Identification of quantitative trait loci affecting reproduction in pigs

The objective of this research was to identify chromosomal regions harboring QTL affecting reproduction in pigs. A three-generation resource population was developed by crossing low-indexing pigs from a randomly selected control line (C) with high-indexing pigs of a line selected for increased index of ovulation rate and embryonic survival (I). Differences between Lines I and C at Generation 10 were 6.7 ova and 3.3 fetuses at 50 d of gestation and 3.1 fully formed and 1.6 live pigs at birth. Phenotypic data were collected on F2 females, born in three replicates, for ovulation rate (n = 423), age at puberty (n = 295), litter size (n = 370), and number of nipples (n = 428). Litter-size data included number of fully formed, live, stillborn, and mummified pigs. Grandparent, F1, and F2 animals were genotyped for 151 microsatellite markers distributed across all 18 autosomes and the X chromosome. Genotypic data were available on 423 F2 females. Average spacing between markers was 19.3 Kosambi centimorgans. Calculations of logarithms of odds (LOD) scores were by least squares, and fixed effects for sire-dam combination and replicate were included in the models. Genome-wide significance level thresholds of 5% and 10% were calculated using a permutation approach. There was evidence (P < 0.05) for QTL affecting ovulation rate on SSC9, age at puberty on SSC7 and SSC8, number of nipples on SSC8 and SSC11, number of stillborn pigs on SSC5 and SSC13, and number of fully formed pigs on SSC11. There was evidence (P < 0.10) for additional QTL affecting age at puberty on SSC7, SSC8, and SSC12, number born live on SSC11, and number of nipples on SSC1, SSC6, and SSC7. Litter size is lowly heritable and sex-limited. Therefore, accuracy of selection for litter size may be enhanced by marker-assisted selection. Ovulation rate and age at puberty are laborious to measure, and thus marker-assisted selection may provide a practical and efficient method of selection.     

Identification of quantitative trait loci for osteoarthritis of hip joints in dogs

OBJECTIVE: To identify quantitative trait loci (QTL) associated with osteoarthritis (OA) of hip joints of dogs by use of a whole-genome microsatellite scan. ANIMALS: 116 founder, backcross, F1, and F2 dogs from a crossbred pedigree. PROCEDURES: Necropsy scores and an optimized set of 342 microsatellite markers were used for interval mapping by means of a combined backcross and F2 design module from an online statistical program. Breed and sex were included in the model as fixed effects. Age of dog at necropsy and body weight at 8 months of age were also included in the model as covariates. The chromosomal location at which the highest F score was obtained was considered the best estimate of a QTL position. Chromosome-wide significance thresholds were determined empirically from 10,000 permutations of marker genotypes. RESULTS: 4 chromosomes contained putative QTL for OA of hip joints in dogs at the 5% chromosome-wide significance threshold: chromosomes 5, 18, 23, and 31. CONCLUSIONS AND CLINICAL RELEVANCE: Osteoarthritis of canine hip joints is a complex disease to which many genes and environmental factors contribute. Identification of contributing QTL is a strategy to elucidate the genetic mechanisms that underlie this disease. Refinement of the putative QTL and subsequent candidate gene studies are needed to identify the genes involved in the disease process.     

Quantitative trait loci for behavioural traits in chickens

The detection of quantitative trait loci (QTL) of behavioural traits has mainly been focussed on mouse and rat. With the rapid development of molecular genetics and the statistical tools, QTL mapping for behavioural traits in farm animals is developing. In chicken, a total of 30 QTL involved in pecking-related traits, open-field behaviour, tonic immobility, response to novel objects, and response to a restraint test were detected in different studies. In the search for a useful early predictor for feather pecking (FP) behaviour in adult laying hens, the following was found: FP in young animals is not a predictor for FP in adult animals, however, open-field behaviour in young animals is genetically correlated with FP in adult hens. Before the implementation of FP behaviour or open-field behaviour in breeding programmes, it is essential to know more about the correlation between these behavioural traits and also their relationship with production traits. Nevertheless, with the QTL for behavioural traits and the chicken genome sequence in progress, a better understanding of the underlying genetic mechanisms of behavioural traits will be feasible.     

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.     

Mapping of quantitative trait loci affecting organ weights and blood variables in a broiler layer cross

1. A genome scan was performed to locate genomic regions associated with traits that are known to vary in birds (most commonly broilers) suffering from heart, lung or muscular dysfunction and for weight of the dressed carcass and some internal organs. 2. The F2 population studied was derived from a cross between a broiler and a layer line and consisted of over 460 birds that were genotyped for 101 markers. 3. There was strong support for segregation of quantitative trait loci (QTL) for carcass and organ weights and blood variables. We identified 11 genome-wide significant QTL (most of them for dressed carcass weight) and several genome-wide suggestive QTL. 4. The results point to some genome regions that may be associated with health-related traits and merit further study, with the final aim of identifying linked genetic markers that could be used in commercial breeding programmes to decrease the incidence of muscular and metabolic disorders in broiler populations.     

Identification of quantitative trait loci for carcass composition and pork quality traits in a commercial finishing cross

A QTL study for carcass composition and meat quality traits was conducted on finisher pigs of a cross between a synthetic Piétrain/Large White boar line and a commercial sow cross. The mapping population comprised 715 individuals evaluated for a total of 30 traits related to growth and fatness (4 traits), carcass composition (11 traits), and meat quality (15 traits). Offspring of 8 sires (n = 715) were used for linkage analysis and genotyped for 73 microsatellite markers covering 14 chromosomal regions representing approximately 50% of the pig genome. The regions examined were selected based on previous studies suggesting the presence of QTL affecting carcass composition or meat quality traits. Thirty-two QTL exceeding the 5% chromosome-wise significance level were identified. Among these, 5 QTL affecting 5 different traits were significant at the 1% chromosome-wise level. The greatest significance levels were found for a QTL affecting loin weight on SSC11 and a QTL with an effect on the Japanese color scale score of the loin on SSC4. About one-third of the identified QTL were in agreement with QTL previously reported. Results showed that QTL affecting carcass composition and meat quality traits segregated within commercial lines. Use of these results for marker-assisted selection offers opportunities for improving pork quality by within-line selection.     

Detection of quantitative trait loci for fat androstenone levels in pigs

A QTL analysis of fat androstenone levels from a three-generation experimental cross between Large White and Meishan pig breeds was carried out. A total of 485 F2 males grouped in 24 full-sib families, their 29 parents and 12 grandparents were typed for 137 markers distributed over the entire porcine genome. The F2 male population was measured for fat androstenone levels at 100, 120, 140, and 160 d of age and at slaughter around 80 kg liveweight. Statistical analyses were performed using two interval mapping methods: a line-cross (LC) regression method, which assumes alternative alleles are fixed in founder lines, and a half- full-sib (HFS) maximum likelihood method, where allele substitution effects were estimated within each half- and full-sib family. Both methods revealed genomewide significant gene effects on chromosomes 3, 7, and 14. The QTL explained, respectively, 7 to 11%, 11 to 15%, and 6 to 8% of phenotypic variance. Three additional significant QTL explaining 4 to 7% of variance were detected on chromosomes 4 and 9 using LC method and on chromosome 6 using HFS method. Suggestive QTL were also obtained on chromosomes 2, 10, 11, 13, and 18. Meishan alleles were associated with higher androstenone levels, except on chromosomes 7, 10, and 13, although 10 and 13 additive effects were near zero. The QTL had essentially additive effects, except on chromosomes 4, 10, and 13. No evidence of linked QTL or imprinting effects on androstenone concentration could be found across the entire porcine genome. The steroid chromosome P450 21-hydroxylase (CYP21) and cytochrome P450 cholesterol side chain cleavage subfamily XIA (CYP11A) loci were investigated as possible candidate genes for the chromosome 7 QTL. No mutation of coding sequence has been found for CYP21. Involvement of a candidate regulatory mutation of CYP11A gene proposed by others can be excluded in our animals.     

Detection of quantitative trait loci for growth and carcass composition in cattle

The objective of the present study was to detect quantitative trait loci for economically important traits in a family from a Bos indicus x Bos taurus sire. A Brahman x Hereford sire was used to develop a half-sib family (n = 547). The sire was mated to Bos taurus cows. Traits analyzed were birth (kg) and weaning weights (kg); hot carcass weight (kg); marbling score; longissimus area (cm2); USDA yield grade; estimated kidney, pelvic, and heart fat (%); fat thickness (cm); fat yield (%); and retail product yield (%). Meat tenderness was measured as Warner-Bratzler shear force (kg) at 3 and 14 d postmortem. Two hundred and thirty-eight markers were genotyped in 185 offspring. One hundred and thirty markers were used to genotype the remaining 362 offspring. A total of 312 markers were used in the final analysis. Seventy-four markers were common to both groups. Significant QTL (expected number of false-positives < 0.05) were observed for birth weight and longissimus area on chromosome 5, for longissimus area on chromosome 6, for retail product yield on chromosome 9, for birth weight on chromosome 21, and for marbling score on chromosome 23. Evidence suggesting (expected number of false-positives < 1) the presence of QTL was detected for several traits. Putative QTL for birth weight were detected on chromosomes 1, 2, and 3, and for weaning weight on chromosome 29. For hot carcass weight, QTL were detected on chromosomes 10, 18, and 29. Four QTL for yield grade were identified on chromosomes 2, 11, 14, and 19. Three QTL for fat thickness were detected on chromosomes 2, 3, 7, and 14. For marbling score, QTL were identified on chromosomes 3, 10, 14, and 27. Four QTL were identified for retail product yield on chromosomes 12, 18, 19, and 29. A QTL for estimated kidney, pelvic, and heart fat was detected on chromosome 15, and a QTL for meat tenderness measured as Warner-Bratzler shear force at 3 d postmortem was identified on chromosome 20. Two QTL were detected for meat tenderness measured as Warner-Bratzler shear force at 14 d postmortem on chromosomes 20 and 29. These results present a complete scan in all available progeny in this family. Regions underlying QTL need to be assessed in other populations.     

猪繁殖性状QTL基因定位研究进展

哺乳动物的繁殖过程包括卵泡和精子的发育成熟、排卵、受精和受精卵在母体子宫内的发育等一系列过程.在此过程中.机体通过神经内分泌系统,特别是下丘脑-垂体-卵泡轴分泌各种激素进行精确的调控.其中任何影响某一步骤的体内或体外因素.都会使动物最终的性能表现发生改变.另外,猪繁殖性状的遗传力一般都较低,如窝产仔数的平均遗传力只有0.1 0(表1)[1]     

Identification of carcass and meat quality quantitative trait loci in a Landrace pig population selected for growth and leanness

The identification of QTL related to production traits that are relevant for the pig industry has been mostly performed by using divergent crosses. The main objective of the current study was to investigate whether these growth, fatness, and meat quality QTL, previously described in diverse experimental populations, were segregating in a Landrace commercial population selected for litter size, backfat thickness, and growth performance. We have found QTL for carcass weight (posterior P > 0.75), cutlet weight (posterior P > 0.99), weight of ham (posterior P > 0.75), shoulders weight (posterior probability > 0.99), and shear firm-ness (posterior P > 0.99) on pig Chromosome 2. Moreover, QTL with posterior P > 0.75 for fat thickness between the 3rd and 4th ribs (Chromosome 7), rib weights (Chromosome 8), backfat thickness (Chromosomes 8, 9, and 10), and b Minolta color component (Chromosome 7) were identified. These results indicate that commercial purebred populations retain a significant amount of genetic variation, even for traits that have been selected for many generations.     

Transmission disequilibrium test for quantitative trait loci detection in livestock populations

The performance of several transmission disequilibrium tests (TDT) for detection of quantitative trait loci (QTL) in data structures typical of outbred livestock populations were investigated. Factorial mating designs were simulated with 10 sires mated to either 50 or 200 dams, each family having five or eight full sibs. A single marker and QTL, both bi‐allelic, were simulated using a disequilibrium coefficient based on complete initial disequilibrium and 50 generations of recombination [i.e. D = D₀(1 ? θ)⁵⁰], where θ is the recombination fraction between marker and QTL. The QTL explained either 10% (small QTL) or 30% (large QTL) of the genetic variance for a trait with heritability of 0.3. Methods were: TDT for QTL (Q‐TDT; both parents known), 1‐TDT (only one parent known) and sibling‐based TDT (S‐TDT; neither parent known, but sibs available). All were found to be effective tests for association and linkage between the QTL and a tightly linked marker (θ < 0.02) in these designs. For a large QTL, θ = 0.01, and five full sibs per family, the empirical power for Q‐TDT, 1‐TDT and S‐TDT was 0.966, 0.602 and 0.974, respectively, in a large population, versus 0.700, 0.414 and 0.654, respectively, in a small population. For a small QTL effect, θ = 0.01, large population the empirical power of these tests were 0.709, 0.287 and 0.634. The power of Q‐TDT, 1‐TDT and S‐TDT was satisfactory for large populations, for QTL with large effects and for five full sibs per family. The 1‐TDT based on a linear model was more powerful than the normal 1‐TDT. The empirical power for Q‐TDT and 1‐TDT with a linear model was 0.978 and 0.995 respectively. TDT based on analogous linear models, incorporating the polygenic covariance structure, provided only small increases in power compared with the usual TDT for QTL.     

A whole-genome scan for quantitative trait loci affecting teat number in pigs

A whole-genome scan was conducted using 132 microsatellite markers to identify chromosomal regions that have an effect on teat number. For this purpose, an experimental cross between Chinese Meishan pigs and five commercial Dutch pig lines was used. Linkage analyses were performed using interval mapping by regression under line cross models including a test for imprinting effects. The whole-genome scan revealed highly significant evidence for three quantitative trait loci (QTL) affecting teat number, of which two were imprinted. Paternally expressed (i.e., maternally imprinted) QTL were found on chromosomes 2 and 12. A Mendelian expressed QTL was found on chromosome 10. The estimated additive effects showed that, for the QTL on chromosomes 10 and 12, the Meishan allele had a positive effect on teat number, but, for the QTL on chromosome 2, the Meishan allele had a negative effect on teat number. This study shows that imprinting may play an important role in the expression of teat number.     

Identification of candidate markers on bovine chromosome 14 (BTA14) under milk production trait quantitative trait loci in Holstein

The objective of this study was to identify single-nucleotide polymorphisms using a bovine chromosome 14 high-density SNP panel after accounting for the effect of DGAT1. Linkage disequilibrium information and sire heterozygosity were used to select markers for linkage analysis on bovine chromosome 14 for milk production traits in 321 Holstein animals. Results show putative milk peaks at 42 and 61 cM, both at p<0.10, a fat yield peak at 42 and 63 cM, both at p<0.05; a protein yield peak at 42 (p<0.01) and 84 cM (p<0.05); fat per cent peaks at 3 (p<0.01) and 29 cM (p<0.05), and a protein per cent peak at 4 cM (p<0.05). Once quantitative trait loci positions were established, allele substitution effects for all markers were evaluated using the same statistical model. Overlaying information between quantitative trait loci (QTL) and allele effect analysis enabled the identification (p<0.01) of 20 SNPs under the milk yield QTL, 2 under both of the fat yield peaks, 8 and 9 under the protein yield peaks, 2 and 6 for the fat per cent peaks and 5 for the protein per cent peak. One SNP in particular, ss61514555:A>C, showed association with 3 of the 5 traits: milk (p=1.59E-04), fat (p=6.88E-05) and protein yields (p=5.76E-05). Overall, combining information from linkage disequilibrium, sire heterozygosity and genetic knowledge of traits enabled the characterization of additional markers with significant associations with milk production traits.     

Mapping of quantitative trait loci for growth and carcass traits in commercial sheep populations

Quantitative trait loci analyses were applied to data from Suffolk and Texel commercial sheep flocks in the United Kingdom. The populations comprised 489 Suffolk animals in three half-sib families and 903 Texel animals in nine half-sib families. Phenotypic data comprised measurements of live weight at 8 and 20 wk of age and ultrasonically measured fat and muscle depth at 20 wk. Lambs and their sires were genotyped across candidate regions on chromosomes 1, 2, 3, 4, 5, 6, 11, 18, and 20. Data were analyzed at the breed level, at the family level, and across extended families when families were genetically related. The breed-level analyses revealed a suggestive QTL on chromosome 1 in the Suffolk breed, between markers BM8246 and McM130, affecting muscle depth, although the effect was only significant in one of the three Suffolk families. A two-QTL analysis suggested that this effect may be due to two adjacent QTL acting in coupling. In total, 24 suggestive QTL were identified from individual family analyses. The most significant QTL affected fat depth and was segregating in a Texel family on chromosome 2, with an effect of 0.62 mm. The QTL was located around marker ILSTS030, 26 cM distal to myostatin. Two of the Suffolk and two of the Texel sires were related, and a three-generation analysis was applied across these two extended families. Seven suggestive QTL were identified in this analysis, including one that had not been detected in the individual family analysis. The most significant QTL, which affected muscle depth, was located on chromosome 18 near the callipyge and Carwell loci. Based on the phenotypic effect and location of the QTL, the data suggest that a locus similar to the Carwell locus may be segregating in the United Kingdom Texel population.     

Detection and characterization of quantitative trait loci for meat quality traits in pigs.

In an experimental cross between Meishan and Dutch Large White and Landrace lines, 785 F2 animals with carcass information and their parents were typed for molecular markers covering the entire porcine genome. Linkage was studied between these markers and eight meat quality traits. Quantitative trait locus analyses were performed using interval mapping by regression under two genetic models: 1) the line-cross approach, where the founder lines were assumed to be fixed for different QTL alleles and 2) a half-sib model where a unique allele substitution effect was fitted within each of the 38 half-sib families. The line-cross approach included tests for genomic imprinting and sex-specific QTL effects. In total, three genome-wide significant and 26 suggestive QTL were detected. The significant QTL on chromosomes 3, 4, and 13, affecting meat color, were only detected under the half-sib model. Failure of the line-cross approach to detect the meat color QTL suggests that the founder lines have similar allele frequencies for these QTL. This study provides information on new QTL affecting meat quality traits. It also shows the benefit of analyzing experimental data under different genetic and statistical models.     

Identification of quantitative trait loci affecting female reproductive traits in a multigeneration Meishan-White composite swine population.

A multigeneration crossbred Meishan-White composite resource population was used to identify quantitative trait loci (QTL) for age at first estrus (AP) and the components of litter size: ovulation rate (OR; number of ova released in an estrous period) and uterine capacity (UC). The population was established by reciprocally mating Meishan (ME) and White composite (WC) pigs. Resultant F1 females were mated to either ME or WC boars to produce backcross progeny (BC) of either 3/4 WC 1/4 ME or 1/4 WC 3/4 ME. To produce the next generation (F3), 3/4 WC 1/4 ME animals were mated to 1/4 WC 3/4 ME animals yielding half-blood (1/2 WC 1/2 ME) progeny. A final generation (F4) was produced by inter se mating F3 animals. Measurements for AP and OR were recorded on 101 BC, 389 F3, and 110 F4 gilts, and UC data were from 101 BC and 110 F4 first parity litters. A genomic scan was conducted with markers (n = 157) spaced approximately 20 cM apart. All parental, F1, BC, and F4 animals but only 84 F3 animals were genotyped and included in this study. The QTL analysis fitted a QTL at 1-cM intervals throughout the genome, and QTL effects were tested using approximate genome-wide significance levels. For OR, a significant (E[false positive] < .05) QTL was detected on chromosome 8, suggestive (E[false positive] < 1.0) QTL were detected on chromosomes 3 and 10, and two additional regions were detected that may possess a QTL (E[false positive] < 2.0) on chromosomes 9 and 15. Two regions possessed suggestive evidence for QTL affecting AP on chromosomes 1 and 10, and one suggestive region on chromosome 8 was identified for UC. Further analyses of other populations of swine are necessary to determine the extent of allelic variation at the identified QTL.     

A genome scan for quantitative trait loci and imprinted regions affecting reproduction in pigs

Quantitative trait loci for reproductive traits in a three-generation resource population of a cross between low-indexing pigs from a control line and high-indexing pigs from a line selected 10 generations for increased index of ovulation rate and embryonic survival are reported. Phenotypic data were collected in F2 females for birth weight (BWT, n = 428), weaning weight (WWT, n = 405), age at puberty (AP, n = 295), ovulation rate (OR, n = 423), number of fully formed pigs (FF, n = 370), number of pigs born alive (NBA, n = 370), number of mummified pigs (MUM, n = 370), and number of stillborn pigs (NSB, n = 370). Grandparent, F1, and F2 animals were genotyped for 151 microsatellite markers. Sixteen putative QTL (P < 0.10) for reproductive traits were identified in previous analyses of these data with single QTL line-cross models. Data were reanalyzed with multiple QTL models, including imprinting effects. Data also were analyzed with half-sib models. Permutation was used to establish genome-wide significance levels ( = 0.01, 0.05, and 0.10). Thirty-one putative QTL for reproductive traits and two QTL for birth weight were identified (P < 0.10). One Mendelian QTL for FF (P < 0.05), one for NBA (P < 0.05), three for NSB (P < 0.05), three for NN (P < 0.05), seven for AP (P < 0.10), five for MUM (P < 0.10), and one for BWT (P < 0.10) were found. Partial imprinting of QTL affecting OR (P < 0.01), BWT (P < 0.05), and MUM (P < 0.05) was detected. There were four paternally expressed QTL for NN (P < 0.10) and one each for AP (P < 0.05) and MUM (P < 0.10). Maternally expressed QTL affecting NSB (P < 0.10), NN (P < 0.10), and MUM (P < 0.10) were detected. No QTL were detected with half-sib analyses. Multiple QTL models with imprinting effects are more appropriate for analyzing F2 data than single Mendelian QTL line-cross models.     

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.     

Combined detection and introgression of quantitative trait loci underlying desirable traits

This study presents a new method that combines QTL mapping and gene introgression. The effectiveness of this method for simultaneous detection and introgression of a desirable QTL from a donor line into a recipient line was evaluated by simulation. For evaluation, we used the fourth backcross generation of 2 inbred lines. The difference between the 2 lines for the trait of interest was described entirely by 1 QTL, with the donor line carrying the superior allele. Nine scenarios, combinations of 3 heritabilities (h(2) = 0.10, 0.05, or 0.01) and 3 population sizes (N = 100, 500, or 1,000) were considered in the simulation. Selection of parents for the next backcross was based solely upon the estimated probability of carrying the superior allele after a QTL analysis. Estimates of the QTL location and allele substitution effect in most scenarios were comparable to the true values. However (with either small h(2) or N) the QTL allele substitution effect was underestimated, and location was also biased. The SE of the estimates decreased with increasing N. The retained donor chromosome segment and linkage drag were close to the expected values from other published work. In general, combined detection and introgression of genes underlying desirable traits not only saves at least 1 generation, but also it ensures that the desirable QTL is introgressed where its function is simultaneously tested in a planned environment and recipient genome structure.     

Confirmation of quantitative trait loci using a low-density single nucleotide polymorphism map for twinning and ovulation rate on bovine chromosome 5

Traditional genetic selection in cattle for traits with low heritability, such as reproduction, has had very little success. With the addition of DNA technologies to the genetic selection toolbox for livestock, the opportunity may exist to improve reproductive efficiency more rapidly in cattle. The US Meat Animal Research Center Production Efficiency Population has 9,186 twinning and 29,571 ovulation rate records for multiple generations of animals, but a significant number of these animals do not have tissue samples available for DNA genotyping. The objectives of this study were to confirm QTL for twinning and ovulation rate previously found on BTA5 and to evaluate the ability of GenoProb to predict genotypic information in a pedigree containing 16,035 animals when using genotypes for 24 SNP from 3 data sets containing 48, 724, or 2,900 animals. Marker data for 21 microsatellites on BTA5 with 297 to 3,395 animals per marker were used in conjunction with each data set of genotyped animals. Genotypic probabilities for females were used to calculate independent variables for regressions of additive, dominance, and imprinting effects. Genotypic regressions were fitted as fixed effects in a 2-trait mixed model analysis by using multiple-trait derivative-free REML. Each SNP was analyzed individually, followed by backward selection fitting all individually significant SNP simultaneously and then removing the least significant SNP until only significant SNP were left. Five significant SNP associations were detected for twinning rate and 3 were detected for ovulation rate. Two of these SNP, 1 for each trait, were significant for imprinting. Additional modeling of paternal and maternal allelic effects confirmed the initial results of imprinting done by contrasting heterozygotes. These results are supported by comparative mapping of mouse and human imprinted genes to this region of bovine chromosome 5.