Parallel Multi-objective Optimization for High-Order Epistasis Detection

The β2-adrenoceptor gene and hypertension: is it the promoter or the coding region or neither?

Gene-guided therapy for catheter-ablation of atrial fibrillation: are we there yet?

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Variants in dehydroepiandrosterone sulfotransferase (SULT2A1) are involved in the regulation of dehydroepiandrosterone (DHEA)/DHEA-Sulfate (DHEAS) levels in the polycystic ovary syndrome

Breast cancer is the most frequently diagnosed cancer and the second leading cause of cancer death in American women. Earlier family linkage studies have identified high-penetrance breast cancer genes, such as BRCA1, BRCA2, and TP53. Moreover, genes involved in DNA repair, such as CHEK2, ATM, BRIP and PALB2, have been associated with moderate breast cancer risk. Recent Genome-wide Association Studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with breast cancer risk. We evaluated whether breast cancer risk is associated with multiple SNPs in DNA damage signaling and repair and immune and inflammatory responses in addition to SNPs identified from GWAS. We hypothesize that targeting critical candidate pathways may yield important information regarding SNP-SNP interactions in breast cancer risk. We selected SNPs from DNA damage signaling and cell cycle control, base excision repair, nucleotide excision repair, double-strand break repair, mismatch repair, and immune and inflammatory responses. We have genotype results of 3,754 SNPs in 910 controls (763 Whites and 147 African Americans) and 793 breast cancer cases (667 Whites and 116 African Americans). 16.2% and 20.6% of controls and cases (respectively) had a first degree relative with breast cancer. 48% and 55.7% of the controls and cases (respectively) had their first child before or at the age of 24. 40.5% and 42.2% of the controls and cases (respectively) had a history of smoking. Our study results suggest that 6 SNPs were associated with breast cancer risk in Whites: (1) 2 SNPs from GWAS - rs3817198 in LSP1 (p<0.001) and rs3803662 in TNRC9 (p<0.001); (2) 2 SNPs from inflammation - rs1801157 in SDF-1 (p<0.001) and rs12720356 in Tyk2 (p<0.001) and (3) 2 SNPs from DNA repair and apoptosis - rs2992 in CHAF1A (p<0.0001) and rs2231301 in BCL2l2 (p<0.001). Only 1 SNP, rs1990760 in IFIH1 (p<0.01) was associated with breast cancer risk in African Americans. The IFIH1 gene was previously linked to Type 1 diabetes but not in cancer risk. There was significant trend in breast cancer risk with increasing numbers of risk genotypes for rs3817198, rs3803662, rs1801157, rs12720356, rs2992, and rs2231301 (p test for trend <0.0001) in Whites after adjustment for potential confounders. Our results suggest that multiple SNPs contribute to breast cancer risk in a racial/ethnic specific manner and larger studies are warranted to further evaluate our findings. More importantly, functional analysis is under way to corroborate the association of multiple SNPs with breast cancer risk. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2613. doi:1538-7445.AM2012-2613

High‐throughput genotyping in estimating genetic resources and detecting pathogens in aquaculture

IL28B single nucleotide polymorphisms in the treatment of hepatitis C

Detecting genes associated with milk fat composition could provide valuable insights into the complex genetic networks of genes underling variation in fatty acids synthesis and point towards opportunities for changing milk fat composition via selective breeding. In this study, we conducted a genome-wide association study (GWAS) for 22 milk fatty acids in 784 Chinese Holstein cows with the PLINK software. Genotypes were obtained with the Illumina BovineSNP50 Bead chip and a total of 40,604 informative, high-quality single nucleotide polymorphisms (SNPs) were used. Totally, 83 genome-wide significant SNPs and 314 suggestive significant SNPs associated with 18 milk fatty acid traits were detected. Chromosome regions that affect milk fatty acid traits were mainly observed on BTA1, 2, 5, 6, 7, 9, 13, 14, 18, 19, 20, 21, 23, 26 and 27. Of these, 146 SNPs were associated with more than one milk fatty acid trait; most of studied fatty acid traits were significant associated with multiple SNPs, especially C18:0 (105 SNPs), C18 index (93 SNPs), and C14 index (84 SNPs); Several SNPs are close to or within the DGAT1, SCD1 and FASN genes which are well-known to affect milk composition traits of dairy cattle. Combined with the previously reported QTL regions and the biological functions of the genes, 20 novel promising candidates for C10:0, C12:0, C14:0, C14:1, C14 index, C18:0, C18:1n9c, C18 index, SFA, UFA and SFA/UFA were found, which composed of HTR1B, CPM, PRKG1, MINPP1, LIPJ, LIPK, EHHADH, MOGAT1, ECHS1, STAT1, SORBS1, NFKB2, AGPAT3, CHUK, OSBPL8, PRLR, IGF1R, ACSL3, GHR and OXCT1. Our findings provide a groundwork for unraveling the key genes and causal mutations affecting milk fatty acid traits in dairy cattle.

BackgroundSingle nucleotide polymorphisms (SNPs) are the most common type of genetic variation. Identification of large numbers of SNPs is helpful for genetic diversity analysis, map-based cloning, genome-wide association analyses and marker-assisted breeding. Recently, identifying genome-wide SNPs in allopolyploid Brassica napus (rapeseed, canola) by resequencing many accessions has become feasible, due to the availability of reference genomes of Brassica rapa (2n = AA) and Brassica oleracea (2n = CC), which are the progenitor species of B. napus (2n = AACC). Although many SNPs in B. napus have been released, the objective in the present study was to produce a larger, more informative set of SNPs for large-scale and efficient genotypic screening. Hence, short-read genome sequencing was conducted on ten elite B. napus accessions for SNP discovery. A subset of these SNPs was randomly selected for sequence validation and for genotyping efficiency testing using the Illumina GoldenGate assay.ResultsA total of 892,536 bi-allelic SNPs were discovered throughout the B. napus genome. A total of 36,458 putative amino acid variants were located in 13,552 protein-coding genes, which were predicted to have enriched binding and catalytic activity as a result. Using the GoldenGate genotyping platform, 94 of 96 SNPs sampled could effectively distinguish genotypes of 130 lines from two mapping populations, with an average call rate of 92%.ConclusionsDespite the polyploid nature of B. napus, nearly 900,000 simple SNPs were identified by whole genome resequencing. These SNPs were predicted to be effective in high-throughput genotyping assays (51% polymorphic SNPs, 92% average call rate using the GoldenGate assay, leading to an estimated >450 000 useful SNPs). Hence, the development of a much larger genotyping array of informative SNPs is feasible. SNPs identified in this study to cause non-synonymous amino acid substitutions can also be utilized to directly identify causal genes in association studies.

BackgroundThe apparent effect of a single nucleotide polymorphism (SNP) on phenotype depends on the linkage disequilibrium (LD) between the SNP and a quantitative trait locus (QTL). However, the phase of LD between a SNP and a QTL may differ between Bos indicus and Bos taurus because they diverged at least one hundred thousand years ago. Here, we test the hypothesis that the apparent effect of a SNP on a quantitative trait depends on whether the SNP allele is inherited from a Bos taurus or Bos indicus ancestor.MethodsPhenotype data on one or more traits and SNP genotype data for 10 181 cattle from Bos taurus, Bos indicus and composite breeds were used. All animals had genotypes for 729 068 SNPs (real or imputed). Chromosome segments were classified as originating from B. indicus or B. taurus on the basis of the haplotype of SNP alleles they contained. Consequently, SNP alleles were classified according to their sub-species origin. Three models were used for the association study: (1) conventional GWAS (genome-wide association study), fitting a single SNP effect regardless of subspecies origin, (2) interaction GWAS, fitting an interaction between SNP and subspecies-origin, and (3) best variable GWAS, fitting the most significant combination of SNP and sub-species origin.ResultsFitting an interaction between SNP and subspecies origin resulted in more significant SNPs (i.e. more power) than a conventional GWAS. Thus, the effect of a SNP depends on the subspecies that the allele originates from. Also, most QTL segregated in only one subspecies, suggesting that many mutations that affect the traits studied occurred after divergence of the subspecies or the mutation became fixed or was lost in one of the subspecies.ConclusionsThe results imply that GWAS and genomic selection could gain power by distinguishing SNP alleles based on their subspecies origin, and that only few QTL segregate in both B. indicus and B. taurus cattle. Thus, the QTL that segregate in current populations likely resulted from mutations that occurred in one of the subspecies and can have both positive and negative effects on the traits. There was no evidence that selection has increased the frequency of alleles that increase body weight.

This chapter contains sections titled: Introduction Informative SNP Selection Disease Association Search Disease Susceptibility Prediction Results and Discussion References

With recent advances in genomewide microarray technologies, whole-genome association (WGA) studies have aimed at identifying susceptibility genes for complex human diseases using hundreds of thousands of single nucleotide polymorphisms (SNPs) genotyped at the same time. In this context and to take into account multiple testing, false discovery rate (FDR)-based strategies are now used frequently. However, a critical aspect of these strAtegies is that they are applied to a collection or a family of hypotheses and, thus, critically depend on these precise hypotheses. We investigated how modifying the family of hypotheses to be tested affected the performance of FDR-based procedures in WGA studies. We showed that FDR-based procedures performed more poorly when excluding SNPs with high prior probability of being associated. Results of simulation studies mimicking WGA studies according to three scenarios are reported, and show the extent to which SNPs elimination (family contraction) prior to the analysis impairs the performance of FDR-based procedures. To illustrate this situation, we used the data from a recent WGA study on type-1 diabetes (Clayton et al. [2005] Nat. Genet. 37:1243-1246) and report the results obtained when excluding or not SNPs located inside the human leukocyte antigen region. Based on our findings, excluding markers with high prior probability of being associated cannot be recommended for the analysis of WGA data with FDR-based strategies.

Many association studies provide the relationship between single nucleotide polymorphisms (SNPs), diseases and cancers, without giving a SNP ID, however. Here, we developed the SNP ID-info freeware to provide the SNP IDs within inputting genetic and physical information of genomes. The program provides an "SNP-ePCR" function to generate the full-sequence using primers and template inputs. In "SNPosition," sequence from SNP-ePCR or direct input is fed to match the SNP IDs from SNP fasta-sequence. In "SNP search" and "SNP fasta" function, information of SNPs within the cytogenetic band, contig position, and keyword input are acceptable. Finally, the SNP ID neighboring environment for inputs is completely visualized in the order of contig position and marked with SNP and flanking hits. The SNP identification problems inherent in NCBI SNP BLAST are also avoided. In conclusion, the SNP ID-info provides a visualized SNP ID environment for multiple inputs and assists systematic SNP association studies. The server and user manual are available at http://bio.kuas.edu.tw/snpid-info.

Extracellular ATP (eATP) released from damaged cells activates the P2X7 receptor (P2X7R) ion channel on the surface of surrounding cells, resulting in calcium influx, potassium efflux and inflammasome activation. Inherited changes in the P2X7R gene (P2RX7) influence eATP induced responses. Single nucleotide polymorphisms (SNPs) of P2RX7 influence both function and signaling of the receptor, that in addition to ion flux includes pathogen control and immunity. Subjects (n = 105) were admitted to the ICU at the University Hospital Ulm, Germany between June 2018 and August 2019. Of these, subjects with a diagnosis of sepsis (n = 75), were also diagnosed with septic shock (n = 24), and/or pneumonia (n = 42). Subjects with pneumonia (n = 43) included those without sepsis (n = 1), sepsis without shock (n = 29) and pneumonia with septic shock (n = 13). Out of the 75 sepsis/septic shock patients, 33 patients were not diagnosed with pneumonia. Controls (n = 30) were recruited to the study from trauma patients and surgical patients without sepsis, septic shock, or pneumonia. SNP frequencies were determined for 16 P2RX7 SNPs known to affect P2X7R function, and association studies were performed between frequencies of these SNPs in sepsis, septic shock, and pneumonia compared to controls. The loss-of-function (LOF) SNP rs17525809 (T253C) was found more frequently in patients with septic shock, and non-septic trauma patients when compared to sepsis. The LOF SNP rs2230911 (C1096G) was found to be more frequent in patients with sepsis and septic shock than in non-septic trauma patients. The frequencies of these SNPs were even higher in sepsis and septic patients with pneumonia. The current study also confirmed a previous study by our group that showed a five SNP combination that included the GOF SNPs rs208294 (C489T) and rs2230912 (Q460R) that was designated #21211 was associated with increased odds of survival in severe sepsis. The results found an association between expression of LOF P2RX7 SNPs and presentation to the ICU with sepsis, and septic shock compared to control ICU patients. Furthermore, frequencies of LOF SNPs were found to be higher in sepsis patients with pneumonia compared to those without pneumonia. In addition, a five SNP GOF combination was associated with increased odds of survival in severe sepsis. These results suggest that P2RX7 is required to control infection in pneumonia and that inheritance of LOF variants increases the risk of sepsis when associated with pneumonia. This study confirms that P2RX7 genotyping in pneumonia may identify patients at risk of developing sepsis. The study also identifies P2X7R as a target in sepsis associated with an excessive immune response in subjects with GOF SNP combinations.

Aspirin-intolerant asthma (AIA) is a subtype of bronchial asthma characterized by development of bronchoconstriction evoked by non-steroidal anti-inflammatory drugs (NSAIDs). NSAIDs inhibit the cyclooxygenase pathway, leading to enhancement of the lipoxygenase pathway. We evaluated allelic association of 370 single nucleotide polymorphisms (SNPs) of 63 candidate genes, mostly from the arachidonic acid metabolic cascade, with AIA. After two rounds of screening with 198 AIA patients, multiple SNPs in the prostaglandin E(2) receptor subtype 2 (EP2) gene were associated with AIA (P<0.05). Among the 77 SNPs identified in the EP2 gene, we selected 17 SNPs on the basis of linkage disequilibrium and allelic frequencies (minor allele frequency >0.1) for further association study. SNPs in the promoter region of the EP2 gene, uS5, uS5b, and uS7, were significantly associated with AIA (permutation P=0.039-0.001). Analysis of haplotypes constructed according to the LD pattern showed a significant association with AIA (permutation P=0.001). The most significantly associated SNP, uS5, located in the regulatory region of the EP2 gene, was in a STATs-binding consensus sequence [AIA 31.1% versus control 22.1% (permutation P=0.0016) or versus aspirin-tolerant asthma 22.2% (permutation P=0.0017)]. Although STAT1 binding was not observed in gel mobility shift assay with HeLa nuclear extract, an unidentified protein was specifically bound to the allelic sequence. In in vitro reporter assay in HCT116 cells, the site containing the uS5 allele showed reduced transcription activity. Taken together, these results suggest that uS5 allele serves as a target of a transcription repressor protein. A functional SNP of the EP2 gene associated with risk of AIA should decrease the transcription level, resulting in reduction of the PGE(2) braking mechanism of inflammation and involvement in the molecular mechanism underlying AIA.