The potential for identifying heritable endocrine parameters associated with fertility in post-partum dairy cows

1999 ◽  
Vol 68 (2) ◽  
pp. 333-347 ◽  
Author(s):  
A. O. Darwash ◽  
G. E. Lamming ◽  
J. A. Woolliams
Keyword(s):  
Genetic Variation ◽  
Genetic Gain ◽  
Production Efficiency ◽  
Negative Impact ◽  
Post Partum ◽  
Genetic Correlations ◽  
Reproductive Efficiency ◽  
Steady Increase ◽  
High Fertility ◽  
Progeny Testing

AbstractFertility is an important component of herd production efficiency, as each additional oestrous cycle that does not result in a planned pregnancy adds to the cost of dairy farming. In addition to the negative impact on milk production, the high costs of veterinary intervention, re-insemination and herd replacement, subfertility can affect the rate of genetic gain in traits of economic merit. In contrast with the steady increase in average milk yield per cow during the last 30 years, there has been a decline in conception rate to artificial insemination in both the USA and in the UK.The genetic correlation between yield and fertility has been equivocal. Attempts to improve the reproductive efficiency in dairy cattle through breeding and selection have been frustrated to date by the lack of heritable reproductive parameters conducive to high fertility. However, the traditional fertility parameters of interval to first service, services per conception, days open and calving intervals are highly influenced by managerial decisions and have, as expected, heritabilities too low to permit a meaningful genetic gain through selection. An alternative approach is to use the growing body of evidence that the majority of endocrine factors affecting reproduction are a result of gene expression at the hypothalamic, pituitary, ovarian or uterine level. Mechanisms such as commencement of post-partum cyclicity, follicle wave patterns, manifestation of oestrus, luteal competence and level of embryo mortality are appropriate for study. Research is required to investigate the genetic component of the variation between animals in these parameters, their phenotypic and genetic correlations with fertility and their association with other production traits.In summary: (a) subfertility is a syndrome with multiple causes and only the symptom in common; (b) improvement in fertility will continue to be frustrated until recorded traits provide more accurate estimates of breeding values; (c) techniques are now available to estimate the genetic variation in physiological components conducive to improved reproductive efficiency; (d) once the heritable components of fertility are identified, these tools could be introduced into progeny testing and breeding nuclei, from which the genetic improvement can be widely disseminated. Selection for those components with sufficient genetic variation will result in the improvement of the integral endocrine and other physiological mechanisms favourably correlated with high fertility (e) these tools may also assist in detecting quantitative trait loci for faster genetic gain through markers-assisted selection.

scholarly journals Efficient use of genomic information for sustainable genetic improvement in small cattle populations

2019 ◽  
Author(s):  
J. Obšteter ◽  
J. Jenko ◽  
J. M. Hickey ◽  
G. Gorjanc
Keyword(s):  
Genetic Variation ◽  
Genomic Selection ◽  
Conversion Efficiency ◽  
Genetic Gain ◽  
Progeny Testing ◽  
Effective Population ◽  
Generation Interval ◽  
Truncation Selection ◽  
Selection Accuracy ◽  
Sire Selection

ABSTRACTThis paper compares genetic gain, genetic variation, and the efficiency of converting variation into gain under different genomic selection scenarios with truncation or optimum contribution selection in a small dairy population by simulation. Breeding programs have to maximize genetic gain but also ensure sustainability by maintaining genetic variation. Numerous studies showed that genomic selection increases genetic gain. Although genomic selection is a well-established method, small populations still struggle with choosing the most sustainable strategy to adopt this type of selection. We developed a simulator of a dairy population and simulated a model after the Slovenian Brown Swiss population with ~10,500 cows. We compared different truncation selection scenarios by varying i) the method of sire selection and their use on cows or bull-dams, and ii) selection intensity and the number of years a sire is in use. Furthermore, we compared different optimum contribution selection scenarios with optimization of sire selection and their usage. We compared the scenarios in terms of genetic gain, selection accuracy, generation interval, genetic and genic variance, the rate of coancestry, effective population size, and the conversion efficiency. The results show that early use of genomically tested sires increased genetic gain compared to progeny testing as expected from changes in selection accuracy and generation interval. A faster turnover of sires from year to year and higher intensity increased the genetic gain even further but increased the loss of genetic variation per year. While maximizing intensity gave the lowest conversion efficiency, a faster turn-over of sires gave an intermediate conversion efficiency. The largest conversion efficiency was achieved with the simultaneous use of genomically and progeny tested sires that were used over several years. Compared to truncation selection optimizing sire selection and their usage increased the conversion efficiency by either achieving comparable genetic gain for a smaller loss of genetic variation or achieving higher genetic gain for a comparable loss of genetic variation. Our results will help breeding organizations to implement sustainable genomic selection.

scholarly journals Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 599
Author(s):  
Miguel A. Gutierrez-Reinoso ◽  
Pedro M. Aponte ◽  
Manuel Garcia-Herreros
Keyword(s):  
Dairy Cattle ◽  
Production Efficiency ◽  
Association Studies ◽  
Phenotypic Traits ◽  
Progeny Testing ◽  
Genome Wide Association Studies ◽  
Genetic Progress ◽  
Breeding Programs ◽  
Increased Risk ◽  
Selection Of

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

Effect of immediate post-partum uterine treatment on subsequent reproductive efficiency

1983 ◽  
Vol 19 (6) ◽  
pp. 811-815 ◽  
Author(s):  
H.H. Dowlen ◽  
R.L. Murphree ◽  
D.O. Richardson ◽  
J.R. Owen
Keyword(s):  
Post Partum ◽  
Reproductive Efficiency

Genetic Parameters and Genotype-by-Environment Interactions in Regional Progeny Tests of Pinus taeda L. in the Southern USA

2020 ◽  
Author(s):  
Edwin Lauer ◽  
Andrew Sims ◽  
Steven McKeand ◽  
Fikret Isik
Keyword(s):  
Genetic Variation ◽  
Pinus Taeda ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Breeding Program ◽  
Model Fit ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment ◽  
Progeny Tests ◽  
Pinus Taeda L

Abstract Genetic parameters were estimated using a five-series multienvironment trial of Pinus taeda L. in the southern USA. There were 324 half-sib families planted in five test series across 37 locations. A set of six variance/covariance matrices for the genotype-by-environment (G × E) effect for tree height and diameter were compared on the basis of model fit. In single-series analysis, extended factor analytical models provided generally superior model fit to simpler models for both traits; however, in the combined-series analysis, diameter was optimally modeled using simpler variance/covariance structures. A three-way compound term for modeling G × E interactions among and within series yielded substantial improvements in terms of model fit and standard errors of predictions. Heritability of family means ranged between 0.63 and 0.90 for both height and diameter. Average additive genetic correlations among sites were 0.70 and 0.61 for height and diameter, respectively, suggesting the presence of some G × E interaction. Pairs of sites with the lowest additive genetic correlations were located at opposite ends of the latitude range. Latent factor regression revealed a small number of parents with large factor scores that changed ranks significantly between southern and northern environments. Study Implications Multienvironmental progeny tests of loblolly pine (Pinus taeda L.) were established over 10 years in the southern United States to understand the genetic variation for the traits of economic importance. There was substantial genetic variation between open-pollinated families, suggesting that family selection would be efficient in the breeding program. Genotype-by-environment interactions were negligible among sites in the deployment region but became larger between sites at the extremes of the distribution. The data from these trials are invaluable in informing the breeding program about the genetic merit of selection candidates and their potential interaction with the environment. These results can be used to guide deployment decisions in the southern USA, helping landowners match germplasm with geography to achieve optimal financial returns and conservation outcomes.

scholarly journals The Molecular Basis of Quantitative Genetic Variation in Central and Secondary Metabolism in Arabidopsis

Genetics ◽  
1998 ◽  
Vol 149 (2) ◽  
pp. 739-747 ◽  
Author(s):  
Thomas Mitchell-Olds ◽  
Deana Pedersen
Keyword(s):  
Enzyme Activity ◽  
Genetic Variation ◽  
Secondary Metabolism ◽  
Genetic Correlations ◽  
Theoretical Models ◽  
Model Systems ◽  
Activity Levels ◽  
Significant Qtls ◽  
Cis Acting ◽  
Quantitative Genetic

Abstract To find the genes controlling quantitative variation, we need model systems where functional information on physiology, development, and gene regulation can guide evolutionary inferences. We mapped quantitative trait loci (QTLs) influencing quantitative levels of enzyme activity in primary and secondary metabolism in Arabidopsis. All 10 enzymes showed highly significant quantitative genetic variation. Strong positive genetic correlations were found among activity levels of 5 glycolytic enzymes, PGI, PGM, GPD, FBP, and G6P, suggesting that enzymes with closely related metabolic functions are coregulated. Significant QTLs were found influencing activity of most enzymes. Some enzyme activity QTLs mapped very close to known enzyme-encoding loci (e.g., hexokinase, PGI, and PGM). A hexokinase QTL is attributable to cis-acting regulatory variation at the AtHXK1 locus or a closely linked regulatory locus, rather than polypeptide sequence differences. We also found a QTL on chromosome IV that may be a joint regulator of GPD, PGI, and G6P activity. In addition, a QTL affecting PGM activity maps within 700 kb of the PGM-encoding locus. This QTL is predicted to alter starch biosynthesis by 3.4%, corresponding with theoretical models, suggesting that QTLs reflect pleiotropic effects of mutant alleles.

scholarly journals Genetic variation and correlation of agronomic traits in meadow bromegrass (Bromus riparius Rehm) clones

2004 ◽  
Vol 34 (2) ◽  
pp. 505-510 ◽  
Author(s):  
Marcelo Renato Alves de Araújo ◽  
Bruce Coulman
Keyword(s):  
Genetic Variation ◽  
Crude Protein ◽  
Genetic Correlations ◽  
Neutral Detergent Fiber ◽  
Broad Sense ◽  
Grass Species ◽  
Broad Sense Heritability ◽  
Bromus Riparius ◽  
Heritability Estimates ◽  
Meadow Bromegrass

Meadow bromegrass (Bromus riparius Rehm.) is a recently introduced pasture grass in western Canada. Its leafy production and rapid regrowth have made it a major grass species for pasturing beef animals in this region. As relatively little breeding work has been done on this species, there is little information on its breeding behaviour. The main objective of this study was to estimate total genetic variability, broad-sense heritability, phenotypic and genetic correlations. Forty-four meadow bromegrass clones were evaluated for agronomic characters. Genetic variation for dry matter yield, seed yield, fertility index, harvest index, plant height, plant spread, crude protein, neutral detergent fiber and acid detergent fiber, was significant. Broad-sense heritability estimates exceeded 50% for all characters. Heritability estimates were at least 3.5 times greater than their standard errors. Phenotypic and genetic correlation between all possible characters were measured. There was general agreement in both sign and magnitude between genetic and phenotypic correlations. Correlations between the different characters demonstrated that it is possible to simultaneously improve seed and forage yield. Based on the results, it appears that the development of higher yielding cultivars with higher crude protein, and lower acid and neutral detergent fibers concentration should be possible.

scholarly journals Genetic Variation for Biomass Yield and Predicted Genetic Gain in Lowland Switchgrass “Kanlow”

Agronomy ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1845
Author(s):  
Santosh Nayak ◽  
Hem Bhandari ◽  
Carl Sams ◽  
Virginia Sykes ◽  
Haileab Hilafu ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Genetic Gain ◽  
Panicum Virgatum ◽  
Biomass Yield ◽  
Block Design ◽  
Perennial Grass ◽  
Warm Season ◽  
Narrow Sense ◽  
Bioenergy Feedstock ◽  
Narrow Sense Heritability

Switchgrass (Panicum virgatum L.) is a warm-season, perennial grass valued as a promising candidate species for bioenergy feedstock production. Biomass yield is the most important trait for any bioenergy feedstock. This study was focused on understanding the genetics underlying biomass yield and feedstock quality traits in a “Kanlow” population. The objectives of this study were to (i) assess genetic variation (ii) estimate the narrow sense heritability, and (iii) predict genetic gain per cycle of selection for biomass yield and the components of lignocelluloses. Fifty-four Kanlow half-sib (KHS) families along with Kanlow check were planted in a randomized complete block design with three replications at two locations in Tennessee: Knoxville and Crossville. The data were recorded for two consecutive years: 2013 and 2014. The result showed a significant genetic variation for biomass yield (p < 0.05), hemicellulose concentration (p < 0.05), and lignin concentration (p < 0.01). The narrow sense heritability estimates for biomass yield was very low (0.10), indicating a possible challenge to improve this trait. A genetic gain of 16.5% is predicted for biomass yield in each cycle of selection by recombining parental clones of 10% of superior progenies.

Genetic variation in net feed efficiency in Hereford cattle and its association with other production traits

1999 ◽  
Vol 1999 ◽  
pp. 47-47
Author(s):  
R.M. Herd ◽  
S.C. Bishop
Keyword(s):  
Growth Rate ◽  
Genetic Variation ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Genetic Correlations ◽  
Feed Consumption ◽  
Production Traits ◽  
Performance Measurements ◽  
Hereford Cattle ◽  
Rate Selection

Net feed efficiency refers to variation in feed consumption between animals net of requirements for maintenance and production, and may be measured as residual feed intake (RFI). Because RFI is independent of liveweight (LW) and growth rate, selection for improved net feed efficiency is likely to reduce feed intake with little change in growth. The purpose of this study was to establish whether there exists genetic variation in RFI in young British Hereford bulls, and to determine the phenotypic and genetic correlations of RFI with key production traits.The data consisted of performance measurements on 540 bull progeny of 154 British Hereford sires, collected over ten 200-day postweaning performance tests conducted between 1979 and 1988. The traits analysed were food intake (FI), 200 to 400-day daily gain (ADG), 400-day weight (W400), predicted carcass lean content (LEAN), lean growth rate (LGR), food conversion ratio (FI/ADG) and lean FCR (LFCR; FI/(ADG x LEAN), described by Bishop (1992).

Genetic variation in fatty acid composition of subcutaneous fat in cattle

2013 ◽  
Vol 53 (2) ◽  
pp. 129 ◽  
Author(s):  
M. J. Kelly ◽  
R. K. Tume ◽  
S. Newman ◽  
J. M. Thompson
Keyword(s):  
Fatty Acids ◽  
Genetic Variation ◽  
Fatty Acid Composition ◽  
Fatty Acid ◽  
Acid Composition ◽  
Saturated Fatty Acids ◽  
Genetic Correlations ◽  
Subcutaneous Fat ◽  
Monounsaturated Fatty Acids ◽  
Selection For

Genetic parameters were estimated for fatty acid composition of subcutaneous beef fat of 1573 animals which were the progeny of 157 sires across seven breeds grown out on pasture and then finished on either grain or grass in northern New South Wales or in central Queensland. There was genetic variation in individual fatty acids with estimates of heritability for the proportions of C14 : 0, C14 : 1c9, C16 : 0, C16 : 1c9, C18 : 0 and C18 : 1c9 fatty acids in subcutaneous beef fat of the order of 0.4 or above. Also substantial correlations between some fatty acids were observed. Genetic correlations between fatty acids and fat depth at the P8 site suggested that much of the genetic variation in fatty acid composition was related to changes in fatness. Selection for decreased fatness resulted in decreased proportions of C18 : 1c9 with concomitant increases in C18 : 0, C14 : 0 and C16 : 0. This suggested that selection for decreased fatness at a given weight will result in a decrease in the proportions of monounsaturated fatty acids in the subcutaneous fat in the carcass with a corresponding increase in the proportions of saturated fatty acids.

scholarly journals Genomic Selection for Any Dairy Breeding Program via Optimized Investment in Phenotyping and Genotyping

2021 ◽  
Vol 12 ◽  
Author(s):  
Jana Obšteter ◽  
Janez Jenko ◽  
Gregor Gorjanc
Keyword(s):  
Genomic Selection ◽  
Genetic Gain ◽  
Breeding Program ◽  
Progeny Testing ◽  
Initial Training ◽  
Training Population ◽  
Breeding Programs ◽  
Use Of Resources ◽  
Dairy Cattle Breeding ◽  
Close Relatives

This paper evaluates the potential of maximizing genetic gain in dairy cattle breeding by optimizing investment into phenotyping and genotyping. Conventional breeding focuses on phenotyping selection candidates or their close relatives to maximize selection accuracy for breeders and quality assurance for producers. Genomic selection decoupled phenotyping and selection and through this increased genetic gain per year compared to the conventional selection. Although genomic selection is established in well-resourced breeding programs, small populations and developing countries still struggle with the implementation. The main issues include the lack of training animals and lack of financial resources. To address this, we simulated a case-study of a small dairy population with a number of scenarios with equal available resources yet varied use of resources for phenotyping and genotyping. The conventional progeny testing scenario collected 11 phenotypic records per lactation. In genomic selection scenarios, we reduced phenotyping to between 10 and 1 phenotypic records per lactation and invested the saved resources into genotyping. We tested these scenarios at different relative prices of phenotyping to genotyping and with or without an initial training population for genomic selection. Reallocating a part of phenotyping resources for repeated milk records to genotyping increased genetic gain compared to the conventional selection scenario regardless of the amount and relative cost of phenotyping, and the availability of an initial training population. Genetic gain increased by increasing genotyping, despite reduced phenotyping. High-genotyping scenarios even saved resources. Genomic selection scenarios expectedly increased accuracy for young non-phenotyped candidate males and females, but also proven females. This study shows that breeding programs should optimize investment into phenotyping and genotyping to maximize return on investment. Our results suggest that any dairy breeding program using conventional progeny testing with repeated milk records can implement genomic selection without increasing the level of investment.

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