-resolution SNP data in three Southeast Asian populations.

The major histocompatibility complex (MHC) containing the classical human leukocyte antigen (HLA) Class I and Class II genes is among the most polymorphic and diverse regions in the human genome. Despite the clinical importance of identifying the HLA types, very few databases jointly characterize densely genotyped single nucleotide polymorphisms (SNPs) and HLA alleles in the same samples. To date, the HapMap presents the only public resource that provides a SNP reference panel for predicting HLA alleles, constructed with four collections of individuals of north-western European, northern Han Chinese, cosmopolitan Japanese and Yoruba Nigerian ancestry. Owing to complex patterns of linkage disequilibrium in this region, it is unclear whether the HapMap reference panels can be appropriately utilized for other populations. Here, we describe a public resource for the Singapore Genome Variation Project with: (i) dense genotyping across ∼ 9000 SNPs in the MHC; (ii) four-digit HLA typing for eight Class I and Class II loci, in 96 southern Han Chinese, 89 Southeast Asian Malays and 83 Tamil Indians. This resource provides population estimates of the frequencies of HLA alleles at these eight loci in the three population groups, particularly for HLA-DPA1 and HLA-DPB1 that were not assayed in HapMap. Comparing between population-specific reference panels and a cosmopolitan panel created from all four HapMap populations, we demonstrate that more accurate imputation is obtained with population-specific panels than with the cosmopolitan panel, especially for the Malays and Indians but even when imputing between northern and southern Han Chinese. As with SNP imputation, common HLA alleles were imputed with greater accuracy than low-frequency variants.

Deep whole-genome sequencing of 100 southeast Asian Malays.

Whole-genome sequencing across multiple samples in a population provides an unprecedented opportunity for comprehensively characterizing the polymorphic variants in the population. Although the 1000 Genomes Project (1KGP) has offered brief insights into the value of population-level sequencing, the low coverage has compromised the ability to confidently detect rare and low-frequency variants. In addition, the composition of populations in the 1KGP is not complete, despite the fact that the study design has been extended to more than 2,500 samples from more than 20 population groups. The Malays are one of the Austronesian groups predominantly present in Southeast Asia and Oceania, and the Singapore Sequencing Malay Project (SSMP) aims to perform deep whole-genome sequencing of 100 healthy Malays. By sequencing at a minimum of 30× coverage, we have illustrated the higher sensitivity at detecting low-frequency and rare variants and the ability to investigate the presence of hotspots of functional mutations. Compared to the low-pass sequencing in the 1KGP, the deeper coverage allows more functional variants to be identified for each person. A comparison of the fidelity of genotype imputation of Malays indicated that a population-specific reference panel, such as the SSMP, outperforms a cosmopolitan panel with larger number of individuals for common SNPs. For lower-frequency (<5%) markers, a larger number of individuals might have to be whole-genome sequenced so that the accuracy currently afforded by the 1KGP can be achieved. The SSMP data are expected to be the benchmark for evaluating the value of deep population-level sequencing versus low-pass sequencing, especially in populations that are poorly represented in population-genetics studies.