scholarly journals Marker-assisted selection using ridge regression

2000 ◽  
Vol 75 (2) ◽  
pp. 249-252 ◽  
Author(s):  
JOHN C. WHITTAKER ◽  
ROBIN THOMPSON ◽  
MIKE C. DENHAM
Keyword(s):  
Linear Regression ◽  
Ridge Regression ◽  
Marker Assisted Selection ◽  
Quantitative Traits ◽  
Selection Response ◽  
Inbred Lines ◽  
Response To Selection ◽  
Satisfactory Method ◽  
The Mean ◽  
Selection Of

In crosses between inbred lines, linear regression can be used to estimate the correlation of markers with a trait of interest; these marker effects then allow marker assisted selection (MAS) for quantitative traits. Usually a subset of markers to include in the model must be selected: no completely satisfactory method of doing this exists. We show that replacing this selection of markers by ridge regression can improve the mean response to selection and reduce the variability of selection response.

scholarly journals Optimal weighting of information in marker-assisted selection

1997 ◽  
Vol 69 (2) ◽  
pp. 137-144 ◽  
Author(s):  
J. C. WHITTAKER ◽  
C. S. HALEY ◽  
R. THOMPSON
Keyword(s):  
Linear Regression ◽  
Marker Assisted Selection ◽  
Quantitative Traits ◽  
Genetic Variance ◽  
Cross Validation ◽  
Inbred Lines ◽  
Response To Selection ◽  
Phenotypic Information ◽  
Optimal Weighting ◽  
Marker Information

In crosses between inbred lines linear regression can be used to estimate marker effects; these marker effects then allow marker-assisted selection (MAS) for quantitative traits. Weighting of marker and phenotypic information in MAS requires estimation of genetic variance associated with the markers: the usual estimators are biased, resulting in too much weight being placed on marker information relative to phenotypic information. In this paper we develop a cross-validation method to remove this bias, and show by simulation that response to selection using this method is almost as high as that achieved using optimal weighting of marker and phenotypic information.

scholarly journals Marker assisted selection of new high oleic and low linolenic winter oilseed rape (Brassica napus L.) inbred lines revealing good agricultural value

PLoS ONE ◽  
2020 ◽  
Vol 15 (6) ◽  
pp. e0233959 ◽  
Author(s):  
Stanisław Spasibionek ◽  
Katarzyna Mikołajczyk ◽  
Hanna Ćwiek–Kupczyńska ◽  
Teresa Piętka ◽  
Krystyna Krótka ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Oilseed Rape ◽  
Marker Assisted Selection ◽  
Inbred Lines ◽  
Winter Oilseed Rape ◽  
Brassica Napus L ◽  
High Oleic ◽  
Low Linolenic ◽  
Selection Of

Choosing trial sites to maximize selection response for grain yield in spring wheat

1981 ◽  
Vol 32 (3) ◽  
pp. 411 ◽  
Author(s):  
DG Pederson ◽  
AJ Rathjen
Keyword(s):  
South Australia ◽  
Selection Response ◽  
Wheat Breeding ◽  
Correlated Response ◽  
Response To Selection ◽  
Selection Scheme ◽  
Experiment Station ◽  
Optimum Selection ◽  
Coefficients Of Variation ◽  
Selection Of

Nine sites used in a wheat breeding programme in South Australia were investigated. Of the six major sites, four occupy farmers' fields and two are located on experiment stations. The data analysed comprised grain yields of 31 genotypes grown in 31 trials over a 5-year period. Relative to that grown at non-station sites, wheat grown at the experiment-station sites generally had higher mean yields, higher coefficients of variation, and lower heritabilities. Data from a set of independently conducted trials were used to estimate the true yields of the 31 genotypes. A heritability of the correlated response to selection was then calculated for each breeding trial, and was generally found to be low for the experiment-station sites. Further investigation showed that the non-station sites are suitable for the selection of genotypes intended for low-yielding environments, and the station sites are better suited for the selection of genotypes intended for high-yielding environments. The optimum selection scheme was found to consist of several unreplicated trials per year, and at least four trials per year are necessary to avoid the possibility of a negative heritability of the correlated response to selection.

A comparison of alternative nucleus breeding systems and a sire referencing scheme for sheep improvement

1996 ◽  
Vol 62 (2) ◽  
pp. 265-270 ◽  
Author(s):  
J. A. Roden
Keyword(s):  
Selection Response ◽  
Best Linear Unbiased Prediction ◽  
Breeding Systems ◽  
Linear Unbiased Prediction ◽  
Sequential Selection ◽  
Best Linear Unbiased ◽  
The Mean ◽  
Nucleus Breeding ◽  
Open Nucleus ◽  
Selection Of

AbstractStochastic simulation was used to compare selection response and rate of inbreeding in four nucleus breeding systems and a sire referencing scheme for sheep: an open nucleus system (ONS), an open nucleus system with sequential selection of the nucleus (ONS-S), a sire referencing scheme (SRS) and a dispersed open nucleus system (DONS). Selection was based on best linear unbiased prediction of breeding values for a single trait measurable on all individuals prior to selection. Selection in a population of 1200 ewes equally divided into 10 flocks was simulated over a 15-year period. The mean rate of genetic gain was proportionately about 0-15 higher in ONS-S and DONS compared with ONS and SRS. The rate of inbreeding in SRS was considerably lower and in ONS-S, considerably higher, than in the other systems. The level of prolificacy in the population did not influence the relative ranking of the breeding systems but may have implications for their optimal structure.

Effectiveness of predictive markers for marker assisted selection of pro-vitamin A carotenoids in medium-late maturing maize (Zea mays L.) inbred lines

2018 ◽  
Vol 79 ◽  
pp. 27-34 ◽  
Author(s):  
Sara Gebremeskel ◽  
Ana Luísa Garcia-Oliveira ◽  
Abebe Menkir ◽  
Victor Adetimirin ◽  
Melaku Gedil
Keyword(s):  
Zea Mays ◽  
Vitamin A ◽  
Marker Assisted Selection ◽  
Zea Mays L ◽  
Inbred Lines ◽  
Predictive Markers ◽  
Selection Of

scholarly journals The selective regularization of a linear regression model

2021 ◽  
Vol 2099 (1) ◽  
pp. 012024
Author(s):  
V N Lutay ◽  
N S Khusainov
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Ridge Regression ◽  
Triangular Decomposition ◽  
System Matrix ◽  
Original Dataset ◽  
The Matrix ◽  
Matrix Conditioning ◽  
Selection Of

Abstract This paper discusses constructing a linear regression model with regularization of the system matrix of normal equations. In contrast to the conventional ridge regression, where positive parameters are added to all diagonal terms of a matrix, in the method proposed only those matrix diagonal entries that correspond to the data with a high correlation are increased. This leads to a decrease in the matrix conditioning and, therefore, to a decrease in the corresponding coefficients of the regression equation. The selection of the entries to be increased is based on the triangular decomposition of the correlation matrix of the original dataset. The effectiveness of the method is tested on a known dataset, and it is performed not only with a ridge regression, but also with the results of applying the widespread algorithms LARS and Lasso.

scholarly journals Marker-assisted Selection in Fish: A Review

2019 ◽  
pp. 1-11 ◽  
Author(s):  
F. Eze
Keyword(s):  
Marker Assisted Selection ◽  
Quantitative Traits ◽  
Selective Breeding ◽  
Breeding Programme ◽  
Genetic Potential ◽  
Breeding Populations ◽  
Trait Improvement ◽  
Performance Traits ◽  
Selective Breeding Programme ◽  
Selection Of

The important economical traits like body growth, resistance to diseases, meat quality, etc. highly influence the profitability of food animals including fishes. The main target of every selective breeding programme is to produce improved traits offspring’s. However, improvement of performance traits through traditional phenotype-based selection needs several generations to optimise these characters. Marker-Assisted Selection (MAS) is a type of indirect method of selection of better performing breeding individuals. MAS is beneficial when the traits are difficult, expensive to measure and has both low heritability and recessive traits. MAS facilitates the exploitation of existing genetic diversity in breeding populations and can be used to improve desirable traits in livestock. MAS depends on identifying the link between a genetic marker and Quantitative Traits Loci (QTL). The distance between marker and target traits determines the association of the marker with the QTL. After identifying the markers linked to QTL, they can be used in the selective breeding programme to select the brooders having better genetic potential for the targeted trait. Improvement of performance traits through MAS is fast and more accurate and allows us to understand the genetic mechanism affecting performance traits.

scholarly journals Application of molecular markers in sunflower breeding

Genetika ◽  
2007 ◽  
Vol 39 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Dejana Saftic-Pankovic
Keyword(s):  
Molecular Markers ◽  
Ssr Markers ◽  
Marker Assisted Selection ◽  
Rapd Markers ◽  
Inbred Lines ◽  
Vegetable Crops ◽  
Large Variability ◽  
Parental Lines ◽  
Early Phases ◽  
Selection Of

The results of the application of molecular markers in sunflower breeding obtained in the Institute of Field and Vegetable Crops in the last decade are reviewed. Our results on genetic distance (GD=7-75%) between sunflower inbred lines obtained with RAPD and SSR markers, indicate large variability and provide important information for the selection of parental lines for future crosses. Interspecific hybridization is often used in sunflower breeding. As only some populations of H. giganteus and H. maximiliani are resistant to sunflower diseases, the investigation of genetic variability in/between two species is of interest. The results obtained with SSR markers are presented. The successful hybridization between H. rigidus and H. annuus was confirmed with RAPD markers, and the variability between F1 and BC1F1 plants is discussed. Desirable alleles and haplotypes can be detected with molecular markers both in early phases of plant development and in early phases of the production of improved lines, which reduces or completely eliminates the large number of testing cycles for desirable phenotypes. CAPS markers for resistance to downy mildew, that can be used in marker assisted selection are presented. .

Divergent selection for retrieving behavior in mice

1973 ◽  
Vol 51 (1) ◽  
pp. 21-26 ◽  
Author(s):  
J. F. Hurnik ◽  
E. D. Bailey ◽  
F. N. Jerome
Keyword(s):  
Linear Regression ◽  
Inbred Strains ◽  
Divergent Selection ◽  
Regression Functions ◽  
Regression Learning ◽  
The Mean ◽  
The Difference ◽  
Single Regression ◽  
Selection Of

To prove the involvement of genetic factors in retrieving activity, divergent selection was applied for five generations of mice. The mice originated from two highly inbred strains, SWR and C57Bl. In the parental generation, an equal number of reciprocal matings were made between the lines. The selection started in F2 generation. The selection of offspring in both directions was based on the mean performance of the mothers in six trials.Multivariance analysis showed positive response to the selection and confirmed a genetic contribution to the determination of retrieving activity. The estimate of realized heritability, adjusted for inbreeding effects, was lower in the group selected for fast retrieving (h2 = 0.26) and higher in the group selected for slow retrieving (h2 = 0.44). The difference between these coefficients was nonsignificant.In single regression functions on trials, only the linear regression was significant. The linear regression (learning rate) was more pronounced in the group selected for fast retrieving. Within groups, the regression on trials was similar during all five selected generations.

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