Displaying publications 1 - 20 of 82 in total

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  1. Mohd Sanusi NSN, Rosli R, Chan KL, Halim MAA, Ting NC, Singh R, et al.
    Comput Biol Chem, 2023 Feb;102:107801.
    PMID: 36528019 DOI: 10.1016/j.compbiolchem.2022.107801
    A high-quality reference genome is an important resource that can help decipher the genetic basis of traits in combination with linkage or association analyses. The publicly available oil palm draft genome sequence of AVROS pisifera (EG5) accounts for 1.535 Gb of the 1.8 Gb oil palm genome. However, the assemblies are fragmented, and the earlier assembly only had 43% of the sequences placed on pseudo-chromosomes. By integrating a number of SNP and SSR-based genetic maps, a consensus map (AM_EG5.1), comprising of 828.243 Mb genomic scaffolds anchored to 16 pseudo-chromosomes, was generated. This accounted for 54% of the genome assembly, which is a significant improvement to the original assembly. The total length of N50 scaffolds anchored to the pseudo-chromosomes increased by ∼18% compared to the previous assembly. A total of 139 quantitative trait loci for agronomically important quantitative traits, sourced from literature, were successfully mapped on the new pseudo-chromosomes. The improved assembly could also be used as a reference to identify potential errors in placement of specific markers in the linkage groups of the genetic maps used to assemble the consensus map. The 3422 unique markers from five genetic maps, anchored to the pseudo-chromosomes of AM_EG5.1, are an important resource that can be used preferentially to either construct new maps or fill gaps in existing genetic maps. Synteny analysis further revealed that the AM_EG5.1 had high collinearity with the date palm genome cultivar 'Barhee BC4' and shared most of its segmental duplications. This improved chromosomal-level genome is a valuable resource for genetic research in oil palm.
    Matched MeSH terms: Quantitative Trait Loci*
  2. Barría A, Trịnh TQ, Mahmuddin M, Peñaloza C, Papadopoulou A, Gervais O, et al.
    Heredity (Edinb), 2021 Sep;127(3):334-343.
    PMID: 34262170 DOI: 10.1038/s41437-021-00447-4
    Enhancing host resistance to infectious disease has received increasing attention in recent years as a major goal of farm animal breeding programs. Combining field data with genomic tools can provide opportunities to understand the genetic architecture of disease resistance, leading to new opportunities for disease control. In the current study, a genome-wide association study was performed to assess resistance to the Tilapia lake virus (TiLV), one of the biggest threats affecting Nile tilapia (Oreochromis niloticus); a key aquaculture species globally. A pond outbreak of TiLV in a pedigreed population of the GIFT strain was observed, with 950 fish classified as either survivor or mortality, and genotyped using a 65 K SNP array. A significant QTL of large effect was identified on chromosome Oni22. The average mortality rate of tilapia homozygous for the resistance allele at the most significant SNP (P value = 4.51E-10) was 11%, compared to 43% for tilapia homozygous for the susceptibility allele. Several candidate genes related to host response to viral infection were identified within this QTL, including lgals17, vps52, and trim29. These results provide a rare example of a major QTL affecting a trait of major importance to a farmed animal. Genetic markers from the QTL region have potential in marker-assisted selection to improve host resistance, providing a genetic solution to an infectious disease where few other control or mitigation options currently exist.
    Matched MeSH terms: Quantitative Trait Loci
  3. Jahan N, Javed MA, Khan A, Manan FA, Tabassum B
    Ecotoxicology, 2021 Jul;30(5):794-805.
    PMID: 33871748 DOI: 10.1007/s10646-021-02413-6
    Aluminum (Al3+) toxicity is one of the factors limiting crop production in acidic soils. Identifying quantitative trait loci (QTLs)/genes for tolerance to Al3+ toxicity at seed germination can aid the development of new tolerant cultivars. The segregating population derived from Pak Basmati (Indica) × Pokkali (Indica) was used for mapping QTLs linked with tolerance to Al3+ toxicity ranging from 0 to 20 mM at pH 4 ± 0.2 at germination. The favorable alleles for all new QTLs were analyzed based on germination traits, i.e., final germination percentage (FG%), germination energy (GE), germination speed (GS), germination index (GI), mean germination time (MGT), germination value (GV), germination velocity (GVe), peak value of germination (GPV), and germination capacity (GC), and growth traits, such as root length (RL), shoot length (SL), total dry biomass (TDB) and germination vigor index (GVI). The phenotypic evolution showed transgressive variations. For genome-wide mapping, 90 polymorphic SSRs with 4 gene-specific markers and Win QTL Cart were used for QTL analysis. In all, 35 QTLs for germination and 11 QTLs for seedling growth were detected in distinct chromosomal regions by composite interval mapping (CIM), and multiple interval mapping (MIM) confirmed the pleiotropy at region RM128 on chromosome 1. Based on our genetic mapping studies, the genes/QTLs underlying tolerance to Al3+ toxicity could differ for both the germination and seedling stages in segregated populations. The QTLs identified in this study could be a source of new alleles for improving tolerance to Al3+ toxicity in rice.
    Matched MeSH terms: Quantitative Trait Loci
  4. 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*
  5. 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
  6. 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
  7. Mohd Ikmal A, Noraziyah AAS, Wickneswari R
    Plants (Basel), 2021 Jan 24;10(2).
    PMID: 33498963 DOI: 10.3390/plants10020225
    Drought and submergence have been the major constraint in rice production. The present study was conducted to develop high-yielding rice lines with tolerance to drought and submergence by introgressing Sub1 into a rice line with drought yield QTL (qDTY; QTL = quantitative trait loci) viz. qDTY3.1 and qDTY12.1 using marker-assisted breeding. We report here the effect of different combinations of Sub1 and qDTY on morpho-physiological, agronomical traits and yield under reproductive stage drought stress (RS) and non-stress (NS) conditions. Lines with outstanding performance in RS and NS trials were also evaluated in vegetative stage submergence stress (VS) trial to assess the tolerance level. The QTL class analysis revealed Sub1 + qDTY3.1 as the best QTL combination affecting the measured traits in RS trial followed by Sub1 + qDTY12.1. The effects of single Sub1, qDTY3.1 and qDTY12.1 were not as superior as when the QTLs are combined, suggesting the positive interaction of Sub1 and qDTY. Best performing lines selected from the RS and NS trials recorded yield advantage up to 4453.69 kg ha-1 and 6954 kg ha-1 over the parents, respectively. The lines were also found having great tolerance to submergence ranging from 80% to 100%, contributed by a lower percentage of shoot elongation and reduction of chlorophyll content after 14 days of VS. These lines could provide yield sustainability to farmers in regions impacted with drought and submergence while serving as important genetic materials for future breeding programs.
    Matched MeSH terms: Quantitative Trait Loci
  8. Glubb DM, Thompson DJ, Aben KKH, Alsulimani A, Amant F, Annibali D, et al.
    Cancer Epidemiol Biomarkers Prev, 2021 Jan;30(1):217-228.
    PMID: 33144283 DOI: 10.1158/1055-9965.EPI-20-0739
    BACKGROUND: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers.

    METHODS: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data.

    RESULTS: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). We found seven loci associated with risk for both cancers (P Bonferroni < 2.4 × 10-9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10-7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation.

    CONCLUSIONS: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis.

    IMPACT: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

    Matched MeSH terms: Quantitative Trait Loci/genetics
  9. 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
  10. Kumar IS, Nadarajah K
    Plants (Basel), 2020 Nov 05;9(11).
    PMID: 33167299 DOI: 10.3390/plants9111491
    Rice blast, sheath blight and bacterial leaf blight are major rice diseases found worldwide. The development of resistant cultivars is generally perceived as the most effective way to combat these diseases. Plant disease resistance is a polygenic trait where a combinatorial effect of major and minor genes affects this trait. To locate the source of this trait, various quantitative trait loci (QTL) mapping studies have been performed in the past two decades. However, investigating the congruency between the reported QTL is a daunting task due to the heterogeneity amongst the QTLs studied. Hence, the aim of our study is to integrate the reported QTLs for resistance against rice blast, sheath blight and bacterial leaf blight and objectively analyze and consolidate the location of QTL clusters in the chromosomes, reducing the QTL intervals and thus identifying candidate genes within the selected meta-QTL. A total of twenty-seven studies for resistance QTLs to rice blast (8), sheath blight (15) and bacterial leaf blight (4) was compiled for QTL projection and analyses. Cumulatively, 333 QTLs associated with rice blast (114), sheath blight (151) and bacterial leaf blight (68) resistance were compiled, where 303 QTLs could be projected onto a consensus map saturated with 7633 loci. Meta-QTL analysis on 294 QTLs yielded 48 meta-QTLs, where QTLs with membership probability lower than 60% were excluded, reducing the number of QTLs within the meta-QTL to 274. Further, three meta-QTL regions (MQTL2.5, MQTL8.1 and MQTL9.1) were selected for functional analysis on the basis that MQTL2.5 harbors the highest number of QTLs; meanwhile, MQTL8.1 and MQTL9.1 have QTLs associated with all three diseases mentioned above. The functional analysis allows for determination of enriched gene ontology and resistance gene analogs (RGAs) and other defense-related genes. To summarize, MQTL2.5, MQTL8.1 and MQTL9.1 have a considerable number of R-genes that account for 10.21%, 4.08% and 6.42% of the total genes found in these meta-QTLs, respectively. Defense genes constitute around 3.70%, 8.16% and 6.42% of the total number of genes in MQTL2.5, MQTL8.1 and MQTL9.1, respectively. This frequency is higher than the total frequency of defense genes in the rice genome, which is 0.0096% (167 defense genes/17,272 total genes). The integration of the QTLs facilitates the identification of QTL hotspots for rice blast, sheath blight and bacterial blight resistance with reduced intervals, which helps to reduce linkage drag in breeding. The candidate genes within the promising regions could be utilized for improvement through genetical engineering.
    Matched MeSH terms: Quantitative Trait Loci
  11. 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
  12. Yaakub Z, Kamaruddin K, Singh R, Mustafa S, Marjuni M, Ting NC, et al.
    BMC Plant Biol, 2020 Jul 29;20(1):356.
    PMID: 32727448 DOI: 10.1186/s12870-020-02563-5
    BACKGROUND: Molecular breeding has opened new avenues for crop improvement with the potential for faster progress. As oil palm is the major producer of vegetable oil in the world, its improvement, such as developing compact planting materials and altering its oils' fatty acid composition for wider application, is important.

    RESULTS: This study sought to identify the QTLs associated with fatty acid composition and vegetative traits for compactness in the crop. It integrated two interspecific backcross two (BC2) mapping populations to improve the genetic resolution and evaluate the consistency of the QTLs identified. A total 1963 markers (1814 SNPs and 149 SSRs) spanning a total map length of 1793 cM were integrated into a consensus map. For the first time, some QTLs associated with vegetative parameters and carotene content were identified in interspecific hybrids, apart from those associated with fatty acid composition. The analysis identified 8, 3 and 8 genomic loci significantly associated with fatty acids, carotene content and compactness, respectively.

    CONCLUSIONS: Major genomic region influencing the traits for compactness and fatty acid composition was identified in the same chromosomal region in the two populations using two methods for QTL detection. Several significant loci influencing compactness, carotene content and FAC were common to both populations, while others were specific to particular genetic backgrounds. It is hoped that the QTLs identified will be useful tools for marker-assisted selection and accelerate the identification of desirable genotypes for breeding.

    Matched MeSH terms: Quantitative Trait Loci*
  13. 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*
  14. 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
  15. 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
  16. 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*
  17. 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*
  18. Oladosu Y, Rafii MY, Samuel C, Fatai A, Magaji U, Kareem I, et al.
    Int J Mol Sci, 2019 Jul 18;20(14).
    PMID: 31323764 DOI: 10.3390/ijms20143519
    Drought is the leading threat to agricultural food production, especially in the cultivation of rice, a semi-aquatic plant. Drought tolerance is a complex quantitative trait with a complicated phenotype that affects different developmental stages in plants. The level of susceptibility or tolerance of rice to several drought conditions is coordinated by the action of different drought-responsive genes in relation with other stress components which stimulate signal transduction pathways. Interdisciplinary researchers have broken the complex mechanism of plant tolerance using various methods such as genetic engineering or marker-assisted selection to develop a new cultivar with improved drought resistance. The main objectives of this review were to highlight the current method of developing a durable drought-resistant rice variety through conventional breeding and the use of biotechnological tools and to comprehensively review the available information on drought-resistant genes, QTL analysis, gene transformation and marker-assisted selection. The response, indicators, causes, and adaptation processes to the drought stress were discussed in the review. Overall, this review provides a systemic glimpse of breeding methods from conventional to the latest innovation in molecular development of drought-tolerant rice variety. This information could serve as guidance for researchers and rice breeders.
    Matched MeSH terms: Quantitative Trait Loci/genetics
  19. 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
  20. 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
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