• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.195-202
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• 2003

Haplotype analysis in SNP is very useful for the study of complex genetic disease due to low cost and high efficiency comparing to individual analysis of each SNP, and is functionally important in biological view. But, the gametic phase of haplotypes is usually unknown in SNP group, and it is difficult to predict haplotype proportions. In this study, haplotype proportions were estimated using EM algorithm from diploid data of SNP group in solid tumor group and normal group. From these results, linkage disequilibrium among SNPs was analyzed.

• Plant Resources
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• v.3 no.3
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• pp.184-193
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• 2000

Soybean [Glycine max (L.) Merr.] seed weight is a important trait in cultivar development. Objective of this study was to identify and confirm quantitative trait loci (QTLs) for seed weight variation in the F2 and F2:3 generations. QTLs for seed weight were identified in F2 and F2:3 generations using interval mapping (MapMaker/QTL) and single-factor analysis of variance (ANOVA). In the F2 plant generation (i.e., F3 seed), three markers, OPL9a, OPM7a, and OPAC12 were significantly (P<0.01) associated with seed weight QTLs. In the F2:3 plant row generation (i.e., F4 seed), five markers, OPA9a, OPG19, OPL9b, OPP11, and Sat_085 were significantly (P<0.01) associated with seed weight QTLs. Two markers, OPL9a and OPL9b were significantly (P<0.05) associated with seed weight QTLs in both generations. Two QTLs on USDA soybean linkage group C1 and R were identified in both F2 and F2:3 generations using interval mapping. The linkage group C1 QTL explained 16% of the variation in seed weight in both generations, and the linkage group R QTL explained 39% and 41% of the variation for F2 and F2:3 generation, respectively. The linkage group C2 QTL identified in F2:3 generation explained 14.9% of variation. Linkage groups C1, C2 and R had previously been identified as harbouring seed size QTLs. The consistency of QTLs across generations and populations indicates that marker-assisted selection is possible in a soybean breeding program.

• Korean journal of applied entomology
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• v.35 no.2
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• pp.159-163
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• 1996

The profenofos-resistant P-Pro strain of house fly (Muscn domestica L.) was derived from the pyraclofos-resistant strain by selecting with profenofos for 7 generations. The resistance was shown to be incompletely dominant by the reciprocal crosses between the resistant and susceptible strains. Linkage group analysis for the dominant factor responsible for this resistance was carried out by the F, male-backcross method, using susceptible multi-chromosomal marker strain. The major factors for profenofos resistance were located on the second and the fifth chromosome and the other chromosomes had a little effect on the development of this resistance. The male determining factor (M) was linked to the third chromosome in this strain.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.5
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• pp.423-428
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• 2004

Soybean seeds contain high amounts of isoflavones that display biological effects and isoflavone content of soybean seed can vary by year, environment, and genotype. Objective of this study was to identify quantitative trait loci that underlie isoflavone content in soybean seeds. The study involved 85 $F_2$ populations derived from Korean soybean cultivar 'Kwangkyo' and wild type soybean 'IT182305' for QTL analysis associated with isoflavone content. Isoflavone content of seeds was determined by HPLC. The genetic map of 33 linkage groups with 207 markers was constructed. The linkage map spanned 2,607.5 cM across all 33 linkage groups. The average linkage distance between pair of markers among all linkage groups was 12.6 cM in Kosambi map units. Isoflavone content in $F_2$ generations varied in a fashion that suggested a continuous, polygenic inheritance. Eleven markers (4 RAPD, 3 SSR, 4 AFLP) were significantly associated with isoflavone content. Only two markers, Satt419 and CTCGAG3 had F-tests that were significant at P<0.01 in $F_2$ generation for isoflavone content. Interval mapping using the $F_2$ data revealed only two putative QTLs for isoflavone content. The peak QTL region on linkage group 3, which was near OPAG03c, explained $14\%$ variation for isoflavone content. The peak QTL region on linkage group 5, which was located near OPN14 accounted for $35.3\%$ variation for isoflavone content. Using both Map-Maker-QTL $(LOD{\geq}2.0)$ and single-factor analysis $(P{\leq}0.05)$, one marker, CTCGAG3 in linkage group 3 was associated with QTLs for isoflavone content. This information would then be used in identification of QTLs for isoflavone content with precision

• Plant Biotechnology Reports
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• v.5 no.2
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• pp.135-146
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• 2011

The objective of the present research was to map QTLs associated with agronomic traits such as days from sowing to flowering, plant height, yield and leaf-related traits in a population of recombinant inbred lines (RILs) of sunflower (Helianthus annuus). Two field experiments were conducted with well-irrigated and partially irrigated conditions in randomized complete block design with three replications. A map with 304 AFLP and 191 SSR markers with a mean density of 1 marker per 3.7 cM was used to identify QTLs related to the studied traits. The difference among RILs was significant for all studied traits in both conditions. Three to seven QTLs were found for each studied trait in both conditions. The percentage of phenotypic variance ($R^2$) explained by QTLs ranged from 4 to 49%. Three to six QTLs were found for each yield-related trait in both conditions. The most important QTL for grain yield per plant on linkage group 13 (GYP-P-13-1) under partial-irrigated condition controls 49% of phenotypic variance ($R^2$). The most important QTL for 1,000-grain weight (TGW-P-11-1) was identified on linkage group 11. Favorable alleles for this QTL come from RHA266. The major QTL for days from sowing to flowering (DSF-P-14-1) were observed on linkage group 14 and explained 38% of the phenotypic variance. The positive alleles for this QTL come from RHA266. The major QTL for HD (HD-P-13-1) was also identified on linkage group 13 and explained 37% of the phenotypic variance. Both parents (PAC2 and RHA266) contributed to QTLs controlling leaf-related traits in both conditions. Common QTL for leaf area at flowering (LAF-P-12-1, LAF-W-12-1) was detected in linkage group 12. The results emphasise the importance of the role of linkage groups 2, 10 and 13 for studied traits. Genomic regions on the linkage groups 9 and 12 are specific for QTLs of leaf-related traits in sunflower.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.10
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• pp.1402-1405
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• 2003

The QTL(quantitative traits loci) linkage mapping of Hanwoo (Korean Cattle) chromosome 6 for daily gain and marbling score was performed using 378 individuals from 18 paternal half-sib families in Hanwoo. Hanwoo chromosome 6 were mapped to total length of 394.2 cM between 28 microsatellite loci using 36 microsatellite primers of BTA 6 linkage group. The QTL analysis for daily gain in Hanwoo showed 8 microsatellite loci (BM3026-5.66, EL03-5.58, BM4311-5.29, ILSTS035-4.50, BMS1242-4.37, BM1329-3.67, BM415-3.11, BMS2460-3.03) in larger than LOD score 3.0. Based on the QTL analysis for marbling score, LOD scores of 12 microsatellite loci (BM415-8.88, BM3026-7.15, ILSTS093-5.45, ILSTS035-4.91, EL03-4.69, BMS690-4.52, BM1329-4.43, BMS511-3.74, BMS1242-3.66, BMS518-3.65, BM4311-3.41, BMC4203-3.36) were found larger than 3.0.

• Genomics & Informatics
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• v.21 no.3
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• pp.28.1-28.13
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• 2023

Mild cognitive impairment (MCI) is a clinical syndrome characterized by the onset and evolution of cognitive impairments, often considered a transitional stage to Alzheimer's disease (AD). The genetic traits of MCI patients who experience a rapid progression to AD can enhance early diagnosis capabilities and facilitate drug discovery for AD. While a genome-wide association study (GWAS) is a standard tool for identifying single nucleotide polymorphisms (SNPs) related to a disease, it fails to detect SNPs with small effect sizes due to stringent control for multiple testing. Additionally, the method does not consider the group structures of SNPs, such as genes or linkage disequilibrium blocks, which can provide valuable insights into the genetic architecture. To address the limitations, we propose a Bayesian bi-level variable selection method that detects SNPs associated with time of conversion from MCI to AD. Our approach integrates group inclusion indicators into an accelerated failure time model to identify important SNP groups. Additionally, we employ data augmentation techniques to impute censored time values using a predictive posterior. We adapt Dirichlet-Laplace shrinkage priors to incorporate the group structure for SNP-level variable selection. In the simulation study, our method outperformed other competing methods regarding variable selection. The analysis of Alzheimer's Disease Neuroimaging Initiative (ADNI) data revealed several genes directly or indirectly related to AD, whereas a classical GWAS did not identify any significant SNPs.

• Journal of Life Science
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• v.13 no.4
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• pp.375-382
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• 2003

A direct and precise explanation of soybean resistance to soybean cyst nematode will be possible only when the individual gene(s) involved in the resistance are tagged. This study was conducted, (1) to identify and localize quantitative trait loci for resistance to soybean cyst nematode race 14 on RAPD map, (2) to identify the magnitude and mode of inheritance for each quantitative trait loci, and (3) to identify the best combinations of quantitative trait loci for resistance to soybean cyst nematode race 14. Thirty markers (29 RAPD and 1 RFLP) showed significant association with resistance to soybean cyst nematode race 14. From MAPMAKER/QTL analysis, we identified two regions (linkage group C-7 and linkage group C-9) for resistance to soybean cyst nematode .ace 14. The first quantitative trait loci that was localized at 6.0 cM from $H06^1$ on linkage group C-7 showed a dominant inheritance mode. However, we can not exclude the possibility of additive inheritance mode. The second quantitative trait loci that was localized between $B15^2$ and $E01^1$ on linkage group C-9 also showed a dominant mode of inheritance. One pair of flanking markers ($H06^1$ and $H06^2$) and B15$^2$ were used for multiple regression analysis. Marker combination that included 2 markers, $B15^2$ and $H06^1$, explained the highest total variance (22.9%) for resistance to soybean cyst nematode race 14. Further localization of genes for resistance to soybean cyst nematode race 14 and examination of interaction between quantitative trait loci will accelerate the exploitation of resistance to soybean cyst nematode.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.7
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• pp.926-935
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• 2015

The efficiency of genome-wide association analysis (GWAS) depends on power of detection for quantitative trait loci (QTL) and precision for QTL mapping. In this study, three different strategies for GWAS were applied to detect QTL for carcass quality traits in the Korean cattle, Hanwoo; a linkage disequilibrium single locus regression method (LDRM), a combined linkage and linkage disequilibrium analysis (LDLA) and a $BayesC{\pi}$ approach. The phenotypes of 486 steers were collected for weaning weight (WWT), yearling weight (YWT), carcass weight (CWT), backfat thickness (BFT), longissimus dorsi muscle area, and marbling score (Marb). Also the genotype data for the steers and their sires were scored with the Illumina bovine 50K single nucleotide polymorphism (SNP) chips. For the two former GWAS methods, threshold values were set at false discovery rate <0.01 on a chromosome-wide level, while a cut-off threshold value was set in the latter model, such that the top five windows, each of which comprised 10 adjacent SNPs, were chosen with significant variation for the phenotype. Four major additive QTL from these three methods had high concordance found in 64.1 to 64.9Mb for Bos taurus autosome (BTA) 7 for WWT, 24.3 to 25.4Mb for BTA14 for CWT, 0.5 to 1.5Mb for BTA6 for BFT and 26.3 to 33.4Mb for BTA29 for BFT. Several candidate genes (i.e. glutamate receptor, ionotropic, ampa 1 [GRIA1], family with sequence similarity 110, member B [FAM110B], and thymocyte selection-associated high mobility group box [TOX]) may be identified close to these QTL. Our result suggests that the use of different linkage disequilibrium mapping approaches can provide more reliable chromosome regions to further pinpoint DNA makers or causative genes in these regions.

• Korean journal of applied entomology
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• v.40 no.4
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• pp.337-344
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• 2001

The house fly (Musca domestica L.) strains were derived from the Yumenoshima III strain by selecting with cypermethrin and methomyl for 19 and 16 generations, respectively. The resulting strains, cypermethrin resistance strain (Cyp-R19) and methomyl resistance strain (Met-R16), showed high level of resistance by 12906 and 51 times, respectively, comparing with the susceptible SRS strain. The Cyp-R19 strain was resistant to synthetic pyrethroids such as deltamethrin, esfenvalerate, fenpropathrin, $\beta$-cyfluthrin, showing > 11000, 1231, 103, 292 times higher $LD_{50}$ values than the SRS strain, respectively. It was also resistant to 3 organophosphates and 2 carbamates such as fenitrothion, profenofos, pyridaphenthion, benfuracarb, methomyl, showing resistance ratios fo 51, 17, 49, 39 and 62 comparing to SRS strain. The Met-R16 strain was resistant to synthetic carbamate benfuracarb, showing 6 times higher $LD_{50}$ value than SRS strain. It was also resistant to 4 organophosphates such as acephate, fenitrothion, profenofos and pyridaphenthion, showing > 40, 103, 19, 60 times higher $LD_{50}$ value. It was also resistant to 5 pyrethroids and a pyrrole such as cypermethrin, deltamethrin, esfenvalerate, fenpropathrin, $\beta$-cyfluthrin and chlorfenapyr, showing 3030, 249, 4063, 34, 330 and 86 times higher $LD_{50}$ values than the SRS strain. Cyp-R14 strain which was selected for 14 generations by cypermethrin and developed 11014 times higher resistance to the SRS strain was used in the dominance and linkage group analysis. Cypermethrin resistance inheritance was incompletely dominant in house fly as judged by the reciprocal cross between the resistant and susceptible strains. The linkage group analysis for the major factors responsible for this resistance was carried out by the$ F_1$male-backcross method, using susceptible multi-chromosomal marker aabys strain. The major factors for cypermethrin resistance were located on the 1st, the 3rd and the 4th chromosomes, and the effect of the 3rd chromosome was most prominent.