The number of loci that affect milk production traits in dairy cattle

We have used the results of an experiment mapping quantitative trait loci (QTL) affecting milk yield and composition to estimate the total number of QTL affecting these traits. We did this by estimating the number of segregating QTL within a half-sib daughter design using logic similar to that used to estimate the "false discovery rate" (FDR). In a half-sib daughter design with six sire families we estimate that the average sire was heterozygous for approximately 5 QTL per trait. Also, in most cases only one sire was heterozygous for any one QTL; therefore at least 30 QTL were likely to be segregating for these milk production traits in this Holstein population.     

A search for quantitative trait loci for milk production traits on chromosome 6 in Finnish Ayrshire cattle

Cattle chromosome 6 was scanned with 11 markers, ten microsatellites and the casein haplotype, to identify quantitative trait loci (QTLs) affecting the following milk production traits: milk yield, fat percentage, fat yield, protein percentage and protein yield. Twelve Finnish Ayrshire half-sib families with a total of 480 sons were genotyped and used in a grand-daughter design. Interval mapping was performed with a multiple-marker regression approach with a one-QTL and a two-QTL model, and the significance threshold values were determined empirically using a permutation test. Across-family analysis with the one-QTL model revealed an effect on protein percentage (P < 0.05) and on milk yield (P < 0.05). The analysis with the two-QTL model identified significant effects (P < 0.05) on protein percentage, milk yield, and fat yield. Comparing these two cases, the results suggest the existence of two QTLs on chromosome 6 with an effect on milk production traits. One of the QTLs was located around the casein genes. As the other QTL was similar in location and effect to a QTL found previously in Holstein-Friesians, an identity-by-descent approach could be applied to fine map this region.     

Detection of loci affecting milk production and health traits in an elite US Holstein population using microsatellite markers

Quantitative trait loci (QTL) affecting health and milk production traits were studied in seven large half-sib US Holstein families by using the granddaughter design. Genotyping for 16 markers was completed and marker allele differences within and pooled-across families were analysed. Potential QTL were identified for somatic cell score (SCS), fat yield, fat percentage, protein yield and protein percentage. Three markers (BM203, BM4505 and BM2078) were associated with significant effects for different traits and, after further analysis, may be useful in marker-assisted selection in specific families. Comparisons between these data and previously identified QTL support the location of a QTL for milk yield and protein yield on chromosome 21.     

Mapping of QTL for Body Conformation and Behavior in Cattle

Genome scans for quantitative trait loci (QTL) in farm animals have concentrated on primary production and health traits, and information on QTL for other important traits is rare. We performed a whole genome scan in a granddaughter design to detect QTL affecting body conformation and behavior in dairy cattle. The analysis included 16 paternal half-sib families of the Holstein breed with 872 sons and 264 genetic markers. The markers were distributed across all 29 autosomes and the pseudoautosomal region of the sex chromosomes with average intervals of 13.9 cM and covering an estimated 3155.5 cM. All families were analyzed jointly for 22 traits using multimarker regression and significance thresholds determined empirically by permutation. QTL that exceeded the experiment-wise significance threshold (5% level) were detected on chromosome 6 for foot angle, teat placement, and udder depth, and on chromosome 29 for temperament. QTL approaching experiment-wise significance (10% level) were located on chromosome 6 for general quality of feet and legs and general quality of udder, on chromosome 13 for teat length, on chromosome 23 for general quality of feet and legs, and on chromosome 29 for milking speed. An additional 51 QTL significant at the 5% chromosome-wise level were distributed over 21 chromosomes. This study provides the first evidence for QTL involved in behavior of dairy cattle and identifies QTL for udder conformation on chromosome 6 that could form the basis of recently reported QTL for clinical mastitis.     

Mapping of quantitative trait loci for flesh colour and growth traits in Atlantic salmon (Salmo salar)

Background

Flesh colour and growth related traits in salmonids are both commercially important and of great interest from a physiological and evolutionary perspective. The aim of this study was to identify quantitative trait loci (QTL) affecting flesh colour and growth related traits in an F2 population derived from an isolated, landlocked wild population in Norway (Byglands Bleke) and a commercial production population.

Methods

One hundred and twenty-eight informative microsatellite loci distributed across all 29 linkage groups in Atlantic salmon were genotyped in individuals from four F2 families that were selected from the ends of the flesh colour distribution. Genotyping of 23 additional loci and two additional families was performed on a number of linkage groups harbouring putative QTL. QTL analysis was performed using a line-cross model assuming fixation of alternate QTL alleles and a half-sib model with no assumptions about the number and frequency of QTL alleles in the founder populations.

Results

A moderate to strong phenotypic correlation was found between colour, length and weight traits. In total, 13 genome-wide significant QTL were detected for all traits using the line-cross model, including three genome-wide significant QTL for flesh colour (Chr 6, Chr 26 and Chr 4). In addition, 32 suggestive QTL were detected (chromosome-wide P < 0.05). Using the half-sib model, six genome-wide significant QTL were detected for all traits, including two for flesh colour (Chr 26 and Chr 4) and 41 suggestive QTL were detected (chromosome-wide P < 0.05). Based on the half-sib analysis, these two genome-wide significant QTL for flesh colour explained 24% of the phenotypic variance for this trait.

Conclusions

A large number of significant and suggestive QTL for flesh colour and growth traits were found in an F2 population of Atlantic salmon. Chr 26 and Chr 4 presented the strongest evidence for significant QTL affecting flesh colour, while Chr 10, Chr 5, and Chr 4 presented the strongest evidence for significant QTL affecting growth traits (length and weight). These QTL could be strong candidates for use in marker-assisted selection and provide a starting point for further characterisation of the genetic components underlying flesh colour and growth.     

Fine-mapping QTL for mastitis resistance on BTA9 in three Nordic red cattle breeds

A QTL affecting clinical mastitis and/or somatic cell score (SCS) has been reported previously on chromosome 9 from studies in 16 families from the Swedish Red and White (SRB), Finnish Ayrshire (FA) and Danish Red (DR) breeds. In order to refine the QTL location, 67 markers were genotyped over the whole chromosome in the 16 original families and 18 additional half-sib families. This enabled linkage disequilibrium information to be used in the analysis. Data were analysed by an approach that combines information from linkage and linkage disequilibrium, which allowed the QTL affecting clinical mastitis to be mapped to a small interval (<1 cM) between the markers BM4208 and INRA084 . This QTL showed a pleiotropic effect on SCS in the DR and SRB breeds. Haplotypes associated with variations in mastitis resistance were identified. The haplotypes were predictive in the general population and can be used in marker-assisted selection. Pleiotropic effects of the mastitis QTL were studied for three milk production traits and eight udder conformation traits. This QTL was also associated with yield traits in DR but not in FA or SRB. No QTL were found for udder conformation traits on chromosome 9.     

A genome scan for quantitative trait loci affecting resistance to Trichostrongylus colubriformis in sheep

A genome linkage scan was carried out using a resource flock of 1029 sheep in six half-sib families. The families were offspring of sires derived by crossing divergent lines of sheep selected for response to challenge with the intestinal parasitic nematode Trichostrongylus colubriformis. All animals in the resource flock were phenotypically assessed for worm resistance soon after weaning using a vaccination/challenge regime. After correcting for fixed effects using a least squares linear model the faecal egg count data obtained following the first challenge and the faecal egg count data obtained after the second challenge were designated Trait 1 and Trait 2, respectively. A total of 472 lambs drawn from the phenotypic extremes of the Trait 2 faecal egg count distribution were genotyped with a panel of 133 microsatellite markers covering all 26 sheep autosomes. Detection of quantitative trait loci (QTL) for each of the faecal egg count traits was determined using interval analysis with the Animap program with recombination rates between markers derived from an existing marker map. No chromosomal regions attained genome-wide significance for QTL influencing either of the traits. However, one region attained chromosome-wide significance and five other regions attained point-wise significance for the presence of QTL affecting parasite resistance.     

利用微卫星进行奶牛数量性状基因位点定位的研究

采用孙女设计法对德国奶牛的３个数量必状－－产奶量、乳脂产量及乳蛋白产量进行了数量性状基因位点的定位研究。实验共有２０个父系半同胞家系的１１３０头种公牛,共测定了３０对染色体上的２２９个微卫星,表型性状的育种值由孙代母牛估计得到。连锁分析采用多重遗传标记回归法,临界Ｆ值由置换实验法计算得到。统计发现在某些染色体上存在着一些显著的ＱＴＬ＇ｓ区域,特别是１４号染色体上某一区域对所有３个产奶性状都有极显著     

QTL mapping in outbred half-sib families using Bayesian model selection

In this article, we propose a model selection method, the Bayesian composite model space approach, to map quantitative trait loci (QTL) in a half-sib population for continuous and binary traits. In our method, the identity-by-descent-based variance component model is used. To demonstrate the performance of this model, the method was applied to map QTL underlying production traits on BTA6 in a Chinese half-sib dairy cattle population. A total of four QTLs were detected, whereas only one QTL was identified using the traditional least square (LS) method. We also conducted two simulation experiments to validate the efficiency of our method. The results suggest that the proposed method based on a multiple-QTL model is efficient in mapping multiple QTL for an outbred half-sib population and is more powerful than the LS method based on a single-QTL model.     

Quantitative trait loci underlying milk production traits in sheep

Improvement of milk production traits in dairy sheep is required to increase the competitiveness of the industry and to maintain the production of high quality cheese in regions of Mediterranean countries with less favourable conditions. Additional improvement over classical selection could be reached if genes with significant effects on the relevant traits were specifically targeted by selection. However, so far, few studies have been undertaken to detect quantitative trait loci (QTL) in dairy sheep. In this study, we present a complete genome scan performed in a commercial population of Spanish Churra sheep to identify chromosomal regions associated with phenotypic variation observed in milk production traits. Eleven half-sib families, including a total of 1213 ewes, were analysed following a daughter design. Genome-wise multi-marker regression analysis revealed a genome-wise significant QTL for milk protein percentage on chromosome 3. Eight other regions, localized on chromosomes 1, 2, 20, 23 and 25, showed suggestive significant linkage associations with some of the analysed traits. To our knowledge, this study represents the first complete genome scan for milk production traits reported in dairy sheep. The experiment described here shows that analysis of commercial dairy sheep populations has the potential to increase our understanding of the genetic determinants of complex production-related traits.     

A quantitative trait locus for live weight maps to bovine Chromosome 23

A multiple-marker mapping approach was used to search for quantitative trait loci (QTLs) affecting production, health, and fertility traits in Finnish Ayrshire dairy cattle. As part of a whole-genome scan, altogether 469 bulls were genotyped for six microsatellite loci in 12 families on Chromosome (Chr) 23. Both multiple-marker interval mapping with regression and maximum-likelihood methods were applied with a granddaughter design. Eighteen traits, belonging to 11 trait groups, were included in the analysis. One QTL exceeded experiment level and one QTL genome level significance thresholds. Across-families analysis provided strong evidence (P_experiment= 0.0314) for a QTL affecting live weight. The QTL for live weight maps between markers BM1258 and BoLA DRBP1. A QTL significant at genome level (P_genome= 0.0087) was mapped for veterinary treatment, and the putative QTL probably affects susceptibility to milk fever or ketosis. In addition, three traits exceeded the chromosome 5% significance threshold: protein percentage of milk, calf mortality (sire), and milking speed. In within-family analyses, protein percentage was associated with markers in one family (LOD score = 4.5). Received: 14 December 1998 / Accepted: 28 March 1998     

Combined analysis of data from two granddaughter designs: A simple strategy for QTL confirmation and increasing experimental power in dairy cattle

A joint analysis of five paternal half-sib Holstein families that were part of two different granddaughter designs (ADR- or Inra-design) was carried out for five milk production traits and somatic cell score in order to conduct a QTL confirmation study and to increase the experimental power. Data were exchanged in a coded and standardised form. The combined data set (JOINT-design) consisted of on average 231 sires per grandsire. Genetic maps were calculated for 133 markers distributed over nine chromosomes. QTL analyses were performed separately for each design and each trait. The results revealed QTL for milk production on chromosome 14, for milk yield on chromosome 5, and for fat content on chromosome 19 in both the ADR- and the Inra-design (confirmed within this study). Some QTL could only be mapped in either the ADR- or in the Inra-design (not confirmed within this study). Additional QTL previously undetected in the single designs were mapped in the JOINT-design for fat yield (chromosome 19 and 26), protein yield (chromosome 26), protein content (chromosome 5), and somatic cell score (chromosome 2 and 19) with genomewide significance. This study demonstrated the potential benefits of a combined analysis of data from different granddaughter designs.     

QTL for mohair traits in South African Angora goats

The aim of this study was to identify QTL associated with mohair production and quality traits in South African Angora goats. Limited research has been performed on QTL influencing the economically important mohair traits of Angora goats. Twelve half-sib Angora goat families with an average of 58 offspring per sire were genotyped for 88 microsatellites covering 22 autosomes. Phenotypic data was collected at second and third shearing for males and females respectively. A linkage analysis was performed under the half-sib model using the least squared regression approach of GridQTL. Three putative QTL were detected for fleece weight on CHI 2, 5 and 24, which corresponds with the locations of keratin and keratin-associated proteins. This study detected two putative QTL associated with mohair fibre diameter (on CHI 4 and 24, respectively), which is the most important price-determining trait. Four QTL were detected on CHI 8, 13, 18 and 20 which influence both comfort factor and spinning fineness. The variance explained by the QTL ranged between 6.9% for fibre diameter and 33.6% for standard deviation along the length of the staple. These results reveal segregation of QTL influencing mohair production and quality, and contribute to the understanding of the genetic variation of mohair traits.     

QTL affecting fleece traits in Angora goats

With the aim to detect chromosome segment (quantitative traits loci, QTL) affecting fleece traits in Angora goats, a genome scan using 76 microsatellite markers spanning 1261 cM on 21 chromosomes was conducted. Eight paternal half-sib families were used, which included a total of 288 kids from a dispersed nucleus herd.Mid-side mohair samples were taken from kids at 4 months of age and eight phenotypic fleece traits were measured.We found putatives QTL for coefficient of variation of average fiber diameter (CVAFD) in chromosome 1 and 13, for kemp fiber (KEMP) in chromosome 5 and for discontinuous medullated fibers (DISC) and staple length (SL) in chromosome 2.These results demonstrate the segregation of quantitative traits involved in mohair production. Further studies will concentrate on these regions to characterize the variation of these QTL.     

Segregation of QTL for production traits in commercial meat-type chickens

This study investigated whether quantitative trait loci (QTL) identified in experimental crosses of chickens provide a short cut to the identification of QTL in commercial populations. A commercial population of broilers was targeted for chromosomal regions in which QTL for traits associated with meat production have previously been detected in extreme crosses. A three-generation design, consisting of 15 grandsires, 608 half-sib hens and over 15 000 third-generation offspring, was implemented within the existing breeding scheme of a broiler breeding company. The first two generations were typed for 52 microsatellite markers spanning regions of nine chicken chromosomes and covering a total of 730 cM, approximately one-fifth of the chicken genome. Using half-sib analyses with a multiple QTL model, linkage was studied between these regions and 17 growth and carcass traits. Out of 153 trait x region comparisons, 53 QTL exceeded the threshold for genome-wide significance while an additional 23 QTL were significant at the nominal 1% level. Many of the QTL affect the carcass proportions and feed intake, for which there are few published studies. Given intensive selection for efficient growth in broilers for more than 50 generations it is surprising that many QTL affecting these traits are still segregating. Future fine-mapping efforts could elucidate whether ancestral mutations are still segregating as a result of pleiotropic effects on fitness traits or whether this variation is due to new mutations.     

QTL analysis of body weight and conformation score in commercial broiler chickens using variance component and half-sib analyses

The aim of the study was to investigate quantitative trait loci (QTL) in previously identified regions of chicken chromosomes 1, 4 and 5 relating to 40-day body weights and conformation scores. Half-sib (HS) and variance component analyses were implemented and compared using QTL Express software. Data were from a two-generation design and consisted of 100 dam families nested in 46 sire families with trait values for 2,708 offspring. Chicken chromosome 4 showed nominal significance for QTL affecting body weight and conformation, and linkage was confirmed for both traits on chromosome 5. Results varied according to method of analysis and with common parent in the HS method.     

QTL affecting conformation traits in Angora goats

A genomic screen for quantitative trait loci (QTL) affecting conformation traits was performed by genotyping 288 Angora goats offspring from 8 half-sub families with 76 microsatellite markers. The following traits were recorded: weaning weight (WW, Kg); stature (S, cm); chest depth (CD, cm); shoulder width (SW, cm); rump length (RL, cm); rump width (RW, cm); head length (HL, cm); head width (HW, cm); shin circumference (SC, cm); chest circumference (CC, cm) and body length (BL, cm). Data were analyzed using the QTL Express program. A total of 5 QTL were detected in five chromosomes with chromosome wide significance level. For the 11 analysed traits the results were: evidence of two possible QTL for HL were found in chromosomes 1 and 4, a putative QTL for trait CD was found in chromosome 2, evidence for BL was found in chromosome 8 and a possible QTL was found for trait CC in chromosome 9. The results reported here show the existence of chromosomal regions in Angora goats involved in conformation traits and represent the first in depth search in some specific-genome sections in order to identify and characterize the genetic variability involved in these traits.     

Modelling QTL effect on BTA06 using random regression test day models

In statistical models, a quantitative trait locus (QTL) effect has been incorporated either as a fixed or as a random term, but, up to now, it has been mainly considered as a time-independent variable. However, for traits recorded repeatedly, it is very interesting to investigate the variation of QTL over time. The major goal of this study was to estimate the position and effect of QTL for milk, fat, protein yields and for somatic cell score based on test day records, while testing whether the effects are constant or variable throughout lactation. The analysed data consisted of 23 paternal half-sib families (716 daughters of 23 sires) of Chinese Holstein-Friesian cattle genotyped at 14 microsatellites located in the area of the casein loci on BTA6. A sequence of three models was used: (i) a lactation model, (ii) a random regression model with a QTL constant in time and (iii) a random regression model with a QTL variable in time. The results showed that, for each production trait, at least one significant QTL exists. For milk and protein yields, the QTL effect was variable in time, while for fat yield, each of the three models resulted in a significant QTL effect. When a QTL is incorporated into a model as a constant over time, its effect is averaged over lactation stages and may, thereby, be difficult or even impossible to be detected. Our results showed that, in such a situation, only a longitudinal model is able to identify loci significantly influencing trait variation.     

Detection of QTL for milk production traits in cattle by application of a specifically developed marker map of BTA6

Interval mapping was carried out to identify quantitative trait loci (QTL) for milk production traits in five granddaughter design families of the German Holstein population. Fourteen randomly generated markers spanning the whole of BTA6 and six targeted microsatellite markers from BTA6q21-31 were included in the analysis. In one family a QTL with effects on milk fat yield and milk protein yield was mapped to the interval TGLA37-FBN13 (3 CM proximal to FBN13, lodscore 3.22) in the middle part of the chromosome. Although there are several reports about QTL with effects on milk production traits on BTA6 in the literature, a QTL with effects on milk fat and milk protein yield has not been previously described.     

Genome wide association studies for milk production traits in Chinese Holstein population

Genome-wide association studies (GWAS) based on high throughput SNP genotyping technologies open a broad avenue for exploring genes associated with milk production traits in dairy cattle. Motivated by pinpointing novel quantitative trait nucleotide (QTN) across Bos Taurus genome, the present study is to perform GWAS to identify genes affecting milk production traits using current state-of-the-art SNP genotyping technology, i.e., the Illumina BovineSNP50 BeadChip. In the analyses, the five most commonly evaluated milk production traits are involved, including milk yield (MY), milk fat yield (FY), milk protein yield (PY), milk fat percentage (FP) and milk protein percentage (PP). Estimated breeding values (EBVs) of 2,093 daughters from 14 paternal half-sib families are considered as phenotypes within the framework of a daughter design. Association tests between each trait and the 54K SNPs are achieved via two different analysis approaches, a paternal transmission disequilibrium test (TDT)-based approach (L1-TDT) and a mixed model based regression analysis (MMRA). In total, 105 SNPs were detected to be significantly associated genome-wise with one or multiple milk production traits. Of the 105 SNPs, 38 were commonly detected by both methods, while four and 63 were solely detected by L1-TDT and MMRA, respectively. The majority (86 out of 105) of the significant SNPs is located within the reported QTL regions and some are within or close to the reported candidate genes. In particular, two SNPs, ARS-BFGL-NGS-4939 and BFGL-NGS-118998, are located close to the DGAT1 gene (160bp apart) and within the GHR gene, respectively. Our findings herein not only provide confirmatory evidences for previously findings, but also explore a suite of novel SNPs associated with milk production traits, and thus form a solid basis for eventually unraveling the causal mutations for milk production traits in dairy cattle.