scholarly journals Additive and Dominance Genomic Analysis for Litter Size in Purebred and Crossbred Iberian Pigs

Genes ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 12
Author(s):  
Houssemeddine Srihi ◽  
José Luis Noguera ◽  
Victoria Topayan ◽  
Melani Martín de Hijas ◽  
Noelia Ibañez-Escriche ◽  
...  
Keyword(s):  
Litter Size ◽  
Genetic Variance ◽  
Mixed Model ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Genomic Analysis ◽  
Gxe Interaction ◽  
Genomic Regions ◽  
Additive Genetic Effects ◽  
Selection Of

INGA FOOD S. A., as a Spanish company that produces and commercializes fattened pigs, has produced a hybrid Iberian sow called CASTÚA by crossing the Retinto and Entrepelado varieties. The selection of the parental populations is based on selection criteria calculated from purebred information, under the assumption that the genetic correlation between purebred and crossbred performance is high; however, these correlations can be less than one because of a GxE interaction or the presence of non-additive genetic effects. This study estimated the additive and dominance variances of the purebred and crossbred populations for litter size, and calculated the additive genetic correlations between the purebred and crossbred performances. The dataset consisted of 2030 litters from the Entrepelado population, 1977 litters from the Retinto population, and 1958 litters from the crossbred population. The individuals were genotyped with a GeneSeek® GGP Porcine70K HDchip. The model of analysis was a ‘biological’ multivariate mixed model that included additive and dominance SNP effects. The estimates of the additive genotypic variance for the total number born (TNB) were 0.248, 0.282 and 0.546 for the Entrepelado, Retinto and Crossbred populations, respectively. The estimates of the dominance genotypic variances were 0.177, 0.172 and 0.262 for the Entrepelado, Retinto and Crossbred populations. The results for the number born alive (NBA) were similar. The genetic correlations between the purebred and crossbred performance for TNB and NBA—between the brackets—were 0.663 in the Entrepelado and 0.881 in Retinto poplulations. After backsolving to obtain estimates of the SNP effects, the additive genetic variance associated with genomic regions containing 30 SNPs was estimated, and we identified four genomic regions that each explained > 2% of the additive genetic variance in chromosomes (SSC) 6, 8 and 12: one region in SSC6, two regions in SSC8, and one region in SSC12.

scholarly journals Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Miguel Gozalo-Marcilla ◽  
Jaap Buntjer ◽  
Martin Johnsson ◽  
Lorena Batista ◽  
Federico Diez ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genetic Variance ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Insulin Signalling ◽  
Additive Genetic Variance ◽  
Genomic Region ◽  
Carcass Composition ◽  
Backfat Thickness ◽  
Genomic Regions

Abstract Background Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds. Methods Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10–6 and used to define genomic regions of interest. The proportion of genetic variance explained by a genomic region was estimated using a ridge regression model. Results We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN. Conclusions Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis.

Multisite genetic parameter estimates from a Callitropsis nootkatensis diallel study with clonally replicated progeny

2015 ◽  
Vol 45 (6) ◽  
pp. 689-697 ◽  
Author(s):  
John H. Russell ◽  
João Costa e Silva ◽  
Brian S. Baltunis
Keyword(s):  
Genetic Variance ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Additive Genetic Variance ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Parameter Estimates ◽  
Narrow Sense ◽  
Spatially Correlated ◽  
Crown Form

Clonally replicated Callitropsis nootkatensis (D. Don) D.P. Little progeny from partial diallels were established in nine trials on coastal British Columbia, Canada. The trials were assessed for height, diameter, and crown form at age 12 years. An individual-genotype, linear mixed model with spatially correlated residuals was used to estimate the variance components and related genetic parameters. The majority of the estimated genetic variance for all traits was additive, and nonadditive genetic variance was predominantly due to dominance effects. Narrow-sense heritabilities for height and diameter at individual sites varied from 0.07 to 0.39, whereas for crown form, they were all less than 0.1. Dominance and epistasis ratios were, for the most part, lower than narrow-sense heritabilities. Common across-site additive and nonadditive genetic correlations were strongly positive and not significantly different from 1.0 for the majority of traits across sites within a series. Significant levels of additive genetic variance, coupled with insignificant to low nonadditive genetic variance for growth and crown form, would seem to be contrary to developing a clonal testing and deployment program. However, the lack of viable orchard seed and the faster delivery of genetic gain to reforestation, as well as more accurate forward selections based on additive genetic effects, makes this strategy viable for C. nootkatensis.

scholarly journals Selection strategies of segregant soybean populations for resistance to Asian rust

2009 ◽  
Vol 44 (11) ◽  
pp. 1452-1459 ◽  
Author(s):  
Aliny Simony Ribeiro ◽  
José Francisco Ferraz de Toledo ◽  
Magno Antonio Patto Ramalho
Keyword(s):  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Infected Leaf ◽  
Good Resistance ◽  
Narrow Sense Heritability ◽  
Growing Seasons ◽  
Selection Strategies ◽  
Line Selection ◽  
Soybean Resistance ◽  
Selection Of

The objective of this work was to identify the best selection strategies for the more promising parental combinations to obtain lines with good resistance to soybean Asian rust (Phakopsora pachyrhizi). Two experiments were carried out in the field during the 2006/2007 and 2007/2008 growing seasons, to determine the percentage of infected leaf area of individual plants of five parents and their segregant F2 and F3 populations. The data obtained indicates that additive genetic variance predominates in the control of soybean resistance to Asian rust, and that the year and time of assessment do not significantly influence the estimates of the genetic parameters obtained. The narrow-sense heritability (h²r) ranged from 23.12 to 55.83%, and indicates the possibility of successful selection of resistant individuals in the early generations of the breeding program. All the procedures used to select the most promising populations to generate superior inbred lines for resistance to P. pachyrhizi presented similar results and identified the BR01-18437 x BRS 232 population as the best for inbred line selection.

scholarly journals Estimate of genetic parameters and predicted gains with early selection of physic nut families

2012 ◽  
Vol 36 (2) ◽  
pp. 163-170 ◽  
Author(s):  
Bruno Galvêas Laviola ◽  
Alexandre Alonso Alves ◽  
Fábio de Lima Gurgel ◽  
Tatiana Barbosa Rosado ◽  
Rhayanne Dias Costa ◽  
...  
Keyword(s):  
Grain Yield ◽  
Genetic Parameters ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Biodiesel Production ◽  
Early Selection ◽  
Physic Nut ◽  
Genetic Gains ◽  
Canopy Volume ◽  
Selection Of

An initial evaluation of early selection of physic nut genotypes based on phenotypic data is presented. In order to predict the genetic gains with early selection, genetic parameters, e.g. additive genetic variance, were first obtained for grain yield along with other numerous traits. The results demonstrated that additive genetic variance exists not only for grain yield, which is considered to be the most important trait for oil and biodiesel production, but also for numerous other traits. The predicted genetic gains for grain yield, considering the selection of the 30, 20, 10 and 5 best families in the second crop year are respectively, 40.47, 48.43, 61.78 and 70.28%. With the selection of highly yielding physic nut genotypes indirectly genotypes with enhanced volume would be also selected, because yield exhibits moderate to high genetic correlations with height e canopy volume. The results here presented demonstrate the potential of the population gathered in the Brazilian physic nut germplasm bank for genetic breeding purposes and that superior physic nut families can be selected with high accuracy based on the evaluation of its second crop.

Genetic and environmental causes of variation in birth weight of Black Bengal goats

1970 ◽  
Vol 74 (3) ◽  
pp. 409-414 ◽  
Author(s):  
S. K. Moulick ◽  
O. Syrstad
Keyword(s):  
Body Weight ◽  
Birth Weight ◽  
Litter Size ◽  
Partial Correlation ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Maternal Environment ◽  
Breeding Station ◽  
Environmental Causes ◽  
Partial Correlation Coefficient

SUMMARYAn investigation on the different environmental and genetic causes of variation in the birth weight of Black Bengal goats was conducted at the Central Livestock Research-cum-Breeding Station, Haringhata, India. The data consisted of 1375 birth weight records of kids from 284 does and 20 bucks during the period from 1955 to 1961. The goats were maintained under standard farm management throughout the period.Year had significant effect on birth weight, while the effect of season was insignificant. The interaction was, however, significant. Male kids were significantly heavier at birth than the females. Age of dam and litter size also caused significant variation in birth weight of kids.From paternal half-sib analysis the heritability of birth weight was estimated to be 0·01. Full sib and maternal half sib analyses estimated the maternal environment common to litter mates to account for 60 % of the variance, out of which 25 % were due to permanent differences between dams. The remaining 39 % were attributed to individual environment, including most of the non-additive genetic variance. The heritability of maternal environment was estimated to be 0·2.The partial correlation coefficient between birth weight of kids and post-kidding body weight of their dam, independent of litter size and age of dam, was 0·175. Thus, body size of dam, as indicated by post kidding body weight, did not reveal much information about maternal environment.

scholarly journals Temporal and genomic analysis of additive genetic variance in breeding programmes

2020 ◽  
Author(s):  
Letícia A. de C. Lara ◽  
Ivan Pocrnic ◽  
R. Chris Gaynor ◽  
Gregor Gorjanc
Keyword(s):  
Linkage Disequilibrium ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Model Fitting ◽  
Genomic Analysis ◽  
Principal Component ◽  
Complex Trait ◽  
Breeding Programme ◽  
Empirical Bayesian ◽  
Genomic Analyses

AbstractThis study demonstrates a framework for temporal and genomic analysis of additive genetic variance in a breeding programme. Traditionally we used specific experimental designs to estimate genetic variance for a specific group of individuals and a general pedigree-based model to estimate genetic variance for pedigree founders. However, with the pedigree-based model we can also analyse temporal changes in genetic variance by summarising sampled realisations of genetic values from a fitted model. Here we extend this analysis to a marker-based model and build a framework for temporal and genomic analyses of genetic variance. The framework involves three steps: (i) fitting a marker-based model to data, (ii) sampling realisations of marker effects from the fitted model and for each sample calculating realisations of genetic values, and (iii) calculating variance of the sampled genetic values by time and genome partitions. Genome partitions enable estimation of contributions from chromosomes and chromosome pairs and genic and linkage-disequilibrium variances. We demonstrate the framework by analysing data from a simulated breeding programme involving a complex trait with additive gene action. We use the full Bayesian and empirical Bayesian approaches to account for the uncertainty due to model fitting. We also evaluate the use of principal component approximation. Results show good concordance between the simulated and estimated variances for temporal and genomic analyses and give insight into genetic processes. For example, we observe reduction of genic variance due to selection and drift and buildup of negative linkage-disequilibrium (the Bulmer effect) due to directional selection. In this study the popular empirical Bayesian approach estimated the variances well but it underestimated uncertainty of the estimates. The principal components approximation biases estimates, in particular for the genic variance. This study gives breeders a framework to analyse genetic variance and its components in different stages of a programme and over time.

scholarly journals Estimation of variance components for bodyweight of grasscutters using expectation maximization algorithm of restricted maximum likelihood

2020 ◽  
Vol 44 (5) ◽  
pp. 5-8
Author(s):  
I. Udeh
Keyword(s):  
Body Weight ◽  
Maximum Likelihood ◽  
Expectation Maximization ◽  
Variance Components ◽  
Genetic Variance ◽  
Phenotypic Variability ◽  
Additive Genetic Variance ◽  
Expectation Maximization Algorithm ◽  
Estimation Of Variance ◽  
Selection Of

The objective of this study was to estimate the variance components and heritability of bodyweight of grasscutters at 4, 6 and 8 months of age using EM algorithm of REML procedures. The data used for the study were obtained from the bodyweight records of 20 grasscutters from four families at 4, 6 and 8 months of age. The heritability of bodyweight of grasscutters at 4, 6 and 8 months of age were 0.14, 0.10 and 0.12 respectively. This implies that about 10 – 14 % of the phenotypic variability of body weight in this grasscutter population was accounted by additive genetic variance while environmental and gene combination variance made a larger contribution. The implication is that selection of grasscutters in this population should not be based on the information on the animals alone but also information fromits relatives.

Measurement of fleece wettability in sheep and its relationship to susceptibility to fleece rot and blowfly strike

1982 ◽  
Vol 33 (1) ◽  
pp. 141 ◽  
Author(s):  
L Pascoe
Keyword(s):  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Economic Importance ◽  
Correlated Response ◽  
Response To Selection ◽  
Significant Incidence ◽  
The Mean ◽  
Selection For ◽  
The One

Fleece wettability in sheep is a character believed to be related to susceptibility to fleece rot and blowfly strike. The present study was undertaken to investigate that hypothesis and to assess wettability as a possible character for a selection program. Wool samples were taken from two flocks which had been subject to selection for wool quality and resistance to fleece rot and a third flock which was unselected. The wettabilities of about 800 samples were determined. The results were found to be repeatable and the technique was capable of distinguishing between sheep. Some problems of measurement are discussed. In the one flock with a significant incidence of fleece rot, susceptibility to fleece rot was found to be associated with higher wettabilities. The mean wettability and the variance were found to be significantly higher in the unselected flock than in the two selected flocks. The heritability of wettability was estimated in the two selected flocks and was found to be low. It is argued that there is likely to be more additive genetic variance in the unselected flock and that the observed difference in wettability was due to a correlated response to selection for resistance to fleece rot. It is considered that further work on the heritability of wettability and its genetic correlations with other characters of economic importance could be fruitful.

scholarly journals Variabilitatea şi heritabilitatea vigorii boabelor de grâu comun la interacţiunea cu Drechslera Sorokiniana

2020 ◽  
Author(s):  
Galina Lupascu ◽  
◽  
Svetlana Gavzer ◽  
Keyword(s):  
Common Wheat ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Broad Sense ◽  
Genetic Progress ◽  
Vigor Index ◽  
Seedling Length ◽  
Selection Of

The article presents data on the effects of the interaction of common wheat with the fungus Drechslera sorokiniana on grain vigor. Its differentiated action on germination and seedling length (LP) was found. The vigor index (VI) depended more on LP (r = 0.90 *) than on the germination 278 level (r = 0.52 *, p≤0.05). The coefficient of heritability in the broad sense (h2) was 71.3% for LP and 60.1% – for VI. The association of h2 and genetic progress with high values reveals the pronounced contribution of additive genetic variance in the control of the vigor index, which offers increased opportunities in the selection of wheat plants resistant to this pathogen in restricted terms.

scholarly journals Using the best linear predictor (BLP) in the selection between and among half-sib progenies of the CMS-39 maize population

1997 ◽  
Vol 20 (4) ◽  
pp. 683-690
Author(s):  
Cleso Antônio Patto Pacheco ◽  
José Ivo Ribeiro Júnior ◽  
Cosme Damião Cruz
Keyword(s):  
Variance Component ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
The Other ◽  
Linear Predictor ◽  
Selection Cycle ◽  
Maize Population ◽  
Best Linear Predictor ◽  
Selection Of

Data of corn ear production (kg/ha) of 196 half-sib progenies (HSP) of the maize population CMS-39 obtained from experiments carried out in four environments were used to adapt and assess the BLP method (best linear predictor) in comparison with to the selection among and within half-sib progenies (SAWHSP). The 196 HSP of the CMS-39 population developed by the National Center for Maize and Sorghum Research (CNPMS-EMBRAPA) were related through their pedigree with the recombined progenies of the previous selection cycle. The two methodologies used for the selection of the twenty best half-sib progenies, BLP and SAWHSP, led to similar expected genetic gains. There was a tendency in the BLP methodology to select a greater number of related progenies because of the previous generation (pedigree) than the other method. This implies that greater care with the effective size of the population must be taken with this method. The SAWHSP methodology was efficient in isolating the additive genetic variance component from the phenotypic component. The pedigree system, although unnecessary for the routine use of the SAWHSP methodology, allowed the prediction of an increase in the inbreeding of the population in the long term SAWHSP selection when recombination is simultaneous to creation of new progenies.

Sign in / Sign up

Export Citation Format

Share Document