Displaying publications 61 - 80 of 82 in total

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  1. Ahmad NS, Redjeki ES, Ho WK, Aliyu S, Mayes K, Massawe F, et al.
    Genome, 2016 Jul;59(7):459-72.
    PMID: 27253730 DOI: 10.1139/gen-2015-0153
    Bambara groundnut (Vigna subterranea (L.) Verdc.) is an indigenous underutilized legume that has the potential to improve food security in semi-arid Africa. So far, there are a lack of reports of controlled breeding populations that could be used for variety development and genetic studies. We report here the construction of the first genetic linkage map of bambara groundnut using a F3 population derived from a "narrow" cross between two domesticated landraces (Tiga Nicuru and DipC) with marked divergence in phenotypic traits. The map consists of 238 DArT array and SSR based markers in 21 linkage groups with a total genetic distance of 608.3 cM. In addition, phenotypic traits were evaluated for a quantitative trait loci (QTL) analysis over two generations. A total of 36 significant QTLs were detected for 19 traits. The phenotypic effect explained by a single QTL ranged from 11.6% to 49.9%. Two stable QTLs were mapped for internode length and growth habit. The identified QTLs could be useful for marker-assisted selection in bambara groundnut breeding programmes.
    Matched MeSH terms: Quantitative Trait Loci
  2. Ting NC, Jansen J, Mayes S, Massawe F, Sambanthamurthi R, Ooi LC, et al.
    BMC Genomics, 2014;15:309.
    PMID: 24767304 DOI: 10.1186/1471-2164-15-309
    Oil palm is an important perennial oil crop with an extremely long selection cycle of 10 to 12 years. As such, any tool that speeds up its genetic improvement process, such as marker-assisted breeding is invaluable. Previously, genetic linkage maps based on AFLP, RFLP and SSR markers were developed and QTLs for fatty acid composition and yield components identified. High density genetic maps of crosses of different genetic backgrounds are indispensable tools for investigating oil palm genetics. They are also useful for comparative mapping analyses to identify markers closely linked to traits of interest.
    Matched MeSH terms: Quantitative Trait Loci
  3. Golam F, Prodhan ZH
    J Sci Food Agric, 2013 Feb;93(3):449-56.
    PMID: 23238771 DOI: 10.1002/jsfa.5983
    Kernel elongation after cooking is an important character of fine rice and most rice consumers prefer length-wise elongation. Although improvement of aromatic rice began early in the 1970s, until now the mechanisms and genetics of kernel elongation has remained unrevealed. Kernel elongation is considered as a physical phenomenon and is influenced by several physicochemical and genetic factors, including genotypes, aging temperature, aging time, water uptake, amylose content and gelatinization temperature. Recently the complete genetic map of fine rice has been created and the gene responsible for kernel length identified; moreover, this gene is tightly linked with the cooked kernel elongation trait. Several molecular markers linked with cooked kernel elongation have been developed. These tools will be helpful for the improvement of this important trait. For the proper study of cooked kernel elongation of rice, this review paper will provide the basis and directional materials for further studies.
    Matched MeSH terms: Quantitative Trait Loci
  4. Lawrenson K, Song F, Hazelett DJ, Kar SP, Tyrer J, Phelan CM, et al.
    Gynecol Oncol, 2019 05;153(2):343-355.
    PMID: 30898391 DOI: 10.1016/j.ygyno.2019.02.023
    OBJECTIVE: Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women.

    METHODS: Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations.

    RESULTS: At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10-8). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10-7) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10-7). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10-7).

    CONCLUSION: While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

    Matched MeSH terms: Quantitative Trait Loci
  5. Wong CK, Bernardo R
    Theor Appl Genet, 2008 Apr;116(6):815-24.
    PMID: 18219476 DOI: 10.1007/s00122-008-0715-5
    Oil palm (Elaeis guineensis Jacq.) requires 19 years per cycle of phenotypic selection. The use of molecular markers may reduce the generation interval and the cost of oil-palm breeding. Our objectives were to compare, by simulation, the response to phenotypic selection, marker-assisted recurrent selection (MARS), and genomewide selection with small population sizes in oil palm, and assess the efficiency of each method in terms of years and cost per unit gain. Markers significantly associated with the trait were used to calculate the marker scores in MARS, whereas all markers were used (without significance tests) to calculate the marker scores in genomewide selection. Responses to phenotypic selection and genomewide selection were consistently greater than the response to MARS. With population sizes of N = 50 or 70, responses to genomewide selection were 4-25% larger than the corresponding responses to phenotypic selection, depending on the heritability and number of quantitative trait loci. Cost per unit gain was 26-57% lower with genomewide selection than with phenotypic selection when markers cost US $1.50 per data point, and 35-65% lower when markers cost $0.15 per data point. With population sizes of N = 50 or 70, time per unit gain was 11-23 years with genomewide selection and 14-25 years with phenotypic selection. We conclude that for a realistic yet relatively small population size of N = 50 in oil palm, genomewide selection is superior to MARS and phenotypic selection in terms of gain per unit cost and time. Our results should be generally applicable to other tree species that are characterized by long generation intervals, high costs of maintaining breeding plantations, and small population sizes in selection programs.
    Matched MeSH terms: Quantitative Trait Loci
  6. Fasahat P, Rahman S, Ratnam W
    J Genet, 2014 Apr;93(1):279-92.
    PMID: 24840849
    Starch accumulates in plants as granules in chloroplasts of source organs such as leaves (transitory starch) or in amyloplasts of sink organs such as seeds, tubers and roots (storage starch). Starch is composed of two types of glucose polymers: the essentially linear polymer amylose and highly branched amylopectin. The amylose content of wheat and rice seeds is an important quality trait, affecting the nutritional and sensory quality of two of the world's most important crops. In this review, we focus on the relationship between amylose biosynthesis and the structure, physical behaviour and functionality of wheat and rice grains. We briefly describe the structure and composition of starch and then in more detail describe what is known about the mechanism of amylose synthesis and how the amount of amylose in starch might be controlled. This more specifically includes analysis of GBSS alleles, the relationship between waxy allelic forms and amylose, and related quantitative trait loci. Finally, different methods for increasing or lowering amylose content are evaluated.
    Matched MeSH terms: Quantitative Trait Loci
  7. Hamdi Y, Soucy P, Kuchenbaeker KB, Pastinen T, Droit A, Lemaçon A, et al.
    Breast Cancer Res Treat, 2017 01;161(1):117-134.
    PMID: 27796716 DOI: 10.1007/s10549-016-4018-2
    PURPOSE: Cis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways.

    METHODS: Using data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of ~320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2.

    RESULTS: We identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 × 10-6). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance.

    CONCLUSION: We identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk.

    Matched MeSH terms: Quantitative Trait Loci
  8. Selamat N, Nadarajah KK
    Plants (Basel), 2021 Apr 07;10(4).
    PMID: 33917162 DOI: 10.3390/plants10040716
    Rice is an important grain that is the staple food for most of the world's population. Drought is one of the major stresses that negatively affects rice yield. The nature of drought tolerance in rice is complex as it is determined by various components and has low heritability. Therefore, to ensure success in breeding programs for drought tolerant rice, QTLs (quantitative trait loci) of interest must be stable in a variety of plant genotypes and environments. This study identified stable QTLs in rice chromosomes in a variety of backgrounds and environments and conducted a meta-QTL analysis of stable QTLs that have been reported by previous research for use in breeding programs. A total of 653 QTLs for drought tolerance in rice from 27 genetic maps were recorded for analysis. The QTLs recorded were related to 13 traits in rice that respond to drought. Through the use of BioMercartor V4.2, a consensus map containing QTLs and molecular markers were generated using 27 genetic maps that were extracted from the previous 20 studies and meta-QTL analysis was conducted on the consensus map. A total of 70 MQTLs were identified and a total of 453 QTLs were mapped into the meta-QTL areas. Five meta-QTLs from chromosome 1 (MQTL 1.5 and MQTL 1.6), chromosome 2 (MQTL2.1 and MQTL 2.2) and chromosome 3 (MQTL 3.1) were selected for functional annotation as these regions have high number of QTLs and include many traits in rice that respond to drought. A number of genes in MQTL1.5 (268 genes), MQTL1.6 (640 genes), MQTL 2.1 (319 genes), MQTL 2.2 (19 genes) and MQTL 3.1 (787 genes) were annotated through Blast2GO. Few major proteins that respond to drought stress were identified in the meta-QTL areas which are Abscisic Acid-Insensitive Protein 5 (ABI5), the G-box binding factor 4 (GBF4), protein kinase PINOID (PID), histidine kinase 2 (AHK2), protein related to autophagy 18A (ATG18A), mitochondrial transcription termination factor (MTERF), aquaporin PIP 1-2, protein detoxification 48 (DTX48) and inositol-tetrakisphosphate 1-kinase 2 (ITPK2). These proteins are regulatory proteins involved in the regulation of signal transduction and gene expression that respond to drought stress. The meta-QTLs derived from this study and the genes that have been identified can be used effectively in molecular breeding and in genetic engineering for drought resistance/tolerance in rice.
    Matched MeSH terms: Quantitative Trait Loci
  9. Li BJ, Zhu ZX, Gu XH, Lin HR, Xia JH
    Mar Biotechnol (NY), 2019 Jun;21(3):384-395.
    PMID: 30863905 DOI: 10.1007/s10126-019-09888-9
    Body color is an interesting economic trait in fish. Red tilapia with red blotches may decrease its commercial values. Conventional selection of pure red color lines is a time-consuming and labor-intensive process. To accelerate selection of pure lines through marker-assisted selection, in this study, double-digest restriction site-associated DNA sequencing (ddRAD-seq) technology was applied to genotype a full-sib mapping family of Malaysia red tilapia (Oreochromis spp.) (N = 192). Genome-wide significant quantitative trait locus (QTL)-controlling red blotches were mapped onto two chromosomes (chrLG5 and chrLG15) explaining 9.7% and 8.2% of phenotypic variances by a genome-wide association study (GWAS) and linkage-based QTL mapping. Six SNPs from the chromosome chrLG5 (four), chrLG15 (one), and unplaced supercontig GL831288-1 (one) were significantly associated to the red blotch trait in GWAS analysis. We developed nine microsatellite markers and validated significant correlations between genotypes and blotch data (p 
    Matched MeSH terms: Quantitative Trait Loci
  10. Lawrenson K, Iversen ES, Tyrer J, Weber RP, Concannon P, Hazelett DJ, et al.
    Carcinogenesis, 2015 Nov;36(11):1341-53.
    PMID: 26424751 DOI: 10.1093/carcin/bgv138
    Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10(-7)). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r (2) with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10(-7)). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene.
    Matched MeSH terms: Quantitative Trait Loci
  11. Lin GW, Xu C, Chen K, Huang HQ, Chen J, Song B, et al.
    Lancet Oncol, 2020 Feb;21(2):306-316.
    PMID: 31879220 DOI: 10.1016/S1470-2045(19)30799-5
    BACKGROUND: Extranodal natural killer T-cell lymphoma (NKTCL; nasal type) is an aggressive malignancy with a particularly high prevalence in Asian and Latin American populations. Epstein-Barr virus infection has a role in the pathogenesis of NKTCL, and HLA-DPB1 variants are risk factors for the disease. We aimed to identify additional novel genetic variants affecting risk of NKTCL.

    METHODS: We did a genome-wide association study of NKTCL in multiple populations from east Asia. We recruited a discovery cohort of 700 cases with NKTCL and 7752 controls without NKTCL of Han Chinese ancestry from 19 centres in southern, central, and northern regions of China, and four independent replication samples including 717 cases and 12 650 controls. Three of these independent samples (451 cases and 5301 controls) were from eight centres in the same regions of southern, central, and northern China, and the fourth (266 cases and 7349 controls) was from 11 centres in Hong Kong, Taiwan, Singapore, and South Korea. All cases had primary NKTCL that was confirmed histopathologically, and matching with controls was based on geographical region and self-reported ancestry. Logistic regression analysis was done independently by geographical regions, followed by fixed-effect meta-analyses, to identify susceptibility loci. Bioinformatic approaches, including expression quantitative trait loci, binding motif and transcriptome analyses, and biological experiments were done to fine-map and explore the functional relevance of genome-wide association loci to the development of NKTCL.

    FINDINGS: Genetic data were gathered between Jan 1, 2008, and Jan 23, 2019. Meta-analysis of all samples (a total of 1417 cases and 20 402 controls) identified two novel loci significantly associated with NKTCL: IL18RAP on 2q12.1 (rs13015714; p=2·83 × 10-16; odds ratio 1·39 [95% CI 1·28-1·50]) and HLA-DRB1 on 6p21.3 (rs9271588; 9·35 × 10-26 1·53 [1·41-1·65]). Fine-mapping and experimental analyses showed that rs1420106 at the promoter of IL18RAP was highly correlated with rs13015714, and the rs1420106-A risk variant had an upregulatory effect on IL18RAP expression. Cell growth assays in two NKTCL cell lines (YT and SNK-6 cells) showed that knockdown of IL18RAP inhibited cell proliferation by cell cycle arrest in NKTCL cells. Haplotype association analysis showed that haplotype 47F-67I was associated with reduced risk of NKTCL, whereas 47Y-67L was associated with increased risk of NKTCL. These two positions are component parts of the peptide-binding pocket 7 (P7) of the HLA-DR heterodimer, suggesting that these alterations might account for the association at HLA-DRB1, independent of the previously reported HLA-DPB1 variants.

    INTERPRETATION: Our findings provide new insights into the development of NKTCL by showing the importance of inflammation and immune regulation through the IL18-IL18RAP axis and antigen presentation involving HLA-DRB1, which might help to identify potential therapeutic targets. Taken in combination with additional genetic and other risk factors, our results could potentially be used to stratify people at high risk of NKTCL for targeted prevention.

    FUNDING: Guangdong Innovative and Entrepreneurial Research Team Program, National Natural Science Foundation of China, National Program for Support of Top-Notch Young Professionals, Chang Jiang Scholars Program, Singapore Ministry of Health's National Medical Research Council, Tanoto Foundation, National Research Foundation Singapore, Chang Gung Memorial Hospital, Recruitment Program for Young Professionals of China, First Affiliated Hospital and Army Medical University, US National Institutes of Health, and US National Cancer Institute.

    Matched MeSH terms: Quantitative Trait Loci
  12. Lu Y, Beeghly-Fadiel A, Wu L, Guo X, Li B, Schildkraut JM, et al.
    Cancer Res, 2018 Sep 15;78(18):5419-5430.
    PMID: 30054336 DOI: 10.1158/0008-5472.CAN-18-0951
    Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10-6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419-30. ©2018 AACR.
    Matched MeSH terms: Quantitative Trait Loci
  13. Darabi H, McCue K, Beesley J, Michailidou K, Nord S, Kar S, et al.
    Am J Hum Genet, 2015 Jul 02;97(1):22-34.
    PMID: 26073781 DOI: 10.1016/j.ajhg.2015.05.002
    Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.
    Matched MeSH terms: Quantitative Trait Loci/genetics
  14. Ghoussaini M, French JD, Michailidou K, Nord S, Beesley J, Canisus S, et al.
    Am J Hum Genet, 2016 Oct 06;99(4):903-911.
    PMID: 27640304 DOI: 10.1016/j.ajhg.2016.07.017
    Genome-wide association studies (GWASs) have revealed increased breast cancer risk associated with multiple genetic variants at 5p12. Here, we report the fine mapping of this locus using data from 104,660 subjects from 50 case-control studies in the Breast Cancer Association Consortium (BCAC). With data for 3,365 genotyped and imputed SNPs across a 1 Mb region (positions 44,394,495-45,364,167; NCBI build 37), we found evidence for at least three independent signals: the strongest signal, consisting of a single SNP rs10941679, was associated with risk of estrogen-receptor-positive (ER+) breast cancer (per-g allele OR ER+ = 1.15; 95% CI 1.13-1.18; p = 8.35 × 10-30). After adjustment for rs10941679, we detected signal 2, consisting of 38 SNPs more strongly associated with ER-negative (ER-) breast cancer (lead SNP rs6864776: per-a allele OR ER- = 1.10; 95% CI 1.05-1.14; p conditional = 1.44 × 10-12), and a single signal 3 SNP (rs200229088: per-t allele OR ER+ = 1.12; 95% CI 1.09-1.15; p conditional = 1.12 × 10-05). Expression quantitative trait locus analysis in normal breast tissues and breast tumors showed that the g (risk) allele of rs10941679 was associated with increased expression of FGF10 and MRPS30. Functional assays demonstrated that SNP rs10941679 maps to an enhancer element that physically interacts with the FGF10 and MRPS30 promoter regions in breast cancer cell lines. FGF10 is an oncogene that binds to FGFR2 and is overexpressed in ∼10% of human breast cancers, whereas MRPS30 plays a key role in apoptosis. These data suggest that the strongest signal of association at 5p12 is mediated through coordinated activation of FGF10 and MRPS30, two candidate genes for breast cancer pathogenesis.
    Matched MeSH terms: Quantitative Trait Loci/genetics
  15. Vithana EN, Aung T, Khor CC, Cornes BK, Tay WT, Sim X, et al.
    Hum Mol Genet, 2011 Feb 15;20(4):649-58.
    PMID: 21098505 DOI: 10.1093/hmg/ddq511
    Central corneal thickness (CCT) is a risk factor of glaucoma, the most common cause of irreversible blindness worldwide. The identification of genetic determinants affecting CCT in the normal population will provide insights into the mechanisms underlying the association between CCT and glaucoma, as well as the pathogenesis of glaucoma itself. We conducted two genome-wide association studies for CCT in 5080 individuals drawn from two ethnic populations in Singapore (2538 Indian and 2542 Malays) and identified novel genetic loci significantly associated with CCT (COL8A2 rs96067, p(meta) = 5.40 × 10⁻¹³, interval of RXRA-COL5A1 rs1536478, p(meta) = 3.05 × 10⁻⁹). We confirmed the involvement of a previously reported gene for CCT and brittle cornea syndrome (ZNF469) [rs9938149 (p(meta) = 1.63 × 10⁻¹⁶) and rs12447690 (p(meta) = 1.92 × 10⁻¹⁴)]. Evidence of association exceeding the formal threshold for genome-wide significance was observed at rs7044529, an SNP located within COL5A1 when data from this study (n = 5080, P = 0.0012) were considered together with all published data (reflecting an additional 7349 individuals, p(Fisher) = 1.5 × 10⁻⁹). These findings implicate the involvement of collagen genes influencing CCT and thus, possibly the pathogenesis of glaucoma.
    Matched MeSH terms: Quantitative Trait Loci
  16. Dadaev T, Saunders EJ, Newcombe PJ, Anokian E, Leongamornlert DA, Brook MN, et al.
    Nat Commun, 2018 06 11;9(1):2256.
    PMID: 29892050 DOI: 10.1038/s41467-018-04109-8
    Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
    Matched MeSH terms: Quantitative Trait Loci
  17. Külheim C, Yeoh SH, Wallis IR, Laffan S, Moran GF, Foley WJ
    New Phytol, 2011 Sep;191(4):1041-1053.
    PMID: 21609332 DOI: 10.1111/j.1469-8137.2011.03769.x
    Eucalyptus is characterized by high foliar concentrations of plant secondary metabolites with marked qualitative and quantitative variation within a single species. Secondary metabolites in eucalypts are important mediators of a diverse community of herbivores. We used a candidate gene approach to investigate genetic associations between 195 single nucleotide polymorphisms (SNPs) from 24 candidate genes and 33 traits related to secondary metabolites in the Tasmanian Blue Gum (Eucalyptus globulus). We discovered 37 significant associations (false discovery rate (FDR) Q < 0.05) across 11 candidate genes and 19 traits. The effects of SNPs on phenotypic variation were within the expected range (0.018 < r(2) < 0.061) for forest trees. Whereas most marker effects were nonadditive, two alleles from two consecutive genes in the methylerythritol phosphate pathway (MEP) showed additive effects. This study successfully links allelic variants to ecologically important phenotypes which can have a large impact on the entire community. It is one of very few studies to identify the genetic variants of a foundation tree that influences ecosystem function.
    Matched MeSH terms: Quantitative Trait Loci
  18. Salleh MZ, Teh LK, Lee LS, Ismet RI, Patowary A, Joshi K, et al.
    PLoS One, 2013;8(8):e71554.
    PMID: 24009664 DOI: 10.1371/journal.pone.0071554
    BACKGROUND: With a higher throughput and lower cost in sequencing, second generation sequencing technology has immense potential for translation into clinical practice and in the realization of pharmacogenomics based patient care. The systematic analysis of whole genome sequences to assess patient to patient variability in pharmacokinetics and pharmacodynamics responses towards drugs would be the next step in future medicine in line with the vision of personalizing medicine.

    METHODS: Genomic DNA obtained from a 55 years old, self-declared healthy, anonymous male of Malay descent was sequenced. The subject's mother died of lung cancer and the father had a history of schizophrenia and deceased at the age of 65 years old. A systematic, intuitive computational workflow/pipeline integrating custom algorithm in tandem with large datasets of variant annotations and gene functions for genetic variations with pharmacogenomics impact was developed. A comprehensive pathway map of drug transport, metabolism and action was used as a template to map non-synonymous variations with potential functional consequences.

    PRINCIPAL FINDINGS: Over 3 million known variations and 100,898 novel variations in the Malay genome were identified. Further in-depth pharmacogenetics analysis revealed a total of 607 unique variants in 563 proteins, with the eventual identification of 4 drug transport genes, 2 drug metabolizing enzyme genes and 33 target genes harboring deleterious SNVs involved in pharmacological pathways, which could have a potential role in clinical settings.

    CONCLUSIONS: The current study successfully unravels the potential of personal genome sequencing in understanding the functionally relevant variations with potential influence on drug transport, metabolism and differential therapeutic outcomes. These will be essential for realizing personalized medicine through the use of comprehensive computational pipeline for systematic data mining and analysis.

    Matched MeSH terms: Quantitative Trait Loci
  19. Kuchenbaecker KB, Ramus SJ, Tyrer J, Lee A, Shen HC, Beesley J, et al.
    Nat Genet, 2015 Feb;47(2):164-71.
    PMID: 25581431 DOI: 10.1038/ng.3185
    Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.
    Matched MeSH terms: Quantitative Trait Loci
  20. Howson JMM, Zhao W, Barnes DR, Ho WK, Young R, Paul DS, et al.
    Nat Genet, 2017 Jul;49(7):1113-1119.
    PMID: 28530674 DOI: 10.1038/ng.3874
    Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10-8, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.
    Matched MeSH terms: Quantitative Trait Loci
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