Development and Evaluation of QTL-NIL for Grain Weight from an Interspecific Cross in Rice

Yeo Tae Yun,Dong Min Kim,In Kyu Park,Chong Tae Chung,Yeaul Kyu Seong,Sang Nag Ahn 한국육종학회 2010 한국육종학회지 Vol.42 No.4

In a previous study, we mapped 12 QTLs for 1,000 grain weight (TGW) in the 172 BC2F2 lines derived from a cross between Oryza sativa ssp. Japonica cv. Hwaseongbyeo and O. rufipogon. These QTLs explained 5.4 - 11.4% of the phenotypic variance for TGW. Marker-aided selection combined with backcrosses was employed to develop QTL-NILs for each QTL. BC2F2 lines with each target QTL were backcrossed to Hwaseongbyeo twice and then allowed to self to produce BC4F5 populations. SSR markers linked to TGW were employed to select QTL-NILs with the respective target QTL. Six QTL-NILs with the recurrent parent, Hwaseongbyeo were evaluated for nine traits for three years from 2007 and 2009. Differences were observed between each of the 6 QTL-NILs and Hwaseongbyeo in TGW. In addition to TGW, these QTL-NILs displayed differences in other agronomic traits possibly indicating a tight linkage of genes controlling these traits. The direction of the QTL for TGW in 6 QTL-NILs was consistent as in the BC2F2 lines from the same cross. Difference in TGW between each of the QTL-NILs and Hwaseongbyeo was associated with the difference in one or two grain shape traits; grain length, grain width, and grain thickness. SSR markers linked to the QTL for TGW will facilitate selection of the grain shape character in a breeding program to diversify grain shape and provide the foundation for map-based gene isolation. Also, the QTL-NILs developed in this report and the progenies from crosses between the QTL-NILs will be useful in clarifying epistatic interactions among QTLs for TGW.

Evaluation of a Fine-mapping Method Exploiting Linkage Disequilibrium in Livestock Populations: Simulation Study

Kim, JongJoo,Farnir, Frederic Asian Australasian Association of Animal Productio 2006 Animal Bioscience Vol.19 No.12

A simulation study was conducted to evaluate a fine-mapping method exploiting population-wide linkage disequilibrium. Data were simulated according to the pedigree structure based on a large paternal half-sib family population with a total of 1,034 or 2,068 progeny. Twenty autosomes of 100 cM were generated with 5 cM or 1 cM marker intervals for all founder individuals in the pedigree, and marker alleles and a number of quantitative trait loci (QTL) explaining a total of 70% phenotypic variance were generated and randomly assigned across the whole chromosomes, assuming linkage equilibrium between the markers. The founder chromosomes were then descended through the pedigree to the current offspring generation, including recombinants that were generated by recombination between adjacent markers. Power to detect QTL was high for the QTL with at least moderate size, which was more pronounced with larger sample size and denser marker map. However, sample size contributed much more significantly to power to detect QTL than map density to the precise estimate of QTL position. No QTL was detected on the test chromosomes in which QTL was not assigned, which did not allow detection of false positive QTL. For the multiple QTL that were closely located, the estimates of the QTL positions were biased, except when the QTL were located on the right marker positions. Our fine mapping simulation results indicate that construction of dense maps and large sample size is needed to increase power to detect QTL and mapping precision for QTL position.

Characterization of QTL for Growth and Meat Quality in Combined Pig QTL Populations

Li, Y.,Choi, B.H.,Lee, Y.M.,Alam, M.,Lee, J.H.,Kim, K.S.,Baek, K.H.,Kim, J.J. Asian Australasian Association of Animal Productio 2011 Animal Bioscience Vol.24 No.12

This study was conducted to detect quantitative trait loci (QTL) for thirteen growth and meat quality traits in pigs by combing QTL experimental populations. Two F2 reference populations that were sired by Korea native pig (KNP) and dammed by Landrace (LN) or Yorkshire (YK) were generated to construct linkage maps using 123 genetic markers (mostly microsatellites) and to perform QTL analysis on porcine chromosomes (SSCs) 1, 2, 3, 6, 7, 8, 9, 11, 13, 14, and 15. A set of line-cross models was applied to detect QTL, and a series of lack-of-fit tests between the models was used to characterize inheritance mode of QTL. A total of 23, 11 and 19 QTL were detected at 5% chromosome-wise level for the data sets of KNP${\times}$LN, KNP${\times}$YK cross and joint sets of the two cross populations, respectively. With the joint data, two Mendelian expressed QTL for live weight and cooking loss were detected on SSC3 and SSC15 at 1% chromosome-wise level, respectively. Another Mendelian expressed QTL was detected for CIE a on SSC7 at 5% genome-wise level. Our results suggest that QTL analysis by combining data from two QTL populations increase power for QTL detection, which could provide more accurate genetic information in subsequent marker-assisted selection.

A Least Squares Regression Model to Detect Quantitative Trait Loci with Polar Overdominance in a Cross of Outbred Breeds: Simulation

Kim, Jong-Joo,Dekkers, Jack C.M. Asian Australasian Association of Animal Productio 2013 Animal Bioscience Vol.26 No.11

A least squares regression interval mapping model was derived to detect quantitative trait loci (QTL) with a unique mode of genomic imprinting, polar overdominance (POD), under a breed cross design model in outbred mammals. Tests to differentiate POD QTL from Mendelian, paternal or maternal expression QTL were also developed. To evaluate the power of the POD models and to determine the ability to differentiate POD from non-POD QTL, phenotypic data, marker data and a biallelic QTL were simulated on 512 F2 offspring. When tests for Mendelian versus parent-of-origin expression were performed, most POD QTL were classified as partially imprinted QTL. The application of the series of POD tests showed that more than 90% and 80% of medium and small POD QTL were declared as POD type. However, when breed-origin alleles were segregating in the grand parental breeds, the proportion of declared POD QTL decreased, which was more pronounced in a mating design with a small number of parents ($F_0$ and $F_1$). Non-POD QTL, i.e. with Mendelian or parent-of-origin expression (complete imprinting) inheritance, were well classified (>90%) as non-POD QTL, except for QTL with small effects and paternal or maternal expression in the design with a small number of parents, for which spurious POD QTL were declared.

Effect of the number of QTL of carcass weight on the accuracy of genomic estimated breeding values in Hanwoo

최영재,김영국,이두호,이동재,이승환 한국동물유전육종학회 2023 한국동물유전육종학회지 Vol.7 No.4

The objective of this study was to investigate the relationship between the number of QTL (Quantitative Trait Loci) affecting the carcass weight of Hanwoo and the accuracy of GEBV (Genomic Estimated Breeding Values). The study was performed simulation study to generate three populations comprising 100, 500 and 1,000 QTL. Each population consisted of 13,500 individuals which were selected from the 6th to 10th generations of all 10 generations, while keeping litter size constant (N=1) in population parameters. The genetic parameters for these populations were set at 0.45 trait heritability, 0.3 QTL heritability and 48,578 total markers. In order to confirm the number of significant QTL under the threshold of Bonferroni correction, both GWAS (Genome-wide association study) and GWAS based on Random Forest (RF) were performed. In each population, there were 33, 50 and 32 QTL identified by only GWAS, with 100, 500 and 1,000 QTL. Additionally, RF-based GWAS detected 65, 260 and 491. These results showed that the number of significant QTL is not related to the overall number of QTL in the population. Furthermore, machine learning based GWAS is more accurate than solely using GWAS. To estimate the accuracy of GEBV (Genomic Best Linear Unbiased Prediction) in each population, 5-fold cross-validation was employed using SNP effect of the QTL over p-value. In the result of the estimation, GEBV rose with an increase in the number of QTL in the population, and the correlation between TBV (True Breeding Values) followed the same tendency. As a result, this study suggested that the number of QTL related to carcass weight in Hanwoo could exert a significant influence on genetic improvement.

Detection of QTL for Carcass Quality on Chromosome 6 by Exploiting Linkage and Linkage Disequilibrium in Hanwoo

Lee, J.H.,Li, Y.,Kim, J.J. Asian Australasian Association of Animal Productio 2012 Animal Bioscience Vol.25 No.1

The purpose of this study was to improve mapping power and resolution for the QTL influencing carcass quality in Hanwoo, which was previously detected on the bovine chromosome (BTA) 6. A sample of 427 steers were chosen, which were the progeny from 45 Korean proven sires in the Hanwoo Improvement Center, Seosan, Korea. The samples were genotyped with the set of 2,535 SNPs on BTA6 that were imbedded in the Illumina bovine 50 k chip. A linkage disequilibrium variance component mapping (LDVCM) method, which exploited both linkage between sires and their steers and population-wide linkage disequilibrium, was applied to detect QTL for four carcass quality traits. Fifteen QTL were detected at 0.1% comparison-wise level, for which five, three, five, and two QTL were associated with carcass weight (CWT), backfat thickness (BFT), longissimus dorsi muscle area (LMA), and marbling score (Marb), respectively. The number of QTL was greater compared with our previous results, in which twelve QTL for carcass quality were detected on the BTA6 in the same population by applying other linkage disequilibrium mapping approaches. One QTL for LMA was detected on the distal region (110,285,672 to 110,633,096 bp) with the most significant evidence for linkage (p< $10^{-5}$). Another QTL that was detected on the proximal region (33,596,515 to 33,897,434 bp) was pleiotrophic, i.e. influencing CWT, BFT, and LMA. Our results suggest that the LDVCM is a good alternative method for QTL fine-mapping in detection and characterization of QTL.

콩 종실 및 생육형질 연관 분자표지 탐색

김정순,송미희,이장용,안상낙,구자환 한국작물학회 2008 한국작물학회지 Vol.53 No.1

신팔달콩2호와 GC83006를 교잡하여 총 118개의 F7 계통을 육성하였다. 127개의 분자마커를 사용하여 유전자지도를 이용하여 종실 및 생육특성에 대한 QTLs분석을 실시하였으며 그 결과를 요약하면 다음과 같다. 1. 100립중, 경장, 엽면적 그리고 개화까지 일수는 정규분포를 보였다. 100립중을 제외한 3개의 형질에서 양친의 값을 벗어나는 초월변이 계통이 관찰되었는데, 특히 개화까지의 일수는 개화기가 지연되는 쪽으로 초월변이 계통이 다수 관찰되었다. 2. 100립중, 경장, 엽면적 그리고 개차까지 일수에 대한 QTL분석 결과, 전체 7개의 QTL이 탐지되었다. 100립중에 관여하는 3개의 QTL은 전체변이의 10.1%~12.5% 를 설명하였고, 경장은 전체변이의 22%를 설명하는 1개의 QTL이 탐지되었다. 엽면적은 전체 변이의 10% 및 8.6%를 설명하는 2개의 QTL이 탐지되었으며 개화기 일수는 전체 변이의 41.0%를 설명하는 1개의 QTL이 탐지되었다. 3. 신팔달콩2호와 GC83006의 모용은 각각 회색과 갈색이었으며 모용색은 1개의 유전자가 관여하는 것으로 나타났다. 분석결과 모용색은 연관군 C2에 위치하는 Satt134 마커와 밀접히 연관되어 있었다. 제색은 신팔달콩2호와 GC83006이 각각 흑색과 황색이었으며 후대 중에는 갈색의 배꼽을 갖고 있는 계통도 발견되었다. 종피색은 신팔달콩 2호와 GC83006이 각각 황색과 녹색을 보였으며 후대에서 황색과 녹색 계통이 1 : 1의 분리비를 보여 종피색에는 하나의 유전자가 관여하는 것으로 나타났고, 이 유전자는 연관군 D1a의 마커 Satt077과 밀접한 연관을 보였다. 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 (R2~;=~;12.5 ), LG A1 (R2~;=~;10.1 ) and LG C2 (R2~;=~;11.5 ) increased the seed weight. A QTL conditioning plant height was linked to markers including Satt134 (LG C2, R2~;=~;25.4 ), and the GC83006 allele increased plant height at this QTL locus. For two QTLs related to leaf area, 1aM on LG M (R2~;=~;10.0 ) and laL on LG L (R2~;=~;8.6 ), the Shinpaldalkong2 alleles had positive effect to increase the leaf area. Satt134 on LG C2 (R2~;=~;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.

Identification of Quantitative Trait Loci (QTL) Affecting Teat Number in Pigs

Kim, Tae-Hun,Choi, Bong-Hwan,Yoon, Du-Hak,Park, Eung-Woo,Jeon, Jin-Tae,Han, Jae-Young,Oh, Sung-Jong,Cheong, Il-Cheong Asian Australasian Association of Animal Productio 2004 Animal Bioscience Vol.17 No.9

Quantitative trait loci (QTL) mapping can be applied to detect chromosomal locations that control economic traits in farm animals. Teat number has been considered as one of the most important factors to evaluate mothering ability of sow. Especially, teat number is more important when the number is less than the litter size. This study was conducted to identify QTL affecting teat number in the Korean native pig${\times}$Landrace resource family. A total of 240 animals was genotyped for 132 polymorphic microsatellites covering the 18 pig autosomes. Mean and standard deviation of teat number in $F_2$animals is 13.46${\pm}$1.40. QTL was analyzed using F2 QTL Analysis Servlet of QTL express. A QTL for teat number on SSC9 was significant at the 1% chromosome-wide level and three suggestive QTL were detected on SSC3, 7 and 14. All QTL detected in this study had additive effect and Landrace alleles were associated with higher teat number in comparison with Korean native pig for three of four QTL.

돼지의 QTL 검색을 위한 유의적 임계수준(Threshold) 결정

이학교,전광주 한국동물자원과학회 2002 한국축산학회지 Vol.44 No.1

양적형질 유전자좌위(Quantitative trait loci; QTL) 연관지도 작성을 위해 regression interval mapping method에 의해 Berkshire종과 Yorkshire종간 교배를 통해 생산된 F_2 집단에서 실시하였다. 염색체내 QTL 위치를 결정하기 위해 regression 모델을 통해 계산된 검정통계량(F-statistic)에 대한 유의적인 threshold 수준의 설정은 permutation test 및 Lander와 kruglyak(1995)에 의해 제시된 방법으로 산출하였다. 525두 F_2 개체에 대해 조사된 기록 중 5형질(도체중, 등심 단면적, 근내지방 교잡도, 콜레스테롤 함량, 척추 늑골 등지방 두께) 기록을 분석에 이용하였고 genome 전체에 걸친 125개의 microsatellite marker에 대해 3세대 집단 모두 개체에 대해 유전자형을 조사하였다. 회귀분석 모형에 따라 additive 및 dominance 효과를 추정하였으며 이때 모든 회귀계수 값과 F-검정통계량은 각각 1cM 단위로 추정하였다. 각 형질별, 염색체별로 10,000회의 permutation에 의해 genome-wise 및 chromosome-wise threshold를 추정하였다. Lander와 Kruglyak(1995)에 의해 제시된 방법으로 산출된 threshold 값은 매우 높게 추정되어 이러한 threshold의 적용시 실제로 QTL 존재여부를 인정할 수 있는 경우의 수가 permutation에 의해 유도된 threshold를 적용했을 때보다 상대적으로 적은 결과를 보였다. 5% genome-wise threshold의 경우 형질별로 다소 상이한 경향을 나타냈으며 분석에 활용된 5개 형질에 대해 총 4개의 QTL이 5% genome-wise 수준에서 검색되었다. Interval mapping using microsatellite markers was employed to detect quantitative trait loci (QTL) in the experimental cross between Berkshire and Yorkshire pigs. In order to derive critical values (CV) for test statistics for declaring significance of QTL, permutation test (PT) of Churchill and Doerge method(1994) and the analytical method(LK) of Lander and Kruglyak(1995) were used by each trait and chromosome. 525 F_2 progeny phenotypes of five traits(carcass weight, loin eye area, marbling score, cholesterol content, last back fat thickness) and genotypes of 125 markers covering the genome were used. Data were analyzed by line cross regression interval mapping with an F-test every by 1cM. PTCV were based on 10,000 permutations. CV at genome-wise test were 10.5 for LK and ranged from 8.1 to 8.3 for PT, depending on th trait. CV, differed substantially between methods, led to different numbers of quantitative trait loci (QTL) to be detected. PT results in the least stringent CV compared at the same % level.

Evaluation of Cofactor Markers for Controlling Genetic Background Noise in QTL Mapping

Lee, Chaeyoung,Wu, Xiaolin Asian Australasian Association of Animal Productio 2003 Animal Bioscience Vol.16 No.4

In order to control the genetic background noise in QTL mapping, cofactor markers were incorporated in single marker analysis (SMACO) and interval mapping (CIM). A simulation was performed to see how effective the cofactors were by the number of QTL, the number and the type of markers, and the marker spacing. The results of QTL mapping for the simulated data showed that the use of cofactors was slightly effective when detecting a single QTL. On the other hand, a considerable improvement was observed when dealing with more than one QTL. Genetic background noise was efficiently absorbed with linked markers rather than unlinked markers. Furthermore, the efficiency was different in QTL mapping depending on the type of linked markers. Well-chosen markers in both SMACO and CIM made the range of linkage position for a significant QTL narrow and the estimates of QTL effects accurate. Generally, 3 to 5 cofactors offered accurate results. Over-fitting was a problem with many regressor variables when the heritability was small. Various marker spacing from 4 to 20 cM did not change greatly the detection of multiple QTLs, but they were less efficient when the marker spacing exceeded 30 cM. Likelihood ratio increased with a large heritability, and the threshold heritability for QTL detection was between 0.30 and 0.05.