Displaying publications 41 - 60 of 82 in total

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  1. High density SNP and DArT-based genetic linkage maps of two closely related oil palm populations
    Gan ST, Wong WC, Wong CK, Soh AC, Kilian A, Low EL, et al.
    J Appl Genet, 2018 Feb;59(1):23-34.
    PMID: 29214520 DOI: 10.1007/s13353-017-0420-7
    Oil palm (Elaeis guineensis Jacq.) is an outbreeding perennial tree crop with long breeding cycles, typically 12 years. Molecular marker technologies can greatly improve the breeding efficiency of oil palm. This study reports the first use of the DArTseq platform to genotype two closely related self-pollinated oil palm populations, namely AA0768 and AA0769 with 48 and 58 progeny respectively. Genetic maps were constructed using the DArT and SNP markers generated in combination with anchor SSR markers. Both maps consisted of 16 major independent linkage groups (2n = 2× = 32) with 1399 and 1466 mapped markers for the AA0768 and AA0769 populations, respectively, including the morphological trait "shell-thickness" (Sh). The map lengths were 1873.7 and 1720.6 cM with an average marker density of 1.34 and 1.17 cM, respectively. The integrated map was 1803.1 cM long with 2066 mapped markers and average marker density of 0.87 cM. A total of 82% of the DArTseq marker sequence tags identified a single site in the published genome sequence, suggesting preferential targeting of gene-rich regions by DArTseq markers. Map integration of higher density focused around the Sh region identified closely linked markers to the Sh, with D.15322 marker 0.24 cM away from the morphological trait and 5071 bp from the transcriptional start of the published SHELL gene. Identification of the Sh marker demonstrates the robustness of using the DArTseq platform to generate high density genetic maps of oil palm with good genome coverage. Both genetic maps and integrated maps will be useful for quantitative trait loci analysis of important yield traits as well as potentially assisting the anchoring of genetic maps to genomic sequences.
    Matched MeSH terms: Quantitative Trait Loci
  2. Fulltext Improvement of Drought Tolerance in Rice (Oryza sativa L.): Genetics, Genomic Tools, and the WRKY Gene Family
    Sahebi M, Hanafi MM, Rafii MY, Mahmud TMM, Azizi P, Osman M, et al.
    Biomed Res Int, 2018;2018:3158474.
    PMID: 30175125 DOI: 10.1155/2018/3158474
    Drought tolerance is an important quantitative trait with multipart phenotypes that are often further complicated by plant phenology. Different types of environmental stresses, such as high irradiance, high temperatures, nutrient deficiencies, and toxicities, may challenge crops simultaneously; therefore, breeding for drought tolerance is very complicated. Interdisciplinary researchers have been attempting to dissect and comprehend the mechanisms of plant tolerance to drought stress using various methods; however, the limited success of molecular breeding and physiological approaches suggests that we rethink our strategies. Recent genetic techniques and genomics tools coupled with advances in breeding methodologies and precise phenotyping will likely reveal candidate genes and metabolic pathways underlying drought tolerance in crops. The WRKY transcription factors are involved in different biological processes in plant development. This zinc (Zn) finger protein family, particularly members that respond to and mediate stress responses, is exclusively found in plants. A total of 89 WRKY genes in japonica and 97 WRKY genes in O. nivara (OnWRKY) have been identified and mapped onto individual chromosomes. To increase the drought tolerance of rice (Oryza sativa L.), research programs should address the problem using a multidisciplinary strategy, including the interaction of plant phenology and multiple stresses, and the combination of drought tolerance traits with different genetic and genomics approaches, such as microarrays, quantitative trait loci (QTLs), WRKY gene family members with roles in drought tolerance, and transgenic crops. This review discusses the newest advances in plant physiology for the exact phenotyping of plant responses to drought to update methods of analysing drought tolerance in rice. Finally, based on the physiological/morphological and molecular mechanisms found in resistant parent lines, a strategy is suggested to select a particular environment and adapt suitable germplasm to that environment.
    Matched MeSH terms: Quantitative Trait Loci
  3. Fulltext A Transcriptome-Wide Association Study Identifies Novel Candidate Susceptibility Genes for Pancreatic Cancer
    Zhong J, Jermusyk A, Wu L, Hoskins JW, Collins I, Mocci E, et al.
    J Natl Cancer Inst, 2020 Oct 01;112(10):1003-1012.
    PMID: 31917448 DOI: 10.1093/jnci/djz246
    BACKGROUND: Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown.

    METHODS: To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples).

    RESULTS: We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction.

    CONCLUSIONS: By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.

    Matched MeSH terms: Quantitative Trait Loci
  4. The genetic and molecular origin of natural variation for the fragrance trait in an elite Malaysian aromatic rice through quantitative trait loci mapping using SSR and gene-based markers
    Golestan Hashemi FS, Rafii MY, Ismail MR, Mohamed MT, Rahim HA, Latif MA, et al.
    Gene, 2015 Jan 25;555(2):101-7.
    PMID: 25445269 DOI: 10.1016/j.gene.2014.10.048
    MRQ74, a popular aromatic Malaysian landrace, allows for charging considerably higher prices than non-aromatic landraces. Thus, breeding this profitable trait has become a priority for Malaysian rice breeding. Despite many studies on aroma genetics, ambiguities considering its genetic basis remain. It has been observed that identifying quantitative trait loci (QTLs) based on anchor markers, particularly candidate genes controlling a trait of interest, can increase the power of QTL detection. Hence, this study aimed to locate QTLs that influence natural variations in rice scent using microsatellites and candidate gene-based sequence polymorphisms. For this purpose, an F2 mapping population including 189 individual plants was developed by MRQ74 crosses with 'MR84', a non-scented Malaysian accession. Additionally, qualitative and quantitative approaches were applied to obtain a phenotype data framework. Consequently, we identified two QTLs on chromosomes 4 and 8. These QTLs explained from 3.2% to 39.3% of the total fragrance phenotypic variance. In addition, we could resolve linkage group 8 by adding six gene-based primers in the interval harboring the most robust QTL. Hence, we could locate a putative fgr allele in the QTL found on chromosome 8 in the interval RM223-SCU015RM (1.63cM). The identified QTLs represent an important step toward recognition of the rice flavor genetic control mechanism. In addition, this identification will likely accelerate the progress of the use of molecular markers for gene isolation, gene-based cloning, and marker-assisted selection breeding programs aimed at improving rice cultivars.
    Matched MeSH terms: Quantitative Trait Loci*
  5. Fulltext Identification of quantitative trait loci for blast resistance in BC₂F₃ and BC₂F5 advanced backcross families of rice
    Rahim HA, Bhuiyan MA, Lim LS, Sabu KK, Saad A, Azhar M, et al.
    Genet. Mol. Res., 2012;11(3):3277-89.
    PMID: 23079822 DOI: 10.4238/2012.September.12.11
    Advanced backcross families derived from Oryza sativa cv MR219/O. rufipogon IRGC105491 were utilized for identification of quantitative trait loci (QTL) for blast resistance using simple sequence repeat markers. Two hundred and sixty-one BC(2)F(3) families were used to construct a linkage map, using 87 markers, which covered 2375.2 cM of 12 rice chromosomes, with a mean density of 27.3 cM. The families were evaluated in a greenhouse for resistance to blast disease caused by pathotypes P7.2 and P5.0 of Magnaporthe oryzae. Five QTLs (qBL5.1, qBL5.2, qBL6.1, qBL8.1, and qBL10.1) for pathotype P5.0 and four QTLs (qBL5.3, qBL5.4, qBL7.1, and qBL8.2) for pathotype P7.2 were identified using the BC(2)F(3) families. Another linkage map was also constructed based on 31 BC(2)F(5) families, using 63 SSR markers, which covered 474.9 cM of 9 rice chromosomes, with a mean density of 8.01 cM. Five suggestive QTLs (qBL11.2, qBL11.3, qBL12.1, qBL12.2, qBL12.3) and one putative QTL (qBL2.1) were identified for pathotype P7.2. Also, seven suggestive QTLs (qBL1.1, qBL2.2, qBL4.1, qBL4.2, qBL5.3, qBL8.3, and qBL11.1) were detected for pathotype P5.0. We conclude that there is a non-race-specific resistance spectrum of O. rufipogon against M. oryzae pathotypes.
    Matched MeSH terms: Quantitative Trait Loci/genetics*
  6. Fulltext Haplotype divergence and multiple candidate genes at Rphq2, a partial resistance QTL of barley to Puccinia hordei
    Yeo FK, Wang Y, Vozabova T, Huneau C, Leroy P, Chalhoub B, et al.
    Theor Appl Genet, 2016 Feb;129(2):289-304.
    PMID: 26542283 DOI: 10.1007/s00122-015-2627-5
    Rphq2, a minor gene for partial resistance to Puccinia hordei , was physically mapped in a 188 kbp introgression with suppressed recombination between haplotypes of rphq2 and Rphq2 barley cultivars.
    Matched MeSH terms: Quantitative Trait Loci*
  7. Fulltext Mapping quantitative trait loci (QTLs) for fatty acid composition in an interspecific cross of oil palm
    Singh R, Tan SG, Panandam JM, Rahman RA, Ooi LC, Low ET, et al.
    BMC Plant Biol, 2009;9:114.
    PMID: 19706196 DOI: 10.1186/1471-2229-9-114
    Marker Assisted Selection (MAS) is well suited to a perennial crop like oil palm, in which the economic products are not produced until several years after planting. The use of DNA markers for selection in such crops can greatly reduce the number of breeding cycles needed. With the use of DNA markers, informed decisions can be made at the nursery stage, regarding which individuals should be retained as breeding stock, which are satisfactory for agricultural production, and which should be culled. The trait associated with oil quality, measured in terms of its fatty acid composition, is an important agronomic trait that can eventually be tracked using molecular markers. This will speed up the production of new and improved oil palm planting materials.
    Matched MeSH terms: Quantitative Trait Loci*
  8. Fulltext SNP variants associated with non-Hodgkin lymphoma (NHL) correlate with human leukocyte antigen (HLA) class II expression
    Ten LC, Chin YM, Tai MC, Chin EF, Lim YY, Suthandiram S, et al.
    Sci Rep, 2017 01 31;7:41400.
    PMID: 28139690 DOI: 10.1038/srep41400
    Large consortia efforts and genome-wide association studies (GWASs) have linked a number of genetic variants within the 6p21 chromosomal region to non-Hodgkin lymphoma (NHL). Complementing these efforts, we genotyped previously reported SNPs in the human leukocyte antigen (HLA) class I (rs6457327) and class II (rs9271100, rs2647012 and rs10484561) regions in a total of 1,145 subjects (567 NHL cases and 578 healthy controls) from two major ethnic groups in Malaysia, the Malays and the Chinese. We identified a NHL-associated (PNHL_add = 0.0008; ORNHL_add = 0.54; 95% CI = 0.37-0.77) and B-cell associated (PBcell_add = 0.0007; ORBcell_add = 0.51; 95% CI = 0.35-0.76) SNP rs2647012 in the Malaysian Malays. In silico cis-eQTL analysis of rs2647012 suggests potential regulatory function of nearby HLA class II molecules. Minor allele rs2647012-T is linked to higher expression of HLA-DQB1, rendering a protective effect to NHL risk. Our findings suggest that the HLA class II region plays an important role in NHL etiology.
    Matched MeSH terms: Quantitative Trait Loci/genetics
  9. Fulltext Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes
    Fachal L, Aschard H, Beesley J, Barnes DR, Allen J, Kar S, et al.
    Nat Genet, 2020 01;52(1):56-73.
    PMID: 31911677 DOI: 10.1038/s41588-019-0537-1
    Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
    Matched MeSH terms: Quantitative Trait Loci*
  10. Fulltext Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility
    Earp M, Tyrer JP, Winham SJ, Lin HY, Chornokur G, Dennis J, et al.
    PLoS One, 2018;13(7):e0197561.
    PMID: 29979793 DOI: 10.1371/journal.pone.0197561
    Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR = 1.33, p = 4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR = 1.07, p = 0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR = 0.90, p = 0.00033; rs927062, OR = 0.94, p = 0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations.
    Matched MeSH terms: Quantitative Trait Loci/genetics
  11. Fulltext Identification of functionally important microRNAs from rice inflorescence at heading stage of a qDTY4.1-QTL bearing Near Isogenic Line under drought conditions
    Cheah BH, Jadhao S, Vasudevan M, Wickneswari R, Nadarajah K
    PLoS One, 2017;12(10):e0186382.
    PMID: 29045473 DOI: 10.1371/journal.pone.0186382
    A cross between IR64 (high-yielding but drought-susceptible) and Aday Sel (drought-tolerant) rice cultivars yielded a stable line with enhanced grain yield under drought screening field trials at International Rice Research Institute. The major effect qDTY4.1 drought tolerance and yield QTL was detected in the IR77298-14-1-2-10 Backcrossed Inbred Line (BIL) and its IR87705-7-15-B Near Isogenic Line (NIL) with 93.9% genetic similarity to IR64. Although rice yield is extremely susceptible to water stress at reproductive stage, currently, there is only one report on the detection of drought-responsive microRNAs in inflorescence tissue of a Japonica rice line. In this study, more drought-responsive microRNAs were identified in the inflorescence tissues of IR64, IR77298-14-1-2-10 and IR87705-7-15-B via next-generation sequencing. Among the 32 families of inflorescence-specific non-conserved microRNAs that were identified, 22 families were up-regulated in IR87705-7-15-B. Overall 9 conserved and 34 non-conserved microRNA families were found as drought-responsive in rice inflorescence with 5 conserved and 30 non-conserved families induced in the IR87705-7-15-B. The observation of more drought-responsive non-conserved microRNAs may imply their prominence over conserved microRNAs in drought response mechanisms of rice inflorescence. Gene Ontology annotation analysis on the target genes of drought-responsive microRNAs identified in IR87705-7-15-B revealed over-representation of biological processes including development, signalling and response to stimulus. Particularly, four inflorescence-specific microRNAs viz. osa-miR5485, osa-miR5487, osa-miR5492 and osa-miR5517, and two non-inflorescence specific microRNAs viz. osa-miR169d and osa-miR169f.2 target genes that are involved in flower or embryonic development. Among them, osa-miR169d, osa-miR5492 and osa-miR5517 are related to flowering time control. It is also worth mentioning that osa-miR2118 and osa-miR2275, which are implicated in the biosynthesis of rice inflorescence-specific small interfering RNAs, were induced in IR87705-7-15-B but repressed in IR77298-14-1-2-10. Further, gene search within qDTY4.1 QTL region had identified multiple copies of NBS-LRR resistance genes (potential target of osa-miR2118), subtilisins and genes implicated in stomatal movement, ABA metabolism and cuticular wax biosynthesis.
    Matched MeSH terms: Quantitative Trait Loci/genetics*
  12. Fulltext Identification of novel breast cancer susceptibility loci in meta-analyses conducted among Asian and European descendants
    Shu X, Long J, Cai Q, Kweon SS, Choi JY, Kubo M, et al.
    Nat Commun, 2020 Mar 05;11(1):1217.
    PMID: 32139696 DOI: 10.1038/s41467-020-15046-w
    Known risk variants explain only a small proportion of breast cancer heritability, particularly in Asian women. To search for additional genetic susceptibility loci for breast cancer, here we perform a meta-analysis of data from genome-wide association studies (GWAS) conducted in Asians (24,206 cases and 24,775 controls) and European descendants (122,977 cases and 105,974 controls). We identified 31 potential novel loci with the lead variant showing an association with breast cancer risk at P loci were replicated in an independent sample of 16,787 cases and 16,680 controls of Asian women (P 
    Matched MeSH terms: Quantitative Trait Loci/genetics
  13. Fulltext Fine scale mapping of the 17q22 breast cancer locus using dense SNPs, genotyped within the Collaborative Oncological Gene-Environment Study (COGs)
    Darabi H, Beesley J, Droit A, Kar S, Nord S, Moradi Marjaneh M, et al.
    Sci Rep, 2016 Sep 07;6:32512.
    PMID: 27600471 DOI: 10.1038/srep32512
    Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90-0.94; P = 8.96 × 10(-15))) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10(-09), r(2) = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10(-11), r(2) = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus.
    Matched MeSH terms: Quantitative Trait Loci/genetics*
  14. Fulltext Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus
    Horne HN, Chung CC, Zhang H, Yu K, Prokunina-Olsson L, Michailidou K, et al.
    PLoS One, 2016;11(8):e0160316.
    PMID: 27556229 DOI: 10.1371/journal.pone.0160316
    The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08-1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.
    Matched MeSH terms: Quantitative Trait Loci*
  15. Fulltext Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer
    Shi J, Zhang Y, Zheng W, Michailidou K, Ghoussaini M, Bolla MK, et al.
    Int J Cancer, 2016 Sep 15;139(6):1303-1317.
    PMID: 27087578 DOI: 10.1002/ijc.30150
    Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb (chr8:127,561,724-129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional p = 5.8 × 10(-6) ), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional p = 1.1 × 10(-6) ) and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional p = 1.1 × 10(-4) ) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r(2)  = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry.
    Matched MeSH terms: Quantitative Trait Loci*
  16. Fulltext Genetical and comparative genomics of Brassica under altered Ca supply identifies Arabidopsis Ca-transporter orthologs
    Graham NS, Hammond JP, Lysenko A, Mayes S, O Lochlainn S, Blasco B, et al.
    Plant Cell, 2014 Jul;26(7):2818-30.
    PMID: 25082855 DOI: 10.1105/tpc.114.128603
    Although Ca transport in plants is highly complex, the overexpression of vacuolar Ca(2+) transporters in crops is a promising new technology to improve dietary Ca supplies through biofortification. Here, we sought to identify novel targets for increasing plant Ca accumulation using genetical and comparative genomics. Expression quantitative trait locus (eQTL) mapping to 1895 cis- and 8015 trans-loci were identified in shoots of an inbred mapping population of Brassica rapa (IMB211 × R500); 23 cis- and 948 trans-eQTLs responded specifically to altered Ca supply. eQTLs were screened for functional significance using a large database of shoot Ca concentration phenotypes of Arabidopsis thaliana. From 31 Arabidopsis gene identifiers tagged to robust shoot Ca concentration phenotypes, 21 mapped to 27 B. rapa eQTLs, including orthologs of the Ca(2+) transporters At-CAX1 and At-ACA8. Two of three independent missense mutants of BraA.cax1a, isolated previously by targeting induced local lesions in genomes, have allele-specific shoot Ca concentration phenotypes compared with their segregating wild types. BraA.CAX1a is a promising target for altering the Ca composition of Brassica, consistent with prior knowledge from Arabidopsis. We conclude that multiple-environment eQTL analysis of complex crop genomes combined with comparative genomics is a powerful technique for novel gene identification/prioritization.
    Matched MeSH terms: Quantitative Trait Loci/genetics
  17. Fulltext Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer
    Lawrenson K, Li Q, Kar S, Seo JH, Tyrer J, Spindler TJ, et al.
    Nat Commun, 2015 Sep 22;6:8234.
    PMID: 26391404 DOI: 10.1038/ncomms9234
    Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10(-5)). For three cis-eQTL associations (P<1.4 × 10(-3), FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10(-10) for risk variants (P<10(-4)) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.
    Matched MeSH terms: Quantitative Trait Loci*
  18. Fulltext Reconstructing directed gene regulatory network by only gene expression data
    Zhang L, Feng XK, Ng YK, Li SC
    BMC Genomics, 2016 Aug 18;17 Suppl 4:430.
    PMID: 27556418 DOI: 10.1186/s12864-016-2791-2
    BACKGROUND: Accurately identifying gene regulatory network is an important task in understanding in vivo biological activities. The inference of such networks is often accomplished through the use of gene expression data. Many methods have been developed to evaluate gene expression dependencies between transcription factor and its target genes, and some methods also eliminate transitive interactions. The regulatory (or edge) direction is undetermined if the target gene is also a transcription factor. Some methods predict the regulatory directions in the gene regulatory networks by locating the eQTL single nucleotide polymorphism, or by observing the gene expression changes when knocking out/down the candidate transcript factors; regrettably, these additional data are usually unavailable, especially for the samples deriving from human tissues.

    RESULTS: In this study, we propose the Context Based Dependency Network (CBDN), a method that is able to infer gene regulatory networks with the regulatory directions from gene expression data only. To determine the regulatory direction, CBDN computes the influence of source to target by evaluating the magnitude changes of expression dependencies between the target gene and the others with conditioning on the source gene. CBDN extends the data processing inequality by involving the dependency direction to distinguish between direct and transitive relationship between genes. We also define two types of important regulators which can influence a majority of the genes in the network directly or indirectly. CBDN can detect both of these two types of important regulators by averaging the influence functions of candidate regulator to the other genes. In our experiments with simulated and real data, even with the regulatory direction taken into account, CBDN outperforms the state-of-the-art approaches for inferring gene regulatory network. CBDN identifies the important regulators in the predicted network: 1. TYROBP influences a batch of genes that are related to Alzheimer's disease; 2. ZNF329 and RB1 significantly regulate those 'mesenchymal' gene expression signature genes for brain tumors.

    CONCLUSION: By merely leveraging gene expression data, CBDN can efficiently infer the existence of gene-gene interactions as well as their regulatory directions. The constructed networks are helpful in the identification of important regulators for complex diseases.

    Matched MeSH terms: Quantitative Trait Loci/genetics
  19. Fulltext Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3
    Mocci E, Kundu P, Wheeler W, Arslan AA, Beane-Freeman LE, Bracci PM, et al.
    Cancer Res, 2021 Jun 01;81(11):3134-3143.
    PMID: 33574088 DOI: 10.1158/0008-5472.CAN-20-3267
    Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10-8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82-0.93; former smokers 1.00, 95% CI, 0.91-1.07; current smokers 1.25, 95% CI 1.12-1.40, P interaction = 3.08 × 10-9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r 2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. SIGNIFICANCE: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.
    Matched MeSH terms: Quantitative Trait Loci*
  20. Fulltext Fine-scale mapping of the 5q11.2 breast cancer locus reveals at least three independent risk variants regulating MAP3K1
    Glubb DM, Maranian MJ, Michailidou K, Pooley KA, Meyer KB, Kar S, et al.
    Am J Hum Genet, 2015 Jan 08;96(1):5-20.
    PMID: 25529635 DOI: 10.1016/j.ajhg.2014.11.009
    Genome-wide association studies (GWASs) have revealed SNP rs889312 on 5q11.2 to be associated with breast cancer risk in women of European ancestry. In an attempt to identify the biologically relevant variants, we analyzed 909 genetic variants across 5q11.2 in 103,991 breast cancer individuals and control individuals from 52 studies in the Breast Cancer Association Consortium. Multiple logistic regression analyses identified three independent risk signals: the strongest associations were with 15 correlated variants (iCHAV1), where the minor allele of the best candidate, rs62355902, associated with significantly increased risks of both estrogen-receptor-positive (ER(+): odds ratio [OR] = 1.24, 95% confidence interval [CI] = 1.21-1.27, ptrend = 5.7 × 10(-44)) and estrogen-receptor-negative (ER(-): OR = 1.10, 95% CI = 1.05-1.15, ptrend = 3.0 × 10(-4)) tumors. After adjustment for rs62355902, we found evidence of association of a further 173 variants (iCHAV2) containing three subsets with a range of effects (the strongest was rs113317823 [pcond = 1.61 × 10(-5)]) and five variants composing iCHAV3 (lead rs11949391; ER(+): OR = 0.90, 95% CI = 0.87-0.93, pcond = 1.4 × 10(-4)). Twenty-six percent of the prioritized candidate variants coincided with four putative regulatory elements that interact with the MAP3K1 promoter through chromatin looping and affect MAP3K1 promoter activity. Functional analysis indicated that the cancer risk alleles of four candidates (rs74345699 and rs62355900 [iCHAV1], rs16886397 [iCHAV2a], and rs17432750 [iCHAV3]) increased MAP3K1 transcriptional activity. Chromatin immunoprecipitation analysis revealed diminished GATA3 binding to the minor (cancer-protective) allele of rs17432750, indicating a mechanism for its action. We propose that the cancer risk alleles act to increase MAP3K1 expression in vivo and might promote breast cancer cell survival.
    Matched MeSH terms: Quantitative Trait Loci*
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