Project description:The influence of genetics on DNA methylation (DNAme) variation is well documented, yet confounding from population stratification is often unaccounted for in DNAme association studies. Existing approaches have been developed to address confounding by population stratification by directly using DNAme data, but have not been validated in additional human populations or tissues, such as the placenta. Results: To aid future placental DNAme studies in assessing population stratification, we developed an ethnicity classifier, PLANET (placental elastic net DNAme ethnicity classifier), on combined Infinium Human Methylation 450k BeadChip array (HM450k) data from placental samples. We used data from five North American cohorts from private and public repositories (n = 509) and show that PLANET can not only accurately predict (accuracy = 0.9379, kappa = 0.8227) major classes of self-reported ethnicity/race (African: n = 58, Asian: n = 53, Caucasian: n = 389), but can also produce probabilities that are highly correlated with genetic ancestry inferred from genome-wide SNP (>2.5 million SNP) and ancestry informative markers (n=50) data. We found that PLANET’s ethnicity classification relies on 1860 DNAme microarray sites, and over half of these were also linked to nearby genetic polymorphisms (n=955). Lastly, we found our placental-optimized method outperforms existing approaches in assessing population stratification in our placental samples from individuals of Asian, African, and Caucasian ethnicities. Conclusion: PLANET outperforms existing methods and heavily relies on the genetic signal present in DNAme microarray data. PLANET can be used to address population stratification in future placental DNAme association studies, and will be especially useful when ethnicity information is missing and genotyping markers are unavailable.
Project description:To accelerate genetic studies in sugarcane, an Axiom Sugarcane100K single nucleotide polymorphism (SNP) array was designed and customized in this study. Target enrichment sequencing 300 sugarcane accessions selected from the world collection of sugarcane and related grass species yielded more than four million SNPs, from which a total of 31,449 single dose (SD) SNPs and 68,648 low dosage (33,277 SD and 35,371 double dose) SNPs from two datasets respectively were selected and tiled on Affymetrix Axiom SNP array. Most of selected SNPs (91.77%) were located within genic regions (12,935 genes), with an average of 7.1 SNPs/gene according to sorghum gene models. This newly developed array was used to genotype 469 sugarcane clones, including one F1 population derived from cross between Green German and IND81-146, one selfing population derived from CP80-1827, and 11 diverse sugarcane accessions as controls. Results of genotyping revealed a high polymorphic SNP rate (77.04%) among the 469 samples. Three linkage maps were constructed by using SD SNP markers, including a genetic map for Green German with 3,482 SD SNP markers spanning 3,336 cM, a map for IND81-146 with 1,513 SD SNP markers spanning 2,615 cM, and a map for CP80-1827 with 536 SD SNP markers spanning 3,651 cM. Quantitative trait loci (QTL) analysis identified a total of 18 QTLs controlling Sugarcane yellow leaf virus resistance segregating in the two mapping populations, harboring 27 disease resistant genes. This study demonstrated the successful development and utilization of a SNP array as an efficient genetic tool for high throughput genotyping in highly polyploid sugarcane.
Project description:This dataset results from the discovery, characterization and validation of 74 genetically variant peptides from fingermark protein. These peptides contain single amino acid polymorphisms, the result of non-synonymous SNPs. Detection of these peptide markers in fingermark proteomic datasets allows inferences to be made about the genotype status of corresponding SNP alleles. These inferences provide an individual genetic profile that may be used to calculate random match probabilities and provide information about potential genetic background. Epidermal corneocytes from five European and four South Asian subjects were isolated, processed, proteolytically digested with trypsin and 0.75 µg applied to a Q ExactiveTM hybrid quadrupole-Orbitrap mass spectrometer. The resulting datasets were used for discovery of genetically variant peptides by a “bottom-up” analysis of potential variants identified in X!Tandem datasets (thegpm.org) or by a “top-down” proteomic confirmation of non-synonymous SNP variants shown to be present in corresponding subject exome datasets. The later method resulted in discovery of a rare allele that was not observed in the 1000 Genome Project. The cumulative profiles of detected genetically variant peptides were obtained for each subject. Candidate genetically variant peptides were then validated by comparing proteomically inferred SNP alleles with matching genotypes in exome datasets. An average of 28.8 ± 4.4 genetically variant peptides were detected from each subject. Across the 9 subjects a total of 264 SNP allele inferences were made resulting in 260 true positives and 4 false positives, a false positive rate of 1.5%. Random match probabilities were calculated using the genotype frequencies of common genetically variant peptides from the matching major populations in the 1000 genome project. Estimates ranged up to a value of 1 in 1.7 x 108, with a median probability of 1 in 2.4 x 106. When probabilities were recalculated using values from other major genetic population groups African values were considerably less conservative, with resulting likelihood ratios (AFR/other populations) ranging up to 6 orders of magnitude. Conversely there was no resolution among estimates obtained from all non-African population groups, where resulting random match probabilities were within an order of magnitude. These genetically variant peptides are a starting point for the development of targeted mass spectrometry-based proteomic analyses that will increase the sensitivity of peptide detection. This project represents a novel mode of genetic information that can be obtained from fingermarks and has the potential to complement or confirm other methods of human identification including analysis of ridge patterns or touch DNA.
Project description:The identification of surrogate single nucleotide polymorphism (SNP) markers that can predict responses to preoperative chemoradiotherapy (CRT) in rectal cancer patients. Genome-wide association studies in clinical populations are theoretically capable of identifying markers that are capable of tumor regression after CRT. We used Affymetrix’s SNP Array 6.0 to detail genetic polymorphism of patient’s group showing differential responsiveness to preoperative CRT and profiled SNP biomarkers.
Project description:The identification of surrogate single nucleotide polymorphism (SNP) markers that can predict responses to chemotherapy could enable the efficient selection of patients for various regimens. Genome-wide association studies in clinical populations are theoretically capable of identifying markers that are capable of influencing drug responses. We used Affymetrix’s SNP Array 6.0 to detail genetic polymorphism of patient’s group showing differential responsiveness to various regimens and profiled SNP biomarkers for various regimens.
2011-12-31 | GSE26853 | GEO
Project description:Genetic Diversity and Population Structure of eddoe Taro in China Using Genome-wide SNP Markers
Project description:Women of sub-Saharan African descent have disproportionately higher incidence of Triple Negative Breast Cancer (TNBC), and TNBC-specific mortality. Population comparative studies show racial differences in TNBC biology, including higher prevalence of basal-like and Quadruple-Negative subtypes in African Americans (AA). However, previous investigations relied on self-reported race (SRR) of primarily United States (US) populations. Due to heterogenous genetic admixture, and biological consequences of social determinants, the true association of African ancestry with TNBC biology is unclear. To address this, we conducted RNAseq on an international cohort of AAs, west and east Africans with TNBC. Using comprehensive genetic ancestry estimation in this African-enriched cohort, we found expression of 613 genes associated with African ancestry and 2000+ associated with regional African ancestry. A subset of African-associated genes also showed differences in normal breast tissue. Pathway enrichment and deconvolution of tumor cellular composition revealed tumor-associated immunological profiles are distinct in patients of African descent.