Single Nucleotide Polymorphisms Consortium Research Articles

Defining the QTL associated with chill requirement during endodormancy in Malus × domestica Borkh

Current weather pattern predictions show the increase in winter temperatures globally. This could have a detrimental effect on fruit grown in temperate environments like the southern part of Africa. A rise in winter temperatures would lead to the non-fulfilment of chill requirements of fruit crops and subsequent losses. A need therefore arises to breed for good quality fruit varieties with a lower chill requirement. Identifying genomic regions that are associated with early flowering is the first step in breeding for such varieties. This study focuses on defining a quantitative trait locus (QTL) that is associated with budbreak in Malus × domestica Borkh. The International Rosaceae SNP consortium apple 8 K single nucleotide polymorphism (SNP) bead array v1 was used with recombination mapping and QTL analysis to identify this QTL on Linkage Group 9. A QTL was verified with association mapping and shown to be in the first 10 Mb of chromosome 9, and consisting of six clusters of SNPs, grouped together. These clusters were shown to segregate together with identical allele specification, as well as having a high linkage disequilibrium within the clusters. The haplotype blocks representing the clusters show a high correlation between them, explaining the substantial size of the QTL found with recombination mapping. Approximately 750 genes were represented by the clusters, most notably a high number of transcription factors and regulators.

Validation of SNP markers for fruit quality and disease resistance loci in apple (Malus \xd7 domestica Borkh.) using the OpenArray\xae platform

Genome mapping has promised much to tree fruit breeding during the last 10 years. Nevertheless, one of the greatest challenges remaining to tree fruit geneticists is the translation of trait loci and whole genome sequences into diagnostic genetic markers that are efficient and cost-effective for use by breeders, who must select genetically optimal parents and subsequently select genetically superior individuals among their progeny. To take this translational step, we designed the apple International RosBREED SNP Consortium OpenArray v1.0 (IRSCOA v1.0) assay using a set of 128 apple single nucleotide polymorphisms (SNPs) linked to fruit quality and pest and disease resistance trait loci. The Thermo Fisher Scientific OpenArray® technology enables multiplexed screening of SNP markers using a real-time PCR instrument with fluorescent probe-based Taqman® assays. We validated the apple IRSCOA v1.0 multi-trait assay by screening 240 phenotyped individuals from the Plant & Food Research apple cultivar breeding programme. This set of individuals comprised commercial and heritage cultivars, elite selections, and families segregating for traits of importance to breeders. In total, 33 SNP markers of the IRSCOA v1.0 were validated for use in marker-assisted selection (MAS) for the scab resistances Rvi2/Vh2, Rvi4/Vh4, Rvi6/Vf, fire blight resistance MR5/RLP1, powdery mildew resistance Pl2, fruit firmness, skin colour, flavour intensity, and acidity. The availability of this set of validated trait-associated SNP markers, which can be used individually on multiple genotyping platforms available to various apple breeding programmes or re-designed using the flanking sequences, represents a large translational genetics step from genomics to crop improvement of apple.

Sun, S. Socio‐Economics of Personalized Medicine in Asia. London and New York: Routledge. 2017. 198 pp. £110 (hbk) ISBN 978‐1138933835

Personalised medicine – tailoring medical practices to individuals based on genetic constitution to enhance diagnosis and treatment – is poised for rapid growth in Asia. However, most literature focuses on scientific perspectives in European and North American contexts. Shirley Sun's new book bucks this trend with a sociological investigation of personalised medicine in Asian countries. It breaks new ground by problematising the obsession in medicine and drug development with ethnicity and race as a proxy for human genetic diversity. The book focuses on cancer treatment and research, the most popular application of personalised medicine, and the Human Genome Organisation's (HUGO) Pan-Asian Single Nucleotide Polymorphism (SNP) Consortium which conducted the largest survey of genetic diversity among Asians. The first chapter sets the scene with a succinct introduction to ethnicity, race, and personalised medicine, and the emphasis on a tension between the promise of targeting individuals and the reality of group and population approaches. According to Sun, limited availability of cost-effective genetic testing for individuals underpins a tendency to take ethnic and racial groups as genetically distinctive populations. This uncritical conversion of socially constructed concepts into genetically meaningful categories is challenged further in the second chapter, with reference to research findings by the SNP Consortium which reported that most ethnic and linguistic populations show genetic relatedness. Sun teases out the limitations of using ethnic and racial categories in genetics research, and draws analogies with other examples of categorisation errors in history, such as nation-state building in Europe and Japan. Chapters three and four examine these issues in drug development, and public health and genomic research policy-making. In chapter three, Sun alleges that a major pharmaceutical company began targeting a lung cancer drug to Asian countries following poor performance in clinical trials in the United States. Although successful treatment depended on the presence of mutations in tumour tissues, clinical trial results hinged on race (Asian or non-Asian) rather than mutation status. Sun argues that this was a misappropriation which only served the interests of the pharmaceutical industry through mitigating costs, gaining regulatory approval, and targeting overseas markets. In chapter four - a case study of cost-effectiveness analysis in public health resources in Singapore - scientists reported using the country's official population indicators as genetically-distinct populations, despite the availability of alternative criteria. Sun rebuts Singapore's public policymaking with a review of the historical formation of ‘Malay’, which demonstrates the reification of simple ethnic and racial categories. Chapter five considers the perspectives of medical oncologists in Singapore who argue that genetic testing should be available for every patient, and treatment decisions should only be based on ethnicity or race as a last resort or in preliminary research. Ironically, despite these arguments, limited resources and training requirements mean that they still rely on these socially constructed categories when prescribing drugs to patients. Chapter six highlights other barriers impeding personalised medicine, such as accessibility, training needs of doctors, prohibitive costs, privacy, and racial discrimination. Notably, high costs mean that personalised medicine is priced out of reach for many patients with low incomes or no health insurance – an ethical dilemma for doctors. Treatment costs are also a challenge for healthcare funders, such as governments, insurance companies, and society. Limited long-term benefits also mean patients and families face moral questions about the value of a few extra months of life. In what follows, Sun questions whether personalised medicine should become the gold-standard for cancer treatment. Overall, the book offers intriguing insights about how cutting-edge developments in medicine and scientific research are embedded in complex social and historical contexts. Its sociological and Asian foci are welcome additions to a literature dominated by scientists in Europe and the United States. It should have wide appeal as the number of clinical trials in Asian countries is increasing. However, the book has a number of weaknesses. There is, for example, a lack of engagement with wider literature on identities and ethnicity in health research and practice. In addition, detail about the methodology of Sun's interviews and data analysis is slim. Interview quotations in several chapters require further analysis as well as interweaving within the main storyline. There are also issues with organisation, style, and clarity. Some sections could be combined, expanded or moved to other chapters. The chapter conclusions do not always summarise their respective chapters, but introduce new data and quotes, as does the concluding chapter. However, these minor issues do not detract from the book's important take-home message, namely, that although personalised medicine will continue to improve cancer diagnosis and treatment, we must consider its limitations. I highly recommend Sun’s book to social scientists, doctors, scientists, politicians, and anyone interested in the history and practice of medicine and drug development.

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.

Identifying SNP markers tightly associated with six major genes in peach [Prunus persica (L.) Batsch] using a high-density SNP array with an objective of marker-assisted selection (MAS)

One of the applications of genomics is to identify genetic markers linked to loci responsible for variation in phenotypic traits, which could be used in breeding programs to select individuals with favorable alleles, particularly at the seedling stage. With this aim, in the framework of the European project FruitBreedomics, we selected five main peach fruit characters and a resistance trait, controlled by major genes with Mendelian inheritance: fruit flesh color Y, fruit skin pubescence G, fruit shape S, sub-acid fruit D, stone adhesion-flesh texture F-M, and resistance to green peach aphid Rm2. They were all previously mapped in Prunus. We then selected three F1 and three F2 progenies segregating for these characters and developed genetic maps of the linkage groups including the major genes, using the single nucleotide polymorphism (SNP) genome-wide scans obtained with the International Peach SNP Consortium (IPSC) 9K SNP array v1. We identified SNPs co-segregating with the characters in all cases. Their positions were in agreement with the known positions of the major genes. The number of SNPs linked to each of these, as well as the size of the physical regions encompassing them, varied depending on the maps. As a result, the number of useful SNPs for marker-assisted selection varied accordingly. As a whole, this study establishes a sound basis for further development of MAS on these characters. Additionally, we also discussed some limitations that were observed regarding the SNP array efficiency.

Single nucleotide polymorphism and its dynamics for pharmacogenomics.

Pharmacogenomics is the study of how the genetic makeup determines the response to a therapeutic intervention. It has the capability to revolutionize the practice of medicine by personalized approach for treatment through the use of novel diagnostic tools. Pharmacogenomic based approaches reduce the trial-and-error approach and restrict the exposure of patients to those drugs which are not effective or are toxic for them. Single Nucleotide Polymorphisms (SNPs) hold the key in defining the risk of an individual's susceptibility to various illnesses and response to drugs. There is an ongoing process of identifying the common, biologically relevant SNPs, in particular those that are associated with the risk of disease and adverse drug reaction. The identification and characterization of these SNPs are necessary before their use as genetic tools. Most of the ongoing SNP related studies are biased deliberately towards coding regions and the data generated from them are therefore unlikely to reflect genome wide distribution of SNPs. To avoid this biasing towards the coding regions SNP, SNP consortium protocol was designed. Though, projects like the HapMap increase credibility and use of SNPs, still there are some concern like the required sample (patient) sizes, the number of SNPs required for mapping, number of association studies, the cost of SNP genotyping, and the interpretation and explanation of results are some of the challenges that surround this field.

Evaluating the possibility of detecting evidence of positive selection across Asia with sparse genotype data from the HUGO Pan-Asian SNP Consortium.

BackgroundThe HUGO Pan-Asian SNP Consortium (PASNP) has generated a genetic resource of almost 55,000 autosomal single nucleotide polymorphisms (SNPs) across more than 1,800 individuals from 73 urban and indigenous populations in Asia. This has offered valuable insights into the correlation between the genetic ancestry of these populations with major linguistic systems and geography. Here, we attempt to understand whether adaptation to local climate, diet and environment partly explains the genetic variation present in these populations by investigating the genomic signatures of positive selection.ResultsTo evaluate the impact to the selection analyses due to the considerably lower SNP density as compared to other population genetics resources such as the International HapMap Project (HapMap) or the Singapore Genome Variation Project, we evaluated the extent of haplotype phasing switch errors and the consistency of selection signals from three haplotype-based approaches (iHS, XP-EHH, haploPS) when the HapMap data is thinned to a similar density as PASNP. We subsequently applied haploPS to detect and characterize positive selection in the PASNP populations, identifying 59 genomics regions that were selected in at least one PASNP populations. A cluster analysis on the basis of these 59 signals showed that indigenous populations such as the Negrito from Malaysia and Philippines, the China Hmong, and the Taiwan Ami and Atayal shared more of these signals. We also reported evidence of a positive selection signal encompassing the beta globin gene in the Taiwan Ami and Atayal that was distinct from the signal in the HapMap Africans, suggesting the possibility of convergent evolution at this locus due to malarial selection.ConclusionsWe established that the lower SNP content of the PASNP data conferred weaker ability to detect signatures of positive selection, but the availability of the new approach haploPS retained modest power. Out of all the populations in PASNP, we identified only 59 signals, suggesting a strong need for high-density population-level genotyping data or sequencing data in order to achieve a comprehensive survey of positive selection in Asian populations.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-332) contains supplementary material, which is available to authorized users.

Molecular-level and trait-level differentiation between the cultivated apple (Malus× domesticaBorkh.) and its main progenitorMalussieversii

The present study is the first to compare the trait-level differentiation (Qst) and the molecular-level differentiation (Fst) betweenMalus× domesticaandMalus sieversii. A set of 115 accessions representingM.× domestica(99) andM. sieversii(16) were genotyped using the International RosBREED SNP Consortium apple 8K SNP array and phenotyped for eight fruit quality traits in a clonally replicated experiment. A set of 3521 single nucleotide polymorphisms (SNPs) with an average call rate of 98% was retained following SNP data quality filters. About 86% of the total SNPs were polymorphic inM. sieversii, while all but three SNPs were polymorphic inM. × domestica. The patterns of linkage disequilibrium were different, especially at the longer distances, between the two species. No differentiation (Fst= 0) was observed for nearly 23% of the SNPs, but about 20% of the SNPs exhibited a high genetic differentiation (Fst≥ 0.15). A highly significant (P< 0.001) genome-levelFst= 0.12 was observed betweenM. × domesticaandM. sieversii. The average estimatedQstvalue was 0.20 (range 0.08–0.40), and for three of the eight studied traits (crispness, flavour intensity and fruit weight),Qstvalue was more than twice the estimated genome-levelFstvalue. A higherQstvalue thanFstvalue for four of the eight fruit quality traits indicated differential (or directional) selection for these traits inM. × domestica. The average posterior probability of assignment ofM. × domesticaaccessions to theM. sieversiigene pool was 11%, supporting the hypothesis ofM. sieversiibeing one of the progenitors of the domesticated apple.

A consensus ‘Honeycrisp’ apple (Malus × domestica) genetic linkage map from three full-sib progeny populations

The apple cultivar Honeycrisp is emerging in North American markets due to its outstanding eating quality. A set of three ‘Honeycrisp’ progeny populations from the University of Minnesota apple breeding program were utilized to construct parental and consensus ‘Honeycrisp’ linkage maps to enable marker-assisted breeding. Two populations were segregated for fruit texture traits and a third was of interest in examining disease resistance. All available individuals were genotyped with the International RosBREED SNP Consortium (IRSC) apple 8K SNP array v1, for a total of 318 progeny individuals. Three unique ‘Honeycrisp’ parental maps (‘Honeycrisp’ × ‘Monark,’ ‘Honeycrisp’ × ‘Gala,’ and ‘Honeycrisp’ × MN1764) were developed, consisting of 1,018, 1,042, and 1,041 single-nucleotide polymorphism (SNP) markers, respectively. Among all three ‘Honeycrisp’ parental maps, 951 SNP markers were in common. Combining these maps with the MergeMap tool, a consensus ‘Honeycrisp’ linkage map with 1,091 SNP markers was developed with an average distance of 1.36 cM between consecutive markers. The ‘Honeycrisp’ consensus map was largely in agreement with the physical position of markers in the ‘Golden Delicious’ reference genome sequence (v1.0, as of February 2013). The consensus linkage map is informative for an elite cultivar that is being utilized in breeding programs worldwide for its superb fruit quality traits.

Genetic dissection of aroma volatile compounds from the essential oil of peach fruit: QTL analysis and identification of candidate genes using dense SNP maps

Volatile organic compounds (VOCs) in plants are involved in aroma and pest resistance. These compounds form a complex mixture whose composition is specific to species and often to varieties. Despite their importance as essential factors that determine peach fruit quality, understanding of molecular, genetic, and physiological mechanisms underlying aroma formation is limited. The aim of this study was the identification in peach of quantitative trait loci (QTLs) for fruit VOCs to understand their genetic basis using an F1 population of 126 seedlings deriving from the cross between “Bolero” (B) and “OroA” (O), two peach cultivars differing in their aroma profile. Dense single nucleotide polymorphism (SNP) and SSR maps covering the eight linkage groups of the peach genome were constructed by genotyping with the International Peach SNP Consortium peach SNP array v1, and data for 23 VOCs with high or unknown “odor activity value” were obtained by gas chromatography–mass spectrometry analysis of fruit essential oil in the years 2007 and 2008. A total of 72 QTLs were identified, most consistent in both years. QTLs were identified for the 23 VOCs studied, including three major QTLs for nonanal, linalool, and for p-menth-1-en-9-al stable in both years. Collocations between candidate genes and major QTLs were identified taking advantage of the peach genome sequence: genes encoding two putative terpene synthases and one lipoxygenase (Lox) might be involved in the biosynthesis of linalool and p-menth-1-en-9-al, and nonanal, respectively. Implications for marker-assisted selection and future research on the subject are discussed.

Development and Evaluation of a 9K SNP Array for Peach by Internationally Coordinated SNP Detection and Validation in Breeding Germplasm

Although a large number of single nucleotide polymorphism (SNP) markers covering the entire genome are needed to enable molecular breeding efforts such as genome wide association studies, fine mapping, genomic selection and marker-assisted selection in peach [Prunus persica (L.) Batsch] and related Prunus species, only a limited number of genetic markers, including simple sequence repeats (SSRs), have been available to date. To address this need, an international consortium (The International Peach SNP Consortium; IPSC) has pursued a coordinated effort to perform genome-scale SNP discovery in peach using next generation sequencing platforms to develop and characterize a high-throughput Illumina Infinium® SNP genotyping array platform. We performed whole genome re-sequencing of 56 peach breeding accessions using the Illumina and Roche/454 sequencing technologies. Polymorphism detection algorithms identified a total of 1,022,354 SNPs. Validation with the Illumina GoldenGate® assay was performed on a subset of the predicted SNPs, verifying ∼75% of genic (exonic and intronic) SNPs, whereas only about a third of intergenic SNPs were verified. Conservative filtering was applied to arrive at a set of 8,144 SNPs that were included on the IPSC peach SNP array v1, distributed over all eight peach chromosomes with an average spacing of 26.7 kb between SNPs. Use of this platform to screen a total of 709 accessions of peach in two separate evaluation panels identified a total of 6,869 (84.3%) polymorphic SNPs.The almost 7,000 SNPs verified as polymorphic through extensive empirical evaluation represent an excellent source of markers for future studies in genetic relatedness, genetic mapping, and dissecting the genetic architecture of complex agricultural traits. The IPSC peach SNP array v1 is commercially available and we expect that it will be used worldwide for genetic studies in peach and related stone fruit and nut species.

Genomic selection - Revolutionary breeding practice in Domestic animals

With more and more Single Nucleotide Polymorphisms (SNPs) being identified throughout the genome, some of those SNPs will be found to be located within candidate genes, allowing the researchers to use the candidate gene approach on a genomewide scale. SNPs have some drawbacks but when compared to other markers they are more efficient and SNP consortium is growing to meet the requirements of genome-wide scans. Genomic selection should be able to at least double the rate of genetic gain in the dairy industry but the incorporation of genomic information into the breeding programs must be carefully considered. One needs to have around 2000 genotypes means a large reference population (population with both phenotype and genotype recorded) to achieve meaningful increases in accuracy. The available information, selection objectives, production circumstances and benefit/cost analysis must be evaluated in order to decide whether or not the population is suitable for GS implementation, and which would be the most convenient way, if any, for its implementation. Animal breeders will need to lead the way on the integration of genomic and phenotypic data into a new era of genome-enabled animal improvement and management.

Current Research Status, Databases and Application of Single Nucleotide Polymorphism

Single Nucleotide Polymorphisms (SNPs) are the most frequent form of DNA variation in the genome. SNPs are genetic markers which are bi-allelic in nature and grow at a very fast rate. Current genomic databases contain information on several million SNPs. More than 6 million SNPs have been identified and the information is publicly available through the efforts of the SNP Consortium and others data bases. The NCBI plays a major role in facillating the identification and cataloging of SNPs through creation and maintenance of the public SNP database (dbSNP) by the biomedical community worldwide and stimulate many areas of biological research including the identification of the genetic components of disease. In this review article, we are compiling the existing SNP databases, research status and their application.

The $1,000 genome, the $100,000 analysis?

The $1,000 genome, the $100,000 analysis?

The case for open‐access chemical biology

Policy‐makers and scientists are increasingly worried about the declining productivity of the pharmaceutical industry. Despite growing levels of investment from governments and industry, the number of new medicines that are approved each year has declined slowly during the past three decades (Betz, 2005; Booth & Zemmel, 2004; Cuatrecasas, 2006). The increased costs of drug discovery and development can no longer be supported by healthcare systems, and regulators are implementing control mechanisms such as price control schemes and increased regulatory demands, which could ultimately affect the drug discovery process by altering the financial and regulatory landscapes for new research programmes (Ess et al , 2003; Miller & Henderson, 2007). > The increased costs of drug discovery and development can no longer be supported by healthcare systems… Over the years, the industry has relied on various technologies to improve drug discovery. However, despite the use of structure‐based drug design, high‐throughput screening, combinatorial chemistry and the various ‘‐omics’ technologies, productivity continues to decline. The various explanations for this lack of success include increasing regulatory requirements, the depletion of therapeutic opportunities and ‘druggable’ targets, competition and organizational inefficiencies (Booth & Zemmel, 2004; Cuatrecasas, 2006; Dickson & Gagnon, 2004; Garnier, 2008). Although each of these explanations rings true, at the heart of the problem is a lack of proper scientific understanding of human biology and disease mechanisms. This is ultimately manifested in the high fraction of clinical programmes that fail owing to a lack of efficacy or safety, often in spite of excellent pre‐clinical data (Fingleton, 2008; Kola & Landis, 2004). Without a doubt, improved drug‐target validation would improve the success rate of drug discovery programmes, but this necessitates a better understanding of fundamental biological processes and the biological role of the drug target—usually a protein—under investigation. Paradoxically, …

Proportioning Whole-Genome Single-Nucleotide–Polymorphism Diversity for the Identification of Geographic Population Structure and Genetic Ancestry

The identification of geographic population structure and genetic ancestry on the basis of a minimal set of genetic markers is desirable for a wide range of applications in medical and forensic sciences. However, the absence of sharp discontinuities in the neutral genetic diversity among human populations implies that, in practice, a large number of neutral markers will be required to identify the genetic ancestry of one individual. We showed that it is possible to reduce the amount of markers required for detecting continental population structure to only 10 single-nucleotide polymorphisms (SNPs), by applying a newly developed ascertainment algorithm to Affymetrix GeneChip Mapping 10K SNP array data that we obtained from samples of globally dispersed human individuals (the Y Chromosome Consortium panel). Furthermore, this set of SNPs was able to recover the genetic ancestry of individuals from all four continents represented in the original data set when applied to an independent, much larger, worldwide population data set (Centre d'Etude du Polymorphisme Humain-Human Genome Diversity Project Cell Line Panel). Finally, we provide evidence that the unusual patterns of genetic variation we observed at the respective genomic regions surrounding the five most informative SNPs is in agreement with local positive selection being the explanation for the striking SNP allele-frequency differences we found between continental groups of human populations.

Evolution of a Length Polymorphism in the Human PER3 Gene, a Component of the Circadian System

Period homologue 3 (PER3) is a component of the mammalian circa-dian system, although its precise role is unknown. A biallelic variable number tandem repeat (VNTR) polymorphism exists in human PER3, consisting of 4 or 5 repeats of a 54-bp sequence in a region encoding a putative phosphorylation domain. This polymorphism has previously been reported to associate with diurnal preference ("morningness" and "eveningness") and delayed sleep-phase syndrome. We have investigated the global allele frequencies of this variant in ethnically distinct indigenous populations. All populations were polymorphic, with the shorter (4-repeat) allele ranging in frequency from 0.19 (Papua New Guinea) to 0.89 (Mongolia). To investigate if allele frequency has been influenced by natural selection, the authors 1) tested for a correlation with latitude and mean annual insolation (incident sunlight energy), using classical markers to correct for historical population differentiation; and they 2) compared allele-frequency difference between European American, African American, and East Asian populations, as measured using F(ST), to an empirical null distribution of F(ST)values based on a genome-wide dataset of single nucleotide polymorphisms (SNPs) of presumed neutral loci that were previously typed by The SNP Consortium. The variation in allele frequencies between indigenous populations did not show a pattern that would indicate selective pressure on PER3resulting from day-length variation or mean annual insolation, and the allele-frequency difference between European Americans, African Americans, and East Asians was not an outlier when compared to the distribution for presumed neutral SNPs. We therefore find no evidence for differential or balancing selection in the contemporary pattern of global PER3allele frequencies.

High-density single-nucleotide polymorphism maps of the human genome

Here we report a large, extensively characterized set of single-nucleotide polymorphisms (SNPs) covering the human genome. We determined the allele frequencies of 55,018 SNPs in African Americans, Asians (Japanese–Chinese), and European Americans as part of The SNP Consortium's Allele Frequency Project. A subset of 8333 SNPs was also characterized in Koreans. Because these SNPs were ascertained in the same way, the data set is particularly useful for modeling. Our results document that much genetic variation is shared among populations. For autosomes, some 44% of these SNPs have a minor allele frequency ≥10% in each population, and the average allele frequency differences between populations with different continental origins are less than 19%. However, the several percentage point allele frequency differences among the closely related Korean, Japanese, and Chinese populations suggest caution in using mixtures of well-established populations for case–control genetic studies of complex traits. We estimate that ∼7% of these SNPs are private SNPs with minor allele frequencies <1%. A useful set of characterized SNPs with large allele frequency differences between populations (>60%) can be used for admixture studies. High-density maps of high-quality, characterized SNPs produced by this project are freely available.

Determination and analysis of single nucleotide polymorphisms and haplotype structure of the human carboxylesterase 2 gene.

Carboxylesterases are members of the serine esterase super family important in the metabolism of a wide variety of substrates, including xenobiotics and prodrugs. There are two known carboxylesterases expressed in human liver, small intestine and other tissues, carboxylesterase 1 (CES1) and carboxylesterase 2 (CES2). The aim of this study was to identify polymorphisms in the CES2 gene and determine whether these polymorphisms affect expression levels of CES2 or rate of metabolism of irinotecan (7-ethyl-10-[4-(1-piperidino)-1-piperidino] carbonyloxy-camptothecin). Microsome samples prepared from liver tissues of 78 normal individuals were used to determine the rate of hydrolysis of irinotecan and procaine (an anaesthetic hydrolysed by CES2 but not CES1). The rate of hydrolysis of irinotecan is highly variable among individuals, ranging from 2.7-138 pmol/mg protein/h (mean +/- SD 26.0 +/- 22.9). Fifteen single nucleotide polymorphisms (SNPs) were identified, one is in an exon, 9 are in introns, three are in the 3'-untranslated region (UTR), and two are in the 5'-flanking region. Eight of the 15 SNP loci have rare allele frequencies greater than 5%, of which three were greater than 20%. Genotyping of samples from the SNP Consortium demonstrated different distributions among African-Americans, Asian-Americans and European-Americans. We also analysed the haplotype structure and estimated linkage disequilibrium (LD). A SNP located in the 5'-UTR (5'-UTR-363) was found in LD with loci in intron 1 (Intron1 + 947, Intron1 + 1361, Intron1 + 1643). Haplotypes with homozygous rare alleles on these loci exhibit lower mRNA levels as determined by real time polymerase chain reaction (P < 0.01) and the incorporation of rare alleles in haplotypes correlate with reduced mRNA (P = 0.03). The 5'-UTR-363 SNP is located in one of the three promoters of CES2. However, we did not observe significant differences in CES2 activities (irinotecan and procaine hydrolysis) among individuals with different haplotypes.

SNPs, Haplotypes, and Cancer: Applications in Molecular Epidemiology

SNPs, Haplotypes, and Cancer: Applications in Molecular Epidemiology