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Detection of Quantitative Trait Loci Associated with Live Measurement Traits in Pigs
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Agricultural Sciences in China 2007, 6(7): 863-868
*B
?: ScienceDirect
July 2007
Detection of Quantitative Trait Loci Associated with Live MeasurementTraits in Pigs ZHANG J i n g - h u 1 . 2 , XIONG Yuan-zhul, ZUO Bo1, LEI M i n g - g a n g l , LI F e n g - e l and LI Jia-liad Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture/College of Animal Science and Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, P.R. China 2 Department of Biology Science & Technology, Zhangzhou Normal College, Zhangrhou 363000, P.R. China I
Abstract Live measurement growth traits are very important economic traits in pig production and breeding. In this research, quantitative trait loci (QTL) were detected for 11 live estimated growth and carcass traits, including birth weight (BWT), average daily gain over testing periods (ADG3), live backfat thickness at last 3-4th lumbar (LBFT3), live loin eye area (LLEA), and so on, in 214 pig resource family population, including 180 F2 individual, by 39 microsatellite marker loci on SSC4, SSC6, SSC7, SSC8, and SSC13. The results indicated that 4 chromosome significant level QTL and one suggestive QTL were detected for ADG3 (at position of 50 cM on SSCS), LBlT3 (at position of 147 cM on SSC4), LLEA (one highly significant at position of 48 cM on SSC7; another significant at position of 125 cM on SSC8) and BWT (suggestive significant at position of 0 cM, at marker sw489 on SSC4). The phenotypic variance of these QTL accounted for 0.95% to 16.91%. Most of them were mentioned in previous reports; except the QTL of LLEA at position of sw1953 on SSC8 which maybe a new QTL.
Key words: pig, quantitative trait loci (QTL), live measurement traits
INTRODUCTION Live measurement growth traits and carcass traits such as average daily gain, live measurement loin eye area, live measurement backfat thickness and live measurement percentage of lean meat are very important economic traits, which are critical when considered in pig production and breeding. Live measurement loin eye area, live measurement backfat thickness and live measurement lean meat percentage are always used in estimating the market value of pigs in wholesale trade, because the three traits are the main factors of market value and meat quality of swine. Hence, it is focused on by the geneticist for the genetic development of these
quantitative traits in research. Since Anderson et al. (1994) had conducted quantitative trait loci (QTL) analysis successfully for growth traits and average backfat traits using a Wild Boar and Large White resource population, many results of QTL mapping for the important economic traits were reported (Bidanel and Rothschild 2002; Hu et al. 2005). For live measurement growth and carcass traits, some QTL mapping results were identical and many results were diverse. It was important to identify and verify different results, because present and future genetic improvements would result from more detailed genetic maps and our growing understanding of the function and structure of the individual genes represented by QTL. In recent years, there were several works about these
Received 27 Februq, 2006 Accepted 20 March, 2007 ZHANG Jing-hu, Ph D, Associate Professor, Tel: +86-596-6372657, E-mail: [email protected]; CorrespondenceXIONG Yuan-zhu, Tel: +86-27-87287390, Fax: +86-27-87394184, E-mail: [email protected]
Q2007, CAAS. All rightsresewed.PuMishedby Elsevier Ctd.
ZHANG Jing-hu et al.
864
investigations in our experiment, and made some progress of linkage map construction and QTL unraveling (Su e l al. 2002a, b, c: Zuo et al. 2003b, 2004). which absorbed the attention of many researchers. In this study, for the sake of combining the genetic analysis of heterosis in pig crossbred populations to QTL, we built the resource family population, and made the genetic analysis of these live measurement traits.
average testing day was 59 d (ADG3 in Table I). The average daily gain over all periods (ADG4) was calculated from the total body weight gain divided by the total raising days. The live measurement carcass traits were taken at about 6 mon, at the end of the testing day before slaughtering, using ultrasonic measurement equipments. The pigs were slaughtered when their body weight reached about 90 kg.
MATERIALS AND METHODS
Microsatellite, PCR amplification and genotype scoring
Population and traits The pig resource family population was established by mating 3 Yorkshire boars (from England) to 5 Meishan sows (from Jiading County, Shanghai, China) randomly. Five males and 21 females in F, generation were selected for intercrossing randomly to give 180 individuals in F, populations, and the progenies were raised in a herd with the same equipment and the same ordinary food, during summer and autumn in 2003. Eleven live measurement traits were recorded according to the method of Xiong and Deng (1999) (Table 1). The experimental pigs had been weaned at the same 35 d, and the body weight weighed (ADGI) at the weaning day. Average daily gain from weaning to testing (ADG2) was calculated from the period of the weaning day to the testing day which began at 68-76 (average 72) d old. There were two testing periods, one was at 68-76 (average 72) d old and ended at 116-127 (average 121) d old, and the average testing day was 49 d (ADG5 in Table 1). The other began at 116-127 (average 121) d old and ended at 157-214 (average 180) d old, and the
Thirty-nine microsatellite markers on SSC4, 6, 7, 8, and 13 were selected based on the US Department of Agriculture - Meat Animal Research Centre (USDAMARC) genome database map (Table 2). All of the microsatellite DNA primer was provided by a US pig genome coordinator, Rothschild M F. PCR and genotyping were according to the method of Zhang et al. (2005).
Method of statistical analysis Linkage analysis was carried out using the CRIMAP software (ver. 2.4, Green et al. 1990). Web software (http://qtl.cap.ed.ac.uk)was used to carry out QTL analysis. The following statistical model was fitted based on a linear model in terms of additive and dominance contributions for a QTL (Haley et al. 1994; Olivo et al. 2000; Zuo el al. 2003b): Y = p +sex +family + covariate + Caa+ C /
+e
Where Y was the observations; p was the mean; sex, family were the fixed effect of traits; the covariate is
Table 1 Describing statistics for traits data in this research Traits
"1
Birth weight (kg). BWT Average daily g i n before weaning (kg). ADGl Average daily gain from weaning to testing (kg). ADG2 Average daily gain over resting period5 during 5-6 mon old (kg). ADG3 Average daily gain over all penods (kg).ADG4 Average daily gain over testing penods dunng 3-4 mon old (kg). ADG5 Live backfat thickness at last rib (mm). LBFTl Live backfat thickness at last 3-4th rib (mm). LBFT2 Live backfat thickness at last 3-4th lumbar (mm). L B R 3 Live loin eye area (square centimetre), LLEA Live lean meat percentage ('7). LLMP
179 179 I79 175 180 175 180 I80 I80 180 180
Means
* SE
N.
0.881 ? 0.016 0.281 ? 0.004 0.385 i 0.007 0.568 ? 0.010 0.497 i 0.004 0.652 0.010 20.477 ? 0.331 23.883 i 0.515 21.661 k 0.396 40.027 k 0.336 47.759 c 0.336
*
24.165 19.015 24.467 24.193 11.807 25.125 21.688 28.935 24.541 11.258 9.448
Max 1 400 0.457 0.592 0.932
0.633 0 885 34.000 49.000 37.000 54.000 58.400
Min 0.500 0.213 0.135 0.121 0.325 0 308 1 1 000 10.000 10.000 33 000 35 400
"Number of aninialr with obsenation value and included in QTL analysis.
0 2007.C M S . All riohts reserved Publishedbv Elsevier Ltd.
865
Detection of Ouantitative Trait Loci Associated with Live Measurement Traits in Pigs
Table 2 Mapping location of the 39 microsatellite markers in F, resource population SSR
sw489 sw835 sw2409 sw2454 so023 sw1996 sw445 so161 sw2406 sw1841 sw1302 swrll30 swl129 sw1473 so121 sw322 swr1343 sw2155 sw 1856 swr2036 sw352 sw252 sw581 so212 sw2410 so098 sw268 sw1037 sw1953 sw2160 sw1085 sw1980 sw1691 sw935 sw864 sw1495 sw520 sw2440 so291 I)
ssc
alleles
4
3 4
4
4 4 4 4 4 4 6 6 6 6 6 6 6 6 I 7 7 I 7 I I I
8 8 8 8 8 8 8 8
13 13 13 13 13 13 13
3 2 4 2 3
m4’) 230 316 238 44 265 217 325
3
157
5 4 3 5 3 3 4 3 3 2
292 267 254 24 1 76 308 316 130 300 96 28 1 304 112 183 140 202 172 146 207 25 8 243 266 289 232 218 134 116 232 133 300 119
5
3 3 3 2 3 3
3 4
4 3 3 3 4 2 2 2 3 3 4 3
Map (W 0 25.6 48.9
69.1 87.5 114 148.2 172.3 0 21.6 41.6 78.2 88.7 114.1 139.4 168.7 0 40.1 69.9 89.3 110.4 122.1 160.3 191.7 0
29.9 68.8 102.4 124.3 139.8 161.7 197.3 0
41.3 69.9 94.9 123.4 147.6 178.3
IM,informative meiosis.
body weight for live measurement carcass traits, and it is the numbers of relative raising days in different periods for growth traits. The coefficient Cawas the probability of the additive effect (a), and C, was that of dominance effect (d) at the chromosome position of the QTL which had been identified. The additive effect (a) and dominance effect (d) were the parameters to be estimated for the QTL. In this study, the additive effects (a) were estimated as P (QQ) - P (qq), in which Q was the QTL allele from Yorkshire, and q was the QTL allele from Meishan, so the dominance effect (d) estimated as P (Qq), for the QTL had been identified. Thus, the positive values of the additive effects of the
QTL allele from Yorkshire denoted increasing effects, and reversed for the negative values (http://qtl.cap.ed. ac.uk). The residuals are represented by e. The additive fraction of F, phenotypic variance (0,’) explained by a QTL was computed assuming that alternative alleles were fmed in each breed; i.e., h2Q=a2/20y2 (Ovilo et al. 2000). Chromosome-wise significance thresholds were calculated empirically by permutation tests of which the number was 1000 (Churchill and Doerge 1994).
RESULTS The statistical parameters of the 11 live measurement traits analyzed are shown in Table 1. The results showed that the variant range of the observed value was broad, and that could make the basis of these QTL research. The results of linkage map construction (Table 2) showed that the orders of microsatellite marker were identical to that reported by the USDA-MARS (http:j/ www .genome.iastate. edu/maps/pig), but the average length of two sex were longer than those in the USDA map. These were similar to that in the previous research by Su et al. (2002a) and Zuo et al. (2003a). The results of the QTL analysis are presented in Table 3 and Fig. Five QTL were detected, one was in chromosome very significant level; three were in chromosome significant and a QTL, in chromosome suggestive level.
QTL for growth trait A QTL with significant effect on ADG3 at position 50 cM, between the markers so098 and sw268 on SSC8 (Pc0.05)was detected (Fig.-A). The QTL could account for about 16.91% of the variance in the population, with an additive effect of 0.07 kg average daily gain during the testing period. The positive additive effect value suggested that the QTL effects were in the expected direction, namely the Yorkshire allele increased daily gain, and the heterozygous pigs had the effect of dominant allele from Yorkshire on increasing the daily gain with 0.016 kg per day (Table 3 ) . It was found that, there was a position that had the effect on birth weight (BWT) near significant level at sw489 on SSC4 (taken as suggestive significant level QTL on chromosome-wise level), with additive effect
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ZHANG Jing-hu er al.
866
of 0.036 kg from Yorkshire allele, and the heterozygous pig had dominantly decreasing effect on birth weight.
QTL for live carcass traits A QTL at position 147 cM, near the marker sw445 on SSC4, which had significant impacts on live backfat thickness at last 3-4th lumbar (mm) (LBFT3) ( P < 0.05), with additive effect of 0.704 cm, which could account for about 0.95% of the phenotypic variation in the pig population was located (Table 3 and Fig.-B). Two QTL were located with highly significant ( P < 0.01) or significant (P<0.05) impacts on LLEA at positions 48 cM (between sw2155 and sw1856, on SSC7) (Fig.-C) and 125 cM (at marker locus sw1953, on
SSC8) (Fig.-D), respectively. The two QTL had additive effects of 1.268 or 0.956 m2 on live loin eye area (m') (LLEA), which could explain approximately 4.38% or 2.52% phenotypic variation, respectively. The two QTL alleles resourced from Yorkshire had effects of increasing the LLEA, but in the heterozygous pig, decreasing the LLEA dramatically, which indicated the negative dominant effects from the two QTL alleles.
DISCUSSION In this research, four QTL and one suggestive QTL were detected on SSC4, 7 and 8 for ADG3, LBFT3, LLEA and BWT, some of them were mentioned in previous reports. The results of QTL mapping for the ADG3 in this
Table 3 The results of QTL mapping for birth weight and growth traits Trait
ssc
Pos (cM)
B W
4 8
0 50
1
117
1 8
JR
ADG3
LBFT LLEA
F-value
Additive effect
Dominant effect
Variance ( W )
sww sO098-sw268
4.96 5 07'
0.036 + 0.023 0.070 t 0.025
-0.088 f 0.034 0.016 c 0.053
sw.145 s w 2 155-sw 1R56 sw 1953
5.9' 6.88" 6.05'
0.704 f 0.626 1.268 ? 0.767 0.956 t 0.566
2 951 f 0.899 -3.850 f 1.409 -3.417 f 1.088
3.18 16.9 I 0.95 4.38
Marker interval
125
2.52
'Sign~iicantat chromosome-wise level ( P < O . O S ) : "very significant at chromosome-wise level (P
Position (cM)
50
100
Positioii (cM)
I50
200 Position ( c M )
Fig. QTL mapping results of average daily gain over testing periods on SSC8 (A), live backfat thickness at last 3-4th lumbar on SSC4 (B), loin eye area on SSC7 (C) and SSC8 (D). The X-axis indicates the relative position on the linkage map; the Y-axis represents the F-ratio. The line indicates the chromosome-wise significance level.
6 2007.CAAS All nghts restved Publishedby Elsevier Ltd
Detection of Quantitative Trait Loci Associated with Live Measurement Traits in Pigs
research were identical to the report by Quintanilla et al. (2002), which mapped the QTL for ADG in the fatting period at the position between sw2410 and swrllol. It was interesting to know that on the USDA-MARC map, the interval of sw2410-swr1101 was about 40 cM which contained marker interval of ~0098-sw268entirely. About the investigation of QTL for explaining live measurement backfat thickness on SSC4, several results were obtained but the mapping positions were diverse, such as 63 cM (live backfat thickness at last 3-4th lumbar, sw835-sw752, Zuo et al. 2003b), 158 cM (average live sidefat thickness, sw445, Su et al. 2002b), 81-82 cM (live backfat thickness at mid-back or shoulder, Walling et al. 1998) and 99.3 cM (last lumber backfat, sw524, Malek et al. 2001). The QTL located in this research was consistent with that of Su et al. (2002b), and there was little difference from the result of Malek et al. (2001), because the marker sw445 was next to the marker sw524 by just 5.5 cM in the USDA-MARC map. It was noted that, the results of QTL mapping about LLEA on SSC7 were consistent with that of Sat0 et al. (2003) and Zuo et al. (2003b). The former had located the loin eye area QTL at position 58 cM, near the marker sw2155 by 15 cM on the map of USDA-MARC, maybe the same QTL in this research. The latter had mapped the loin eye area QTL at position 63 cM, the same marker interval of sw2155-sw1856 on SSC7, and the genetic effect of the results were similar to the results in this study. It was confirmed that there was a QTL associated with the loin eye area at that point. Another QTL for LLEA on SSC8 could be noted in the report by Rohrer and Keele (1998), in which a QTL was mapped at the position of 105.7 cM between the markers sw1671 and sw1551, which had a large interval apart from the QTL in this result, and it was might be another QTL. About the suggestive significant level QTL at position 0 cM on SSC4 for BWT, the same result was reported by Paszek et al. (1999), who had mapped the suggestive QTL in the interval of 7.4-27.1 cM on SSC4, with the additive effect from Meishan allele by -0.05, which decreased the birth weight in F, population, and it accounted for 16.6% variance of phenotype. The resolution of pin pointing the gene in a position of QTL would be dependent on the development and
867
progress of map-position clone technology, such as pig-human comparative map and chromosome manipulation. The fine map of QTL location would facilitate the search for QTL responsible genes. Based on the results, it would benefit to look for the candidate genes for the mapped QTL in further research.
Acknowledgements We wish to thank the USDA-MARC for providing the microsatellite primers. The authors also gratefully extend their acknowledgements to the teachers and postgraduate students of the Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, and the Swine Breeding Centre of China for their cooperation. This work was supported by the National 973 Project of China (G2000016105), and National Natural Science Foundation of China (30500358).
References Andersson L, Haley C S, Ellegren H, Knott S A, Johansson M, Andersson K, Andersson-Eklund L, Edfors-Lilja I, Fredholm M, Hansson I, H&ansson J, Lundstrom K. 1994. Genetic mapping of quantitative trait loci for growth and fatness in pigs. Science, 263, 1771-1774. Bidanel J P, Rothschild M. 2002. Current status of quantitative trait locus mapping in pigs. Pig News and Information, 23, 39N-54N. Churchill G A, Doerge R W. 1994. Empirical threshold values for quantitative trait mapping. Genetics, 138,963-971. Green P, Falls K, Crooks S. 1990. Documentation for CRIMAP, Ver. 2.4. School of Medicine, Washington University, St. Louis, Mo. Haley C S, Knott S A, Elsen J M. 1994. Mapping quantitative trait loci in crosses between outbred lines using least squares. Genetics, 136, 1195-1207. Hu Z L, Dracheva S, Jang W, Maglott D, Bastiaansen J, Rothschild M F, Reecy J M. 2005. A QTL resource and comparison tool for pigs: PigQTLDB. Mammalian Genome, 15, 792800. Malek M, Dekkers J C M, Lee H K, Baas T J, Rothschild M F. 200 1. A molecular genome scan analysis to identify chromosomal regions influencing economic traits in the pig. I . Growth and body composition. Mammalian Genome, 12, 630-636. Ovilo C, Perez-Enciso M, Barragiin C, Clop A, Rodriguez C, Oliver M A, Tor0 M A, Noguera J L. 2000. A QTL for intramuscularfat and backfat thickness is located on porcine
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chromosome 6. Mammalian Genome, 11,344-346. Paszek AA, Wilkie P J. Flickinger G H, Rohrer G A, Alexander L J, Beattie C W, Schook L B. 1999. Interval mapping of growth in divergent swine cross. Murnmaliun Genome, 10, 117-122. Quintanilla R, Milan D, Bidanel J P. 2002. A further look at quantitative trait loci affecting growth and fatness in across between Meishan and Large White pig populations. Genetics Selection Evolution, 34, 193-210. Rohrer G A, Keele J W. 1998. Identification of quantitative trait loci affecting carcass composition in swine: 11. Muscling and wholesale product yield traits. Journal of Animal Science, 76. 2255-2262. Sato S , Oyamada Y, Atsuji K, Nade T, Sat0 S , Kobayashi E, Mitsuhashi T, Nirasawa K, Komatsuda A, Saito Y, Terai S, Hayashi T, Sugimoto Y. 2003. Quantitative trait loci analysis for growth and carcass traits in a Meishan x Duroc F, resource population. Journal of Animal Science, 81,2938-2949. Su Y H, Xiong Y Z, Zhang Q, Jiang S W, Lei M G, Yu L, Zheng R, Deng C Y. 2002a. Mapping quantitative trait loci for fat deposition in carcass in pigs. Acta Genetica Sinica, 29,68 1684. (in Chinese) Su Y H, Xiong Y Z, Zhang Q, Jiang S W,Yu L, Lei M G , Zheng R, Deng C Y. 2002b. Detection of quantitative trait loci for growth in Large White x Meishan intercross. Acta Genetica Sinica, 29, 607-61 1. (in Chinese) Su Y H, Xiong Y Z. Zhang Q, Xia X Y, Jiang S W, Deng C Y,
ZHANG Jina-hu er al. Zheng R, Lei M G , Yang Z M. 2002~.Construction of linkage map of chromosomes 1 and 3 in Large White x Meishan reference family. Acta Genetica Sinica, 29,16-20. (in Chinese) Walling G A, Archibald A L, Cattermole J A, Downing A C, Finlayson H A, Nicholson D, Visscher P M, Walker C A, Haley C S. 1998. Mapping of quantitative trait loci on porcine chromosome 4. Animal Genetics, 29,415-424. Xiong Y Z, Deng C Y. 1999. Principle and Method of Swine Testing. China Agricultural Press, Beijing. (in Chinese) Zhang J H, Xiong Y Z, Deng C Y. 2005. Correlations of genic heterozygosity and variances with heterosis in pig population revealed by microsatellite DNA marker. Asian-Australian Journal of Animal Science, 18,620-625. Zuo B, Xiong Y Z, Su Y H, Deng C Y, Lei M G, Zheng R, Jiang S W, Li F E. 2004. Mapping of quantitative trait loci on porcine chromosome 7 using combined data analysis. AsianAustralian Journal of Animal Science, 17, 1350-1354. Zuo B, Xiong Y Z, Su Y H, Deng C Y,Yu L, Zheng R. 2003a. Genetic linkage map construction of some microsatellites on pig chromosome 4 and 7. Journal of Agricultural Biotechnology, 11,70-74. (in Chinese) Zuo B, Xiong Y Z, Su Y H, Deng C Y, Zheng R, Lei M G , Yu L. 2003b. Mapping and genetic effect analysis of swine quantitative trait loci using 24 microsatellites. Acta Veterinuria et Zootechnica Sinica, 34, 139-146. (in Chinese) (Edited by LIN Jian-fei)
Q2007. CAAS. All nghts reserved Published by Elsever Ltd
Agricultural Sciences in China 2007, 6(7): 863-868
*B
?: ScienceDirect
July 2007
Detection of Quantitative Trait Loci Associated with Live MeasurementTraits in Pigs ZHANG J i n g - h u 1 . 2 , XIONG Yuan-zhul, ZUO Bo1, LEI M i n g - g a n g l , LI F e n g - e l and LI Jia-liad Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture/College of Animal Science and Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, P.R. China 2 Department of Biology Science & Technology, Zhangzhou Normal College, Zhangrhou 363000, P.R. China I
Abstract Live measurement growth traits are very important economic traits in pig production and breeding. In this research, quantitative trait loci (QTL) were detected for 11 live estimated growth and carcass traits, including birth weight (BWT), average daily gain over testing periods (ADG3), live backfat thickness at last 3-4th lumbar (LBFT3), live loin eye area (LLEA), and so on, in 214 pig resource family population, including 180 F2 individual, by 39 microsatellite marker loci on SSC4, SSC6, SSC7, SSC8, and SSC13. The results indicated that 4 chromosome significant level QTL and one suggestive QTL were detected for ADG3 (at position of 50 cM on SSCS), LBlT3 (at position of 147 cM on SSC4), LLEA (one highly significant at position of 48 cM on SSC7; another significant at position of 125 cM on SSC8) and BWT (suggestive significant at position of 0 cM, at marker sw489 on SSC4). The phenotypic variance of these QTL accounted for 0.95% to 16.91%. Most of them were mentioned in previous reports; except the QTL of LLEA at position of sw1953 on SSC8 which maybe a new QTL.
Key words: pig, quantitative trait loci (QTL), live measurement traits
INTRODUCTION Live measurement growth traits and carcass traits such as average daily gain, live measurement loin eye area, live measurement backfat thickness and live measurement percentage of lean meat are very important economic traits, which are critical when considered in pig production and breeding. Live measurement loin eye area, live measurement backfat thickness and live measurement lean meat percentage are always used in estimating the market value of pigs in wholesale trade, because the three traits are the main factors of market value and meat quality of swine. Hence, it is focused on by the geneticist for the genetic development of these
quantitative traits in research. Since Anderson et al. (1994) had conducted quantitative trait loci (QTL) analysis successfully for growth traits and average backfat traits using a Wild Boar and Large White resource population, many results of QTL mapping for the important economic traits were reported (Bidanel and Rothschild 2002; Hu et al. 2005). For live measurement growth and carcass traits, some QTL mapping results were identical and many results were diverse. It was important to identify and verify different results, because present and future genetic improvements would result from more detailed genetic maps and our growing understanding of the function and structure of the individual genes represented by QTL. In recent years, there were several works about these
Received 27 Februq, 2006 Accepted 20 March, 2007 ZHANG Jing-hu, Ph D, Associate Professor, Tel: +86-596-6372657, E-mail: [email protected]; CorrespondenceXIONG Yuan-zhu, Tel: +86-27-87287390, Fax: +86-27-87394184, E-mail: [email protected]
Q2007, CAAS. All rightsresewed.PuMishedby Elsevier Ctd.
ZHANG Jing-hu et al.
864
investigations in our experiment, and made some progress of linkage map construction and QTL unraveling (Su e l al. 2002a, b, c: Zuo et al. 2003b, 2004). which absorbed the attention of many researchers. In this study, for the sake of combining the genetic analysis of heterosis in pig crossbred populations to QTL, we built the resource family population, and made the genetic analysis of these live measurement traits.
average testing day was 59 d (ADG3 in Table I). The average daily gain over all periods (ADG4) was calculated from the total body weight gain divided by the total raising days. The live measurement carcass traits were taken at about 6 mon, at the end of the testing day before slaughtering, using ultrasonic measurement equipments. The pigs were slaughtered when their body weight reached about 90 kg.
MATERIALS AND METHODS
Microsatellite, PCR amplification and genotype scoring
Population and traits The pig resource family population was established by mating 3 Yorkshire boars (from England) to 5 Meishan sows (from Jiading County, Shanghai, China) randomly. Five males and 21 females in F, generation were selected for intercrossing randomly to give 180 individuals in F, populations, and the progenies were raised in a herd with the same equipment and the same ordinary food, during summer and autumn in 2003. Eleven live measurement traits were recorded according to the method of Xiong and Deng (1999) (Table 1). The experimental pigs had been weaned at the same 35 d, and the body weight weighed (ADGI) at the weaning day. Average daily gain from weaning to testing (ADG2) was calculated from the period of the weaning day to the testing day which began at 68-76 (average 72) d old. There were two testing periods, one was at 68-76 (average 72) d old and ended at 116-127 (average 121) d old, and the average testing day was 49 d (ADG5 in Table 1). The other began at 116-127 (average 121) d old and ended at 157-214 (average 180) d old, and the
Thirty-nine microsatellite markers on SSC4, 6, 7, 8, and 13 were selected based on the US Department of Agriculture - Meat Animal Research Centre (USDAMARC) genome database map (Table 2). All of the microsatellite DNA primer was provided by a US pig genome coordinator, Rothschild M F. PCR and genotyping were according to the method of Zhang et al. (2005).
Method of statistical analysis Linkage analysis was carried out using the CRIMAP software (ver. 2.4, Green et al. 1990). Web software (http://qtl.cap.ed.ac.uk)was used to carry out QTL analysis. The following statistical model was fitted based on a linear model in terms of additive and dominance contributions for a QTL (Haley et al. 1994; Olivo et al. 2000; Zuo el al. 2003b): Y = p +sex +family + covariate + Caa+ C /
+e
Where Y was the observations; p was the mean; sex, family were the fixed effect of traits; the covariate is
Table 1 Describing statistics for traits data in this research Traits
"1
Birth weight (kg). BWT Average daily g i n before weaning (kg). ADGl Average daily gain from weaning to testing (kg). ADG2 Average daily gain over resting period5 during 5-6 mon old (kg). ADG3 Average daily gain over all penods (kg).ADG4 Average daily gain over testing penods dunng 3-4 mon old (kg). ADG5 Live backfat thickness at last rib (mm). LBFTl Live backfat thickness at last 3-4th rib (mm). LBFT2 Live backfat thickness at last 3-4th lumbar (mm). L B R 3 Live loin eye area (square centimetre), LLEA Live lean meat percentage ('7). LLMP
179 179 I79 175 180 175 180 I80 I80 180 180
Means
* SE
N.
0.881 ? 0.016 0.281 ? 0.004 0.385 i 0.007 0.568 ? 0.010 0.497 i 0.004 0.652 0.010 20.477 ? 0.331 23.883 i 0.515 21.661 k 0.396 40.027 k 0.336 47.759 c 0.336
*
24.165 19.015 24.467 24.193 11.807 25.125 21.688 28.935 24.541 11.258 9.448
Max 1 400 0.457 0.592 0.932
0.633 0 885 34.000 49.000 37.000 54.000 58.400
Min 0.500 0.213 0.135 0.121 0.325 0 308 1 1 000 10.000 10.000 33 000 35 400
"Number of aninialr with obsenation value and included in QTL analysis.
0 2007.C M S . All riohts reserved Publishedbv Elsevier Ltd.
865
Detection of Ouantitative Trait Loci Associated with Live Measurement Traits in Pigs
Table 2 Mapping location of the 39 microsatellite markers in F, resource population SSR
sw489 sw835 sw2409 sw2454 so023 sw1996 sw445 so161 sw2406 sw1841 sw1302 swrll30 swl129 sw1473 so121 sw322 swr1343 sw2155 sw 1856 swr2036 sw352 sw252 sw581 so212 sw2410 so098 sw268 sw1037 sw1953 sw2160 sw1085 sw1980 sw1691 sw935 sw864 sw1495 sw520 sw2440 so291 I)
ssc
alleles
4
3 4
4
4 4 4 4 4 4 6 6 6 6 6 6 6 6 I 7 7 I 7 I I I
8 8 8 8 8 8 8 8
13 13 13 13 13 13 13
3 2 4 2 3
m4’) 230 316 238 44 265 217 325
3
157
5 4 3 5 3 3 4 3 3 2
292 267 254 24 1 76 308 316 130 300 96 28 1 304 112 183 140 202 172 146 207 25 8 243 266 289 232 218 134 116 232 133 300 119
5
3 3 3 2 3 3
3 4
4 3 3 3 4 2 2 2 3 3 4 3
Map (W 0 25.6 48.9
69.1 87.5 114 148.2 172.3 0 21.6 41.6 78.2 88.7 114.1 139.4 168.7 0 40.1 69.9 89.3 110.4 122.1 160.3 191.7 0
29.9 68.8 102.4 124.3 139.8 161.7 197.3 0
41.3 69.9 94.9 123.4 147.6 178.3
IM,informative meiosis.
body weight for live measurement carcass traits, and it is the numbers of relative raising days in different periods for growth traits. The coefficient Cawas the probability of the additive effect (a), and C, was that of dominance effect (d) at the chromosome position of the QTL which had been identified. The additive effect (a) and dominance effect (d) were the parameters to be estimated for the QTL. In this study, the additive effects (a) were estimated as P (QQ) - P (qq), in which Q was the QTL allele from Yorkshire, and q was the QTL allele from Meishan, so the dominance effect (d) estimated as P (Qq), for the QTL had been identified. Thus, the positive values of the additive effects of the
QTL allele from Yorkshire denoted increasing effects, and reversed for the negative values (http://qtl.cap.ed. ac.uk). The residuals are represented by e. The additive fraction of F, phenotypic variance (0,’) explained by a QTL was computed assuming that alternative alleles were fmed in each breed; i.e., h2Q=a2/20y2 (Ovilo et al. 2000). Chromosome-wise significance thresholds were calculated empirically by permutation tests of which the number was 1000 (Churchill and Doerge 1994).
RESULTS The statistical parameters of the 11 live measurement traits analyzed are shown in Table 1. The results showed that the variant range of the observed value was broad, and that could make the basis of these QTL research. The results of linkage map construction (Table 2) showed that the orders of microsatellite marker were identical to that reported by the USDA-MARS (http:j/ www .genome.iastate. edu/maps/pig), but the average length of two sex were longer than those in the USDA map. These were similar to that in the previous research by Su et al. (2002a) and Zuo et al. (2003a). The results of the QTL analysis are presented in Table 3 and Fig. Five QTL were detected, one was in chromosome very significant level; three were in chromosome significant and a QTL, in chromosome suggestive level.
QTL for growth trait A QTL with significant effect on ADG3 at position 50 cM, between the markers so098 and sw268 on SSC8 (Pc0.05)was detected (Fig.-A). The QTL could account for about 16.91% of the variance in the population, with an additive effect of 0.07 kg average daily gain during the testing period. The positive additive effect value suggested that the QTL effects were in the expected direction, namely the Yorkshire allele increased daily gain, and the heterozygous pigs had the effect of dominant allele from Yorkshire on increasing the daily gain with 0.016 kg per day (Table 3 ) . It was found that, there was a position that had the effect on birth weight (BWT) near significant level at sw489 on SSC4 (taken as suggestive significant level QTL on chromosome-wise level), with additive effect
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ZHANG Jing-hu er al.
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of 0.036 kg from Yorkshire allele, and the heterozygous pig had dominantly decreasing effect on birth weight.
QTL for live carcass traits A QTL at position 147 cM, near the marker sw445 on SSC4, which had significant impacts on live backfat thickness at last 3-4th lumbar (mm) (LBFT3) ( P < 0.05), with additive effect of 0.704 cm, which could account for about 0.95% of the phenotypic variation in the pig population was located (Table 3 and Fig.-B). Two QTL were located with highly significant ( P < 0.01) or significant (P<0.05) impacts on LLEA at positions 48 cM (between sw2155 and sw1856, on SSC7) (Fig.-C) and 125 cM (at marker locus sw1953, on
SSC8) (Fig.-D), respectively. The two QTL had additive effects of 1.268 or 0.956 m2 on live loin eye area (m') (LLEA), which could explain approximately 4.38% or 2.52% phenotypic variation, respectively. The two QTL alleles resourced from Yorkshire had effects of increasing the LLEA, but in the heterozygous pig, decreasing the LLEA dramatically, which indicated the negative dominant effects from the two QTL alleles.
DISCUSSION In this research, four QTL and one suggestive QTL were detected on SSC4, 7 and 8 for ADG3, LBFT3, LLEA and BWT, some of them were mentioned in previous reports. The results of QTL mapping for the ADG3 in this
Table 3 The results of QTL mapping for birth weight and growth traits Trait
ssc
Pos (cM)
B W
4 8
0 50
1
117
1 8
JR
ADG3
LBFT LLEA
F-value
Additive effect
Dominant effect
Variance ( W )
sww sO098-sw268
4.96 5 07'
0.036 + 0.023 0.070 t 0.025
-0.088 f 0.034 0.016 c 0.053
sw.145 s w 2 155-sw 1R56 sw 1953
5.9' 6.88" 6.05'
0.704 f 0.626 1.268 ? 0.767 0.956 t 0.566
2 951 f 0.899 -3.850 f 1.409 -3.417 f 1.088
3.18 16.9 I 0.95 4.38
Marker interval
125
2.52
'Sign~iicantat chromosome-wise level ( P < O . O S ) : "very significant at chromosome-wise level (P
Position (cM)
50
100
Positioii (cM)
I50
200 Position ( c M )
Fig. QTL mapping results of average daily gain over testing periods on SSC8 (A), live backfat thickness at last 3-4th lumbar on SSC4 (B), loin eye area on SSC7 (C) and SSC8 (D). The X-axis indicates the relative position on the linkage map; the Y-axis represents the F-ratio. The line indicates the chromosome-wise significance level.
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Detection of Quantitative Trait Loci Associated with Live Measurement Traits in Pigs
research were identical to the report by Quintanilla et al. (2002), which mapped the QTL for ADG in the fatting period at the position between sw2410 and swrllol. It was interesting to know that on the USDA-MARC map, the interval of sw2410-swr1101 was about 40 cM which contained marker interval of ~0098-sw268entirely. About the investigation of QTL for explaining live measurement backfat thickness on SSC4, several results were obtained but the mapping positions were diverse, such as 63 cM (live backfat thickness at last 3-4th lumbar, sw835-sw752, Zuo et al. 2003b), 158 cM (average live sidefat thickness, sw445, Su et al. 2002b), 81-82 cM (live backfat thickness at mid-back or shoulder, Walling et al. 1998) and 99.3 cM (last lumber backfat, sw524, Malek et al. 2001). The QTL located in this research was consistent with that of Su et al. (2002b), and there was little difference from the result of Malek et al. (2001), because the marker sw445 was next to the marker sw524 by just 5.5 cM in the USDA-MARC map. It was noted that, the results of QTL mapping about LLEA on SSC7 were consistent with that of Sat0 et al. (2003) and Zuo et al. (2003b). The former had located the loin eye area QTL at position 58 cM, near the marker sw2155 by 15 cM on the map of USDA-MARC, maybe the same QTL in this research. The latter had mapped the loin eye area QTL at position 63 cM, the same marker interval of sw2155-sw1856 on SSC7, and the genetic effect of the results were similar to the results in this study. It was confirmed that there was a QTL associated with the loin eye area at that point. Another QTL for LLEA on SSC8 could be noted in the report by Rohrer and Keele (1998), in which a QTL was mapped at the position of 105.7 cM between the markers sw1671 and sw1551, which had a large interval apart from the QTL in this result, and it was might be another QTL. About the suggestive significant level QTL at position 0 cM on SSC4 for BWT, the same result was reported by Paszek et al. (1999), who had mapped the suggestive QTL in the interval of 7.4-27.1 cM on SSC4, with the additive effect from Meishan allele by -0.05, which decreased the birth weight in F, population, and it accounted for 16.6% variance of phenotype. The resolution of pin pointing the gene in a position of QTL would be dependent on the development and
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progress of map-position clone technology, such as pig-human comparative map and chromosome manipulation. The fine map of QTL location would facilitate the search for QTL responsible genes. Based on the results, it would benefit to look for the candidate genes for the mapped QTL in further research.
Acknowledgements We wish to thank the USDA-MARC for providing the microsatellite primers. The authors also gratefully extend their acknowledgements to the teachers and postgraduate students of the Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, Huazhong Agricultural University, and the Swine Breeding Centre of China for their cooperation. This work was supported by the National 973 Project of China (G2000016105), and National Natural Science Foundation of China (30500358).
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