Associations of scrotal circumference with semen traits in young beef bulls

Associations of percent live sperm, sperm number, sperm concentration, sperm motility, and potential breeding efficiency score with scrotal circumference were studied using data from the records of 465 Polled Hereford and 264 Simmental bulls. Data were subdivided by breed and within breed into three groups according to scrotal circumference (SC) size. Group I bulls had SC measurements <32 cm. Group II included bulls with SC measurements between 32 cm and the mean measurement of the breed (i.e., 35 cm for Polled Hereford and 38 cm for Simmentals). Group III was comprised of bulls with SC values above their respective breed averages. Age and body weight differences were also evaluated in the three groups. Average age differences among bulls in the three groups differed by not more than nine days in the two breeds. Average body weight differences among the three groups were statistically significant (P<0.05) with the maximum difference between any two groups within breed being 80 pounds. Average differences in percent live sperm and sperm number were greater (P<0.05) in Groups II and III than in Group I. For sperm concentration ratings, sperm motility ratings and potential breeding efficiency score, and for both breeds, Group I had a significantly lower (P<0.05) number of bulls classified satisfactory and a significantly greater (P<0.05) number of bulls classified unsatisfactory than did groups II and III.     

Genome-wide associations for investigating time-dependent genetic effects for milk production traits in dairy cattle

Phenotypic variation in milk production traits has been described over the course of a lactation as well as between different parities. The objective of this study was to investigate whether variation in production is affected by different loci across lactations. A genome-wide association study (GWAS) using a 50-k SNP chip was conducted in 152 divergent German Holstein Friesian cows to test for association with milk production traits over different lactations. The first four lactations were analysed regarding milk yield, fat, protein, lactose, milk urea nitrogen yield and content as well as somatic cell score. Two approaches were used: (i) Wilmink curve parameters were used to assess the genetic effects over the course of a lactation and (ii) test-day yield deviations (YD) were used as a normative approach for a GWAS. The significant effects were largest for markers affecting curve parameters for which there was a statistical power <0.8 of detection even in this small design. While significant markers for YDs were detected in this study, the power to detect effects of a similar magnitude was only 0.11, suggesting that many loci may have been missed with this approach in the present design. Furthermore, all significant effects were specific for a single lactation, leading to the conclusion that the variance explained by a certain locus changes from lactation to lactation. We confirm the common evidence that most production traits vary in the degree of persistency after the peak as a result of genetic influence.     

Genome‐wide association study for semen traits of the bulls in Chinese Holstein

A genome‐wide association study (GWAS) was performed to identify markers and candidate genes for five semen traits in the Holstein bull population in China. The analyzed dataset consisted of records from 692 bulls from eight bull stations; each bull was genotyped using the Illumina BovineSNP50 BeadChip. Association tests between each trait and the 41 188 informative high‐quality SNPs were achieved with gapit software. In total, 19 suggestive significant SNPs, partly located within the reported QTL regions or within or close to the reported candidate genes, associated with five semen traits were detected. By combining our GWAS results with the biological functions of these genes, eight novel promising candidate genes, including ETNK1, PDE3A, PDGFRB, CSF1R, WT1, DSCAML1, SOD1 and RUNX2, were identified that potentially relate to semen traits. Our findings may provide a basis for further research on the genetic mechanism of semen traits and marker‐assisted selection of such traits in Holstein bulls.     

Mapping of quantitative trait loci for carcass traits in a Japanese Black (Wagyu) cattle population

To detect quantitative trait loci (QTL) that influence economically important traits in a purebred Japanese Black cattle population, we performed a preliminary genome-wide scan using 187 microsatellite markers across a paternal half-sib family composed of 258 offspring. We located six QTL at the 1% chromosome-wise level on bovine chromosomes (BTA) 4, 6, 13, 14 and 21. A second screen of these six QTL regions using 138 additional paternal offspring half-sib from the same sire, provided further support for five QTL: carcass weight on BTA14 (22-39 cM), one for rib thickness on BTA6 (27-58 cM) and three for beef marbling score (BMS) on BTA4 (59-67 cM), BTA6 (68-89 cM) and BTA21 (75-84 cM). The location of QTL for subcutaneous fat thickness on BTA13 was not supported by the second screen (P > 0.05). We determined that the combined contribution of the three QTLs for BMS was 10.1% of the total variance. The combined phenotypic average of these three Q was significantly different (P < 0.001) from those of other allele combinations. Analysis of additional half-sib families will be necessary to confirm these QTL.     

Estimates of non-genetic effects and genetic parameters for semen traits in Piemontese bulls

Male reproductive performances are often ignored in cattle breeding programmes, although semen traits might be used to improve bull breeding soundness. Effects of genetic and environmental factors on semen production and quality traits were estimated in 693 Piemontese bulls with the aim of providing the first estimates of genetic parameters for semen traits for this breed. Volume and concentrations of individual ejaculates (up to three per each test-day), and volume, concentration, total number of spermatozoa and post-thawing progressive motility of within test-day pooled semen were available for 19 060 ejaculates. Bulls reached the maximum amount of daily semen production after their third year of age, with concentration rapidly increasing until 23 months of age, and then slowly decreasing. Semen volume was at its highest when collection days were at least 15 days apart, whereas the maximum concentration was reached when the interval was 6 days. Heritability estimates were generally moderate (0.14–0.26), and low for progressive motility (0.08). Estimates of genetic correlation among the volumes of the individual ejaculates were high and positive (≥0.79), as were the genetic correlations among their concentrations (≥0.46). Genetic correlations among volume and concentration traits varied from −0.47 (with a 95% high posterior density interval ranging from −0.65 to −0.23) to −0.32 (with a 95% high posterior density interval ranging from −0.55 to −0.09). Progressive motility was unrelated with the other traits, but moderately positively correlated with volumes of the second and third ejaculates. The magnitude of heritabilities showed that selection for semen traits is possible. However, the unfavourable relationship between volume and concentration must be taken into account if a future selection programme is to be established.     

Selection of buffalo bulls: Sexual behavior and its relationship to semen production and fertility

Forty-four buffalo bulls, used for artificial insemination, were studied to develop libido, mating ability and sexual behavior indices for selection purposes. For each index, 5 categories (i.e., excellent, very good, good, fair and poor) were established. The sexual behavior index was found to be more reliable than the libido and mating ability indices. Buffalo bulls in good to excellent categories were considered acceptable sires.

Reaction time, sexual aggressiveness, and scores of libido, mating ability and sexual behavior differed significantly among the various categories of the 3 indices. Libido significantly correlated with mating ability (r=0.89; P<0.001). Sexual behavior expressed significant relationship with age (r=0.41; P<0.01) and body weight (r=0.48; P<0.01), but was nonsignificant with the scrotal circumference (r=0.28; P>0.05) of buffalo bulls. However, these relationships were absent (P>0.05) in the acceptable sires. Semen production was correlated with sexual behavior in only the fair and poor categories of buffalo bulls (r=0.84; P<0.005). Sexual behavior had no relationship with the fertility rate of buffalo bulls (r=0.44; P>0.05). It is concluded that the sexual behavior index can be used successfully for the selection of buffalo bulls. Excellent- to good bulls should be used in an artificial breeding program if they qualify in the other selection indices.     

Testicular ultrasonogram pixel intensity during sexual development and its relationship with semen quality, sperm production, and quantitative testicular histology in beef bulls

This study was conducted to evaluate testicular ultrasonogram pixel intensity during sexual development in bulls and to determine its relationship with semen quality, sperm production, and quantitative testicular histology. Beef bulls (N = 152) were examined from 14 - 26 to 70 - 74 wk of age in four different years. Testicular echogenicity increased during sexual development, but the pattern of change differed among years. Echogenicity increased between 26 and 42 to 46 wk of age in 2 yr, but increased considerably earlier in the other 2 yr, reaching maximum values at 34 wk of age. Because increased echogenicity was likely associated with testicular changes leading to initiation of spermatogenesis, these differences were difficult to explain considering that age at puberty did not differ significantly among years. When data were evaluated according to age normalized to puberty, echogenicity started to increase 16 to 12 wk before puberty and reached maximum values 4 wk before or at puberty. These results indicate that a certain developmental stage of the testicular parenchyma must be reached before puberty and that the composition of the parenchyma remained consistent after puberty. Testicular echogenicity was associated with sperm production, seminiferous tubule and epithelium area, and sperm morphology, but the associations were not consistent. Testicular echogenicity was a good indicator of pubertal and mature status, but was not superior to scrotal circumference. In conclusion, although testicular ultrasonogram pixel intensity analysis might be useful for research purposes, clinical application of this technology in the present form for bull breeding soundness evaluation is not justifiable.     

Genome-wide association mapping in Norwegian Red cattle identifies quantitative trait loci for fertility and milk production on BTA12

Reproductive performance is a critical trait in dairy cattle. Poor reproductive performance leads to prolonged calving intervals, higher culling rates and extra expenses related to multiple inseminations, veterinary treatments and replacements. Genetic gain for improved reproduction through traditional selection is often slow because of low heritability and negative correlations with production traits. Detection of DNA markers associated with improved reproductive performance through genome-wide association studies could lead to genetic gain that is more balanced between fertility and production. Norwegian Red cattle are well suited for such studies, as very large numbers of detailed reproduction records are available. We conducted a genome-wide association study for non-return rate, fertility treatments and retained placenta using almost 1 million records on these traits and 17 343 genome-wide single-nucleotide polymorphisms. Genotyping costs were minimized by genotyping the sires of the cows recorded and by using daughter averages as phenotypes. The genotyped sires were assigned to either a discovery or a validation population. Associations were only considered to be validated if they were significant in both groups. Strong associations were found and validated on chromosomes 1, 5, 8, 9, 11 and 12. Several of these were highly supported by findings in other studies. The most important result was an association for non-return rate in heifers in a region of BTA12 where several associations for milk production traits have previously been found. Subsequent fine-mapping verified the presence of a quantitative trait loci (QTL) having opposing effects on non-return rate and milk production at 18 Mb. The other reproduction QTL did not have pleiotropic effects on milk production, and these are therefore of considerable interest for use in marker-assisted selection.     

Identification of quantitative trait loci for production traits in commercial pig populations

The aim of this study was to investigate methods for detecting QTL in outbred commercial pig populations. Several QTL for back fat and growth rate, previously detected in experimental resource populations, were examined for segregation in 10 different populations. Two hundred trait-by-population-by-chromosome tests were performed, resulting in 20 tests being significant at the 5% level. In addition, 53 QTL tests for 11 meat quality traits were declared significant, using a subset of the populations. These results show that a considerable amount of phenotypic variance observed in these populations can be explained by major alleles segregating at several of the loci described. Thus, despite a relatively strong selection pressure for growth and back fat traits in these populations, these alleles have not yet reached fixation. The approaches used here demonstrate that it is possible to verify segregation of QTL in commercial populations by limited genotyping of a selection of informative animals. Such verified QTL may be directly exploited in marker-assisted selection (MAS) programs in commercial populations and their molecular basis may be revealed by positional candidate cloning.     

Trait-based analyses for the detection of linkage between marker loci and quantitative trait loci in crosses between inbred lines

Summary Methods are presented for determining linkage between a marker locus and a nearby locus affecting a quantitative trait (quantitative trait locus=QTL), based on changes in the marker allele frequencies in selection lines derived from the F-2 of a cross between inbred lines, or in the high and low phenotypic classes of an F-2 or BC population. The power of such trait-based (TB) analyses was evaluated and compared with that of methods for determining linkage based on the mean quantitative trait value of marker genotypes in F-2 or BC populations [marker-based (MB) analyses]. TB analyses can be utilized for marker-QTL linkage determination in situations where the MB analysis is not applicable, including analysis of polygenic resistance traits where only a part of the population survives exposure to the Stressor and analysis of marker-allele frequency changes in selection lines. TB analyses may be a useful alternative to MB analyses when interest is centered on a single quantitative trait only and costs of scoring for markers are high compared with costs of raising and obtaining quantitative trait information on F-2 or BC individuals. In this case, a TB analysis will enable equivalent power to be obtained with fewer individuals scored for the marker, but more individuals scored for the quantitative trait. MB analyses remain the method of choice when more than one quantitative trait is to be analyzed in a given population.Contribution from the ARO, Bet Dagan, Israel. No. 1698-E, 1986 series     

Explaining the heritability of an ecologically significant trait in terms of individual quantitative trait loci

Most natural populations display substantial genetic variation in behaviour, morphology, physiology, life history and the susceptibility to disease. A major challenge is to determine the contributions of individual loci to variation in complex traits. Quantitative trait locus (QTL) mapping has identified genomic regions affecting ecologically significant traits of many species. In nearly all cases, however, the importance of these QTLs to population variation remains unclear. In this paper, we apply a novel experimental method to parse the genetic variance of floral traits of the annual plant Mimulus guttatus into contributions of individual QTLs. We first use QTL-mapping to identify nine loci and then conduct a population-based breeding experiment to estimate V(Q), the genetic variance attributable to each QTL. We find that three QTLs with moderate effects explain up to one-third of the genetic variance in the natural population. Variation at these loci is probably maintained by some form of balancing selection. Notably, the largest effect QTLs were relatively minor in their contribution to heritability.     

Detection of quantitative trait loci for meat quality traits in cattle

A whole-genome scan was carried out to detect quantitative trait loci (QTL) affecting sensory, organoleptic, physical and chemical properties of meat. The study used phenotypic data from 235 second-generation cross-bred bull calves of a Charolais × Holstein experimental population. Loin muscle samples were evaluated for yield force, intramuscular fat and nitrogen contents, myofibrillar fragmentation index, haem pigment concentration, moisture content and pH at 24 h postmortem. A sensory assessment was performed on grilled loin and roasted silverside joints by trained panellists. A linear regression analysis based on 165 markers revealed 35 QTL at the 5% chromosome-wide significance level (20 for sensory traits and 15 for physical and chemical traits), five of which were highly significant ( F -value: ≥9). The most significant QTL was located on chromosome 6 (with the best likely position at 39 cM) and affected haem pigment concentration. The Holstein allele for this QTL was associated with an increase of 0.53 SD in the haem scores. A QTL for pH_24h was identified on chromosome 14 (at 40 cM) and a QTL for moisture content was identified on chromosome 22 (at 21 cM). Two highly significant QTL were identified for sensory panel-assessed traits: beef odour intensity (grilled sample) on chromosome 10 (at 119 cM), and juiciness (roast sample) on chromosome 16 (at 70 cM). The proportion of phenotypic variance explained by the significant QTL ranged from 3.6% (for nitrogen content on chromosome 10) to 9.5% (for juiciness, roast sample on chromosome 16).     

Detection of quantitative trait loci for carcass composition traits in pigs

A quantitative trait locus (QTL) analysis of carcass composition data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. A total of 488 F2 males issued from six F1 boars and 23 F1 sows, the progeny of six LW boars and six MS sows, were slaughtered at approximately 80 kg live weight and were submitted to a standardised cutting of the carcass. Fifteen traits, i.e. dressing percentage, loin, ham, shoulder, belly, backfat, leaf fat, feet and head weights, two backfat thickness and one muscle depth measurements, ham + loin and back + leaf fat percentages and estimated carcass lean content were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half/full sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Additional analyses were performed to search for multiple linked QTL and imprinting effects. Significant gene effects were evidenced for both leanness and fatness traits in the telomeric regions of SSC 1q and SSC 2p, on SSC 4, SSC 7 and SSC X. Additional significant QTL were identified for ham weight on SSC 5, for head weight on SSC 1 and SSC 7, for feet weight on SSC 7 and for dressing percentage on SSC X. LW alleles were associated with a higher lean content and a lower fat content of the carcass, except for the fatness trait on SSC 7. Suggestive evidence of linked QTL on SSC 7 and of imprinting effects on SSC 6, SSC 7, SSC 9 and SSC 17 were also obtained.     

Methods for multiple-marker mapping of quantitative trait loci in half-sib populations

In this paper we consider the detection of individual loci controlling quantitative traits of interest (quantitative trait loci or QTLs) in the large half-sib family structure found in some species. Two simple approaches using multiple markers are proposed, one using least squares and the other maximum likelihood. These methods are intended to provide a relatively fast screening of the entire genome to pinpoint regions of interest for further investigation. They are compared with a more traditional single-marker least-squares approach. The use of multiple markers is shown to increase power and has the advantage of providing an estimate for the location of the QTL. The maximum-likelihood and the least-squares approaches using multiple markers give similar power and estimates for the QTL location, although the likelihood approach also provides estimates of the QTL effect and sire heterozygote frequency. A number of assumptions have been made in order to make the likelihood calculations feasible, however, and computationally it is still more demanding than the least-squares approach. The least-squares approach using multiple markers provides a fast method that can easily be extended to include additional effects.     

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.     

Mapping of quantitative trait loci for clinical–chemical traits in swine

Clinical–chemical traits are diagnostic parameters essential for characterization of health and disease in veterinary practice. The traits show significant variability and are under genetic control, but little is known about the fundamental genetic architecture of this variability, especially in swine. We have identified QTL for alkaline phosphatase (ALP), lactate (LAC), bilirubin (BIL), creatinine (CRE) and ionized sodium (Na⁺), potassium (K⁺) and calcium (Ca⁺⁺) from the serum of 139 F₂ pigs from a Meishan/Pietrain family before and after challenge with Sarcocystis miescheriana , a protozoan parasite of muscle. After infection, the pigs passed through three stages representing acute disease, subclinical disease and chronic disease. Forty-two QTL influencing clinical–chemical traits during these different stages were identified on 15 chromosomes. Eleven of the QTL were significant on a genome-wide level; 31 QTL were chromosome-wide significant. QTL showed specific health/disease patterns with respect to the baseline values of the traits as well as the values obtained through the different stages of disease. QTL influencing different traits at different times were found primarily on chromosomes 1, 3, 7 and 14. The most prominent QTL for the investigated clinical–chemical traits mapped to SSC3 and 7. Baseline traits of ALP, LAC, BIL, Ca⁺⁺ and K⁺ were influenced by QTL regions on SSC3, 6, 7, 8 and 13. Single QTL explained up to 21.7% of F₂ phenotypic variance. Our analysis confirms that variation of clinical–chemical traits is associated with multiple chromosomal regions.     

Validated quantitative trait loci for eggshell quality in experimental and commercial laying hens

Compromised eggshell quality causes considerable economic losses for the egg industry. Breeding for improved eggshell quality has been very challenging. Eggshell quality is a trait that would greatly benefit from marker‐assisted selection, which would allow the selection of sires for their direct contribution to the trait and would also allow implementation of measurements integrating a number of shell parameters that are difficult to measure. In this study, we selected the most promising autosomal quantitative trait loci (QTL) affecting eggshell quality on chromosomes 2, 3, 6 and 14 from earlier experiments and we extended the F₂ population to include 1599 F₂ females. The study was repeated on two commercial populations: Lohmann Tierzucht Rhode Island Red line (n = 692 females) and a Hy‐Line White Plymouth Rock line (n = 290 progeny tested males). We analyzed the selected autosomal QTL regions on the three populations with SNP markers at 4–13 SNPs/Mb density. QTL for eggshell quality were replicated on all studied regions in the F₂ population. New QTL were detected for eggshell color on chromosomes 3 and 6. Marker associations with eggshell quality traits were validated in the tested commercial lines on chromosomes 2, 3 and 6, thus paving the way for marker‐assisted selection for improved eggshell quality.