Staff Publications

Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
  • About

    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Records 1 - 17 / 17

  • help
  • print

    Print search results

  • export

    Export search results

  • alert
    We will mail you new results for this query: q=Guldbrandtsen
Check title to add to marked list
Impact of rare and low-frequency sequence variants on reliability of genomic prediction in dairy cattle
Zhang, Qianqian ; Sahana, Goutam ; Su, Guosheng ; Guldbrandtsen, Bernt ; Lund, Mogens Sandø ; Calus, Mario P.L. - \ 2018
Genetics, Selection, Evolution 50 (2018)1. - ISSN 0999-193X - 10 p.

BACKGROUND: Availability of whole-genome sequence data for a large number of cattle and efficient imputation methodologies open a new opportunity to include rare and low-frequency variants (RLFV) in genomic prediction in dairy cattle. The objective of this study was to examine the impact of including RLFV that are within genes and selected from whole-genome sequence variants, on the reliability of genomic prediction for fertility, health and longevity in dairy cattle. RESULTS: All genic RLFV with a minor allele frequency lower than 0.05 were extracted from imputed sequence data and subsets were created using different strategies. These subsets were subsequently combined with Illumina 50 k single nucleotide polymorphism (SNP) data and used for genomic prediction. Reliability of prediction obtained by using 50 k SNP data alone was used as reference value and absolute changes in reliabilities are referred to as changes in percentage points. Adding a component that included either all the genic or a subset of selected RLFV into the model in addition to the 50 k component changed the reliability of predictions by - 2.2 to 1.1%, i.e. hardly no change in reliability of prediction was found, regardless of how the RLFV were selected. In addition to these empirical analyses, a simulation study was performed to evaluate the potential impact of adding RLFV in the model on the reliability of prediction. Three sets of causal RLFV (containing 21,468, 1348 and 235 RLFV) that were randomly selected from different numbers of genes were generated and accounted for 10% additional genetic variance of the estimated variance explained by the 50 k SNPs. When genic RLFV based on mapping results were included in the prediction model, reliabilities improved by up to 4.0% and when the causal RLFV were included they improved by up to 6.8%. CONCLUSIONS: Using selected RLFV from whole-genome sequence data had only a small impact on the empirical reliability of genomic prediction in dairy cattle. Our simulations revealed that for sequence data to bring a benefit, the key is to identify causal RLFV.

Host genetics and the rumen microbiome jointly associate with methane emissions in dairy cows
Difford, Gareth Frank ; Plichta, Damian Rafal ; Løvendahl, Peter ; Lassen, Jan ; Noel, Samantha Joan ; Højberg, Ole ; Wright, André Denis G. ; Zhu, Zhigang ; Kristensen, Lise ; Nielsen, Henrik Bjørn ; Guldbrandtsen, Bernt ; Sahana, Goutam - \ 2018
Plos Genetics 14 (2018)10. - ISSN 1553-7404

Cattle and other ruminants produce large quantities of methane (~110 million metric tonnes per annum), which is a potent greenhouse gas affecting global climate change. Methane (CH4) is a natural by-product of gastro-enteric microbial fermentation of feedstuffs in the rumen and contributes to 6% of total CH4 emissions from anthropogenic-related sources. The extent to which the host genome and rumen microbiome influence CH4 emission is not yet well known. This study confirms individual variation in CH4 production was influenced by individual host (cow) genotype, as well as the host's rumen microbiome composition. Abundance of a small proportion of bacteria and archaea taxa were influenced to a limited extent by the host's genotype and certain taxa were associated with CH4 emissions. However, the cumulative effect of all bacteria and archaea on CH4 production was 13%, the host genetics (heritability) was 21% and the two are largely independent. This study demonstrates variation in CH4 emission is likely not modulated through cow genetic effects on the rumen microbiome. Therefore, the rumen microbiome and cow genome could be targeted independently, by breeding low methane-emitting cows and in parallel, by investigating possible strategies that target changes in the rumen microbiome to reduce CH4 emissions in the cattle industry.

Human-mediated introgression of haplotypes in a modern dairy cattle breed
Zhang, Qianqian ; Calus, Mario P.L. ; Bosse, Mirte ; Sahana, Goutam ; Lund, Mogens Sandø ; Guldbrandtsen, Bernt - \ 2018
Genetics 209 (2018)4. - ISSN 0016-6731 - p. 1305 - 1317.
High-yielding cattle breeds - Modern dairy cattle breed - Selective introgression - Signature of selection

Domestic animals can serve as model systems of adaptive introgression and their genomic signatures. In part, their usefulness as model systems is due to their well-known histories. Different breeding strategies such as introgression and artificial selection have generated numerous desirable phenotypes and superior performance in domestic animals. The modern Danish Red Dairy Cattle is studied as an example of an introgressed population. It originates from crossing the traditional Danish Red Dairy Cattle with the Holstein and Brown Swiss breeds, both known for high milk production. This crossing happened, among other things due to changes in the production system, to raise milk production and overall performance. The genomes of modern Danish Red Dairy Cattle are heavily influenced by regions introgressed from the Holstein and Brown Swiss breeds and under subsequent selection in the admixed population. The introgressed proportion of the genome was found to be highly variable across the genome. Haplotypes introgressed from Holstein and Brown Swiss contained or overlapped known genes affecting milk production, as well as protein and fat content (CD14, ZNF215, BCL2L12, and THRSP for Holstein origin and ITPR2, BCAT1, LAP3, and MED28 for Brown Swiss origin). Genomic regions with high introgression signals also contained genes and enriched QTL associated with calving traits, body confirmation, feed efficiency, carcass, and fertility traits. These introgressed signals with relative identity-by-descent scores larger than the median showing Holstein or Brown Swiss introgression are mostly significantly correlated with the corresponding test statistics from signatures of selection analyses in modern Danish Red Dairy Cattle. Meanwhile, the putative significant introgressed signals have a significant dependency with the putative significant signals from signatures of selection analyses. Artificial selection has played an important role in the genomic footprints of introgression in the genome of modern Danish Red Dairy Cattle. Our study on a modern cattle breed contributes to an understanding of genomic consequences of selective introgression by demonstrating the extent to which adaptive effects contribute to shape the specific genomic consequences of introgression.

Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals
Bouwman, Aniek C. ; Daetwyler, Hans D. ; Chamberlain, Amanda J. ; Ponce, Carla Hurtado ; Sargolzaei, Mehdi ; Schenkel, Flavio S. ; Sahana, Goutam ; Govignon-Gion, Armelle ; Boitard, Simon ; Dolezal, Marlies ; Pausch, Hubert ; Brøndum, Rasmus F. ; Bowman, Phil J. ; Thomsen, Bo ; Guldbrandtsen, Bernt ; Lund, Mogens S. ; Servin, Bertrand ; Garrick, Dorian J. ; Reecy, James ; Vilkki, Johanna ; Bagnato, Alessandro ; Wang, Min ; Hoff, Jesse L. ; Schnabel, Robert D. ; Taylor, Jeremy F. ; Vinkhuyzen, Anna A.E. ; Panitz, Frank ; Bendixen, Christian ; Holm, Lars Erik ; Gredler, Birgit ; Hozé, Chris ; Boussaha, Mekki ; Sanchez, Marie Pierre ; Rocha, Dominique ; Capitan, Aurelien ; Tribout, Thierry ; Barbat, Anne ; Croiseau, Pascal ; Drögemüller, Cord ; Jagannathan, Vidhya ; Vander Jagt, Christy ; Crowley, John J. ; Bieber, Anna ; Purfield, Deirdre C. ; Berry, Donagh P. ; Emmerling, Reiner ; Götz, Kay Uwe ; Frischknecht, Mirjam ; Russ, Ingolf ; Sölkner, Johann ; Tassell, Curtis P. van; Fries, Ruedi ; Stothard, Paul ; Veerkamp, Roel F. ; Boichard, Didier ; Goddard, Mike E. ; Hayes, Ben J. - \ 2018
Nature Genetics 50 (2018). - ISSN 1061-4036 - p. 362 - 367.
Stature is affected by many polymorphisms of small effect in humans1. In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes2,3. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10−8) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP–seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.
Exploiting whole genome sequence variants in cattle breeding : Unraveling the distribution of genetic variants and role of rare variants in genomic evaluation
Zhang, Qianqian - \ 2017
Wageningen University. Promotor(en): Henk Bovenhuis; M.S. Lund, co-promotor(en): G. Sahana; Mario Calus; B. Guldbrandtsen. - Wageningen : Wageningen University - ISBN 9788793643147 - 249
cattle - genomes - genetic variation - inbreeding - homozygosity - longevity - quantitative traits - animal breeding - animal genetics - rundvee - genomen - genetische variatie - inteelt - homozygotie - gebruiksduur - kwantitatieve kenmerken - dierveredeling - diergenetica

The availability of whole genome sequence data enables to better explore the genetic mechanisms underlying different quantitative traits that are targeted in animal breeding. This thesis presents different strategies and perspectives on utilization of whole genome sequence variants in cattle breeding. Using whole genome sequence variants, I show the genetic variation, recent and ancient inbreeding, and genome-wide pattern of introgression across the demographic and breeding history in different cattle populations. Using the latest genomic tools, I demonstrate that recent inbreeding can accurately be estimated by runs of homozygosity (ROH). This can further be utilized in breeding programs to control inbreeding in breeding programs. In chapter 2 and 4, by in-depth genomic analysis on whole genome sequence data, I demonstrate that the distribution of functional genetic variants in ROH regions and introgressed haplotypes was shaped by recent selective breeding in cattle populations. The contribution of whole genome sequence variants to the phenotypic variation partly depends on their allele frequencies. Common variants associated with different traits have been identified and explain a considerable proportion of the genetic variance. For example, common variants from whole genome sequence associated with longevity have been identified in chapter 5. However, the identified common variants cannot explain the full genetic variance, and rare variants might play an important role here. Rare variants may account for a large proportion of the whole genome sequence variants, but are often ignored in genomic evaluation, partly because of difficulty to identify associations between rare variants and phenotypes. I compared the powers of different gene-based association mapping methods that combine the rare variants within a gene using a simulation study. Those gene- based methods had a higher power for mapping rare variants compared with mixed linear models applying single marker tests that are commonly used for common variants. Moreover, I explored the role of rare and low-frequency variants in the variation of different complex traits and their impact on genomic prediction reliability. Rare and low-frequency variants contributed relatively more to variation for health-related traits than production traits, reflecting the potential of improving prediction reliability using rare and low-frequency variants for health-related traits. However, in practice, only marginal improvement was observed using selected rare and low-frequency variants when combined with 50k SNP genotype data on the reliability of genomic prediction for fertility, longevity and health traits. A simulation study did show that reliability of genomic prediction could be improved provided that causal rare and low-frequency variants affecting a trait are known.

Biodiversity within and between European Red dairy breeds – conservation through utilization
Hinrichs, D. ; Calus, M.P.L. ; Koning, Dirk Jan De; Bennewitz, J. ; Meuwissen, T. ; Thaller, G. ; Szyda, J. ; Tetens, J. ; Juskiene, V. ; Guldbrandtsen, B. - \ 2017
In: Book of Abstracts of the 68th Annual Meeting of the European Federation of Animal Science. - Wageningen : Wageningen Academic Publishers (Book of abstracts 23) - ISBN 9789086863129 - p. 82 - 82.
Red dairy breeds across Europe represent a unique source of genetic diversity and are partly organized in transnational breeding programs but are also well adapted to local conditions. ReDiverse’s objective is to develop and to set in place collaborative and integrated novel breeding and management concepts to achieve a resilient and competitive use of these resources and to strengthen best practices for small farm holders to improve product quality and to supply ecosystem services according to their specific circumstances. The challenge of establishing appropriate breeding and maintenance strategies for diverse farm systems and regional markets is met by multi-actor operations considering economic, structural and social diversity in participating countries to offer tailored solutions. The holistic approach relies on integrative research of scientists in the fields of animal genetics, proteomics, economy and social sciences. Cutting edge technology such as large scale genomic and proteomic tools will be implemented to enhance genetic progress and to characterize specific properties. Innovative survey approaches will assess the impact of the sector on social acceptance and the needs of farmers. The project will generate novel knowledge and concepts that will be timely disseminated to lead-users in the breeding and dairy industries, food sector, farmers’ cooperatives and among farmers.
Contribution of rare and low-frequency whole-genome sequence variants to complex traits variation in dairy cattle
Zhang, Qianqian ; Calus, Mario P.L. ; Guldbrandtsen, Bernt ; Lund, Mogens Sandø ; Sahana, Goutam - \ 2017
Genetics, Selection, Evolution 49 (2017)1. - ISSN 0999-193X
Background: Whole-genome sequencing and imputation methodologies have enabled the study of the effects of genomic variants with low to very low minor allele frequency (MAF) on variation in complex traits. Our objective was to estimate the proportion of variance explained by imputed sequence variants classified according to their MAF compared with the variance explained by the pedigree-based additive genetic relationship matrix for 17 traits in Nordic Holstein dairy cattle. Results: Imputed sequence variants were grouped into seven classes according to their MAF (0.001-0.01, 0.01-0.05, 0.05-0.1, 0.1-0.2, 0.2-0.3, 0.3-0.4 and 0.4-0.5). The total contribution of all imputed sequence variants to variance in deregressed estimated breeding values or proofs (DRP) for different traits ranged from 0.41 [standard error (SE) = 0.026] for temperament to 0.87 (SE = 0.011) for milk yield. The contribution of rare variants (MAF < 0.01) to the total DRP variance explained by all imputed sequence variants was relatively small (a maximum of 12.5% for the health index). Rare and low-frequency variants (MAF < 0.05) contributed a larger proportion of the explained DRP variances (>13%) for health-related traits than for production traits (<11%). However, a substantial proportion of these variance estimates across different MAF classes had large SE, especially when the variance explained by a MAF class was small. The proportion of DRP variance that was explained by all imputed whole-genome sequence variants improved slightly compared with variance explained by the 50 k Illumina markers, which are routinely used in bovine genomic prediction. However, the proportion of DRP variance explained by imputed sequence variants was lower than that explained by pedigree relationships, ranging from 1.5% for milk yield to 37.9% for the health index. Conclusions: Imputed sequence variants explained more of the variance in DRP than the 50 k markers for most traits, but explained less variance than that captured by pedigree-based relationships. Although in humans partitioning variants into groups based on MAF and linkage disequilibrium was used to estimate heritability without bias, many of our bovine estimates had a high SE. For a reliable estimate of the explained DRP variance for different MAF classes, larger sample sizes are needed.
Domesticated Animal Biobanking : Land of Opportunity
Groeneveld, Linn F. ; Gregusson, Sigbjørn ; Guldbrandtsen, Bernt ; Hiemstra, Sipke J. ; Hveem, Kristian ; Kantanen, Juha ; Lohi, Hannes ; Stroemstedt, Lina ; Berg, Peer - \ 2016
PloS Biology 14 (2016)7. - ISSN 1545-7885

In the past decade, biobanking has fuelled great scientific advances in the human medical sector. Well-established domesticated animal biobanks and integrated networks likewise harbour immense potential for great scientific advances with broad societal impacts, which are currently not being fully realised. Political and scientific leaders as well as journals and ethics committees should help to ensure that we are well equipped to meet future demands in livestock production, animal models, and veterinary care of companion animals.

Comparison of gene-based rare variant association mapping methods for quantitative traits in a bovine population with complex familial relationships
Zhang, Qianqian ; Guldbrandtsen, Bernt ; Calus, Mario P.L. ; Lund, Mogens Sandø ; Sahana, Goutam - \ 2016
Genetics, Selection, Evolution 48 (2016)1. - ISSN 0999-193X

Background: There is growing interest in the role of rare variants in the variation of complex traits due to increasing evidence that rare variants are associated with quantitative traits. However, association methods that are commonly used for mapping common variants are not effective to map rare variants. Besides, livestock populations have large half-sib families and the occurrence of rare variants may be confounded with family structure, which makes it difficult to disentangle their effects from family mean effects. We compared the power of methods that are commonly applied in human genetics to map rare variants in cattle using whole-genome sequence data and simulated phenotypes. We also studied the power of mapping rare variants using linear mixed models (LMM), which are the method of choice to account for both family relationships and population structure in cattle. Results: We observed that the power of the LMM approach was low for mapping a rare variant (defined as those that have frequencies lower than 0.01) with a moderate effect (5 to 8 % of phenotypic variance explained by multiple rare variants that vary from 5 to 21 in number) contributing to a QTL with a sample size of 1000. In contrast, across the scenarios studied, statistical methods that are specialized for mapping rare variants increased power regardless of whether multiple rare variants or a single rare variant underlie a QTL. Different methods for combining rare variants in the test single nucleotide polymorphism set resulted in similar power irrespective of the proportion of total genetic variance explained by the QTL. However, when the QTL variance is very small (only 0.1 % of the total genetic variance), these specialized methods for mapping rare variants and LMM generally had no power to map the variants within a gene with sample sizes of 1000 or 5000. Conclusions: We observed that the methods that combine multiple rare variants within a gene into a meta-variant generally had greater power to map rare variants compared to LMM. Therefore, it is recommended to use rare variant association mapping methods to map rare genetic variants that affect quantitative traits in livestock, such as bovine populations.

Genome-wide association study for longevity with whole-genome sequencing in 3 cattle breeds
Zhang, Qianqian ; Guldbrandtsen, Bernt ; Thomasen, Jørn Rind ; Lund, Mogens Sandø ; Sahana, Goutam - \ 2016
Journal of Dairy Science 99 (2016)9. - ISSN 0022-0302 - p. 7289 - 7298.
Cattle - Genome-wide association study - Longevity - Whole-genome sequencing

Longevity is an important economic trait in dairy production. Improvements in longevity could increase the average number of lactations per cow, thereby affecting the profitability of the dairy cattle industry. Improved longevity for cows reduces the replacement cost of stock and enables animals to achieve the highest production period. Moreover, longevity is an indirect indicator of animal welfare. Using whole-genome sequencing variants in 3 dairy cattle breeds, we carried out an association study and identified 7 genomic regions in Holstein and 5 regions in Red Dairy Cattle that were associated with longevity. Meta-analyses of 3 breeds revealed 2 significant genomic regions, located on chromosomes 6 (META-CHR6-88MB) and 18 (META-CHR18-58MB). META-CHR6-88MB overlaps with 2 known genes: neuropeptide G-protein coupled receptor (NPFFR2; 89,052,210-89,059,348 bp) and vitamin D-binding protein precursor (GC; 88,695,940-88,739,180 bp). The NPFFR2 gene was previously identified as a candidate gene for mastitis resistance. META-CHR18-58MB overlaps with zinc finger protein 717 (ZNF717; 58,130,465-58,141,877 bp) and zinc finger protein 613 (ZNF613; 58,115,782-58,117,110 bp), which have been associated with calving difficulties. Information on longevity-associated genomic regions could be used to find causal genes/variants influencing longevity and exploited to improve the reliability of genomic prediction.

Meta-analysis of GWAS of bovine stature with >50,000 animals imputed to whole-genome sequence
Bouwman, A.C. ; Pausch, H. ; Govignon-Gion, A. ; Hoze, C. ; Sanchez, M.P. ; Boussaha, M. ; Boichard, D.A. ; Sahana, G. ; Brondum, R.F. ; Guldbrandtsen, B. ; Lund, M. ; Vilkki, J. ; Sargolzaei, M. ; Schenkel, F.S. ; Taylor, J. ; Hoff, J.L. ; Schnabel, R.D. ; Veerkamp, R.F. ; Goddard, M.E. ; Hayes, B.J. - \ 2015
Extensive meta analysis of GWAS in humans has identified 697 significant SNP, however these SNP explain
only 20% the total genetic variation. In order to compare the genetic architecture of stature in humans to
stature in cattle, we performed a large meta-analysis using imputed sequence data. The 1000 Bull Genomes
project provided a multi-breed reference population of 1,147 sequenced animals to impute SNP-chip
genotypes up to whole genome sequence for 15 populations. The populations from Australia, Canada,
Denmark, Finland, France, Germany, the Netherlands, and the USA represented the Angus, Fleckvieh,
Holstein, Jersey, Montbeliarde, Normande, and Nordic Red Dairy Cattle breeds. Genome-wide association
studies were performed on stature phenotypes for each of the populations. Individual GWAS studies revealed
many QTL regions and several regions harboured good candidate genes, e.g. PLAG1, IGF2. Results from
these GWAS studies were combined in a meta-analysis to increase the power for QTL detection and to
refine QTL regions exploiting the different patterns of LD among the breeds. Results of this meta-analysis
will be validated in an independent population to determine how much of the variation in stature can be
explained by the significant SNP
Runs of homozygosity and distribution of functional variants in the cattle genome
Zhang, Qianqian ; Guldbrandtsen, Bernt ; Bosse, Mirte ; Lund, Mogens S. ; Sahana, Goutam - \ 2015
BMC Genomics 16 (2015). - ISSN 1471-2164
Cattle - Genome sequencing - Inbreeding - Polymorphisms - Runs of homozygosity

Background: Recent developments in sequencing technology have facilitated widespread investigations of genomic variants, including continuous stretches of homozygous genomic regions. For cattle, a large proportion of these runs of homozygosity (ROH) are likely the result of inbreeding due to the accumulation of elite alleles from long-term selective breeding programs. In the present study, ROH were characterized in four cattle breeds with whole genome sequence data and the distribution of predicted functional variants was detected in ROH regions and across different ROH length classes. Results: On average, 19.5 % of the genome was located in ROH across four cattle breeds. There were an average of 715.5 ROH per genome with an average size of ~750 kbp, ranging from 10 (minimum size considered) to 49,290 kbp. There was a significant correlation between shared short ROH regions and regions putatively under selection (p <0.001). By investigating the relationship between ROH and the predicted deleterious and non-deleterious variants, we gained insight into the distribution of functional variation in inbred (ROH) regions. Predicted deleterious variants were more enriched in ROH regions than predicted non-deleterious variants, which is consistent with observations in the human genome. We also found that increased enrichment of deleterious variants was significantly higher in short (3 Mbp) ROH regions (P <0.001), which is different than what has been observed in the human genome. Conclusions: This study illustrates the distribution of ROH and functional variants within ROH in cattle populations. These patterns are different from those in the human genome but consistent with the natural history of cattle populations, which is confirmed by the significant correlation between shared short ROH regions and regions putatively under selection. These findings contribute to understanding the effects of inbreeding and probably selection in shaping the distribution of functional variants in the cattle genome.

Estimation of inbreeding using pedigree, 50k SNP chip genotypes and full sequence data in three cattle breeds
Zhang, Qianqian ; Calus, M.P.L. ; Guldbrandtsen, Bernt ; Lund, Mogens S. ; Sahana, Goutam - \ 2015
BMC Genetics 16 (2015)1. - ISSN 1471-2156
Cattle - Inbreeding - Runs of homozygosity - Whole-genome sequence

Levels of inbreeding in cattle populations have increased in the past due to the use of a limited number of bulls for artificial insemination. High levels of inbreeding lead to reduced genetic diversity and inbreeding depression. Various estimators based on different sources, e.g., pedigree or genomic data, have been used to estimate inbreeding coefficients in cattle populations. However, the comparative advantage of using full sequence data to assess inbreeding is unknown. We used pedigree and genomic data at different densities from 50k to full sequence variants to compare how different methods performed for the estimation of inbreeding levels in three different cattle breeds. Results: Five different estimates for inbreeding were calculated and compared in this study: pedigree based inbreeding coefficient (FPED); run of homozygosity (ROH)-based inbreeding coefficients (FROH); genomic relationship matrix (GRM)-based inbreeding coefficients (FGRM); inbreeding coefficients based on excess of homozygosity (FHOM) and correlation of uniting gametes (FUNI). Estimates using ROH provided the direct estimated levels of autozygosity in the current populations and are free effects of allele frequencies and incomplete pedigrees which may increase in inaccuracy in estimation of inbreeding. The highest correlations were observed between FROH estimated from the full sequence variants and the FROH estimated from 50k SNP (single nucleotide polymorphism) genotypes. The estimator based on the correlation between uniting gametes (FUNI) using full genome sequences was also strongly correlated with FROH detected from sequence data. Conclusions: Estimates based on ROH directly reflected levels of homozygosity and were not influenced by allele frequencies, unlike the three other estimates evaluated (FGRM, FHOM and FUNI), which depended on estimated allele frequencies. FPED suffered from limited pedigree depth. Marker density affects ROH estimation. Detecting ROH based on 50k chip data was observed to give estimates similar to ROH from sequence data. In the absence of full sequence data ROH based on 50k can be used to access homozygosity levels in individuals. However, genotypes denser than 50k are required to accurately detect short ROH that are most likely identical by descent (IBD).

Bos taurus strain:dairy beef (cattle): 1000 Bull Genomes Run 2, Bovine Whole Genome Sequence
Bouwman, A.C. ; Daetwyler, H.D. ; Chamberlain, Amanda J. ; Ponce, Carla Hurtado ; Sargolzaei, Mehdi ; Schenkel, Flavio S. ; Sahana, Goutam ; Govignon-Gion, Armelle ; Boitard, Simon ; Dolezal, Marlies ; Pausch, Hubert ; Brøndum, Rasmus F. ; Bowman, Phil J. ; Thomsen, Bo ; Guldbrandtsen, Bernt ; Lund, Mogens S. ; Servin, Bertrand ; Garrick, Dorian J. ; Reecy, James M. ; Vilkki, Johanna ; Bagnato, Alessandro ; Wang, Min ; Hoff, Jesse L. ; Schnabel, Robert D. ; Taylor, Jeremy F. ; Vinkhuyzen, Anna A.E. ; Panitz, Frank ; Bendixen, Christian ; Holm, Lars-Erik ; Gredler, Birgit ; Hozé, Chris ; Boussaha, Mekki ; Sanchez, Marie Pierre ; Rocha, Dominique ; Capitan, Aurelien ; Tribout, Thierry ; Barbat, Anne ; Croiseau, Pascal ; Drögemüller, Cord ; Jagannathan, Vidhya ; Vander Jagt, Christy ; Crowley, John J. ; Bieber, Anna ; Purfield, Deirdre C. ; Berry, Donagh P. ; Emmerling, Reiner ; Götz, Kay Uwe ; Frischknecht, Mirjam ; Russ, Ingolf ; Sölkner, Johann ; Tassell, Curtis P. van; Fries, Ruedi ; Stothard, Paul ; Veerkamp, R.F. ; Boichard, Didier ; Goddard, Mike E. ; Hayes, Ben J. - \ 2014
Bos taurus - PRJNA238491
Whole genome sequence data (BAM format) of 234 bovine individuals aligned to UMD3.1. The aim of the study was to identify genetic variants (SNPs and indels) for downstream analysis such as imputation, GWAS, and detection of lethal recessives. Additional sequences for later 1000 bull genomes runs can be found at partners individual projects including PRJEB9343, PRJNA176557, PRJEB18113, PRNJA343262, PRJNA324822, PRJNA324270, PRJNA277147, PRJEB5462.
1000 Bull Genomes - Toward genomic Selectionf from whole genome sequence Data in Dairy and Beef Cattle
Hayes, B. ; Daetwyler, H.D. ; Fries, R. ; Guldbrandtsen, B. ; Mogens Sando Lund, M. ; Didier A. Boichard, D.A. ; Stothard, P. ; Veerkamp, R.F. ; Hulsegge, B. ; Rocha, D. ; Tassell, C. ; Mullaart, E. ; Gredler, B. ; Druet, T. ; Bagnato, A. ; Goddard, M.E. ; Chamberlain, H.L. - \ 2013
Genomic prediction of breeding values is now used as the basis for selection of dairy cattle, and in some cases beef cattle, in a number of countries. When genomic prediction was introduced most of the information was to thought to be derived from linkage disequilibrium between markers and causative variants. It has become clear that much of the predictive power, based on 50,000 DNA markers, in fact derives from prediction of the effect of large chromosome segments that segregate within fairly closely related animals. This has lead to problems with across breed prediction, rapid decay of predictive power over generations and insufficient accuracy in some situations. Using full genome sequence data in genomic prediction should overcome these problems. If linkage disequilibrium between SNP on standard arrays and causative mutations affecting the quantitative trait is incomplete, accuracy of prediction should be improved as a result of including the actual causative mutations affecting the trait of interest in the data set. Secondly, persistence of accuracy of genomic predictions across generations will be improved with full sequence data, as the genomic predictions no longer depend on associations between SNP and causative mutations which currently erode quite rapidly with recombination. Thirdly, if genomic predictions are made across breeds, using full sequence data is likely to be particularly advantageous, as there is no longer a need to rely on marker- associations which may not persist across breeds. However, the cost of sequencing is such that the very large numbers of animals required for genomic prediction will not be sequenced An alternative strategy is to sequence key ancestors of the population, then impute the genotypes for the sequence variants into much larger reference sets with phenotypes and SNP panel genotypes. The 1000 Bull Genomes Project aims at building such a resource of sequenced key ancestor bulls for the bovine research community. The most recent run of the project included 238 full genome sequences of 130 Holstein, 43 Fleckvieh, 48 Angus and 15 Jersey bulls, sequenced at an average of 10.5 fold coverage. There were 25.2 million filtered sequence variants detected in the sequences, including 23.5 million SNP and 1.7 million insertion-deletions. Agreement of sequence genotypes to genotypes from an 800K SNP array in the sequenced Holstein bulls, where there was most data, was excellent at 98.8%. This increased to 99.7% when the genotypes were imputed based on all sequences. Concordance was slightly lower in other breeds. This project will provide an excellent opportunity to identify the most important causative variants, leading to greater understanding of biology underlying quantitative traits. Examples are given of genomic predictions for fertility, health and production traits using imputed sequence data.
Toward genomic prediction from genome sequence data and the 1000 bull genomes project
Hayes, B. ; Anderson, C.L. ; Daetwyler, H.D. ; Fries, R. ; Guldbrandtsen, B. ; Lund, M. ; Boichard, D.A. ; Stothard, P. ; Veerkamp, R.F. ; Hulsegge, B. ; Rocha, D. ; Tassell, C. ; Coote, D. ; Goddard, M.E. ; The 1000 Bull Genomes Consortium, - \ 2012
In: 4th International Conference of Quantative Genetics. - - p. 55 - 55.
1000 Bull Genomes Consortium Project
Hayes, B.J. ; Fries, R. ; Lund, M.S. ; Boichard, D.A. ; Stothard, P. ; Veerkamp, R.F. ; Tassell, C. ; Anderson, C.L. ; Hulsegge, B. ; Guldbrandtsen, B. ; Rocha, D. ; Hinirichs, D. ; Bagnato, A. ; Georges, M. ; Spelman, R.J. ; Reecy, J.M. ; Archibald, A.L. ; Goddard, M.E. ; Gredler, B. - \ 2012
In: Plant and Animal Genome XX Conference, San Diego, CA, USA, 14-18 January 2012. -
Genomic selection, where selection decisions are based on estimates of breeding value from genome wide-marker effects, has enormous potential to improve genetic gain in dairy and beef cattle. Although successful in dairy cattle, some major challenges remain 1) only a proportion of the genetic variance is captured, particularly for some traits 2) marker effects are rarely consistent across breeds, 3) accuracy of genomic predictions decays rapidly over time. Using full genome sequences rather than DNA markers in genomic selection could address these challenges. However, sequencing all individuals in the very large resource populations required to estimate the typically small effects of mutations on target traits would be prohibitively expensive. An alternative is to sequence key ancestors contributing most of the genetic material of the current population, and to use this reference for imputation of sequence from SNP chip data. The reference set must still be large, in order to capture for example, rare variants which are likely to explain some of the variation in our target traits. Recognising the need for a comprehensive “reference set” of key ancestors by many groups undertaking cattle research and cattle breeding programs, we have initiated the 1000 bull genomes project. The project will assemble whole genome sequences of cattle from institutions around the world, to provide an extended data base for imputation of genetic variants. This will enable the bovine genomics community to impute full genome sequence from SNP genotypes, and then use this data for genomic selection, and rapid discovery of causal mutations. Some preliminary results from the variant detection pipeline will be reported.
Check title to add to marked list

Show 20 50 100 records per page

 
Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.