scholarly journals Genomic Prediction for Twin Pregnancies

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 843
Author(s):  
Shaileen P. McGovern ◽  
Daniel J. Weigel ◽  
Brenda C. Fessenden ◽  
Dianelys Gonzalez-Peña ◽  
Natascha Vukasinovic ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Management Practices ◽  
Selection Index ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Genetic And Environmental Factors ◽  
Effective Inclusion ◽  
Sound Management ◽  
Multitrait Selection ◽  
Twin Pregnancies

Twinning is a multifactorial trait influenced by both genetic and environmental factors that can negatively impact animal welfare and economic sustainability on commercial dairy operations. To date, using genetic selection as a tool for reducing twinning rates on commercial dairies has been proposed, but not yet implemented. In response to this market need, Zoetis (Kalamazoo, MI, USA) has developed a genomic prediction for twin pregnancies, and included it in a comprehensive multitrait selection index. The objectives of this study were to (1) describe a genetic evaluation for twinning in Holstein cattle, (2) demonstrate the efficacy of the predictions, (3) propose strategies to reduce twin pregnancies using this information. Data were retrieved from commercial dairies and provided directly by producers upon obtaining their permission. The twin pregnancies trait (TWIN) was defined as a pregnancy resulting in birth or abortion of twin calves, classified as a binary (0,1) event, and analysed using a threshold animal model. Predictions for a subset of cows were compared to their on-farm twin records. The heritability for twin pregnancies was 0.088, and genomic predicted transmitting abilities ((g)PTAs) ranged from −7.45–20.79. Genetic correlations between TWIN and other traits were low, meaning that improvement for TWIN will not negatively impact improvement for other traits. TWIN was effectively demonstrated to identify cows most and least likely to experience a twin pregnancy in a given lactation, regardless of reproductive protocol used. Effective inclusion of the prediction in a multitrait selection index offers producers a comprehensive tool to inform selection and management decisions. When combined with sound management practices, this presents a compelling opportunity for dairy producers to proactively reduce the incidence of twin pregnancies on commercial dairy operations.

Can we breed Merino sheep with softer, whiter, more photostable wool?

2010 ◽  
Vol 50 (12) ◽  
pp. 1089 ◽  
Author(s):  
S. Hatcher ◽  
P. I. Hynd ◽  
K. J. Thornberry ◽  
S. Gabb
Keyword(s):  
Genetic Parameters ◽  
Selection Index ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Phenotypic Selection ◽  
Quality Traits ◽  
Current Generation ◽  
Merino Sheep ◽  
Initial Cohort ◽  
Selection For

Genetic parameters (heritability, phenotypic and genetic correlations) were estimated for a range of visual and measured wool traits recorded from the 2008 shearing of the initial cohort of Merino progeny born into the Sheep CRC’s Information Nucleus Flock. The aim of this initial analysis was to determine the feasibility of selectively breeding Merino sheep for softer, whiter, more photostable wool and to quantify the likely impact on other wool production and quality traits. The estimates of heritability were high for handle and clean colour (0.86 and 0.70, respectively) and moderate for photostability (0.18), with some evidence of maternal effects for both handle and photostability. The phenotypic correlations between handle and clean colour and between handle and photostability were close to zero, indicating that achieving the ‘triple’ objective of softer, whiter, more photostable wool in the current generation through phenotypic selection alone would be difficult. There was evidence of an antagonistic relationship between handle and photostability (–0.36), such that genetic selection for softer wool will produce less photostable wool that will yellow on exposure to UV irradiation. However genetic selection for whiter wool is complementary to photostability and will result in whiter wool that is less likely to yellow. Genetic selection to improve handle, colour and photostability can be achieved with few detrimental effects on other visual and measured wool traits, particularly if they are included in an appropriate selection index.

scholarly journals 179 Breeding for enhancing feed efficiency in dairy cattle

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 183-184
Author(s):  
Flavio Schenkel ◽  
Luiz Brito ◽  
Hinayah Oliveira ◽  
Tatiane Chud ◽  
David Seymour ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Feed Efficiency ◽  
Selection Index ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Methane Emissions ◽  
Genome Project ◽  
Nutrient Loss ◽  
Breeding Value ◽  
Selection For

Abstract Genetically selecting for improved feed efficiency has been recognized by the dairy cattle industry as an important economic and environmental goal. Improved feed efficiency has the potential to significantly reduce costs, improving dairy farmers’ profitability and, at the same time, minimize environmental impact, for example by reducing nutrient loss in manure and methane emissions. Feed efficiency is recognized as a complex trait that may be define in different ways, but it generally describes units of product output per unit of feed required. An overview of genetic selection for improved feed efficiency and international initiatives to implement genomic selection for feed efficiency in dairy cattle is presented. In general, studies have indicated that feed efficiency, defined and assessed in alternative ways, is moderately heritable and genetic selection could be successfully implemented. Various initiatives around the world have worked collaboratively to carried out research and create reference datasets for joint genomic evaluations. An example is the large international Efficient Dairy Genome Project (EDGP) led by Canada. The EDGP database was developed in 2017 to allow data sharing among the international collaborators. Currently, the database contains genotypes and records on feed intake of 5,289 cows and on methane emissions of 1,337 cows from eight research herds in six countries (Australia, Canada, Denmark, Switzerland, United Kingdom and United States). Genetic parameters (heritability and genetic correlations) were estimated for dry matter intake, metabolic body weight and energy corrected milk at two time-periods: a) 5–60 DIM and b) 60–150 DIM. These parameters provide a basis for development of breeding value estimation procedures and subsequent selection index for feed efficiency, which will incorporate genomic information.

Genetic aspects of cold resistance and related characters in newborn Merino lambs

1991 ◽  
Vol 31 (2) ◽  
pp. 175 ◽  
Author(s):  
J Slee ◽  
G Alexander ◽  
LR Bradley ◽  
N Jackson ◽  
D Stevens
Keyword(s):  
Fixed Effects ◽  
Cold Resistance ◽  
Selection Index ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Skin Thickness ◽  
Significant Other ◽  
Manual Palpation ◽  
Rate Of Recovery ◽  
Body Cooling

Resistance to body cooling and rate of recovery from induced hypothermia were measured in 287 single, newborn Merino lambs from 24 different sire families, using a water bath test in which partly immersed lambs were progressively cooled. Birth weight, birthcoat type (fine-hairy) and skin thickness were recorded at the time of test. There was an unexpected occurrence of congenital goitre, the incidence and severity of which was estimated by manual palpation of the thyroid gland. Heritability (� s.e.) of cold resistance (CR), estimated by paternal half-sib analysis, was 0.70 � 0.25. Sex of lamb, type of weather, time of test, Fecundin treatment and age of ewe were fitted in the model as fixed effects but none were significant. Other heritable traits (h2 � s.e.) included birthweight (0.50 � 0.22), birthcoat grade (0.61 � 0.24), coat depth (0.62 � 0.24), skin thickness (0.35 � 0.19) and the severity of goitre (0.21 � 0.16). Significant genetic correlations (r �s.e.) between cold resistance and other traits were: birthweight, +0.76 � 0.18; birthcoat grade, +0.56 � 0.24; birthcoat depth, +0.56 � 0.24; skin thickness, +0.51 � 0.27; goitre, -0.58 � 0.40. Most of the corresponding phenotypic correlations were small. Goitre did not affect CR significantly, despite the genetic correlation between them. Heritability of CR, further adjusted for the effects of birthweight, birthcoat grade and depth, and skin thickness as covariates, was 0.55 � 0.23. About 40% of the variation in CR was accounted for by fitting fixed effects and covariates, but significant sire effects remained. Rate of recovery from hypothermia was not heritable and it was unrelated to any other variable except goitre, which tended to be associated with slower recovery (rp = 0.18). It was concluded that genetic selection for increased CR would succeed but would promote birthcoat hairiness unless a corrective selection index was used. The relationship between birthcoat type and CR was considered to be mediated by genes affecting both coat type and CR, not primarily by a direct effect of coat insulation.

scholarly journals Genetic Parameters of Honey Bee Colonies Traits in a Canadian Selection Program

Insects ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 587 ◽  
Author(s):  
Ségolène Maucourt ◽  
Frédéric Fortin ◽  
Claude Robert ◽  
Pierre Giovenazzo
Keyword(s):  
Honey Bee ◽  
Honey Bees ◽  
Genetic Parameters ◽  
Selection Index ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Hygienic Behavior ◽  
Domestic Species ◽  
Honey Production ◽  
High Heritability

Genetic selection has led to spectacular advances in animal production in many domestic species. However, it is still little applied to honey bees (Apis mellifera), whose complex genetic and reproductive characteristics are a challenge to model statistically. Advances in informatics now enable creation of a statistical model consistent with honey bee genetics, and, consequently, genetic selection for this species. The aim of this project was to determine the genetic parameters of several traits important for Canadian beekeepers with a view to establishing a breeding program in a northern context. Our results show that the five traits measured (Varroa destructor infestation, spring development, honey production, winter consumption, and hygienic behavior) are heritable. Thus, the rate of V. destructor infestation has a high heritability (h2 = 0.44 ± 0.56), spring development and honey production have a medium heritability (respectively, h2 = 0.30 ± 0.14 and h2 = 0.20 ± 0.13), and winter consumption and hygienic behavior have a low heritability (respectively, h2 = 0.11 ± 0.09 and h2 = 0.18 ± 0.13). Furthermore, the genetic correlations between these traits are all positive or null, except between hygienic behavior and V. destructor infestation level. These genetic parameters will be instrumental to the development of a selection index that will be used to improve the capacity of honey bees to thrive in northern conditions.

scholarly journals Prediction of meat quality traits in the abattoir using portable near-infrared spectrometers: heritability of predicted traits and genetic correlations with laboratory-measured traits

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Simone Savoia ◽  
Andrea Albera ◽  
Alberto Brugiapaglia ◽  
Liliana Di Stasio ◽  
Alessio Cecchinato ◽  
...  
Keyword(s):  
Meat Quality ◽  
Near Infrared ◽  
External Validation ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Quality Traits ◽  
Eye Muscle ◽  
Meat Quality Traits ◽  
Color Traits ◽  
Selection Of

Abstract Background The possibility of assessing meat quality traits over the meat chain is strongly limited, especially in the context of selective breeding which requires a large number of phenotypes. The main objective of this study was to investigate the suitability of portable infrared spectrometers for phenotyping beef cattle aiming to genetically improving the quality of their meat. Meat quality traits (pH, color, water holding capacity, tenderness) were appraised on rib eye muscle samples of 1,327 Piemontese young bulls using traditional (i.e., reference/gold standard) laboratory analyses; the same traits were also predicted from spectra acquired at the abattoir on the intact muscle surface of the same animals 1 d after slaughtering. Genetic parameters were estimated for both laboratory measures of meat quality traits and their spectra-based predictions. Results The prediction performances of the calibration equations, assessed through external validation, were satisfactory for color traits (R2 from 0.52 to 0.80), low for pH and purge losses (R2 around 0.30), and very poor for cooking losses and tenderness (R2 below 0.20). Except for lightness and purge losses, the heritability estimates of most of the predicted traits were lower than those of the measured traits while the genetic correlations between measured and predicted traits were high (average value 0.81). Conclusions Results showed that NIRS predictions of color traits, pH, and purge losses could be used as indicator traits for the indirect genetic selection of the reference quality phenotypes. Results for cooking losses were less effective, while the NIR predictions of tenderness were affected by a relatively high uncertainty of estimate. Overall, genetic selection of some meat quality traits, whose direct phenotyping is difficult, can benefit of the application of infrared spectrometers technology.

scholarly journals Optimal breeding-value prediction using a Sparse Selection Index

Genetics ◽  
2021 ◽  
Author(s):  
Marco Lopez-Cruz ◽  
Gustavo de los Campos
Keyword(s):  
Sample Size ◽  
Dna Sequences ◽  
Genomic Prediction ◽  
Prediction Accuracy ◽  
Regularization Parameter ◽  
Selection Index ◽  
Prediction Method ◽  
Training Data ◽  
Breeding Value ◽  
Data Set

Abstract Genomic prediction uses DNA sequences and phenotypes to predict genetic values. In homogeneous populations, theory indicates that the accuracy of genomic prediction increases with sample size. However, differences in allele frequencies and in linkage disequilibrium patterns can lead to heterogeneity in SNP effects. In this context, calibrating genomic predictions using a large, potentially heterogeneous, training data set may not lead to optimal prediction accuracy. Some studies tried to address this sample size/homogeneity trade-off using training set optimization algorithms; however, this approach assumes that a single training data set is optimum for all individuals in the prediction set. Here, we propose an approach that identifies, for each individual in the prediction set, a subset from the training data (i.e., a set of support points) from which predictions are derived. The methodology that we propose is a Sparse Selection Index (SSI) that integrates Selection Index methodology with sparsity-inducing techniques commonly used for high-dimensional regression. The sparsity of the resulting index is controlled by a regularization parameter (λ); the G-BLUP (the prediction method most commonly used in plant and animal breeding) appears as a special case which happens when λ = 0. In this study, we present the methodology and demonstrate (using two wheat data sets with phenotypes collected in ten different environments) that the SSI can achieve significant (anywhere between 5-10%) gains in prediction accuracy relative to the G-BLUP.

scholarly journals High Heritabilities for Antibiotic Usage Show Potential to Breed for Disease Resistance in Finishing Pigs

Antibiotics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 829
Author(s):  
Wim Gorssen ◽  
Dominiek Maes ◽  
Roel Meyermans ◽  
Jürgen Depuydt ◽  
Steven Janssens ◽  
...  
Keyword(s):  
Pathogenic Bacteria ◽  
Animal Health ◽  
Molecular Genetic ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Antibiotic Usage ◽  
Finishing Pigs ◽  
Production Traits ◽  
Parenteral Antibiotic ◽  
On Farm

The use of antimicrobials in animal production is under public debate, mainly due to the risk of transfer of resistance to pathogenic bacteria in humans. Therefore, measures have been taken during the last few decades to reduce antibiotic usage in animals, for instance, by national monitoring programmes and by improving animal health management. Although some initiatives exist in molecular genetic selection, quantitative genetic selection of animals towards decreased antibiotic usage is an underexplored area to reduce antibiotic usage. However, this strategy could yield cumulative effects. In this study, we derived new phenotypes from on-farm parenteral antibiotic records from commercially grown crossbred finishing pigs used in the progeny test of Piétrain terminal sires to investigate the heritability of antibiotics usage. Parenteral antibiotic records, production parameters and pedigree records of 2238 full-sib pens from two experimental farms in Belgium between 2014 and 2020 were analysed. Heritability estimates were moderate (18–44%) for phenotypes derived from all antibiotic treatments, and low (1–15%) for phenotypes derived from treatments against respiratory diseases only. Moreover, genetic correlations between these new phenotypes and mortality were low to moderate (0.08–0.60) and no strong adverse genetic correlations with production traits were found. The high heritabilities and favourable genetic correlations suggest these new phenotypes, derived from on-farm antibiotics records, to be promising for inclusion in future pig breeding programs to breed for a decrease in antibiotics usage.

scholarly journals Corrigendum to: Consequences of genetic selection for environmental impact traits on economically important traits in dairy cows

2018 ◽  
Vol 58 (10) ◽  
pp. 1966
Author(s):  
Purna Kandel ◽  
Sylvie Vanderick ◽  
Marie-Laure Vanrobays ◽  
Hélène Soyeurt ◽  
Nicolas Gengler
Keyword(s):  
Dairy Cows ◽  
Body Condition Score ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Selection Response ◽  
Direct Selection ◽  
Correlated Response ◽  
Production Traits ◽  
Ch4 Emissions ◽  
Natural Logarithm

Methane (CH4) emission is an important environmental trait in dairy cows. Breeding aiming to mitigate CH4 emissions require the estimation of genetic correlations with other economically important traits and the prediction of their selection response. In this study, test-day CH4 emissions were predicted from milk mid-infrared spectra of Holstein cows. Predicted CH4 emissions (PME) and log-transformed CH4 intensity (LMI) computed as the natural logarithm of PME divided by milk yield (MY). Genetic correlations of PME and LMI with traits used currently were approximated from correlations between estimated breeding values of sires. Values were for PME with MY 0.06, fat yield (FY) 0.09, protein yield (PY) 0.13, fertility 0.17; body condition score (BCS) –0.02; udder health (UDH) 0.22; and longevity 0.22. As expected by its definition, values were negative for LMI with production traits (MY –0.61; FY –0.15 and PY –0.40) and positive with fertility (0.36); BCS (0.20); UDH (0.08) and longevity (0.06). The genetic correlations of 33 type traits with PME ranged from –0.12 to 0.25 and for LMI ranged from –0.22 to 0.18. Without selecting PME and LMI (status quo) the relative genetic change through correlated responses of other traits were in PME by 2% and in LMI by –15%, but only due to the correlated response to MY. Results showed for PME that direct selection of this environmental trait would reduce milk carbon foot print but would also affect negatively fertility. Therefore, more profound changes in current indexes will be required than simply adding environmental traits as these traits also affect the expected progress of other traits.

Multi-trait selection index and cluster analyses in Angus cattle

2021 ◽  
pp. 1-8
Author(s):  
G. M. Fernandes ◽  
R. P. Savegnago ◽  
L. A. Freitas ◽  
L. El Faro ◽  
V. M. Roso ◽  
...  
Keyword(s):  
Production System ◽  
Selection Process ◽  
Selection Index ◽  
Genetic Selection ◽  
Genetic Profile ◽  
Breeding Values ◽  
Cluster Analyses ◽  
Scrotal Circumference ◽  
Breeding Programmes ◽  
Economic Selection

Abstract In breeding programmes, the genetic selection process is based on the prediction of animal breeding values, and its results may vary according to the employed selection method. The current study developed an economic selection index for animals of the Angus breed; performed cluster analyses using the breeding values in order to evaluate the genetic profile of the animals candidates to selection, and compared the obtained results between the economic selection index and the cluster analyses. The evaluated traits included weaning weight, 18-month weight, scrotal circumference, fat thickness and ribeye area. Economic values were obtained using bioeconomic modelling, simulating a complete cycle production system of beef cattle breeds in Brazil, and the selection objective were the weaning rate and slaughter weight. The chosen selection index was composed of all of the traits used as selection criteria for the simulated production system. During the cluster analyses, the population was divided into two to four groups, in which the groupings containing potential animals were assessed. The animals of the grouping which was used for comparison with the selection index were identified, and most of the bulls that were included in the index were among the best in the analysed group. These results suggest that the cluster analyses can be used as a tool for the selection of animals to be used as parents for future generations.

The incorporation of fertility indices in genetic improvement programmes

2001 ◽  
Vol 26 (1) ◽  
pp. 237-249 ◽  
Author(s):  
J.E. Pryce ◽  
R.F. Veerkamp
Keyword(s):  
Genetic Variance ◽  
Selection Index ◽  
Genetic Correlations ◽  
Live Weight ◽  
Parameter Estimates ◽  
Phenotypic Variance ◽  
Production Traits ◽  
Genetic Progress ◽  
Detection Rates ◽  
Days Open

AbstractIn recent years there has been considerable genetic progress in milk production. Yet, increases in yield have been accompanied by an apparent lengthening of calving intervals, days open, days to first heat and a decline in conception rates, which appears to be both at the genetic and phenotypic level. Fertility has a high relative economic value compared to production traits such as protein, making it attractive to include in a breeding programme. To do this there needs to be genetic variance in fertility. Measures of fertility calculated from service dates have a small genetic compared to phenotypic variance, hence heritability estimates are small, typically less than 5%, although coefficients of genetic variance are comparable to those of production traits. Heritabilities of commencement of luteal activity determined using progesterone profiles are generally higher, and have been reported as being from 0.16 to 0.28, which could be because of a more precise quantification of genetic variance, as management influences such as delaying insemination and heat detection rates are excluded. However, it might not be the use of progesterone profiles alone, as days to first heat observed by farm staff has a heritability of 0.15. The most efficient way to breed for improved fertility is to construct a selection index using the genetic and phenotypic parameter estimates of all traits of interest in addition to their respective economic values. Index traits for fertility could include measures such as calving interval, days open, days to first service, or days to first heat but there may also be alternative measures. Examples include traits related to energy balance, such as live weight and condition score (change), both of which have higher heritabilities than fertility measures and have genetic correlations of sufficient magnitude to make genetic progress by using them feasible. To redress the balance between fertility and production, some countries already publish genetic evaluations of fertility including: Denmark, Finland, France, Germany, Israel, The Netherlands, Norway and Sweden.

Sign in / Sign up

Export Citation Format

Share Document