Displaying publications 1 - 20 of 82 in total

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  1. Molecular and morphological approaches in discrimination of endangered Probarbus jullieni of Malaysia and Thailand stocks
    Bhassu S, Abd Rashid Z
    Genetika, 2009 Sep;45(9):1244-9.
    PMID: 19824545
    The population structure of Probarbus jullieni from Malaysia and Thailand stocks was based on seven microsatellite primers and truss network measurements. Truss morphometric measurements were made on Temoleh, Probarbus jullieni to demonstrate the degree of speciation that can be induced by both biotic and abiotic conditions and contribute to the definition of different stocks of Probarbus sp. At the momment no relevant information on stock definition has been produced recently concerning Probarbus spp., which is now in IUCN threatened red list. We also summarize the possible discriminant morphological characteristics that shows differentiation between Malaysia and Thailand stocks. We also compare the levels of morphology and genetic differences for Malaysian stocks throughout one year of sampling to determine whether sampling season and possible sexual dimorphism can be detected in this fishes. A total of 25 different alleles were found across the two populations by the seven microsatellites, of which 21 and 19 alleles were detected in Pahang, Malaysia and Thailand, respectively At the population level, the mean number of alleles of Pahang (3.4991) per locus was higher than that (3.1665) of Thailand. From both molecular and morphometric measurements showed that there were two distinct populations. However the differences between these two populations showed that they belong to the same species with least degree of separation
    Matched MeSH terms: Quantitative Trait Loci/genetics*
  2. 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
  3. Fulltext Development and Validation of a High-Density SNP Genotyping Array for African Oil Palm
    Kwong QB, Teh CK, Ong AL, Heng HY, Lee HL, Mohamed M, et al.
    Mol Plant, 2016 Aug 01;9(8):1132-1141.
    PMID: 27112659 DOI: 10.1016/j.molp.2016.04.010
    High-density single nucleotide polymorphism (SNP) genotyping arrays are powerful tools that can measure the level of genetic polymorphism within a population. To develop a whole-genome SNP array for oil palms, SNP discovery was performed using deep resequencing of eight libraries derived from 132 Elaeis guineensis and Elaeis oleifera palms belonging to 59 origins, resulting in the discovery of >3 million putative SNPs. After SNP filtering, the Illumina OP200K custom array was built with 170 860 successful probes. Phenetic clustering analysis revealed that the array could distinguish between palms of different origins in a way consistent with pedigree records. Genome-wide linkage disequilibrium declined more slowly for the commercial populations (ranging from 120 kb at r(2) = 0.43 to 146 kb at r(2) = 0.50) when compared with the semi-wild populations (19.5 kb at r(2) = 0.22). Genetic fixation mapping comparing the semi-wild and commercial population identified 321 selective sweeps. A genome-wide association study (GWAS) detected a significant peak on chromosome 2 associated with the polygenic component of the shell thickness trait (based on the trait shell-to-fruit; S/F %) in tenera palms. Testing of a genomic selection model on the same trait resulted in good prediction accuracy (r = 0.65) with 42% of the S/F % variation explained. The first high-density SNP genotyping array for oil palm has been developed and shown to be robust for use in genetic studies and with potential for developing early trait prediction to shorten the oil palm breeding cycle.
    Matched MeSH terms: Quantitative Trait Loci/genetics*
  4. Fulltext Major QTLs for Trunk Height and Correlated Agronomic Traits Provide Insights into Multiple Trait Integration in Oil Palm Breeding
    Teh CK, Ong AL, Mayes S, Massawe F, Appleton DR
    Genes (Basel), 2020 07 21;11(7).
    PMID: 32708151 DOI: 10.3390/genes11070826
    Superior oil yield is always the top priority of the oil palm industry. Short trunk height (THT) and compactness traits have become increasingly important to improve harvesting efficiency since the industry started to suffer yield losses due to labor shortages. Breeding populations with low THT and short frond length (FL) are actually available, such as Dumpy AVROS pisifera (DAV) and Gunung Melayu dura (GM). However, multiple trait stacking still remains a challenge for oil palm breeding, which usually requires 12-20 years to complete a breeding cycle. In this study, yield and height increment in the GM × GM (GM-3341) and the GM × DAV (GM-DAV-3461) crossing programs were evaluated and palms with good yield and smaller height increment were identified. In the GM-3341 family, non-linear THT growth between THT_2008 (seven years old) and THT_2014 (13 years old) was revealed by a moderate correlation, suggesting that inter-palm competition becomes increasingly important. In total, 19 quantitative trait loci (QTLs) for THT_2008 (8), oil per palm (O/P) (7) and FL (4) were localized on the GM-3341 linkage map, with an average mapping interval of 2.01 cM. Three major QTLs for THT_2008, O/P and FL are co-located on chromosome 11 and reflect the correlation of THT_2008 with O/P and FL. Multiple trait selection for high O/P and low THT (based on the cumulative effects of positive alleles per trait) identified one palm from 100 palms, but with a large starting population of 1000-1500 seedling per cross, this low frequency could be easily compensated for during breeding selection.
    Matched MeSH terms: Quantitative Trait Loci*
  5. 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*
  6. Fulltext Application of an Effective Statistical Technique for an Accurate and Powerful Mining of Quantitative Trait Loci for Rice Aroma Trait
    Golestan Hashemi FS, Rafii MY, Ismail MR, Mohamed MT, Rahim HA, Latif MA, et al.
    PLoS One, 2015;10(6):e0129069.
    PMID: 26061689 DOI: 10.1371/journal.pone.0129069
    When a phenotype of interest is associated with an external/internal covariate, covariate inclusion in quantitative trait loci (QTL) analyses can diminish residual variation and subsequently enhance the ability of QTL detection. In the in vitro synthesis of 2-acetyl-1-pyrroline (2AP), the main fragrance compound in rice, the thermal processing during the Maillard-type reaction between proline and carbohydrate reduction produces a roasted, popcorn-like aroma. Hence, for the first time, we included the proline amino acid, an important precursor of 2AP, as a covariate in our QTL mapping analyses to precisely explore the genetic factors affecting natural variation for rice scent. Consequently, two QTLs were traced on chromosomes 4 and 8. They explained from 20% to 49% of the total aroma phenotypic variance. Additionally, by saturating the interval harboring the major QTL using gene-based primers, a putative allele of fgr (major genetic determinant of fragrance) was mapped in the QTL on the 8th chromosome in the interval RM223-SCU015RM (1.63 cM). These loci supported previous studies of different accessions. Such QTLs can be widely used by breeders in crop improvement programs and for further fine mapping. Moreover, no previous studies and findings were found on simultaneous assessment of the relationship among 2AP, proline and fragrance QTLs. Therefore, our findings can help further our understanding of the metabolomic and genetic basis of 2AP biosynthesis in aromatic rice.
    Matched MeSH terms: Quantitative Trait Loci*
  7. 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
  8. Quantitative trait loci in Anopheles gambiae controlling the encapsulation response against Plasmodium cynomolgi Ceylon
    Zheng L, Wang S, Romans P, Zhao H, Luna C, Benedict MQ
    BMC Genet, 2003 Oct 24;4:16.
    PMID: 14577840
    Anopheles gambiae females are the world's most successful vectors of human malaria. However, a fraction of these mosquitoes is refractory to Plasmodium development. L3-5, a laboratory selected refractory strain, encapsulates transforming ookinetes/early oocysts of a wide variety of Plasmodium species. Previous studies on these mosquitoes showed that one major (Pen1) and two minor (Pen2, Pen3) autosomal dominant quantitative trait loci (QTLs) control the melanotic encapsulation response against P. cynomolgi B, a simian malaria originating in Malaysia.
    Matched MeSH terms: Quantitative Trait Loci*
  9. Genomewide selection in oil palm: increasing selection gain per unit time and cost with small populations
    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
  10. 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
  11. Fulltext Screening of rice landraces for salinity tolerance at seedling stage through morphological and molecular markers
    Ali MN, Yeasmin L, Gantait S, Goswami R, Chakraborty S
    Physiol Mol Biol Plants, 2014 Oct;20(4):411-23.
    PMID: 25320465 DOI: 10.1007/s12298-014-0250-6
    The present investigation was carried out to evaluate 33 rice landrace genotypes for assessment of their salt tolerance at seedling stage. Growth parameters like root length, shoot length and plant biomass were measured after 12 days of exposure to six different levels of saline solution (with electrical conductivity of 4, 6, 8, 10, 12 or 14 dS m (-1)). Genotypes showing significant interaction and differential response towards salinity were assessed at molecular level using 11 simple sequence repeats (SSR) markers, linked with salt tolerance quantitative trait loci. Shoot length, root length and plant biomass at seedling stage decreased with increasing salinity. However, relative salt tolerance in terms of these three parameters varied among genotypes. Out of the 11 SSR markers RM8094, RM336 and RM8046, the most competent descriptors to screen the salt tolerant genotypes with higher polymorphic information content coupled with higher marker index value, significantly distinguished the salt tolerant genotypes. Combining morphological and molecular assessment, four lanraces viz. Gheus, Ghunsi, Kuthiahara and Sholerpona were considered as true salt tolerant genotypes which may contribute in greater way in the development of salt tolerant genotypes in rice.
    Matched MeSH terms: Quantitative Trait Loci
  12. 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*
  13. Fulltext Polymorphisms in a Putative Enhancer at the 10q21.2 Breast Cancer Risk Locus Regulate NRBF2 Expression
    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. Fulltext Ageing Effects, Generation Means, and Path Coefficient Analyses on High Kernel Elongation in Mahsuri Mutan and Basmati 370 Rice Populations
    Ab Halim AAB, Rafii MY, Osman MB, Oladosu Y, Chukwu SC
    Biomed Res Int, 2021;2021:8350136.
    PMID: 34095311 DOI: 10.1155/2021/8350136
    High kernel elongation (HKE) is one of the high-quality characteristics in rice. The objectives of this study were to determine the effects of ageing treatments, gene actions, and inheritance pattern of kernel elongation on cooking quality in two populations of rice and determine the path of influence and contribution of other traits to kernel elongation in rice. Two rice populations derived from crosses between MR219 × Mahsuri Mutan and MR219 × Basmati 370 were used. The breeding materials included two F1 progenies from the two populations, and their respective parents were grown in four different batches at a week interval to synchronize the flowering between the female and male plants. Scaling tests and generation means analysis were carried out to determine ageing effects and estimate additive-dominance gene action and epistasis. The estimation of gene interaction was based on quantitative traits. Path coefficient analysis was done using SAS software version 9.4 to determine the path of influence (direct or indirect) of six quantitative traits on HKE. Results obtained showed that nonallelic gene interaction was observed in all traits. The results before ageing and after ageing showed significant differences in all traits, while the gene interaction changed after ageing. The HKE value improved after ageing, suggesting that ageing is an external factor that could influence gene expression. The epistasis effect for HKE obtained from the cross Mahsuri Mutan × MR219 showed duplicate epistasis while that obtained from a cross between Basmati 370 × MR219 showed complimentary epistasis. Besides, the heritability of HKE was higher in Basmati 370 × MR219 compared to that obtained in Mahsuri Mutan × MR219. The path analysis showed that the cooked grain length and length-width ratio positively significantly affected HKE. It was concluded that ageing treatment is an external factor that could improve the expression of HKE. The findings from this study would be useful to breeders in the selection and development of new specialty (HKE) rice varieties.
    Matched MeSH terms: Quantitative Trait Loci/genetics
  15. Fulltext Identification of six new susceptibility loci for invasive epithelial ovarian cancer
    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
  16. Fulltext Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders
    Cross-Disorder Group of the Psychiatric Genomics Consortium. Electronic address: plee0@mgh.harvard.edu, Cross-Disorder Group of the Psychiatric Genomics Consortium
    Cell, 2019 Dec 12;179(7):1469-1482.e11.
    PMID: 31835028 DOI: 10.1016/j.cell.2019.11.020
    Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.
    Matched MeSH terms: Quantitative Trait Loci*
  17. Fulltext Pythium Damping-Off and Root Rot of Capsicum annuum L.: Impacts, Diagnosis, and Management
    Arora H, Sharma A, Sharma S, Haron FF, Gafur A, Sayyed RZ, et al.
    Microorganisms, 2021 Apr 13;9(4).
    PMID: 33924471 DOI: 10.3390/microorganisms9040823
    Capsicum annuum L. is a significant horticulture crop known for its pungent varieties and used as a spice. The pungent character in the plant, known as capsaicinoid, has been discovered to have various health benefits. However, its production has been affected due to various exogenous stresses, including diseases caused by a soil-borne pathogen, Pythium spp. predominantly affecting the Capsicum plant in younger stages and causing damping-off, this pathogen can incite root rot in later plant growth stages. Due to the involvement of multiple Pythium spp. and their capability to disperse through various routes, their detection and diagnosis have become crucial. However, the quest for a point-of-care technology is still far from over. The use of an integrated approach with cultural and biological techniques for the management of Pythium spp. can be the best and most sustainable alternative to the traditionally used and hazardous chemical approach. The lack of race-specific resistance genes against Pythium spp. can be compensated with the candidate quantitative trait loci (QTL) genes in C. annuum L. This review will focus on the epidemiological factors playing a major role in disease spread, the currently available diagnostics in species identification, and the management strategies with a special emphasis on Pythium spp. causing damping-off and root rot in different cultivars of C. annuum L.
    Matched MeSH terms: Quantitative Trait Loci
  18. 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*
  19. 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*
  20. Fulltext Evidence that the 5p12 Variant rs10941679 Confers Susceptibility to Estrogen-Receptor-Positive Breast Cancer through FGF10 and MRPS30 Regulation
    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
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