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D J de Koning

Publications and source records attributed to D J de Koning.

At least 19 recordsLinked to original sources

Genetical genomics in livestock: potentials and pitfalls.

Genetical genomics combines gene mapping and gene expression approaches to identify loci controlling gene expression (eQTLs) that may underlie functional trait variation. The combination of genomic tools has great potential to facilitate dissection of complex traits, but studies need careful design and interpretation. Here we explore both the potential and the pitfalls of this approach with illustrations from actual studies. There are now an appreciable number of studies in model species and even humans demonstrating the feasibility of genetical genomics. However, most studies are too limited in size and design to unlock the full potential of the approach. Limited statistical power of studies exacerbates the problem of detection of false-positive eQTL and some reported results should be interpreted with caution. As one approach to more successful implementation of genetical genomics, we propose to combine expression studies with fine mapping of functional trait loci. This synergistic approach facilitates the implementation of genetical genomics for species without inbred resources but is equally applicable to model species. These properties make it particularly suitable for livestock populations where many QTL are already in the public domain and potentially very large pedigreed populations can be accessed.

Animals↗

Quantitative trait Loci for health traits in Finnish Ayrshire cattle.

A whole-genome scan was conducted to search for quantitative trait loci (QTL) affecting health traits in Finnish Ayrshire dairy cattle. The mapping population consisted of 12 bulls and their 491 sons in a granddaughter design. A total of 150 markers were typed covering all 29 autosomes. The traits under study were somatic cell score, mastitis, and a group of other veterinary treatments. Effects of the QTL and positions were estimated with the regression method. When carrying out interval mapping on each chromosome, cofactors were used to adjust for QTL identified at other chromosomes. Empirical P-values were obtained by permutation. Altogether 17 QTL were detected with genomewise significant P-values in the across family analysis. Quantitative trait loci affecting SCS were identified on chromosomes 1, 3, 11, 18, 21, 24, 27, 29, and QTL for mastitis on chromosomes 14, 18. Quantitative trait loci for other veterinary treatments were found on chromosomes 1, 2, 5, 8, 15, 22, and 23. The allele substitution effects were from 0.5 to 1.7 genetic standard deviations. The positions of these health QTL did not overlap with milk QTL detected in previous studies of the same population.

Animals↗

Quantitative trait locus detection in commercial broiler lines using candidate regions.

A QTL that explained a large proportion of the phenotypic difference between broiler and layer chickens in an experimental cross was evaluated in a commercial broiler line. A three-generation design, consisting of 15 grandsires, 608 half-sib hens, and more than 50,000 third-generation offspring, was implemented within the existing breeding scheme of a broiler breeding company. Four markers from a candidate region on chicken chromosome 4 were selected for their informativeness in the grandsires and used to genotype the first two generations. Using half-sib analyses, linkage was studied between these markers and 13 growth and carcass traits. The QTL analyses confirmed the presence of significant QTL for body weight (P < 0.01) and residual feed intake (P < 0.05) on chicken chromosome 4. Furthermore, evidence was found for QTL affecting the relative weight of bone and muscle in the thigh. Four more markers were added to increase resolution of the QTL positions. This increased the significance of the QTL for body weight (P < 0.001) and residual feed intake (P < 0.01) and showed evidence (P < 0.05) for additional QTL affecting carcass weight and conformation score. This study showed for the first time that a QTL that explains differences between broilers and layers was segregating in lines that have been selected for body weight over 50 generations. A possible explanation could be a pleiotropic or closely linked effect on fitness-related traits that are not part of the present study. The results demonstrate the feasibility of QTL detection and the potential for marker-assisted selection within a commercial broiler line without altering the existing breeding scheme.

Animals↗

Full pedigree quantitative trait locus analysis in commercial pigs using variance components.

In commercial livestock populations, QTL detection methods often use existing half-sib family structures and ignore additional relationships within and between families. We reanalyzed the data from a large QTL confirmation experiment with 10 pig lines and 10 chromosome regions using identity-by-descent (IBD) scores and variance component analyses. The IBD scores were obtained using a Monte Carlo Markov Chain method, as implemented in the LOKI software, and were used to model a putative QTL in a mixed animal model. The analyses revealed 61 QTL at a nominal 5% level (out of 650 tests). Twenty-seven QTL mapped to areas where QTL have been reported, and eight of these exceeded the threshold to claim confirmed linkage (P < 0.01). Forty-two of the putative QTL were detected previously using half-sib analyses, whereas 46 QTL previously identified by half-sib analyses could not be confirmed using the variance component approach. Some of the differences could be traced back to the underlying assumptions between the two methods. Using a deterministic approach to estimate IBD scores on a subset of the data gave very similar results to LOKI. We have demonstrated the feasibility of applying variance component QTL analysis to a large amount of data, equivalent to a genome scan. In many situations, the deterministic IBD approach offers a fast alternative to LOKI.

Analysis of Variance↗

Quantitative trait loci affecting milk production traits in Finnish Ayrshire dairy cattle.

A whole genome scan of Finnish Ayrshire was conducted to map quantitative trait loci (QTL) affecting milk production. The analysis included 12 half-sib families containing a total of 494 bulls in a granddaughter design. The families were genotyped with 150 markers to construct a 2764 cM (Haldane) male linkage map. In this study interval mapping with multiple-marker regression approach was extended to analyse multiple chromosomes simultaneously. The method uses identified QTL on other chromosomes as cofactors to increase mapping power. The existence of multiple QTL on the same linkage group was also analyzed by fitting a two-QTL model to the analysis. Empirical values for chromosome-wise significance thresholds were determined using a permutation test. Two genome-wise significant QTL were identified when chromosomes were analyzed individually, one affecting fat percentage on chromosome (BTA) 14 and another affecting fat yield on BTA12. The cofactor analysis revealed in total 31 genome-wise significant QTL. The result of two-QTL analysis suggests the existence of two QTL for fat percentage on BTA3. In general, most of the identified QTL confirm results from previous studies of Holstein-Friesian cattle. A new QTL for all yield components was identified on BTA12 in Finnish Ayrshire.

Animals↗

Mapping of quantitative trait loci affecting quality and production traits in egg layers.

A mapping population segregating for egg quality traits was created by a line cross between two egg layer lines and screened by a genome scan. The F2 generation consisted of 307 hens, which were scored for egg quality and production traits. The mapping population was genotyped for 99 microsatellite loci, spanning nine macrochromosomes and five small linkage groups. The linkage maps were used in mapping QTL affecting 14 traits, by using multiple markers and a least-squares approach. We detected 14 genomewide significant and six suggestive QTL that were located on chromosomes 2, 3, 4, 5, and, 8 and sex chromosome Z. A significant QTL affecting egg white thinning was found on chromosome 2. For eggshell strength, a significant QTL was found on chromosome Z. For production traits, the most interesting area was on chromosome 4, where highly significant QTL effects were detected for BW, egg weight, and feed intake in the same area. The most significant QTL explains 25.8% of the phenotypic variance in F2 of body weight. An area affecting the age at first egg, egg weight, and the number of eggs was located on chromosome Z.

Animals↗

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.

Alleles↗

Mapping of multiple quantitative trait loci by simple regression in half-sib designs.

Detection of QTL in outbred half-sib family structures has mainly been based on interval mapping of single QTL on individual chromosomes. Methods to account for linked and unlinked QTL have been developed, but most of them are only applicable in designs with inbred species or pose great demands on computing facilities. This study describes a strategy that allows for rapid analysis, involving multiple QTL, of complete genomes. The methods combine information from individual analyses after which trait scores for a specific linkage group are adjusted for identified QTL at other linkage groups. Regression methods are used to estimate QTL positions and effects; permutation tests are used to obtain empirical threshold values. The description of the methods is complemented by an example of the combined analysis of 28 bovine chromosomes and their associations with milk yield in Finnish Ayrshire cattle. In this example, the individual analysis revealed five suggestive QTL affecting milk yield. Following the strategy presented in this paper, the final combined analysis showed eight significant QTL affecting milk yield. This clearly demonstrates the potential gain of using the combined analysis. The use of regression methods, with low demands on computing resources, makes this approach very practical for total genome scans.

Animals↗

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.

Animals↗

Genome-wide scan for body composition in pigs reveals important role of imprinting.

The role of imprinting in body composition was investigated in an experimental cross between Chinese Meishan pigs and commercial Dutch pigs. A whole-genome scan revealed significant evidence for five quantitative trait loci (QTL) affecting body composition, of which four were imprinted. Imprinting was tested with a statistical model that separated the expression of paternally and maternally inherited alleles. For back fat thickness, a paternally expressed QTL was found on Sus scrofa chromosome 2 (SSC2), and a Mendelian-expressed QTL was found on SSC7. In the same region of SSC7, a maternally expressed QTL affecting muscle depth was found. Chromosome 6 harbored a maternally expressed QTL on the short arm and a paternally expressed QTL on the long arm, both affecting intramuscular fat content. The individual QTL explained from 2% up to 10% of the phenotypic variance. The known homologies to human and mouse did not reveal positional candidate genes. This study demonstrates that testing for imprinting should become a standard procedure to unravel the genetic control of multifactorial traits.

Adipose Tissue↗

Combined analyses of data from quantitative trait loci mapping studies. Chromosome 4 effects on porcine growth and fatness.

For many species several similar QTL mapping populations have been produced and analyzed independently. Joint analysis of such data could be used to increase power to detect QTL and evaluate population differences. In this study, data were collated on almost 3000 pigs from seven different F(2) crosses between Western commercial breeds and either the European wild boar or the Chinese Meishan breed. Genotypes were available for 31 markers on chromosome 4 (on average 8.3 markers per population). Data from three traits common to all populations (birth weight, mean backfat depth at slaughter or end of test, and growth rate from birth to slaughter or end of test) were analyzed for individual populations and jointly. A QTL influencing birth weight was detected in one individual population and in the combined data, with no significant interaction of the QTL effect with population. A QTL affecting backfat that had a significantly greater effect in wild boar than in Meishan crosses was detected. Some evidence for a QTL affecting growth rate was detected in all populations, with no significant differences between populations. This study is the largest F(2) QTL analysis achieved in a livestock species and demonstrates the potential of joint analysis.

Adipose Tissue↗

The effect of adipocyte and heart fatty acid-binding protein genes on intramuscular fat and backfat content in Meishan crossbred pigs.

Effects of genetic variation in porcine adipocyte and heart fatty acid-binding protein genes, A-FABP and H-FABP, respectively, on intramuscular fat (IMF) content and backfat thickness (BFT) were examined in F2 crossbreds of Meishan and Western pigs. The involvement of each FABP gene in IMF accretion was studied to confirm previous results for Duroc pigs. The F2 crossbred pigs were genotyped for various markers including microsatellite sequences situated within both FABP genes. Linkage analysis assigned the A-FABP and H-FABP genes to marker intervals S0001-S0217 (20 cM) on SSC4 and Sw316-S0003 (16.6 cM) on SSC6, respectively, refining previous chromosomal assignments. Next, the role of both chromosome regions/genes on genetic variation in IMF content and BFT was studied by 1) screening SSC4 and SSC6 for QTL affecting both traits by performing a line-cross analysis and 2) estimation of the effect of individual A-FABP and H-FABP alleles on both traits. In the first analysis, suggestive and chromosome-wise significant evidence for a QTL affecting IMF was detected on SSC6. The H-FABP gene is a candidate gene for this effect because it resides within the large region containing this putative QTL. The second analysis showed a considerable but nonsignificant effect of H-FABP microsatellite alleles on IMF content. Suggestive evidence for a QTL affecting BFT was found on SSC6, but H-FABP was excluded as a candidate gene. In conclusion, present and previous results support involvement of H-FABP gene polymorphisms in IMF accretion independently from BFT in pigs. Therefore, implementation of these polymorphisms in marker-assisted selection to control IMF content independently from BFT may be considered. In contrast to previous findings for Duroc pigs, no evidence was found for an effect of the A-FABP gene on IMF or BFT in this population.

Adipocytes↗

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).

Alleles↗

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.

Animals↗

Detection of quantitative trait loci for backfat thickness and intramuscular fat content in pigs (Sus scrofa).

In an experimental cross between Meishan and Dutch Large White and Landrace lines, 619 F(2) animals and their parents were typed for molecular markers covering the entire porcine genome. Associations were studied between these markers and two fatness traits: intramuscular fat content and backfat thickness. Association analyses were performed using interval mapping by regression under two genetic models: (1) an outbred line-cross model 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 19 half-sib families. Both approaches revealed for backfat thickness a highly significant QTL on chromosome 7 and suggestive evidence for a QTL at chromosome 2. Furthermore, suggestive QTL affecting backfat thickness were detected on chromosomes 1 and 6 under the line-cross model. For intramuscular fat content the line-cross approach showed suggestive evidence for QTL on chromosomes 2, 4, and 6, whereas the half-sib analysis showed suggestive linkage for chromosomes 4 and 7. The nature of the QTL effects and assumptions underlying both models could explain discrepancies between the findings under the two models. It is concluded that both approaches can complement each other in the analysis of data from outbred line crosses.

Adipose Tissue↗

Developing microsatellite markers from cDNA: a tool for adding expressed sequence tags to the genetic linkage map of the chicken.

A chicken embryonic cDNA library was screened with a (TG)13 probe in order to develop polymorphic microsatellite markers. The redundancy of the embryonic cDNA library with a chicken brain cDNA library, which was used for microsatellite development in a previous study, was extremely high. Of the 300 (TG)13 positive clones, only 80 were unique for the embryonic cDNA library. Still, nine expressed sequences derived from the embryonic cDNA library were mapped in the Wageningen (WAU) resource population. In addition seven microsatellite markers from the chicken brain cDNA library, which were monomorphic or unlinked in the two international reference families in the previous study, were also mapped in the WAU population. Three of the 16 mapped chicken expressed sequence tags (ESTs) showed relatively high percentages of sequence similarity to sequences found in other species. As two of these genes, RAB6 and ZFX/ZFY, have been mapped in humans, they contribute to the comparative map of the chicken.

Animals↗

Mapping of serum amylase-1 and quantitative trait loci for milk production traits to cattle chromosome 4.

The present study was undertaken to confirm and refine the mapping of a quantitative trait locus in cattle for milk fat percentage that had earlier been reported to be linked to the serum amylase-1 locus, AM1. Five half-sib families from the previous study and 7 new ones were genotyped for nine microsatellite markers spanning chromosome 4. AM1 was mapped between the microsatellite markers BMS648 and BR6303. In a granddaughter design, interval mapping based on multiple-marker regression was utilized for an analysis of five milk production traits: milk yield, fat percentage and yield, and protein percentage and yield. In the families reported on previously, significant effects for fat and protein percentages were detected. In the new families, an effect on milk and fat yields was found. The most likely positions of the quantitative trait locus in both groups of families were in the same area of chromosome 4 in the vicinity of the obese locus. Direct effects of the obese locus were tested for using polymorphism in two closely linked microsatellites located 2.5 and 3.6 top downstream of the coding sequence. No firm evidence was found for an association between the obese locus and the tested traits.

Amylases↗