Objective: The objective of this study was to identify environmental factors strongly associated with and to estimate genetic parameters of reproductive traits in Japanese Black heifers. Methods: Data included reproduction records of Japanese Black heifers born between 2004 and 2014. First service non-return rate (NRR) to 56 days from first to successful insemination (FS), number of services per conception (IN), age at first calving (AFC) and gestation length were analyzed with the use of the general linear model. Genetic parameters were estimated with the use of the univariate animal model of the residual maximum likelihood. Results: Averages of reproductive traits over eleven years were assessed, and the effects of farm, year, month, artificial insemination technician and interaction of farm×year on the traits were determined. Estimated heritability of FS was very low and that of AFC was higher than that of the other traits. A close genetic relation was observed among NRR, IN, and FS; however, their heritabilities were very low. AFC shows favorable genetic correlation with IN and FS. Conclusion: Low heritabilities of most reproductive traits in Japanese Black heifers are strongly influenced by farm management practices, and that large residual variances make genetic evaluation difficult. Among the reproductive traits, AFC is potentially more useful for genetic improvement of heifer reproductive traits because it has high heritability and favorable genetic correlations with IN and FS.
Chrenek, P.;Huba, J.;Vasicek, D.;Peskovicova, D.;Bulla, J.
Asian-Australasian Journal of Animal Sciences
/
v.16
no.10
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pp.1397-1401
/
2003
The aim of this study was to determine genotypes of four genetic markers and to investigate their association with milk production traits in Brown Swiss cattle imported to Slovakia. The bovine $\kappa$-casein, $\beta$-lactoglobulin, growth hormone and prolactin genotypes of 107 cows were identified by polymerase chain reaction. Effects all four genetic markers on milk, fat, protein and lactose yields and fat, protein and lactose percentage were estimated from a data set of 249 lactations. The frequency of desirable B allele of $\kappa$-casein gene to milk production was 0.46, alleles A of $\beta$-lactoglobulin gene was 0.55, allele and L of growth hormone gene was 0.45 and allele A and B of bovine prolactin gene were 0.61 and 0.39. The results of milk production obtained in our work showed that BB genotypes of $\kappa$-CN gene, AA genotypes of $\beta$-LG gene, LL genotypes of bGH gene were significantly associated with better milk production traits, mainly about the fat content. Association of a bovine prolactin genotypes with milk production were not found.
The identification and utilization of potential candidate genes with significant effects on economically important traits have become increasingly important in poultry breeding programs. The ovocalyxin-32 (OCX-32) gene is located chromosome 9 in chicken, plays an important role in eggshell formation. This study was performed to assess the association between single nucleotide polymorphisms (SNPs) of OCX-32 gene and egg production traits in the Korean native chicken. Four Korean native chicken population (n = 181; including 46 females of Ogol, 46 females of white, 43 females of gray and 46 females of black) were used to analyze two SNPs (c.494A>C and c.267T>G) in the OCX-32 gene by PCR-RFLP (Polymerase Chain Reaction-Restricted Fragment Length Polymorphism). We measured egg production traits of age at first egg, first egg weight, egg production ratio and egg weight. The SNP c.494A>C was significantly associated with egg production ratio in Korean Ogol chickens (p<0.001) and egg weight in Korean white chickens (p<0.05). SNP c.267T>C was significantly associated with egg weight in Korean Ogol chickens (p<0.05). But there was no significant association in Korean gray and black chickens. Results suggest the possibility of using molecular markers in OCX-32 gene as a tool for performance and egg production traits in Korean native chicken breeding program.
To investigate the influence of the prolactin receptor 3 (PRLR3) gene and the retinol-binding protein 4 (RBP4) gene on the production traits of swine, genotyping was performed on 156 and 141 Berkshire pigs, respectively, that were carefully selected for economic traits. The frequencies of allele A in the PRLR3 locus and allele B in the RBP4 locus were 0.50 and 0.42, respectively. Neither locus was in the Hardy-Weinberg equilibrium. After a genotype was assigned to the individuals whose parents had the homozygous genotype, a statistical analysis was conducted for 291 pigs. The animals with the PRLR3 and RBP4 genotypes included 182 and 227 head, respectively. Even though the genotypic effects of PRLR3 (p<0.05) and RBP4 (p<0.01) had a significant influence on the pigs' back fat thickness, the interaction of both genes was not highly significant in terms of the back fat thickness (p = 0.1235). While the estimated epistasis effects of aaBB and aaBb decreased the back fat thickness and reduced the growth rate, the effects of AAbb and aabb increased the growth rate. Despite the insignificant difference in the PRLR genotypes in terms of the days to 90 kg and the average daily gain, the back fat thickness showed a significant difference (p<0.05), and the additive effect of allele A and the dominant effect of the hetero-genotype were -0.377 and 1.206 mm, respectively. The RBP4 genotypes had a very significant effect (p<0.01) on the back fat thickness, the days to 90 kg, and the average daily gain. The additive effects of allele B of the RBP4 locus on the back fat thickness, the days to 90 kg, and the average daily gain were 0.70 mm, -1.3 days and 6.2 g, respectively. Moreover, the dominant effects of the heterozygote for those traits were 0.63 mm, 9.9 days and -45.0 g, respectively. Allele A of the PRLR3 locus favorably influenced the back fat thickness, the days to 90 kg of the body weight, and the average daily gain and its dominant effect unfavorably influenced those traits. Allele B of RBP4 showed an incremental growth rate and back fat thickness, which could lower the lean meat percentage in the carcass. The RBP4 hetero-genotype negatively affected the pork production. These results strongly imply that the selection of allele A of PRLR3 and allele B of RBP4 would produce highly productive pigs in the Berkshire breed. Careful selection of allele B of RBP4 is required because of the increase in the back fat thickness.
Objective: The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. Methods: A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. Results: All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from $0.78{\pm}0.01$ to $0.82{\pm}0.03$, between the first and second parities, from $0.73{\pm}0.03$ to $0.8{\pm}0.04$ between the first and third parities, and from $0.82{\pm}0.02$ to $0.84{\pm}0.04$ between the second and third parities. Conclusion: These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.
Sajjad, Yasar;Jaskani, Muhammad Jafar;Qasim, Muhammad;Akhtar, Gulzar;Mehmood, Asim
Horticultural Science & Technology
/
v.33
no.6
/
pp.812-819
/
2015
Gladiolus is one of the most popular cut flowers in the world floral market and is highly attractive to consumers. The production of poor-quality gladiolus spikes is one of the most important hurdles to obtaining high prices for this crop. The main objectives of this study were to improve the quantitative characteristics of gladiolus spikes, to increase propagule production and to enhance chemical constituent levels in leaves to help improve plant growth. We performed foliar application of bioregulators, including polyamines (putrescine and spermine) and vitamins (ascorbic acid and thiamine), at different concentrations (0, 0.1, 0.4, 0.7 and 1 mM) to gladiolus plants at the three leaf, five leaf and slipping stages. Application of 1 mM putrescine was the most effective treatment, with prominent effects on economically important spike traits including spike length (55.53 cm), spike diameter (7.53 mm), florets per spike (13.99), first floret diameter (9.66 cm) and first floret weight (4.90 g), followed by spermine treatment. The 1 mM putrescine treatment also had positive effects on corm-associated traits including corm diameter and corm weight, with values of 4.57 cm and 26.16 g compared to 3.47 cm and 17.16 g in control plants, respectively. The contents of chemical constituents in leaves, including total chlorophylls ($8.06mg{\cdot}g^{-1}$), total carotenoids ($1.66mg{\cdot}g^{-1}$), total soluble sugars ($4.75 mg{\cdot}g^{-1}$) and phenolics ($0.89mg{\cdot}g^{-1}$) increased in response to foliar application of 1 mM putrescine compared to the control. Ascorbic acid and thiamine also had positive effects on various plant morphological traits and chemical constituents in leaves compared to control plants, but the growth-promoting effects of polyamines were more pronounced. Hence, applying polyamines to gladiolus leaves will help improve spike production and increasing propagule (cormel) yields.
The difference in the breeding programs and population history may have diversely shaped the genomes of Korean native cattle breeds. In the absence of phenotypic data, comparisons of breeds that have been subjected to different selective pressures can aid to identify genomic regions and genes controlling qualitative and complex traits. In this study to decipher genetic variation and identify evidence of divergent selection, 3 Korean cattle breeds were genotyped using the recently developed high-density GeneSeek Genomic Profiler F250 (GGP-F250) array. The three Korean cattle breeds clustered according to their coat color phenotypes and breeding programs. The Heugu breed reliably showed smaller effective population size at all generations considered. Across the autosomal chromosomes, 113 and 83 annotated genes were identified from Hanwoo-Chikso and Hanwoo-Heugu comparisons, respectively of which 16 genes were shared between the two pairwise comparisons. The most important signals of selection were detected on bovine chromosomes 14 (24.39-25.13 Mb) and 18 (13.34-15.07 Mb), containing genes related to body size, and coat color (XKR4, LYN, PLAG1, SDR16C5, TMEM68, CDH15, MC1R, and GALNS). Some of the candidate genes are also associated with meat quality traits (ACSF3, EIF2B1, BANP, APCDD1, and GALM) and harbor quantitative trait locus (QTL) for beef production traits. Further functional analysis revealed that the candidate genes (DBI, ACSF3, HINT2, GBA2, AGPAT5, SCAP, ELP6, APOB, and RBL1) were involved in gene ontology (GO) terms relevant to meat quality including fatty acid oxidation, biosynthesis, and lipid storage. Candidate genes previously known to affect beef production and quality traits could be used in the beef cattle selection strategies.
Previous studies in Holstein have shown 35% to 51.8% heritability in milk production traits, such as milk yield, fat, and protein, using pedigree data. Other studies in complex human traits could be captured by common single-nucleotide polymorphisms (SNPs), and their genetic variations, attributed to chromosomes, are in proportion to their length. Using genome-wide estimation and partitioning approaches, we analyzed three quantitative Holstein traits relevant to milk production in Korean Holstein data harvested from 462 individuals genotyped for 54,609 SNPs. For all three traits (milk yield, fat, and protein), we estimated a nominally significant (p = 0.1) proportion of variance explained by all SNPs on the Illumina BovineSNP50 Beadchip ($h^2_G$). These common SNPs explained approximately most of the narrow-sense heritability. Longer genomic regions tended to provide more phenotypic variation information, with a correlation of 0.46~0.53 between the estimate of variance explained by individual chromosomes and their physical length. These results suggested that polygenicity was ubiquitous for Holstein milk production traits. These results will expand our knowledge on recent animal breeding, such as genomic selection in Holstein.
In this study, canonical correlation analysis (CCA) was applied to estimate the relationship between three different sexual maturity traits (X set: days to first egg (DFE), weight of the first egg (WFE), body weight at first egg (BWFE)) and level of nutrient intake (Y set: energy (EI) and protein intake (PI)) or the egg production traits at two different periods (Z set: number of egg (NE1 and NET) and weight of egg (WE1 and WET) from 22 to 25 (Wfirst) and 22 to 33 wk of age (Wall), respectively), which were measured from 64 egg-type pullets (Isa Brown) manipulated for time of access to energy and protein sources to onset of egg production. Partial CCA (PCCA) was used to eliminate the contribution of differences in the levels of nutrient intake to canonical variables for X and Z sets at the first production period. Estimated canonical correlation coefficients between X set and Y set (0.429, p = 0.042), X set and Z set (0.390, p = 0.007 for Wfirst) and within Z set (between Wfirst and Wall; 0.780, p<0.001), and partial canonical correlation coefficient between X set and Z set (0.415, p = 0.009) were significant. Canonical weights and loadings from CCA indicated that the BWFE had the largest contribution compared to the DFE and WFE to variation of egg number produced at two different periods. The results from PCCA indicated that the contribution of PI and EI to the degree of the correlation between canonical variables for X and Z sets were unfavourable. In conclusion, the effect of body weight at sexual maturity upon the availability of nutrients can have a higher contribution to variation of egg production in pullets if the contribution of differences in nutrient intakes to onset of egg production were eliminated.
Background: Despite the importance of relationships between somatic cell score (SCS) and currently selected traits (milk, fat and protein yield) of Holstein cows, there was a lack of comprehensive literature for it in Iran. Therefore we tried to examine heritabilities and relationships between these traits using a fixed-regression animal model and Bayesian inference. The data set consisted of 1,078,966 test-day observations from 146,765 primiparous daughters of 1930 sires, with calvings from 2002 to 2013. Results: Marginal posterior means of heritability estimates for SCS ($0.03{\pm}0.002$) were distinctly lower than those for milk ($0.204{\pm}0.006$), fat ($0.096{\pm}0.004$) and protein ($0.147{\pm}0.005$) yields. In the case of phenotypic correlations, the relationships between production and SCS were near zero at the beginning of lactation but become increasingly negative as days in milk increased. Although all environmental correlations between production and SCS were negative ($-0.177{\pm}0.007$, $-0.165{\pm}0.008$ and $-0.152{\pm}0.007$ between SCS and milk, fat, and protein yield, respectively), slightly antagonistic genetic correlations were found; with posterior mean of relationships ranging from $0.01{\pm}0.039$ to $0.11{\pm}0.036$. This genetic opposition was distinctly higher for protein than for fat. Conclusion: Although small, the positive genetic correlations suggest some genetic antagonism between desired increased milk production and reduced SCS (i.e., single-trait selection for increased milk production will also increase SCS).
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