Identification of common haplotypes for fine scale mapping of QTL.

Abstract

AAABG Vol 15 IDENTIFICATION OF COMMON HAPLOTYPES FOR FINE SCALE MAPPING OF QTL FOR RETAIL BEEF YIELD Y. Li, B. Harrison, R. Bunch and W. Barendse CRC for Cattle and Beef Quality CSIRO Livestock Industries, Queensland Biosciences Precinct, 306 Carmody Rd, St Lucia, QL D 4067, Australia SUMMARY Haplotype information is an essential ingredient in many analyses of fine-scale mapping of QTL. Various methods are being used for identification of haplotypes. When genotyping methods do not provide phase information, one method that can be used to infer phase is to reconstruct haplotypes by choosing the most probable haplotype assignment, given the genotype data and the estimated population haplotype frequencies. We applied this method to fine scale mapping of QTL for retail beef yield in Beef CRC populations. It proved to be an efficient method to identify the QTL region affecting the quantitative trait. Keywords : common haplotype, QTL, retail beef yield, Beef CRC population. INTRODUCTION Haplotype information is an essential ingredient in many analyses of fine-scale mapping of QTL, such as for resistance to disease (Risch and Merikangas 1996), milk quality (McPartlan et al. 2001) and growth traits (Li et al. 2002). These information will greatly facilitate the identification a nd cloning of the causative genes. It is expected some common haplotypes originating from common ancestors may carry on and segregate among individuals of a breeding line, particularly when selection is applied. Our focus here is population data where genotyping methods do not provide phase information due to lack of parental genotypes. One statistical method that can be used to infer phase is to reconstruct haplotypes by choosing the most probable haplotype assignment given the genotype data and the estimated population haplotype frequencies (Excoffier and Slatkin 1995). This paper reports on the value of using that method to identify common haplotypes for retail beef yield using the Beef CRC animals. MATERIALS AND METHODS Animals. Two groups of beef cattle consisting of temperate (Angus, Hereford and Shorthorn) and tropically adapted (Brahman, Belmont Red and Santa Gertrudis) breeds were used for the study. They were chosen from the CRC DNA bank. Information stored in the CRC database was used to select animals across a range of 3 purchasing markets and 4 finishing regimes (see Table 1). The first group (260 individuals) comprised animals of extremes (high and low) of retail beef yield (ADJRBY). In essence, the procedure was to select cattle in each cohort which were of extreme phenotypes, ensuring that no sire was represented by a cluster of offspring, that all markets and finishing regimes were included in each extreme, so that extremes were not biased by being representative of a particular market or finishing regime. The second group (528 individuals) comprised the first group (extreme) and an addition of 268 non-extremes animals. The second group was chosen to be 31 Detection of QTL representative of across-the-range population. These two groups form the base for the identification of common haplotypes (Table 1). Table 1. Part I: Number of sires and contemporary groups within each population. Part II: Number of animals in each breed/finish/market class Effect Extreme Combined Total 260 528 Part I Sires 87 110 Contemporary GroupsA 151 183 Part II Breed Angus 37 78 Belmont Red 39 92 Brahman 43 96 Hereford 50 95 Santa Gertrudis 51 94 Shorthorn 31 82 Finish Pasture South 62 135 Pasture North 46 107 Grain South 96 163 Grain North 56 123 Market Domestic 106 199 Korean 102 215 Japanese 52 114 A Contemporary group was defined as the combination of herd of origin, cohort and kill code. Genotyping and haplotype identification. A single chromosome (anonymous for IP protection) with 9 DNA microsatellite makers was used for this study. The chromosome was chosen for finescale mapping because of the presence of a QTL for retail beef yield identified in the CBX experiments (Hetzel et al., 1997) and further confirmed by the Beef CRC marker evaluation project (Li et al., unpublished). Five hundred and twenty-eight animals were genotyped using 9 microsatellite markers. T haplotypes (allele linkage phases) of the animals were established he according to the orders of linked markers from public maps i.e. haplotypes were reconstructed by choosing the most probable haplotype assignment, given the genotype data and the estimated population haplotype frequencies. The SAS program (Version 8.2, SAS Inst. Inc., Cary, NC) was used to derive the frequencies of pair-wise marker alleles. Statistical Analysis. Analyses were performed between the most commonly observed haplotypes and retail beef yield (ADJRBY) using the SAS mixed model procedure, where the difference between animals with and without haplotypes was tes ted. A complete dominance effect of the haplotype was assumed, in which animals carrying either one or two copies of the haplotype were treated the same. Fixed effects in the model included finish and haplotype type. Contemporary groups were treated as a random effect. The statistical model was Trait = mean + contemporary group + haplotype + finish + 32 AAABG Vol 15 carcass weight within market endpoint. Contemporary group was defined as the combination of herd of origin, cohort and kill code. Carcass weight within market endpoint (Japanese, Korean, domestic) was used as a covariate to adjust for differences in weight and to a lesser extent, age effects. Since breed was confounded with contemporary group, it was not independently fitted in the model. All effects but haplotype were nested within breed. Haplotype type was defined as 1 when the individual had the haplotype or 0 when the individual was without the haplotype. When the most common haplotype could not be determined between two adjacent loci due to similar frequenci of two es haplotypes, the haplotype type was then defined as 1, 2 or 0 (i.e. two common haplotypes for the adjacent loci). Summary statistics of the trait are presented in Table 2. Table 2. Summary statistics of retail beef yield in both populations Population and trait Mean Range Extreme population ADJRBY (%) 66.87 56 _ 77.16 Combined population ADJRBY (%) 66.72 55 _ 77.16 SD 4.79 4.47 RESULTS AND DISCUSSION Identification of common haplotypes. The number of alleles in each marker is shown in Table 3. On average, 12.3 alleles were detected for each locus of the chromosome in the extreme population, with a range of 5 to 25 alleles per locus. The average was slightly higher in the combined population (12.9). In both populations, the phase of the most common haplotypes was readily determined for the first six markers based on the frequencies of alleles at adjacent loci along the chromosome. However, there were difficulties with the last three loci due to the similar frequencies of two haplotypes. The extra two rare alleles in markers 6 and 7 were not the cause of the difficulty. Therefore, two common haplotypes were assigned as 1 and 2 for analysis in these three loci (see Table 4). Association between a haplotype and ADJRBY. Associations between the most common haplotypes, which were exclusively haplotypes of adjacent loci, and ADJRBY are shown in Table 4. In both populations, a consistent significant effect was identified for the common haplotype 121-153 within markers 1 and 2 (P<0.05). The haplotype had a very high frequency of 40% in both populations relative to the other haplotypes (ranging from 9% to 40%). It explained 33% of trait variation in terms of standard deviation. There was no significant effect due to the other haplotypes. Despite of the lack of parental genotype information, the identification of the common haplotype has further confirmed the existence of a QTL for ADJRBY on the chromosome identified by the CBX QTL experiment (Hetzel et al., 1997) and the CRC marker evaluation project. It will provide useful information for further characterization of the gene(s) of interest in the region. H aplotypes can generally be identified using the identity by descent method with the genotype information available at least from the sires of animals. However, with commercial populations, where sires or dams may not be genotyped due to the cost, these results demonstrate that common haplytypes can be used to detect potential QTL. 33 Detection of QTL Table 3. Number of alleles from each microsatellite marker in b populations oth Marker Extreme Population Combined Population M1 9 9 M2 8 9 M3 9 9 M4 25 25 M5 19 19 M6 5 7 M7 9 11 M8 13 13 M9 14 14 Average 12.3 12.9 Table 4. Association between haplotypes and ADJRBY in two populations. Two common haplotypes were assigned for markers 7, 8 and 9 Extreme Combined HaplotypeA Freq. P-value Effect � S.D Freq. P-value Effect � S.D M1-121, M2-153 0.43 0.046* 1.56 � 0.73 0.40 0.024* 1.49� 0.629 M2-153, M3-114 0.48 0.068 1.31� 0.68 0.40 0.19 0.798� 0.595 M3-114, M4-193 0.25 0.57 -0.43 � 0.75 0.21 0.67 -0.272 � 0.629 M4-193, M5-187 0.11 0.39 -0.92 � 1.03 0.093 0.48 0.619 � 0.864 M5-187, M6-163 0.27 0.088 -1.27 � 0.70 0.21 0.40 0.544 � 0.643 M6-163, M7-100 0.20 0.67 0.635 � 0.827 0.17 0.64 0.569 � 0.708 M6-163, M7-104 0.26 0.50 � 0.753 0.22 0.458 � 0.664 M7-100, M8-155 0.15 0.33 0.0462� 0.958 0.13 0.31 -0.137� 0.802 M7-104, M8-141 0.18 1.25� 0.816 0.15 1.12� 0.739 M8-155, M9-181 0.16 0.67 -0.765� 0.932 0.18 0.64 -0.709� 0.779 M8-141, M9-189 0.23 -0.443� 0.784 0.21 -0.334� 0.691 A The haplotypes were named by two alleles of a pair of loci. For example M1 121, M2-153 represents a segment of chromosome having allele 121 of M1 and allele 153 of M2. * P < 0.05 REFERENCES Excoffier, L. and Slatkin, M. (1995) Mol. Biol. Evol. 12:921. 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