• Genes and Genomics
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• v.40 no.12
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• pp.1351-1361
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• 2018

A new cold tolerant germplasm resource named glutinous rice 89-1 (Gr89-1, Oryza sativa L.) can overwinter using axillary buds, with these buds being ratooned the following year. The overwintering seedling rate (OSR) is an important factor for evaluating cold tolerance. Many quantitative trait loci (QTLs) controlling cold tolerance at different growth stages in rice have been identified, with some of these QTLs being successfully cloned. However, no QTLs conferring to the OSR trait have been located in the perennial O. sativa L. To identify QTLs associated with OSR and to evaluate cold tolerance. 286 $F_{12}$ recombinant inbred lines (RILs) derived from a cross between the cold tolerant variety Gr89-1 and cold sensitive variety Shuhui527 (SH527) were used. A total of 198 polymorphic simple sequence repeat (SSR) markers that were distributed uniformly on 12 chromosomes were used to construct the linkage map. The gene ontology (GO) annotation of the major QTL was performed through the rice genome annotation project system. Three main-effect QTLs (qOSR2, qOSR3, and qOSR8) were detected and mapped on chromosomes 2, 3, and 8, respectively. These QTLs were located in the interval of RM14208 (35,160,202 base pairs (bp))-RM208 (35,520,147 bp), RM218 (8,375,236 bp)-RM232 (9,755,778 bp), and RM5891 (24,626,930 bp)-RM23608 (25,355,519 bp), and explained 19.6%, 9.3%, and 11.8% of the phenotypic variations, respectively. The qOSR2 QTL displayed the largest effect, with a logarithm of odds score (LOD) of 5.5. A total of 47 candidate genes on the qOSR2 locus were associated with 219 GO terms. Among these candidate genes, 11 were related to cell membrane, 7 were associated with cold stress, and 3 were involved in response to stress and biotic stimulus. OsPIP1;3 was the only one candidate gene related to stress, biotic stimulus, cold stress, and encoding a cell membrane protein. After QTL mapping, a total of three main-effect QTLs-qOSR2, qOSR3, and qOSR8-were detected on chromosomes 2, 3, and 8, respectively. Among these, qOSR2 explained the highest phenotypic variance. All the QTLs elite traits come from the cold resistance parent Gr89-1. OsPIP1;3 might be a candidate gene of qOSR2.

• Animal Bioscience
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• v.36 no.6
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• pp.861-868
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• 2023

Objective: Loin muscle area (LMA) is an important target trait of pig breeding. This study aimed to identify single nucleotide polymorphisms (SNPs) and genes associated with LMA in the Duroc×(Landrace×Yorkshire) crossbred pigs (DLY). Methods: A genome-wide association study was performed using the Illumina 50K chip to map the genetic marker and genes associated with LMA in 511 DLY pigs (255 boars and 256 sows). Results: After quality control, we detected 35,426 SNPs, including six SNPs significantly associated with LMA in pigs, with MARC0094338 and ASGA0072817 being the two key SNPs responsible for 1.77% and 2.48% of the phenotypic variance of LMA, respectively. Based on previous research, we determined two candidate genes (growth hormone receptor [GHR] and 3-oxoacid Co A-transferase 1 [OXCT1]) that are associated with fat deposition and muscle growth and found further additional genes (MYOCD, ARHGAP44, ELAC2, MAP2K4, FBXO4, FBLL1, RARS1, SLIT3, and RANK3) that are presumed to have an effect on LMA. Conclusion: This study contributes to the identification of the mutation that underlies quantitative trait loci associated with LMA and to future pig breeding programs based on marker-assisted selection. Further studies are needed to elucidate the role of the identified candidate genes in the physiological processes involved in LMA regulation.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.25-25
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• 2022

Drought becomes frequent and severe because of continuous global warming, leading to a significant loss of crop yield. In soybean (Glycine max [L.]), most of quantitative trait loci (QTLs) analyses for drought tolerance have conducted by investigating yield changes under water-restricted conditions at the reproductive stages. More recently, the necessity of QTL studies to use physiological indices responding to drought at the early growth stages besides the reproductive ones has arisen due to the unpredictable and prevalent occurrence of drought throughout the soybean growing season. In this study, we thus identified QTLs conferring wilting scores and moisture contents of soybean subjected to drought stress in the early vegetative stage using an recombinant inbred line (RIL) population derived from a cross between Taekwang (drought-sensitive) and SS2-2 (drought-tolerant). For the two traits, the same major QTL was located on chromosome 10, accounting for up to 11.5% of phenotypic variance explained with LOD score of 12.5. This QTL overlaps with a reported QTL for the limited transpiration trait in soybean and harbors an ortholog of the Arabidopsis ABA and drought-induced RING-D UF1117 gene. Meanwhile, one of important features of plant drought tolerance is their ability to limit transpiration rates under high vapor pressure deficiency in response to mitigate water loss. However, monitoring their transpiration rates is time-consuming and laborious. Therefore, only a few population-level studies regarding transpiration rates under the drought condition have been reported so far. Via employing an Arduino-based platform, for the reasons addressed, we are measuring and recording total pot weights of soybean plants every hour from the 1^st day after water restriction to the days when the half of the RILs exhibited permanent tissue damage in at least one trifoliate. Gradual decrease in moisture of soil in pots as time passes refers increase in the severity of drought stress. By tracking changes in the total pot weights of soybean plants, we will infer transpiration rates of the mapping parents and their RILs according to different levels of VPD and drought stress. The profile of transpiration rates from different levels of severity in the stresses facilitates a better understanding of relationship between transpiration-related features, such as limited maximum transpiration rates, to water saving performances, as well as those to other drought-responsive phenotypes. Our findings will provide primary insights on drought tolerance mechanisms in soybean and useful resources for improvement of soybean varieties tolerant to drought stress.

• Korean Journal of Breeding Science
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• v.51 no.4
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• pp.395-403
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• 2019

Rice blast caused by the fungus Magnaporthe grisea (anamorphic: Pyricularia oryzae) is an important disease in rice and development of resistant varieties to blast is one of the most important goals in rice breeding programs. A japonica rice variety, Palgong, has shown resistance to the Korean blast pathogen since it was developed in 1996. Nine blast resistance quantitative trait loci (QTLs) in Palgong alleles were identified on chromosomes 2, 4, 7, and 11. Four QTLs of qBn2.3, qBn4.2, qBn11.1, and qBn11.2 explained 28-56.7% of total phenotypic variation, while five QTLs of qBn2.2, qBn2.4, qBn4.1, qBn7.1, and qBn7.2 explained 9.7-18.8%. In a previous study, one to four resistance genes were located on the loci qBn2.2, qBn2.3, qBn4.2, qBn11.1, and qBn11.2, however, resistance genes were not located on the loci qBn2.4, qBn4.1, and qBn7.1. A major QTL, qBn11.2, explaining 56.7% of total phenotypic variation was related to the durable resistance of Palgong. Additionally, rice stripe virus resistance of Palgong was assumed to be based on the Stvb-i gene, which is located on a major QTL qBn11.2.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.1
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• pp.85-92
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• 2008

An RIL population from a Shinpaldalkong2/GC83006 cross was employed to identify quantitative trait loci (QTL) associated with agronomic traits in soybean. The genetic map consisted of 127 loci which covered about 3,000cM and were assigned into 20 linkage groups. Phenotypic data were collected for the following traits; plant height, leaf area, flowering time, pubescence color, seed coat color and hilum color in 2005. Seed weight was evaluated using seeds collected in 2003 to 2005 at Suwon and in 2005 at Pyeongchang and Miryang sites. Three QTLs were associated with 100-seed weight in the combined analysis across three years. Among the three QTLs related to seed weight, all GC83006 alleles on LG O ($R^2\;=\;12.5$), LG A1 ($R^2\;=\;10.1$) and LG C2 ($R^2\;=\;11.5$) increased the seed weight. A QTL conditioning plant height was linked to markers including Satt134 (LG C2, $R^2\;=\;25.4$), and the GC83006 allele increased plant height at this QTL locus. For two QTLs related to leaf area, 1aM on LG M ($R^2\;=\;10.0$) and laL on LG L ($R^2\;=\;8.6$), the Shinpaldalkong2 alleles had positive effect to increase the leaf area. Satt134 on LG C2 ($R^2\;=\;41.0$) was associated with QTL for days to flowering. Satt134 (LG C2) showed a linkage to a gene for pubescence color. Satt363 (LG C2) and Satt354 (LG I) were linked to the hilum color gene, and Sat077 (LG D1a) was linked to the seed coat color. The QTL conditioning plant height was in the similar genomic location as the QTLs for days to flowering in this population, indicating pleiotropic effect of one gene or the tight linkage of several genes. These linked markers would be useful in marker assisted selection for these traits in a soybean breeding program.

• Asian Journal of Turfgrass Science
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• v.22 no.1
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• pp.85-100
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• 2008

Gray leaf spot (GLS) is a serious fungal disease caused by Pyricularia oryzae Cavara, recently reported on the important turf and forage species, perennial ryegrass (Lolium perenneL.). This fungus also causes rice blast, which is usually controlled by host resistance, but durability of resistance is a problem. Few instances of GLS resistance have been reported in perennial ryegrass. However, two major QTL for GLS resistance have been detected on linkage groups 3 and 6 in an Italian x perennial ryegrass mapping population. To confirm that those QTL are still detectable in the next generation and can function in a different genetic background, a resistant segregant from this population has been crossed with an unrelated susceptible perennial clone, to form a new mapping population segregating for GLS resistance. QTL analysis has been performed in the new population, using two different ryegrass field isolates and RAPD, RFLP, and SSR marker-based linkage maps for each parent. Results indicate the previously identified QTL on linkage group 3 is still significant in the new population, with LOD and percent of phenotypic variance explained ranging from 2.0 to 3.5 and 5% to 10%, respectively. Also two QTL were detected in the susceptible parent, with similar LOD and phenotypic variance explained. Although the linkage group 6 QTL was not detected, the major QTL on linkage group 3 appears to beconfirmed. These results will add to our understanding of the genetic architecture of GLS resistance in ryegrass, which will facilitate its use in perennial ryegrass breeding programs.

• Journal of Life Science
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• v.25 no.8
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• pp.925-931
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• 2015

We performed a molecular marker-based analysis of quantitative trait loci (QTLs) for traits that determine the quality of the appearance of grains, using 120 doubled-haploid (DH) lines developed by another culture from the F1 cross between ‘Cheongcheong’ (Oryza sativa L. ssp. Indica) and ‘Nagdong’ (Oryza sativa L. ssp. Japonica). The traits studied included length, width, and thickness of the grains, as well as length-to-width ratio and 1,000-grain weight. The objective of this study was to determine the genetic control of these traits in order to formulate a strategy for improving the appearance of this hybrid. Within the DH population, five traits exhibited wide variation, with mean values occurring within the range of the two parents. Three QTLs were identified for grain length on chromosomes 2, 5, and 7. Three QTLs were mapped for grain width on chromosome 2: qGW2-1, qGW2-2, and qGW2-3. Six chromosomes were identified for the grain length-to-width ratio; four of these were on chromosome 2, whereas the other two were on chromosomes 7 and 12. One QTL influencing 1,000-grain weight was identified and located on chromosome 8. The results presented in the present study should facilitate rice-breeding, especially for improved hybrid-rice quality.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.5
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• pp.704-711
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• 2020

Objective: Muscle fiber types, numbers and area are crucial aspects associated with meat production and quality. However, there are few studies of pig muscle fibre traits in terms of the detection power, false discovery rate and confidence interval precision of whole-genome quantitative trait loci (QTL). We had previously performed genome scanning for muscle fibre traits using 183 microsatellites and detected 8 significant QTLs in a White Duroc×Erhualian F₂ population. The confidence intervals of these QTLs ranged between 11 and 127 centimorgan (cM), which contained hundreds of genes and hampered the identification of QTLs. A whole-genome sequence imputation of the population was used for fine mapping in this study. Methods: A whole-genome sequences association study was performed in the F₂ population. Genotyping was performed for 1,020 individuals (19 F₀, 68 F₁, and 933 F₂). The whole-genome variants were imputed and 21,624,800 single nucleotide polymorphisms (SNPs) were identified and examined for associations to 11 longissimus dorsi muscle fiber traits. Results: A total of 3,201 significant SNPs comprising 7 novel QTLs showing associations with the relative area of fiber type I (I_RA), the fiber number per square centimeter (FN) and the total fiber number (TFN). Moreover, one QTL on pig chromosome 14 was found to affect both FN and TFN. Furthermore, four plausible candidate genes associated with FN (kinase non-catalytic C-lobe domain containing [KNDC1]), TFN (KNDC1), and I_RA (solute carrier family 36 member 4, contactin associated protein like 5, and glutamate metabotropic receptor 8) were identified. Conclusion: An efficient and powerful imputation-based association approach was utilized to identify genes potentially associated with muscle fiber traits. These identified genes and SNPs could be explored to improve meat production and quality via marker-assisted selection in pigs.

• Journal of Plant Biotechnology
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• v.42 no.4
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• pp.312-325
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• 2015

In this review, we summarized the trends of genomics and transcriptomics research on peach, a model species of Rosaceae. Peach genome maps have been developed from various progeny groups with many next-generation sequencing (NGS) based single nucleotide polymorphism markers. Molecular markers of qualitative traits and quantitative trait loci (QTL) such as fruit characteristics, blooming date, and disease resistance have been analyzed. Among many characteristics, markers related to flesh softening and flesh adhesion are useful for marker assisted selection. Through comparative genomics, peach genome has been compared to the genome of Arabidopsis, Populus, Malus, and Fragaria species. Through transcriptomics and proteomics, fruit growth and development, and flavonoid synthesis, postharvest related transcriptomes and disease resistance related proteins have been reported. Recently, development of NGS based markers, construction of core collection of germplasm, and genotyping of various progenies have been preceded. In the near future, accurate QTL analysis and identification of useful genes are expected to establish a foundation for effective molecular breeding.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.9
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• pp.1184-1191
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• 2011

We attempted to generate a linkage map using Illumina Porcine 60K SNP Beadchip genotypes of the $F_2$ offspring from Korean native pig (KNP) crossed with Yorkshire (YS) pig, and to identify quantitative trait loci (QTL) using the line-cross model. Among the genotype information of the 62,136 SNPs obtained from the high-density SNP analysis, 45,308 SNPs were used to select informative markers with allelic frequencies >0.7 between the KNP (n = 16) and YS (n = 8) F0 animals. Of the selected SNP markers, a final set of 500 SNPs with polymorphic information contents (PIC) values of >0.300 in the $F_2$ groups (n = 252) was used for detection of thirty meat quality-related QTL on chromosomes at the 5% significance level and 10 QTL at the 1% significance level. The QTL for crude protein were detected on SSC2, SSC3, SSC6, SSC9 and SSC12; for intramuscular fat and marbling on SSC2, SSC8, SSC12, SSC14 and SSC18; meat color measurements on SSC1, SSC3, SSC4, SSC5, SSC6, SSC10, SSC11, SSC12, SSC16 and SSC18; water content related measurements in pork were detected on SSC4, SSC6, SSC7, SSC10, SSC12 and SSC14. Additional QTL of pork quality traits such as texture, tenderness and pH were detected on SSC6, SSC12, SSC13 and SSC16. The most important chromosomal region of superior pork quality in KNP compared to YS was identified on SSC12. Our results demonstrated that a QTL linkage map of the $F_2$ design in the pig breed can be generated with a selected data set of high density SNP genotypes. The QTL regions detected in this study will provide useful information for identifying genetic factors related to better pork quality in KNP.