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Anna Wolc,
Chris Stricker, Jesus Arango,
Petek Settar,
Janet E Fulton,
Neil P O’Sullivan,
Rudolf Preisinger,
David Habier,
Rohan Fernando,
Dorian J Garrick,
Susan J Lamont,
Jack CM Dekkers
[show abstract]
[hide abstract]
ABSTRACT: BackgroundGenomic selection involves breeding value estimation of selection candidates based on high-density SNP genotypes. To quantify
the potential benefit of genomic selection, accuracies of estimated breeding values (EBV) obtained with different methods
using pedigree or high-density SNP genotypes were evaluated and compared in a commercial layer chicken breeding line.
MethodsThe following traits were analyzed: egg production, egg weight, egg color, shell strength, age at sexual maturity, body weight,
albumen height, and yolk weight. Predictions appropriate for early or late selection were compared. A total of 2,708 birds
were genotyped for 23,356 segregating SNP, including 1,563 females with records. Phenotypes on relatives without genotypes
were incorporated in the analysis (in total 13,049 production records).
The data were analyzed with a Reduced Animal Model using a relationship matrix based on pedigree data or on marker genotypes
and with a Bayesian method using model averaging. Using a validation set that consisted of individuals from the generation
following training, these methods were compared by correlating EBV with phenotypes corrected for fixed effects, selecting
the top 30 individuals based on EBV and evaluating their mean phenotype, and by regressing phenotypes on EBV.
ResultsUsing high-density SNP genotypes increased accuracies of EBV up to two-fold for selection at an early age and by up to 88%
for selection at a later age. Accuracy increases at an early age can be mostly attributed to improved estimates of parental
EBV for shell quality and egg production, while for other egg quality traits it is mostly due to improved estimates of Mendelian
sampling effects. A relatively small number of markers was sufficient to explain most of the genetic variation for egg weight
and body weight.
Genetics Selection Evolution 04/2012; 43(1):1-9. · 2.88 Impact Factor
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[show abstract]
[hide abstract]
ABSTRACT: The predictive ability of genomic estimated breeding values (GEBV) originates both from associations between high-density markers and QTL (Quantitative Trait Loci) and from pedigree information. Thus, GEBV are expected to provide more persistent accuracy over successive generations than breeding values estimated using pedigree-based methods. The objective of this study was to evaluate the accuracy of GEBV in a closed population of layer chickens and to quantify their persistence over five successive generations using marker or pedigree information.
The training data consisted of 16 traits and 777 genotyped animals from two generations of a brown-egg layer breeding line, 295 of which had individual phenotype records, while others had phenotypes on 2,738 non-genotyped relatives, or similar data accumulated over up to five generations. Validation data included phenotyped and genotyped birds from five subsequent generations (on average 306 birds/generation). Birds were genotyped for 23,356 segregating SNP. Animal models using genomic or pedigree relationship matrices and Bayesian model averaging methods were used for training analyses. Accuracy was evaluated as the correlation between EBV and phenotype in validation divided by the square root of trait heritability.
Pedigree relationships in outbred populations are reduced by 50% at each meiosis, therefore accuracy is expected to decrease by the square root of 0.5 every generation, as observed for pedigree-based EBV (Estimated Breeding Values). In contrast the GEBV accuracy was more persistent, although the drop in accuracy was substantial in the first generation. Traits that were considered to be influenced by fewer QTL and to have a higher heritability maintained a higher GEBV accuracy over generations. In conclusion, GEBV capture information beyond pedigree relationships, but retraining every generation is recommended for genomic selection in closed breeding populations.
Genetics Selection Evolution 06/2011; 43:23. · 2.88 Impact Factor
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Mervi Honkatukia,
Maria Tuiskula-Haavisto,
Virpi Ahola,
Pekka Uimari,
Matthias Schmutz,
Rudolf Preisinger,
David Cavero,
Pia Vennerström, Jesus Arango,
Neil O'Sullivan,
Janet Fulton,
Johanna Vilkki
[show abstract]
[hide abstract]
ABSTRACT: Occurrence of blood and meat inclusions is an internal egg quality defect. Mass candling reveals most of the spots, but because brown eggshell hampers selection in brown chicken lines it has not been possible to eliminate the defect by selection. Estimated frequency of blood and meat inclusions in brown layers is about 18% whereas it is 0.5% in white egg layers. Several factors are known to increase the incidence of this fault: genetic background, low level of vitamin A and/or D, stress or infections, for instance. To study the genetic background of the defect, a mapping population of 1599 F2 hens from a cross of White Rock and Rhode Island Red lines was set up.
Our histopathological analyses show that blood spots consist of mainly erythrocytes and that meat spots are accumulations of necrotic material. Linkage analysis of 27 chromosomes with 162 microsatellite markers revealed one significant quantitative trait locus (QTL) affecting blood spot and meat spot frequency. We sequenced a fragment of a candidate gene within the region, ZO-2, coding for a tight junction protein. Nine polymorphisms were detected and two of them were included in fine-mapping and association analysis. Fine-mapping defined the QTL result. To further verify the QTL, association analyses were carried out in two independent commercial breeding lines with the marker MCW241 and surrounding SNPs. Association was found mainly in a 0.8 Mb-wide chromosomal area on GGAZ.
There was good agreement between the location of the QTL region on chromosome Z and the association results in the commercial breeds analyzed. Variations found in tight junction protein ZO-2 and microRNA gga-mir-1556 may predispose egg layers to blood and meat spot defects. This paper describes the first results of detailed QTL analyses of the blood and meat spots trait(s) in chickens.
BMC Genetics 06/2011; 12:55. · 2.47 Impact Factor
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Anna Wolc,
Chris Stricker, Jesus Arango,
Petek Settar,
Janet Fulton,
Neil O&apos,
Sullivan,
Rudolf Preisinger,
David Habier,
Rohan Fernando,
Dorian Garrick,
Susan Lamont,
Jack Dekkers
[show abstract]
[hide abstract]
ABSTRACT: Abstract Background Genomic selection involves breeding value estimation of selection candidates based on high-density SNP genotypes. To quantify the potential benefit of genomic selection, accuracies of estimated breeding values (EBV) obtained with different methods using pedigree or high-density SNP genotypes were evaluated and compared in a commercial layer chicken breeding line. Methods The following traits were analyzed: egg production, egg weight, egg color, shell strength, age at sexual maturity, body weight, albumen height, and yolk weight. Predictions appropriate for early or late selection were compared. A total of 2,708 birds were genotyped for 23,356 segregating SNP, including 1,563 females with records. Phenotypes on relatives without genotypes were incorporated in the analysis (in total 13,049 production records). The data were analyzed with a Reduced Animal Model using a relationship matrix based on pedigree data or on marker genotypes and with a Bayesian method using model averaging. Using a validation set that consisted of individuals from the generation following training, these methods were compared by correlating EBV with phenotypes corrected for fixed effects, selecting the top 30 individuals based on EBV and evaluating their mean phenotype, and by regressing phenotypes on EBV. Results Using high-density SNP genotypes increased accuracies of EBV up to two-fold for selection at an early age and by up to 88% for selection at a later age. Accuracy increases at an early age can be mostly attributed to improved estimates of parental EBV for shell quality and egg production, while for other egg quality traits it is mostly due to improved estimates of Mendelian sampling effects. A relatively small number of markers was sufficient to explain most of the genetic variation for egg weight and body weight.
Genetics Selection Evolution. 01/2011;
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Behnam Abasht,
Erin Sandford, Jesus Arango,
Petek Settar,
Janet Fulton,
Neil O'Sullivan,
Abebe Hassen,
David Habier,
Rohan Fernando,
Jack Dekkers,
Susan Lamont
[show abstract]
[hide abstract]
ABSTRACT: Abstract
Background
The genome sequence and a high-density SNP map are now available for the chicken and can be used to identify genetic markers for use in marker-assisted selection (MAS). Effective MAS requires high linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), and sustained marker-QTL LD over generations. This study used data from a 3,000 SNP panel to assess the level and consistency of LD between single nucleotide polymorphisms (SNPs) over consecutive years in two egg-layer chicken lines, and analyzed one line by two methods (SNP-wise association and genome-wise Bayesian analysis) to identify markers associated with egg-quality and egg-production phenotypes.
Results
The LD between markers pairs was high at short distances (r<sup>2 </sup>> 0.2 at < 2 Mb) and remained high after one generation (correlations of 0.80 to 0.92 at < 5 Mb) in both lines. Single- and 3-SNP regression analyses using a mixed model with SNP as fixed effect resulted in 159 and 76 significant tests (P < 0.01), respectively, across 12 traits. A Bayesian analysis called BayesB, that fits all SNPs simultaneously as random effects and uses model averaging procedures, identified 33 SNPs that were included in the model >20% of the time ( φ > 0.2) and an additional ten 3-SNP windows that had a sum of φ greater than 0.35. Generally, SNPs included in the Bayesian model also had a small P -value in the 1-SNP analyses.
Conclusion
High LD correlations between markers at short distances across two generations indicate that such markers will retain high LD with linked QTL and be effective for MAS. The different association analysis methods used provided consistent results. Multiple single SNPs and 3-SNP windows were significantly associated with egg-related traits, providing genomic positions of QTL that can be useful for both MAS and to identify causal mutations.
BMC Genomics. 01/2009;
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Behnam Abasht,
Erin Sandford, Jesus Arango,
Petek Settar,
Janet E Fulton,
Neil P O'Sullivan,
Abebe Hassen,
David Habier,
Rohan L Fernando,
Jack C M Dekkers,
Susan J Lamont
[show abstract]
[hide abstract]
ABSTRACT: The genome sequence and a high-density SNP map are now available for the chicken and can be used to identify genetic markers for use in marker-assisted selection (MAS). Effective MAS requires high linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), and sustained marker-QTL LD over generations. This study used data from a 3,000 SNP panel to assess the level and consistency of LD between single nucleotide polymorphisms (SNPs) over consecutive years in two egg-layer chicken lines, and analyzed one line by two methods (SNP-wise association and genome-wise Bayesian analysis) to identify markers associated with egg-quality and egg-production phenotypes.
The LD between markers pairs was high at short distances (r2 > 0.2 at < 2 Mb) and remained high after one generation (correlations of 0.80 to 0.92 at < 5 Mb) in both lines. Single- and 3-SNP regression analyses using a mixed model with SNP as fixed effect resulted in 159 and 76 significant tests (P < 0.01), respectively, across 12 traits. A Bayesian analysis called BayesB, that fits all SNPs simultaneously as random effects and uses model averaging procedures, identified 33 SNPs that were included in the model >20% of the time (phi > 0.2) and an additional ten 3-SNP windows that had a sum of phi greater than 0.35. Generally, SNPs included in the Bayesian model also had a small P-value in the 1-SNP analyses.
High LD correlations between markers at short distances across two generations indicate that such markers will retain high LD with linked QTL and be effective for MAS. The different association analysis methods used provided consistent results. Multiple single SNPs and 3-SNP windows were significantly associated with egg-related traits, providing genomic positions of QTL that can be useful for both MAS and to identify causal mutations.
BMC Genomics 01/2009; 10 Suppl 2:S2. · 4.07 Impact Factor
