David Cavero
Research Subjects
Research Interests
David Cavero has a total of 24 co-authors. Here are the top co-authors by number of shared publications:
- Ian Chisholm Dunn
Roslin Institute, University of Edinburgh, Scotland, UK
3 shared publications - Peter W. Wilson
The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, Scotland, UK
3 shared publications - Anita C. Jones
School of Chemistry, The University of Edinburgh, Edinburgh, UK
2 shared publications - Henner Simianer
Department of Animal Sciences, Animal Breeding and Genetics Group University of Goettingen Goettingen Germany
2 shared publications - Malena Erbe
Bavarian State Research Centre for Agriculture Institute for Animal Breeding Poing‐Grub Germany
2 shared publications - Maureen M. Bain
College of Medical, Veterinary and Life Sciences (MVLS), IBAHCM, University of Glasgow, Glasgow, Scotland, UK
2 shared publications
Latest Publications
- Open Access
- 3 November 2026
- Published by Springer Nature in Genetics Selection Evolution
- Vol. 58 (1) , 80
Genetic architecture of bone strength and composition in White Leghorn laying hens
Background: Skeletal issues such as fractures and poor bone quality are increasingly recognized for their negative impacts on animal welfare and the economic challenges they bring to the poultry industry. Previous pedigree-based analyses in White Leghorn laying hens have reported moderate heritabilities for cortical and medullary bone composition traits (ranging from 0.18 to 0.41) and strong genetic correlations (0.69 to 0.90) with tibia breaking strength and density. This study uses genome-wide association studies (GWAS) to identify genetic markers associated with bone strength and composition traits, aiming to advance our understanding of the genetic architecture of bone quality in White Leghorn laying hens. Results: We identified a set of markers on chromosome 20 (11.55–12.29 Mb) in strong LD with each other ( r 2 > 0.8), significantly associated with humeral stiffness, and overlapping with humeral strength and tibial cortical thickness. These markers were located within the previously identified QTL on chromosome 20 for bone biomechanical strength and body weight. This region harbors a bone morphogenetic protein 7 gene ( BMP7 ) with a known role in skeletogenesis and growth in chicken. Genetic markers with the strongest suggestive association with organic and mineral contents, and total amount of carbonate in bone mineral MinCO3 1415 in tibia medullary bone were detected on chromosome 1 (173.5–173.6 Mb). This region contains the long non-coding RNA LOC107052041 (LncFAM) , which has previously been mapped within growth-related QTL and its polymorphisms have been associated with body weight and skeletal dimensions in chickens. Finally, more accurate heritabilities were estimated for thermogravimetry measurements of bone compositional traits as compared to infrared spectroscopy, with medullary organic and mineral contents being the most heritable (~0.19) and highly correlated with tibia density (0.7). Conclusions: This study identified genomic loci associated with variation in bone quality traits, providing candidates for functional validation and for future evaluation of their potential to improve the prediction of bone strength in laying hens.
- 3 November 2026
- Published by Springer Nature in Genetics Selection Evolution
- Vol. 58 (1) , 80
Open AccessGenetic architecture of bone strength and composition in White Leghorn laying hens
Background: Skeletal issues such as fractures and poor bone quality are increasingly recognized for their negative impacts on animal welfare and the economic challenges they bring to the poultry industry. Previous pedigree-based analyses in White Leghorn laying hens have reported moderate heritabilities for cortical and medullary bone composition traits (ranging from 0.18 to 0.41) and strong genetic correlations (0.69 to 0.90) with tibia breaking strength and density. This study uses genome-wide association studies (GWAS) to identify genetic markers associated with bone strength and composition traits, aiming to advance our understanding of the genetic architecture of bone quality in White Leghorn laying hens. Results: We identified a set of markers on chromosome 20 (11.55–12.29 Mb) in strong LD with each other ( r 2 > 0.8), significantly associated with humeral stiffness, and overlapping with humeral strength and tibial cortical thickness. These markers were located within the previously identified QTL on chromosome 20 for bone biomechanical strength and body weight. This region harbors a bone morphogenetic protein 7 gene ( BMP7 ) with a known role in skeletogenesis and growth in chicken. Genetic markers with the strongest suggestive association with organic and mineral contents, and total amount of carbonate in bone mineral MinCO3 1415 in tibia medullary bone were detected on chromosome 1 (173.5–173.6 Mb). This region contains the long non-coding RNA LOC107052041 (LncFAM) , which has previously been mapped within growth-related QTL and its polymorphisms have been associated with body weight and skeletal dimensions in chickens. Finally, more accurate heritabilities were estimated for thermogravimetry measurements of bone compositional traits as compared to infrared spectroscopy, with medullary organic and mineral contents being the most heritable (~0.19) and highly correlated with tibia density (0.7). Conclusions: This study identified genomic loci associated with variation in bone quality traits, providing candidates for functional validation and for future evaluation of their potential to improve the prediction of bone strength in laying hens.
- Open Access
- 27 July 2020
- Published by Springer Nature in BMC Genomics
- Vol. 21 (1) , 1-15
Transcriptome analysis of the uterus of hens laying eggs differing in cuticle deposition
Background: Avian eggs have a proteinaceous cuticle. The quantity of cuticle varies and the deposition of a good cuticle in the uterus (Shell-gland) prevents transmission of bacteria to the egg contents. Results: To understand cuticle deposition, uterus transcriptomes were compared between hens with i) naturally good and poor cuticle and, ii) where manipulation of the hypothalamo-pituitary-gonadal-oviduct axis produced eggs with or without cuticle. The highest expressed genes encoded eggshell matrix and cuticle proteins, e.g. MEPE (OC-116), BPIFB3 (OVX-36), RARRES1 (OVX-32), WAP (OVX-25), and genes for mitochondrial oxidative phosphorylation, active transport and energy metabolism. Expression of a number of these genes differed between hens laying eggs with or without cuticle. There was also a high expression of clock genes. PER2, CRY2, CRY1, CLOCK and BMAL1 were differentially expressed when cuticle deposition was prevented, and they also changed throughout the egg formation cycle. This suggests an endogenous clock in the uterus may be a component of cuticle deposition control. Cuticle proteins are glycosylated and glycosaminoglycan binding genes had a lower expression when cuticle proteins were deposited on the egg. The immediate early genes, JUN and FOS, were expressed less when the cuticle had not been deposited and changed over the egg formation cycle, suggesting they are important in oviposition and cuticle deposition. The uterus transcriptome of hens with good and poor cuticle deposition did not differ. Conclusions: We have gained insights into the factors that can affect the production of the cuticle especially clock genes and immediate early genes. We have demonstrated that these genes change their expression over the period of eggshell formation supporting their importance. The lack of differences in expression between the uterus of hens laying eggs with the best and worse cuticle suggest the genetic basis of the trait may lie outside the oviduct.
- 27 July 2020
- Published by Springer Nature in BMC Genomics
- Vol. 21 (1) , 1-15
Open AccessTranscriptome analysis of the uterus of hens laying eggs differing in cuticle deposition
Background: Avian eggs have a proteinaceous cuticle. The quantity of cuticle varies and the deposition of a good cuticle in the uterus (Shell-gland) prevents transmission of bacteria to the egg contents. Results: To understand cuticle deposition, uterus transcriptomes were compared between hens with i) naturally good and poor cuticle and, ii) where manipulation of the hypothalamo-pituitary-gonadal-oviduct axis produced eggs with or without cuticle. The highest expressed genes encoded eggshell matrix and cuticle proteins, e.g. MEPE (OC-116), BPIFB3 (OVX-36), RARRES1 (OVX-32), WAP (OVX-25), and genes for mitochondrial oxidative phosphorylation, active transport and energy metabolism. Expression of a number of these genes differed between hens laying eggs with or without cuticle. There was also a high expression of clock genes. PER2, CRY2, CRY1, CLOCK and BMAL1 were differentially expressed when cuticle deposition was prevented, and they also changed throughout the egg formation cycle. This suggests an endogenous clock in the uterus may be a component of cuticle deposition control. Cuticle proteins are glycosylated and glycosaminoglycan binding genes had a lower expression when cuticle proteins were deposited on the egg. The immediate early genes, JUN and FOS, were expressed less when the cuticle had not been deposited and changed over the egg formation cycle, suggesting they are important in oviposition and cuticle deposition. The uterus transcriptome of hens with good and poor cuticle deposition did not differ. Conclusions: We have gained insights into the factors that can affect the production of the cuticle especially clock genes and immediate early genes. We have demonstrated that these genes change their expression over the period of eggshell formation supporting their importance. The lack of differences in expression between the uterus of hens laying eggs with the best and worse cuticle suggest the genetic basis of the trait may lie outside the oviduct.
- Open Access
- 17 July 2019
- Published by Springer Nature in BMC Genetics
- Vol. 20 (1) , 1-11
Phasing quality assessment in a brown layer population through family- and population-based software
Haplotype data contains more information than genotype data and provides possibilities such as imputing low frequency variants, inferring points of recombination, detecting recurrent mutations, mapping linkage disequilibrium (LD), studying selection signatures, estimating IBD probabilities, etc. In addition, haplotype structure is used to assess genetic diversity and expected accuracy in genomic selection programs. Nevertheless, the quality and efficiency of phasing has rarely been a subject of thorough study but was assessed mainly as a by-product in imputation quality studies. Moreover, phasing studies based on data of a poultry population are non-existent. The aim of this study was to evaluate the phasing quality of FImpute and Beagle, two of the most used phasing software. We simulated ten replicated samples of a layer population comprising 888 individuals from a real SNP dataset of 580 k and a pedigree of 12 generations. Chromosomes analyzed were 1, 7 and 20. We measured the percentage of SNPs that were phased equally between true and phased haplotypes (Eqp), proportion of individuals completely correctly phased, number of incorrectly phased SNPs or Breakpoints (Bkp) and the length of inverted haplotype segments. Results were obtained for three different groups of individuals, with no parents or offspring genotyped in the dataset, with only one parent, and with both parents, respectively. The phasing was performed with Beagle (v3.3 and v4.1) and FImpute v2.2 (with and without pedigree). Eqp values ranged from 88 to 100%, with the best results from haplotypes phased with Beagle v4.1 and FImpute with pedigree information and at least one parent genotyped. FImpute haplotypes showed a higher number of Bkp than Beagle. As a consequence, switched haplotype segments were longer for Beagle than for FImpute. We concluded that for the dataset applied in this study Beagle v4.1 or FImpute with pedigree information and at least one parent genotyped in the data set were the best alternatives for obtaining high quality phased haplotypes.
- 17 July 2019
- Published by Springer Nature in BMC Genetics
- Vol. 20 (1) , 1-11
Open AccessPhasing quality assessment in a brown layer population through family- and population-based software
Haplotype data contains more information than genotype data and provides possibilities such as imputing low frequency variants, inferring points of recombination, detecting recurrent mutations, mapping linkage disequilibrium (LD), studying selection signatures, estimating IBD probabilities, etc. In addition, haplotype structure is used to assess genetic diversity and expected accuracy in genomic selection programs. Nevertheless, the quality and efficiency of phasing has rarely been a subject of thorough study but was assessed mainly as a by-product in imputation quality studies. Moreover, phasing studies based on data of a poultry population are non-existent. The aim of this study was to evaluate the phasing quality of FImpute and Beagle, two of the most used phasing software. We simulated ten replicated samples of a layer population comprising 888 individuals from a real SNP dataset of 580 k and a pedigree of 12 generations. Chromosomes analyzed were 1, 7 and 20. We measured the percentage of SNPs that were phased equally between true and phased haplotypes (Eqp), proportion of individuals completely correctly phased, number of incorrectly phased SNPs or Breakpoints (Bkp) and the length of inverted haplotype segments. Results were obtained for three different groups of individuals, with no parents or offspring genotyped in the dataset, with only one parent, and with both parents, respectively. The phasing was performed with Beagle (v3.3 and v4.1) and FImpute v2.2 (with and without pedigree). Eqp values ranged from 88 to 100%, with the best results from haplotypes phased with Beagle v4.1 and FImpute with pedigree information and at least one parent genotyped. FImpute haplotypes showed a higher number of Bkp than Beagle. As a consequence, switched haplotype segments were longer for Beagle than for FImpute. We concluded that for the dataset applied in this study Beagle v4.1 or FImpute with pedigree information and at least one parent genotyped in the data set were the best alternatives for obtaining high quality phased haplotypes.
- Open Access
- 4 June 2019
- Published by Springer Nature in Genetics Selection Evolution
- Vol. 51 (1) , 25
Genetic variation and potential for genetic improvement of cuticle deposition on chicken eggs
The cuticle is an invisible glycosylated protein layer that covers the outside of the eggshell and forms a barrier to the transmission of microorganisms. Cuticle-specific staining and in situ absorbance measurements have been used to quantify cuticle deposition in several pure breeds of chicken. For brown eggs, a pre-stain and a post-stain absorbance measurement is required to correct for intrinsic absorption by the natural pigment. For white eggs, a post-stain absorbance measurement alone is sufficient to estimate cuticle deposition. The objective of the research was to estimate genetic parameters and provide data to promote adoption of the technique to increase cuticle deposition and reduce vertical transmission of microorganisms. For all pure breeds examined here, i.e. Rhode Island Red, two White Leghorns, White Rock and a broiler breed, the estimate of heritability for cuticle deposition from a meta-analysis was moderately high (0.38 ± 0.04). In the Rhode Island Red breed, the estimate of the genetic correlation between measurements recorded at early and late times during the egg-laying period was ~ 1. There was no negative genetic correlation between cuticle deposition and production traits. Estimates of the genetic correlation of cuticle deposition with shell color ranged from negative values or 0 in brown-egg layers to positive values in white- or tinted-egg layers. Using the intrinsic fluorescence of tryptophan in the cuticle proteins to quantify the amount of cuticle deposition failed because of complex quenching processes. Tryptophan fluorescence intensity at 330 nm was moderately heritable, but there was no evidence of a non-zero genetic correlation with cuticle deposition. This was complicated furthermore by a negative genetic correlation of fluorescence with color in brown eggs, due to the quenching of tryptophan fluorescence by energy transfer to protoporphyrin pigment. We also confirmed that removal of the cuticle increased reflection of ultraviolet wavelengths from the egg. These results provide additional evidence for the need to incorporate cuticle deposition into breeding programs of egg- and meat-type birds in order to reduce vertical and horizontal transmission of potentially pathogenic organisms and to help improve biosecurity in poultry.
- 4 June 2019
- Published by Springer Nature in Genetics Selection Evolution
- Vol. 51 (1) , 25
Open AccessGenetic variation and potential for genetic improvement of cuticle deposition on chicken eggs
The cuticle is an invisible glycosylated protein layer that covers the outside of the eggshell and forms a barrier to the transmission of microorganisms. Cuticle-specific staining and in situ absorbance measurements have been used to quantify cuticle deposition in several pure breeds of chicken. For brown eggs, a pre-stain and a post-stain absorbance measurement is required to correct for intrinsic absorption by the natural pigment. For white eggs, a post-stain absorbance measurement alone is sufficient to estimate cuticle deposition. The objective of the research was to estimate genetic parameters and provide data to promote adoption of the technique to increase cuticle deposition and reduce vertical transmission of microorganisms. For all pure breeds examined here, i.e. Rhode Island Red, two White Leghorns, White Rock and a broiler breed, the estimate of heritability for cuticle deposition from a meta-analysis was moderately high (0.38 ± 0.04). In the Rhode Island Red breed, the estimate of the genetic correlation between measurements recorded at early and late times during the egg-laying period was ~ 1. There was no negative genetic correlation between cuticle deposition and production traits. Estimates of the genetic correlation of cuticle deposition with shell color ranged from negative values or 0 in brown-egg layers to positive values in white- or tinted-egg layers. Using the intrinsic fluorescence of tryptophan in the cuticle proteins to quantify the amount of cuticle deposition failed because of complex quenching processes. Tryptophan fluorescence intensity at 330 nm was moderately heritable, but there was no evidence of a non-zero genetic correlation with cuticle deposition. This was complicated furthermore by a negative genetic correlation of fluorescence with color in brown eggs, due to the quenching of tryptophan fluorescence by energy transfer to protoporphyrin pigment. We also confirmed that removal of the cuticle increased reflection of ultraviolet wavelengths from the egg. These results provide additional evidence for the need to incorporate cuticle deposition into breeding programs of egg- and meat-type birds in order to reduce vertical and horizontal transmission of potentially pathogenic organisms and to help improve biosecurity in poultry.
- Open Access
A simple test identifies selection on complex traits in breeding and experimentally-evolved populations
Important traits in agricultural, natural, and human populations are increasingly being shown to be under the control of many genes that individually contribute only a small proportion of genetic variation. However, the majority of modern tools in quantitative and population genetics, including genome wide association studies and selection mapping protocols, are designed to identify individual genes with large effects. We have developed an approach to identify traits that have been under selection and are controlled by large numbers of loci. In contrast to existing methods, our technique utilizes additive effects estimates from all available markers, and relates these estimates to allele frequency change over time. Using this information, we generate a composite statistic, denoted Ĝ , which can be used to test for significant evidence of selection on a trait. Our test requires pre- and post-selection genotypic data but only a single time point with phenotypic information. Simulations demonstrate that Ĝ is powerful for identifying selection, particularly in situations where the trait being tested is controlled by many genes, which is precisely the scenario where classical approaches for selection mapping are least powerful. We apply this test to breeding populations of maize and chickens, where we demonstrate the successful identification of selection on traits that are documented to have been under selection.
Open AccessA simple test identifies selection on complex traits in breeding and experimentally-evolved populations
Important traits in agricultural, natural, and human populations are increasingly being shown to be under the control of many genes that individually contribute only a small proportion of genetic variation. However, the majority of modern tools in quantitative and population genetics, including genome wide association studies and selection mapping protocols, are designed to identify individual genes with large effects. We have developed an approach to identify traits that have been under selection and are controlled by large numbers of loci. In contrast to existing methods, our technique utilizes additive effects estimates from all available markers, and relates these estimates to allele frequency change over time. Using this information, we generate a composite statistic, denoted Ĝ , which can be used to test for significant evidence of selection on a trait. Our test requires pre- and post-selection genotypic data but only a single time point with phenotypic information. Simulations demonstrate that Ĝ is powerful for identifying selection, particularly in situations where the trait being tested is controlled by many genes, which is precisely the scenario where classical approaches for selection mapping are least powerful. We apply this test to breeding populations of maize and chickens, where we demonstrate the successful identification of selection on traits that are documented to have been under selection.