Power of a genome scan to detect and locate quantitative trait loci in cattle using dense single nucleotide polymorphisms

There is increasing use of dense single nucleotide polymorphisms (SNPs) for whole‐genome association studies (WGAS) in livestock to map and identify quantitative trait loci (QTL). These studies rely on linkage disequilibrium (LD) to detect an association between SNP genotypes and phenotypes. The power and precision of these WGAS are unknown, and will depend on the extent of LD in the experimental population. One complication for WGAS in livestock populations is that they typically consist of many paternal half‐sib families, and in some cases full‐sib families; unless this subtle population stratification is accounted for, many spurious associations may be reported. Our aim was to investigate the power, precision and false discovery rates of WGAS for QTL discovery, with a commercial SNP array, given existing patterns of LD in cattle. We also tested the efficiency of selective genotyping animals. A total of 365 cattle were genotyped for 9232 SNPs. We simulated a QTL effect as well as polygenic and environmental effects for all animals. One QTL was simulated on a randomly chosen SNP and accounted for 5%, 10% or 18% of the total variance. The power to detect a moderate‐sized additive QTL (5% of the phenotypic variance) with 365 animals genotyped was 37% (p < 0.001). Most importantly, if pedigree structure was not accounted for, the number of false positives significantly increased above those expected by chance alone. Selective genotyping also resulted in a significant increase in false positives, even when pedigree structure was accounted for.     

Genomic best linear unbiased prediction method reflecting the degree of linkage disequilibrium

The degree of linkage disequilibrium (LD) between markers differs depending on the location of the genome; this difference biases genetic evaluation by genomic best linear unbiased prediction (GBLUP). To correct this bias, we used three GBLUP methods reflecting the degree of LD (GBLUP‐LD). In the three GBLUP‐LD methods, genomic relationship matrices were conducted from single nucleotide polymorphism markers weighted according to local LD levels. The predictive abilities of GBLUP‐LD were investigated by estimating variance components and assessing the accuracies of estimated breeding values using simulation data. When quantitative trait loci (QTL) were located at weak LD regions, the predictive abilities of the three GBLUP‐LD methods were superior to those of GBLUP and Bayesian lasso except when the number of QTL was small. In particular, the superiority of GBLUP‐LD increased with decreasing trait heritability. The rates of QTL at weak LD regions would increase when selection by GBLUP continues; this consequently decreases the predictive ability of GBLUP. Thus, the GBLUP‐LD could be applicable for populations selected by GBLUP for a long time. However, if QTL were located at strong LD regions, the accuracies of three GBLUP‐LD methods were lower than GBLUP and Bayesian lasso.     

Multiple QTL on chromosome six in dairy cattle affecting yield and content traits

A granddaughter design containing five half-sib families from German Holstein–Friesian cattle was subjected to QTL analysis starting from the hypothesis of the existence of more than one QTL on chromosome BTA 6 affecting milk yield, fat yield, protein yield and content of fat and protein. The marker map consisted of 16 microsatellite markers with marker heterozygosity varying from 0.44 to 0.94. Two statistical methods were used: least squares (LS) and residual maximum likelihood (REML) allowing for two QTL simultaneously. The test statistics were calculated in steps of one cM along the chromosome. Significant QTL at the chromosome-wise 5% level according to the permutation test critical value were detected mainly in single families. The results were in conformance with the findings of several previous studies with approximate positions of putative QTL at 49 cM for milk yield, at 70 cM for fat and protein yield, and at 46 cM for protein content. Further QTL positions were suggested mostly for yield traits and protein content in the area of the casein gene cluster at 90…95 cM. The results of the two-QTL model analyses when using LS led to family specific inferences of a second QTL for fat yield and content of protein and fat, partly supported by the epistasis model.     

A quantitative trait locus for faecal worm egg and blood eosinophil counts on chromosome 23 in Australian goats

Three microsatellite markers on goat chromosome 23 adjacent to the MHC were used to test for quantitative trait loci (QTL) affecting faecal worm egg count (WEC) and leukocyte traits in ten Australian Angora and twelve Australian Cashmere half‐sib families (n = 16–57 per family). Data were collected from 280 Angora and 347 Cashmere kids over a 3‐ and 4‐year period. A putative QTL affecting trichostrongyle WEC was found in two small families at the 5% chromosome‐wise threshold level. The biggest QTL effect for WEC of 1.65 standard deviations (σ_p) was found within the region of OarCP73‐BM1258. A significant QTL affecting blood eosinophil counts at the 1% chromosome–wise threshold level was detected at marker BM1258 (at 26 cM) in two Angora and Cashmere families. The magnitude of the putative QTL was 0.69 and 0.85 σ_p in Angora and Cashmere families, respectively. Due to the comparatively low power of the study these findings should be viewed as indicative rather than definitive.     

Interval mapping of growth quantitative trait loci in Japanese Black beef cattle using microsatellite DNA markers and half-sib regression analysis

A confirmatory scan for the regions of bovine chromosome 1 segregating the quantitative trait loci (QTL) influencing birthweight, weaning weight, yearling weight, and preweaning and postweaning average daily gains was performed by genotyping half‐sib progeny of four Japanese Black sires using microsatellite DNA markers. Data were analyzed by generating an F‐statistic every 1 cM on a linkage map by the regression of phenotype on the probabilities of inheriting an allele from the sire after adjusting for the fixed effects of sire, sex, parity and season of birth as well as age as a covariate. Permutation tests at chromosome‐wide significance thresholds were carried out over 10 000 iterations. A significant QTL for birthweight at 114 cM was detected in the sire 2 family. This identification of a birthweight QTL in Japanese Black cattle may be useful for the implementation of marker‐assisted selection.     

Primary genome scan to identify putative quantitative trait loci for feedlot growth rate, feed intake, and feed efficiency of beef cattle

Feed intake and feed efficiency of beef cattle are economically relevant traits. The study was conducted to identify QTL for feed intake and feed efficiency of beef cattle by using genotype information from 100 microsatellite markers and 355 SNP genotyped across 400 progeny of 20 Angus, Charolais, or Alberta Hybrid bulls. Traits analyzed include feedlot ADG, daily DMI, feed-to-gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F)], and residual feed intake (RFI). A mixed model with sire as random and QTL effects as fixed was used to generate an F-statistic profile across and within families for each trait along each chromosome, followed by empirical permutation tests to determine significance thresholds for QTL detection. Putative QTL for ADG (chromosome-wise P < 0.05) were detected across families on chromosomes 5 (130 cM), 6 (42 cM), 7 (84 cM), 11 (20 cM), 14 (74 cM), 16 (22 cM), 17 (9 cM), 18 (46 cM), 19 (53 cM), and 28 (23 cM). For DMI, putative QTL that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (93 cM), 3 (123 cM), 15 (31 cM), 17 (81 cM), 18 (49 cM), 20 (56 cM), and 26 (69 cM) in the across-family analyses. Putative across-family QTL influencing F:G that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 3 (62 cM), 5 (129 cM), 7 (27 cM), 11 (16 cM), 16 (30 cM), 17 (81 cM), 22 (72 cM), 24 (55 cM), and 28 (24 cM). Putative QTL influencing RFI that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (90 cM), 5 (129 cM), 7 (22 cM), 8 (80 cM), 12 (89 cM), 16 (41 cM), 17 (19 cM), and 26 (48 cM) in the across-family analyses. In addition, a total of 4, 6, 1, and 8 chromosomes showed suggestive evidence (chromosome-wise, P < 0.10) for putative ADG, DMI, F:G, and RFI QTL, respectively. Most of the QTL detected across families were also detected within families, although the locations across families were not necessarily the locations within families, which is likely because of differences among families in marker informativeness for the different linkage groups. The locations and direction of some of the QTL effects reported in this study suggest potentially favorable pleiotropic effects for the underlying genes. Further studies will be required to confirm these QTL in other populations so that they can be fine-mapped for potential applications in marker-assisted selection and management of beef cattle.     

Mapping the quantitative trait loci (QTL) for body shape and conformation measurements on BTA1 in Japanese Black cattle

The detection and mapping of segregating quantitative trait loci (QTL) that influence withers height, hip height, hip width, body length, chest width, chest depth, shoulder width, lumbar width, thurl width, pin bone width, rump length, cannon circumference, chest girth, abdominal width and abdominal girth at weaning was conducted on chromosomal regions of bovine chromosome one. The QTL analysis was performed by genotyping half‐sib progeny of five Japanese Black sires using microsatellite DNA markers. Probability coefficients of inheriting allele 1 or 2 from the sire at specific chromosomal locations were computed. The phenotypic data of progeny were regressed on these probability coefficients in a within‐common‐parent regression analysis using a linear model that included fixed effects of sex, parity and season of birth, as well as age as a covariate. F‐statistics were calculated every 1 cM on a linkage map. Permutation tests of 10 000 iterations were conducted to obtain chromosome‐wide significance thresholds. A significant QTL for chest width was detected at 91 cM in family 3. The detection of this QTL boosts the prospects of implementing marker‐assisted selection for body conformation traits in Japanese Black beef cattle.     

Fine mapping of a quantitative trait locus on chromosome 9 affecting non-return rate in Swedish dairy cattle

We previously mapped a quantitative trait locus (QTL) affecting the trait non-return rate at 56 days in heifers to bovine chromosome 9. The purpose of this study was to confirm and refine the position of the QTL by using a denser marker map and fine mapping methods. Five families that previously showed segregation for the QTL were included in the study. The mapping population consisted of 139 bulls in a granddaughter design. All bulls were genotyped for 25 microsatellite markers surrounding the QTL on chromosome 9. We also analysed the correlated trait number of inseminations per service period in heifers. Both traits describe the heifer's ability to become pregnant after insemination. Linkage analysis, linkage disequilibrium and combined linkage and linkage disequilibrium analysis were used to analyse the data. Analysis of the families jointly by linkage analysis resulted in a significant but broad QTL peak for non-return rate. Results from the combined analysis gave a sharp QTL peak with a well-defined maximum in between markers BMS1724 and BM7209, at the same position as where the highest peak from the linkage disequilibrium analysis was found. One of the sire families segregated clearly at this position and the difference in effects between the two sire haplotypes was 2.9 percentage units in non-return rate. No significant results were found for the number of inseminations in the combined analysis.     

A region on bovine chromosome 15 influences beef longissimus tenderness in steers.

A genome scan was conducted using 196 microsatellite DNA markers spanning 29 autosomal bovine chromosomes and Warner-Bratzler shear force collected at d 2 and 14 postmortem on steaks from the longissimus muscle of 294 progeny from one Brahman x Hereford bull mated to Bos taurus cows to identify QTL for beef tenderness. One QTL was identified and located 28 cM (95% confidence interval is 17 to 40 cM) from the most centromeric marker on BTA15. The QTL interacted significantly with slaughter group. The difference in shear force of steaks aged 14 d postmortem between progeny with the Brahman paternally inherited allele vs those with Hereford was 1.19 phenotypic standard deviations (explained 26% of phenotypic variance) for one slaughter group and was not significant for three other slaughter groups. Apparently, unknown environmental factors present for three of the four slaughter groups were capable of masking the effect of this QTL. The sensitivity of the QTL effect to environmental factors may complicate utilization of markers for genetic improvement. Future research to elucidate the cause of the QTL x slaughter group interaction may lead to improved strategies for controlling variation in meat tenderness via marker-assisted selection, postmortem processing, or live animal management.     

Models for marker-assisted genetic evaluation with multiple QTL in a crossbred population

The efficiency of alternative models for marker-assisted genetic evaluation with multiple previously identified QTL for a trait with heritability 0.1 was evaluated by stochastic simulation. Three biallelic unlinked additive QTL were simulated in the middle of marker intervals of 0, 10, and 20 cM, with each QTL explaining 12, 6, or 3% of genetic variance in the F₂ of a cross between inbred lines. Three models for marker-assisted genetic evaluation were compared to standard BLUP (B): BM = B with fixed marker effects; BMR = BM plus inclusion of random QTL effects; M = selection on the number of favorable marker alleles. All MAS models resulted in greater responses than B in initial generations, but extra gains declined over generations. The impact of the magnitude of QTL variance used for genetic evaluation for BMR on average QTL frequencies and response was limited. Selection with M gave greater response than B only up to the F₅. For BM and BMR, extra response over B and QTL frequencies increased when QTL effects increased and size of marker intervals decreased. The number of QTL that explained a given total amount of variance had no effect on the ranking of models in terms of QTL frequencies although a larger number of QTL resulted in higher genetic gains in later generations. Heritability had no effect on the ranking of the models. Based on genetic gains and ease of implementation, model BM is recommended as the most suitable model for marker-assisted selection in crosses of inbred lines.     

Investigations in the character of QTL affecting negatively correlated milk traits

The primary aim of this study was to investigate the quantitative trait loci (QTL) on BTA6 that affect negatively correlated milk traits, using bivariate covariance component analysis of milk yield and fat (or protein) content, protein yield and fat content, and fat yield and protein content. A set of five different genetic models was adapted to differentiate trait‐specific QTL in close linkage from pleiotropy. Using a grand‐daughter design consisting of five half‐sib families from the German Holstein population and 298 sons genotyped for 16 microsatellite markers on BTA6, we found significant trait‐specific QTL for fat content and protein yield, 24 cM apart. Markers BM1329 and FBN12 bracketed the QTL for fat content, and the region between TGLA37 and FBN13 most likely harbours a QTL for protein yield. The analysis based on the close linkage model fully confirmed this result. Despite the pure QTL findings confirming results from the literature, distinguishing pleiotropic and closely linked QTL for competitive traits is a new aspect. Our multivariate analysis results did not suggest a pleiotropic QTL for the investigated negatively correlated traits. The QTL‐based trait correlations were discussed as an important aspect of modelling that needs to be considered in the future.     

QTL detection for milk production traits in goats using a longitudinal model.

Eight paternal half-sib families were used to identify chromosomal regions associated with variation in the lactation curves of dairy goats. DNA samples from 162 animals were amplified by PCR for 37 microsatellite markers, from Capra hircus autosomes CHI3, CHI6, CHI14 and CHI20. Milk samples were collected during 6 years, and there were 897 records for milk yield (MY) and 814 for fat (FP) and protein percentage (PP). The analysis was conducted in two stages. First, a random regression model with several fixed effects was fitted to describe the lactation function, using a scale (alpha) plus four shape parameters: beta and gamma, both associated with a decrease in the slope of the curve, and delta and phi that are related to the increase in slope. Predictions of alpha, beta, gamma, delta and phi were regressed using an interval mapping model, and F-tests were used to test for quantitative trait loci (QTL) effects. Significant (p < 0.05) QTLs were found for: (i) MY: CHI6 at 70-80 cM for all parameters; CHI14 at 14 cM for delta and phi; (ii) FP: CHI14, at 63 cM was associated with beta; CHI20, at 72 cM, showed association with alpha; (iii) PP: chromosomal regions associated with beta were found at 59 cM in CHI3 and at 55 cM in CHI20 with alpha and gamma. Analyses using more families and more animals will be useful to confirm or to reject these findings.     

红三叶遗传图谱构建及抗白粉病基因QTL定位

本研究以感(岷山红三叶)、抗(澳大利亚红三叶品种♀Sensation×Renegade♂杂交新品系“甘农PR1”)白粉病红三叶材料为父母本杂交并种植成苗经人工接菌后筛选出抗、感白粉病的F₁群体为作图群体,利用AFLP标记构建红三叶高密度遗传图谱,并利用区间作图法对抗白粉病QTL进行了定位分析,可以为红三叶抗白粉病基因克隆和转基因等分子辅助育种奠定基础。结果表明,149个AFLP标记构建得到的遗传图谱包含7个连锁群(LG1,LG2,LG3,LG4,LG5,LG6和LG7),遗传图谱的总距离为640.5 cM。其中,LG1连锁群的遗传距离(140.6 cM)和标记间平均距离(9.4 cM)均最大;LG4连锁群的遗传距离(55.2 cM)和标记间平均距离(1.8 cM)最小。应用区间作图法对红三叶抗白粉病基因进行QTL分析定位,共检测到5个抗白粉病相关QTL位点(qrp-1,qrp-2,qrp-3,qrp-4和qrp-5),其中qrp-1、qrp-2、qrp-3和qrp-4位于LG4连锁群上,qrp-5位于LG5连锁群上。5个QTL位点对抗白粉病的贡献率为29%~90%,qrp-1对红三叶白粉病抗性的贡献率最大(90%),为主效QTL。     

Precision of estimated QTL positions in granddaughter designs using combined haplotype sharing TDT and linkage analysis

The aim of this study was to develop the linear haplotype sharing transmission disequilibrium test (LHS-TDT) method and combine this method with the simple regression method to estimate the precision of QTL positions in granddaughter designs. This precision was determined by Monte Carlo simulation in granddaughter designs. A single bi-allelic QTL at the midpoint of a linkage group and 26 markers with 1 cM intervals and with two alleles each were simulated. Three linear models, (i.e. the simple regression model, the linear haplotype sharing TDT method and the combination of these two models) were compared. The mean of absolute differences (A) between the estimated and true QTL position of each method was considered for six different scenarios consisting of combinations of a number of markers and the most frequent haplotypes. The mean of A, using the simple regression method, was 4.38 centimorgan (cM). The means of A using the LHS-TDT method were less than the simple regression method in all scenarios and ranged from 1.86 to 3.82 cM depending on the scenario. The mean of A using the combined method was more than the LHS-TDT method and less than the simple regression method. The means of A using the combined method ranged from 2.32 to 4.36 cM. Therefore, for populations similar to those population simulated in this study, the LHS-TDT was better than the simple regression method and the combined method for precision of estimated QTL position in granddaughter designs.     

Marker‐assisted selection reduces expected inbreeding but can result in large effects of hitchhiking

We used computer simulations to investigate to what extent true inbreeding, i.e. identity‐by‐descent, is affected by the use of marker‐assisted selection (MAS) relative to traditional best linear unbiased predictions (BLUP) selection. The effect was studied by varying the heritability (h² = 0.04 vs. 0.25), the marker distance (MAS vs. selection on the gene, GAS), the favourable QTL allele effect (α = 0.118 vs. 0.236) and the initial frequency of the favourable QTL allele (p = 0.01 vs. 0.1) in a population resembling the breeding nucleus of a dairy cattle population. The simulated genome consisted of two chromosomes of 100 cM each in addition to a polygenic component. On chromosome 1, a biallelic QTL as well as 4 markers were simulated in linkage disequilibrium. Chromosome 2 was selectively neutral. The results showed that, while reducing pedigree estimated inbreeding, MAS and GAS did not always reduce true inbreeding at the QTL relative to BLUP. MAS and GAS differs from BLUP by increasing the weight on Mendelian sampling terms and thereby lowering inbreeding, while increasing the fixation rate of the favourable QTL allele and thereby increasing inbreeding. The total outcome in terms of inbreeding at the QTL depends on the balance between these two effects. In addition, as a result of hitchhiking, MAS results in extra inbreeding in the region surrounding QTL, which could affect the overall genomic inbreeding.     

Fine mapping a quantitative trait locus affecting ovulation rate in swine on chromosome 8

Ovulation rate is an integral component of litter size in swine, but is difficult to directly select for in commercial swine production. Because a QTL has been detected for ovulation rate at the terminal end of chromosome 8p, genetic markers for this QTL would enable direct selection for ovulation rate in both males and females. Eleven genes from human chromosome 4p16-p15, as well as one physiological candidate gene, were genetically mapped in the pig. Large insert swine genomic libraries were screened, clones were isolated and then screened for microsatellite repeats, and informative microsatellite markers were developed for seven genes (GNRHR, IDUA, MAN2B2, MSX1, PDE6B, PPP2R2C, and RGS12). Three genes (LRPAP1, GPRK2L, and FLJ20425) were mapped using genotyping assays developed from single nucleotide polymorphisms. Two genes were assigned since they were present in clones that contained mapped markers (HGFAC and HMX1). The resulting linkage map of pig chromosome 8 contains markers associated with 14 genes in the first 27 cM. One inversion spanning at least 3 Mb in the human genome was detected; all other differences could be explained by resolution of mapping techniques used. Fourteen of the most informative microsatellite markers in the first 27 cM of the map were genotyped across the entire MARC swine resource population, increasing the number of markers typed from 2 to 14 and more than doubling the number ofgenotyped animals with ovulation rate data (295 to 600). Results from the revised data set for the QTL analysis, assuming breed specific QTL alleles, indicated that the most likely position of the QTL resided at 4.85 cM on the new linkage map (F1,592 = 20.5150, genome-wide probability less than 0.015). The updated estimate of the effect of an allele substitution was -1.65 ova for the Meishan allele. The F-ratio peak was closest to markers for MAN2B2 (4.80 cM) and was flanked on the other side by markers for PPP2R2C. Two positional candidate genes included in this study are MAN2B2 and RGS12. These results validate the presence of a QTL affecting ovulation rate on chromosome 8 and facilitate selection of positional candidate genes to be evaluated.     

Detection of quantitative trait loci affecting non-return rate in French dairy cattle

The purpose of this study was to map quantitative trait loci (QTL) influencing female fertility estimated by non-return rate (NRR) in the French dairy cattle breeds Prim'Holstein, Normande and Montbeliarde. The first step was a QTL detection study on NRR at 281 days after artificial insemination on 78 half-sib families including 4993 progeny tested bulls. In Prim'Holstein, three QTL were identified on Bos taurus chromosomes BTA01, BTA02 and BTA03 (p < 0.01), whereas one QTL was identified in Normande on BTA01 (p < 0.05). The second step aimed at confirming these three QTL and refining their location by selecting and genotyping additional microsatellite markers on a sub-sample of 41 families from the three breeds using NRR within 56, 90 and 281 days after AI. Only the three QTL initially detected in Prim'Holstein were confirmed. Moreover, the analysis of NRR within 56, 90 and 281 days after AI allowed us to distinguish two FF QTL on BTA02 in Prim'Holstein, one for NRR56 and one for NRR90. Estimated QTL variance was 18%, 14%, 11.5% and 14% of the total genetic variance, respectively, for QTL mapping to BTA01, BTA02 (NRR90 and NRR56) and BTA03.     

Genome-wide linkage and QTL mapping in porcine F2 families generated from Pietrain, Meishan and Wild Boar crosses

Three informative pig F₂ families based on European Wild Boar (W), Meishan (M) and Pietrain (P) crosses have been used for genome‐wide linkage and quantitative trait loci (QTL) analysis. Altogether 129 microsatellites, 56 type I loci and 46 trait definitions (specific to growth, fattening, fat deposition, muscling, meat quality, stress resistance and body conformation) were included in the study. In the linkage maps of M × P, W × P and W × M families, average spacing of markers were 18.4, 19.7 and 18.8 cM, the numbers of informative meioses were 582, 534 and 625, and the total lengths of autosomes measured were 27.3, 26.0 and 26.2 Morgan units, respectively. Maternal maps were on average 1.3 times longer than paternal maps. QTLs contributing more than 3% of F₂ phenotypic variance could be identified at p < 0.05 chromosome‐wide level. Differences in the numbers and positions of QTLs were observed between families. Genome‐wide significant QTL effects were mapped for growth and fattening traits on eight chromosomes (1, 2, 4, 13, 14, 17, 18 and X), for fat deposition traits on seven chromosomes (1, 2, 3, 4, 6, 7 and X), for muscling traits on 11 chromosomes (1, 2, 3, 4, 6, 7, 8, 12, 14, 15 and X), for meat quality and stress resistance traits on seven chromosomes (2, 3, 6, 13, 16, 18 and X), and QTLs for body‐conformation traits were detected on 14 chromosomes. Closely correlated traits showed similar QTL profiles within families. Major QTL effects for meat quality and stress resistance traits were found on SSC6 in the interval RYR1‐A1BG in the W × P and M × P families, and could be attributed to segregation of the RYR1 allele T derived from Pietrain, whereas no effect in the corresponding SSC6 interval was found in family W × M, where Wild Boar and Meishan both contributed the RYR1 allele C. QTL positions were mostly similar in two of the three families for body conformation traits and for growth, fattening, fat deposition and muscling traits, especially on SSC4 (interval SW1073‐NGFB). QTLs with large effects were also mapped on SSC7 in the major histocompatibility complex (MHC) (interval CYP21A2‐S0102) and affected body length, weight of head and many other traits. The identification of DNA variants in genes causative for the QTLs requires further fine mapping of QTL intervals and a positional cloning. However, for these subsequent steps, the genome‐wide QTL mapping in F₂ families represents an essential starting point and is therefore significant for animal breeding.     

标记辅助选择在猪育种中应用效果的研究

本研究针对猪育种中重点考虑的窝产活仔猪数（NBA）、达100 kg体重日增重（ADG）、饲料利用率（FCR）、达100 kg体重的背膘厚（BF）、肌内脂肪含量（IMF） 5个性状,利用连锁平衡（linkage equilibrium,LE）、连锁不平衡（linkage disequilibrium,LD）标记和直接标记（direct marker,DR）3种类型的分子遗传标记,设计了3个规模不同的基础群,母猪数分别为100、200、300头,公猪数都为10头,基础群个体间无亲缘关系,育种群实施闭锁繁育。用Monte Carlo方法模拟了MAS的5个世代选择试验。育种值估计采用标准BLUP（Standard BLUP,SBLUP）模型（此育种值作为对照）、QBLUP模型（使用DR标记）、MBLUP模型（使用LD和LE标记）。结果表明,利用DR标记在各种情况下都比利用LD和LE标记获得的选择效率高;5个性状中,MAS对低遗传力、限性性状NBA的选择效率最高;当性状的QTL方差占遗传方差基本相同时,中等遗传力性状FCR的选择效率比高遗传力性状BF的更高;当性状的遗传力差异不大时,QTL方差占遗传方差比例大的性状FCR的选择效率比QTL方差占遗传方差比例小的性状ADG的更高。当利用QBLUP模型时,MAS对NBA的选择效率最高,ADG的选择效率最低。     

Fine mapping quantitative trait loci for feed intake and feed efficiency in beef cattle

Feed intake and feed efficiency are economically important traits in beef cattle because feed is the greatest variable cost in production. Feed efficiency can be measured as feed conversion ratio (FCR, intake per unit gain) or residual feed intake (RFI, measured as DMI corrected for BW and growth rate, and sometimes a measure of body composition, usually carcass fatness, RFI(bf)). The goal of this study was to fine map QTL for these traits in beef cattle using 2,194 markers on 24 autosomes. The animals used were from 20 half-sib families originating from Angus, Charolais, and University of Alberta Hybrid bulls. A mixed model with random sire and fixed QTL effect nested within sire was used to test each location (cM) along the chromosomes. Threshold levels were determined at the chromosome and genome levels using 20,000 permutations. In total, 4 QTL exceeded the genome-wise threshold of P < 0.001, 3 exceeded at P < 0.01, 17 at P < 0.05, and 30 achieved significance at the chromosome-wise threshold level (at least P < 0.05). No QTL were detected on BTA 8, 16, and 27 above the 5% chromosome-wise significance threshold for any of the traits. Nineteen chromosomes contained RFI QTL significant at the chromosome-wise level. The RFI(bf) QTL results were generally similar to those of RFI, the positions being similar, but occasionally differing in the level of significance. Compared with RFI, fewer QTL were detected for both FCR and DMI, 12 and 4 QTL, respectively, at the genome-wise thresholds. Some chromosomes contained FCR QTL, but not RFI QTL, but all DMI QTL were on chromosomes where RFI QTL were detected. The most significant QTL for RFI was located on BTA 3 at 82 cM (P = 7.60 x 10(-5)), for FCR on BTA 24 at 59 cM (P = 0.0002), and for DMI on BTA 7 at 54 cM (P = 1.38 x 10(-5)). The RFI QTL that showed the most consistent results with previous RFI QTL mapping studies were on BTA 1, 7, 18, and 19. The identification of these QTL provides a starting point to identify genes affecting feed intake and efficiency for use in marker-assisted selection and management.