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Sivabharathi RC, Rajagopalan VR, Suresh R, Sudha M, Karthikeyan G, Jayakanthan M, Raveendran M. Haplotype-based breeding: A new insight in crop improvement. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2024; 346:112129. [PMID: 38763472 DOI: 10.1016/j.plantsci.2024.112129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 05/09/2024] [Accepted: 05/15/2024] [Indexed: 05/21/2024]
Abstract
Haplotype-based breeding (HBB) is one of the cutting-edge technologies in the realm of crop improvement due to the increasing availability of Single Nucleotide Polymorphisms identified by Next Generation Sequencing technologies. The complexity of the data can be decreased with fewer statistical tests and a lower probability of spurious associations by combining thousands of SNPs into a few hundred haplotype blocks. The presence of strong genomic regions in breeding lines of most crop species facilitates the use of haplotypes to improve the efficiency of genomic and marker-assisted selection. Haplotype-based breeding as a Genomic Assisted Breeding (GAB) approach harnesses the genome sequence data to pinpoint the allelic variation used to hasten the breeding cycle and circumvent the challenges associated with linkage drag. This review article demonstrates ways to identify candidate genes, superior haplotype identification, haplo-pheno analysis, and haplotype-based marker-assisted selection. The crop improvement strategies that utilize superior haplotypes will hasten the breeding progress to safeguard global food security.
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Affiliation(s)
- R C Sivabharathi
- Department of Genetics and Plant breeding, CPBG, Tamil Nadu Agricultural University, Coimbatore 641003, India
| | - Veera Ranjani Rajagopalan
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, 641003, India
| | - R Suresh
- Department of Rice, CPBG, Tamil Nadu Agricultural University, Coimbatore 641003, India
| | - M Sudha
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, 641003, India.
| | - G Karthikeyan
- Department of Plant Pathology, CPPS, Tamil Nadu Agricultural University, Coimbatore 641003, India
| | - M Jayakanthan
- Department of Plant Molecular Biology and Bioinformatics, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641003, India
| | - M Raveendran
- Directorate of research, Tamil Nadu Agricultural University, Coimbatore 641003, India.
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Worku D, Verma A. Genetic variation in bovine LAP3 and SIRT1 genes associated with fertility traits in dairy cattle. BMC Genom Data 2024; 25:32. [PMID: 38500063 PMCID: PMC10949778 DOI: 10.1186/s12863-024-01209-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 02/15/2024] [Indexed: 03/20/2024] Open
Abstract
BACKGROUND The genetic progress of fertility and reproduction traits in dairy cattle has been constrained by the low heritability of these traits. Identifying candidate genes and variants associated with fertility and reproduction could enhance the accuracy of genetic selection and expedite breeding process of dairy cattle with low-heritability traits. While the bovine LAP3 and SIRT1 genes exhibit well-documented associations with milk production traits in dairy cattle, their effect on cow fertility have not yet been explored. Eleven single nucleotide polymorphisms (SNPs), comprising five in the promoter (rs717156555: C > G, rs720373055: T > C, rs516876447: A > G, rs461857269: C > T and rs720349928: G > A), two in 5'UTR (rs722359733: C > T and rs462932574: T > G), two in intron 12 (rs110932626: A > G and rs43702363: C > T), and one in 3'UTR of exon 13 (rs41255599: C > T) in LAP3 and one in SIRT1 (rs718329990:T > C) genes, have previously been reported to be associated with various traits of milk production and clinical mastitis in Sahiwal and Karan Fries dairy cattle. In this study, the analysis primarily aimed to assess the impact of SNPs within LAP3 and SIRT1 genes on fertility traits in Sahiwal and Karan Fries cattle. Association studies were conducted using mixed linear models, involving 125 Sahiwal and 138 Karan Fries animals in each breed. The analysis utilized a designated PCR-RFLP panel. RESULTS In the promoter region of the LAP3 gene, all variants demonstrated significant (P < 0.05) associations with AFC, except for rs722359733: C > T. However, specific variants with the LAP3 gene's promoter region, namely rs722359733: C > T, rs110932626: A > G, rs43702363: C > T, and rs41255599: C > T, showed significant associations with CI and DO in Sahiwal and Karan Fries cows, respectively. The SNP rs718329990: T > C in the promoter region of SIRT1 gene exhibited a significant association with CI and DO in Sahiwal cattle. Haplotype-based association analysis revealed significant associations between haplotype combinations and AFC, CI and DO in the studied dairy cattle population. Animals with H2H3 and H2H4 haplotype combination exhibited higher AFC, CI and DO than other combinations. CONCLUSIONS These results affirm the involvement of the LAP3 and SIRT1 genes in female fertility traits, indicating that polymorphisms within these genes are linked to the studied traits. Overall, the significant SNPs and haplotypes identified in this study could have the potential to enhance herd profitability and ensure long-term sustainability on dairy farms by enabling the selection of animals with early age first calving and enhance reproductive performance in the dairy cattle breeding program.
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Affiliation(s)
- Destaw Worku
- Department of Animal Science, College of Agriculture, Food and Climate Science, Injibara University, Injibara, Ethiopia.
| | - Archana Verma
- Animal Genetics and Breeding Division, ICAR -National Dairy Research Institute, Karnal, India
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Warburton CL, Costilla R, Engle BN, Moore SS, Corbet NJ, Fordyce G, McGowan MR, Burns BM, Hayes BJ. Concurrently mapping quantitative trait loci associations from multiple subspecies within hybrid populations. Heredity (Edinb) 2023; 131:350-360. [PMID: 37798326 PMCID: PMC10673866 DOI: 10.1038/s41437-023-00651-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 09/19/2023] [Accepted: 09/21/2023] [Indexed: 10/07/2023] Open
Abstract
Many of the world's agriculturally important plant and animal populations consist of hybrids of subspecies. Cattle in tropical and sub-tropical regions for example, originate from two subspecies, Bos taurus indicus (Bos indicus) and Bos taurus taurus (Bos taurus). Methods to derive the underlying genetic architecture for these two subspecies are essential to develop accurate genomic predictions in these hybrid populations. We propose a novel method to achieve this. First, we use haplotypes to assign SNP alleles to ancestral subspecies of origin in a multi-breed and multi-subspecies population. Then we use a BayesR framework to allow SNP alleles originating from the different subspecies differing effects. Applying this method in a composite population of B. indicus and B. taurus hybrids, our results show that there are underlying genomic differences between the two subspecies, and these effects are not identified in multi-breed genomic evaluations that do not account for subspecies of origin effects. The method slightly improved the accuracy of genomic prediction. More significantly, by allocating SNP alleles to ancestral subspecies of origin, we were able to identify four SNP with high posterior probabilities of inclusion that have not been previously associated with cattle fertility and were close to genes associated with fertility in other species. These results show that haplotypes can be used to trace subspecies of origin through the genome of this hybrid population and, in conjunction with our novel Bayesian analysis, subspecies SNP allele allocation can be used to increase the accuracy of QTL association mapping in genetically diverse populations.
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Affiliation(s)
- Christie L Warburton
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St. Lucia, QLD, Australia.
| | - Roy Costilla
- Agresearch Limited, Ruakura Research Centre, Hamilton, 3214, New Zealand
| | - Bailey N Engle
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St. Lucia, QLD, Australia
| | - Stephen S Moore
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St. Lucia, QLD, Australia
| | - Nicholas J Corbet
- Formerly Central Queensland University, School of Health, Medical and Applied Sciences, Rockhampton, QLD, Australia
| | - Geoffry Fordyce
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St. Lucia, QLD, Australia
| | - Michael R McGowan
- The University of Queensland, School of Veterinary Science, St Lucia, QLD, Australia
| | - Brian M Burns
- Formerly Department of Agriculture and Fisheries, Rockhampton, QLD, Australia
| | - Ben J Hayes
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St. Lucia, QLD, Australia
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Ahmad SF, Singh A, Gangwar M, Kumar S, Dutt T, Kumar A. Haplotype-based association study of production and reproduction traits in multigenerational Vrindavani population. Gene 2023; 867:147365. [PMID: 36918047 DOI: 10.1016/j.gene.2023.147365] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/23/2023] [Accepted: 03/08/2023] [Indexed: 03/14/2023]
Abstract
Haplotype-based association analysis promises to reveal important information regarding the effect of genetic variants on economic traits of interest. The present study aimed to evaluate the haplotype structure of Vrindavani cattle and explore the association of haplotypes with (re)production traits of economic interest. Genotyping array data of medium density (Bovine50KSNP BeadChip) on 96 randomly selected Vrindavani cows was used in the present study. Genotypes were called in GenomeStudio program while quality control was undertaken in PLINK using standard thresholds. The phenotypic traits used in the present study included age at first calving, dry days, lactation length, peak yield, total lactation milk yield, inter-calving period and service period. The haplotype structure of Vrindavani population was assessed, using a sliding window of 20 SNP with a shift of 5 SNPs at a time, in terms of the size of haplotype blocks regarding their length (in Kb) and frequency in chromosome-wise fashion. Haplotype blocks were assessed for possible association with important production and reproduction traits across three lactation cycles in Vrindavani cattle population. The first ten principal components were included in the model for haplotype-based association analysis to correct for stratification effects of assessed individuals. Multiple haplotypes were found to be associated with age at first calving, total lactation milk yield, peak yield, dry days, inter-calving period and service period. Various candidate genes were found to overlap haplotypes that were significantly associated with age at first calving (CDH18, MARCHF11, MYO10, FBXL7), total lactation milk yield (TGF, PDE1A, and COL8A1), peak yield (PPARGC1A, RCAN1, KCNE1, SMIM34 and MRPS6), dry days (CPNE4, ACAD11 and MRAS), inter-calving period (ABCG5, ABCG8 and COX7A2L) and service period (FOXL2 and PIK3CB). The putative candidate genes overlapping the significantly associated haplotypes revealed important pathways affecting the production and reproduction performance of animals. The identified genes and pathways may serve as good candidate markers to select animals for improved production and reproduction performance in future generations.
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Affiliation(s)
- Sheikh Firdous Ahmad
- ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Akansha Singh
- ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Munish Gangwar
- ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Subodh Kumar
- ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Triveni Dutt
- ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Amit Kumar
- ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
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Li H, Wang Z, Xu L, Li Q, Gao H, Ma H, Cai W, Chen Y, Gao X, Zhang L, Gao H, Zhu B, Xu L, Li J. Genomic prediction of carcass traits using different haplotype block partitioning methods in beef cattle. Evol Appl 2022; 15:2028-2042. [PMID: 36540636 PMCID: PMC9753827 DOI: 10.1111/eva.13491] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 09/18/2022] [Indexed: 09/22/2023] Open
Abstract
Genomic prediction (GP) based on haplotype alleles can capture quantitative trait loci (QTL) effects and increase predictive ability because the haplotypes are expected to be in linkage disequilibrium (LD) with QTL. In this study, we constructed haploblocks using LD-based and the fixed number of single nucleotide polymorphisms (fixed-SNP) methods with Illumina BovineHD chip in beef cattle. To evaluate the performance of different haplotype block partitioning methods, we constructed haploblocks based on LD thresholds (from r 2 > 0.2 to r 2 > 0.8) and the number of fixed-SNPs (5, 10, 20). The performance of predictive methods for three carcass traits including liveweight (LW), dressing percentage (DP), and longissimus dorsi muscle weight (LDMW) was evaluated using three approaches (GBLUP and BayesB model based on the SNP, GHBLUP, and BayesBH models based on the haploblock, and GHBLUP+GBLUP and BayesBH+BayesB models based on the combined haploblock and the nonblocked SNPs, which were located between blocks). In this study, we found the accuracies of LD-based and fixed-SNP haplotype Bayesian methods outperformed the Bayesian models (up to 8.54 ± 7.44% and 5.74 ± 2.95%, respectively). GHBLUP showed a high improvement (up to 11.29 ± 9.87%) compared with GBLUP. The Bayesian models have higher accuracies than BLUP models in most scenarios. The average computing time of the BayesBH+BayesB model can reduce by 29.3% compared with the BayesB model. The prediction accuracies using the LD-based haplotype method showed higher improvements than the fixed-SNP haplotype method. In addition, to avoid the influence of rare haplotypes generated from haplotype construction, we compared the performance of GP by filtering four types of minor haplotype allele frequency (MHAF) (0.01, 0.025, 0.05, and 0.1) under different conditions (LD levels were set at r 2 > 0.3, and the fixed number of SNPs was 5). We found the optimal MHAF threshold for LW was 0.01, and the optimal MHAF threshold for DP and LDMW was 0.025.
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Affiliation(s)
- Hongwei Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Zezhao Wang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Lei Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Qian Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Han Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Haoran Ma
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Wentao Cai
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yan Chen
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Xue Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Lupei Zhang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Huijiang Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Bo Zhu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Lingyang Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Junya Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingChina
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Araujo AC, Carneiro PLS, Alvarenga AB, Oliveira HR, Miller SP, Retallick K, Brito LF. Haplotype-Based Single-Step GWAS for Yearling Temperament in American Angus Cattle. Genes (Basel) 2021; 13:17. [PMID: 35052358 PMCID: PMC8775055 DOI: 10.3390/genes13010017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 12/14/2021] [Accepted: 12/18/2021] [Indexed: 01/23/2023] Open
Abstract
Behavior is a complex trait and, therefore, understanding its genetic architecture is paramount for the development of effective breeding strategies. The objective of this study was to perform traditional and weighted single-step genome-wide association studies (ssGWAS and WssGWAS, respectively) for yearling temperament (YT) in North American Angus cattle using haplotypes. Approximately 266 K YT records and 70 K animals genotyped using a 50 K single nucleotide polymorphisms (SNP) panel were used. Linkage disequilibrium thresholds (LD) of 0.15, 0.50, and 0.80 were used to create the haploblocks, and the inclusion of non-LD-clustered SNPs (NCSNP) with the haplotypes in the genomic models was also evaluated. WssGWAS did not perform better than ssGWAS. Cattle YT was found to be a highly polygenic trait, with genes and quantitative trait loci (QTL) broadly distributed across the whole genome. Association studies using LD-based haplotypes should include NCSNPs and different LD thresholds to increase the likelihood of finding the relevant genomic regions affecting the trait of interest. The main candidate genes identified, i.e., ATXN10, ADAM10, VAX2, ATP6V1B1, CRISPLD1, CAPRIN1, FA2H, SPEF2, PLXNA1, and CACNA2D3, are involved in important biological processes and metabolic pathways related to behavioral traits, social interactions, and aggressiveness in cattle. Future studies should further investigate the role of these candidate genes.
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Affiliation(s)
- Andre C. Araujo
- Graduate Program in Animal Sciences, State University of Southwestern Bahia, Itapetinga 45700-000, Brazil;
- Department of Animal Science, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.)
| | - Paulo L. S. Carneiro
- Department of Biology, State University of Southwest Bahia, Jequié 45205-490, Brazil;
| | - Amanda B. Alvarenga
- Department of Animal Science, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.)
| | - Hinayah R. Oliveira
- Department of Animal Science, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.)
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G2W1, Canada
| | - Stephen P. Miller
- American Angus Association, Angus Genetics Inc., 3201 Frederick Ave, St. Joseph, MO 64506, USA; (S.P.M.); (K.R.)
| | - Kelli Retallick
- American Angus Association, Angus Genetics Inc., 3201 Frederick Ave, St. Joseph, MO 64506, USA; (S.P.M.); (K.R.)
| | - Luiz F. Brito
- Department of Animal Science, Purdue University, West Lafayette, IN 47907, USA; (A.B.A.); (H.R.O.)
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Bhat JA, Yu D, Bohra A, Ganie SA, Varshney RK. Features and applications of haplotypes in crop breeding. Commun Biol 2021; 4:1266. [PMID: 34737387 PMCID: PMC8568931 DOI: 10.1038/s42003-021-02782-y] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 10/09/2021] [Indexed: 12/17/2022] Open
Abstract
Climate change with altered pest-disease dynamics and rising abiotic stresses threatens resource-constrained agricultural production systems worldwide. Genomics-assisted breeding (GAB) approaches have greatly contributed to enhancing crop breeding efficiency and delivering better varieties. Fast-growing capacity and affordability of DNA sequencing has motivated large-scale germplasm sequencing projects, thus opening exciting avenues for mining haplotypes for breeding applications. This review article highlights ways to mine haplotypes and apply them for complex trait dissection and in GAB approaches including haplotype-GWAS, haplotype-based breeding, haplotype-assisted genomic selection. Improvement strategies that efficiently deploy superior haplotypes to hasten breeding progress will be key to safeguarding global food security.
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Affiliation(s)
- Javaid Akhter Bhat
- National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Deyue Yu
- National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Abhishek Bohra
- Crop Improvement Division, ICAR- Indian Institute of Pulses Research (ICAR- IIPR), Kanpur, India
| | - Showkat Ahmad Ganie
- Department of Biotechnology, Visva-Bharati, Santiniketan, 731235, WB, India.
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India.
- State Agricultural Biotechnology Centre, Centre for Crop & Food Research Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, Australia.
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Ahmar S, Ballesta P, Ali M, Mora-Poblete F. Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing. Int J Mol Sci 2021; 22:10583. [PMID: 34638922 PMCID: PMC8508745 DOI: 10.3390/ijms221910583] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 09/26/2021] [Accepted: 09/27/2021] [Indexed: 12/23/2022] Open
Abstract
Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.
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Affiliation(s)
- Sunny Ahmar
- Institute of Biological Sciences, University of Talca, 1 Poniente 1141, Talca 3460000, Chile;
| | - Paulina Ballesta
- The National Fund for Scientific and Technological Development, Av. del Agua 3895, Talca 3460000, Chile
| | - Mohsin Ali
- Department of Forestry and Range Management, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan;
| | - Freddy Mora-Poblete
- Institute of Biological Sciences, University of Talca, 1 Poniente 1141, Talca 3460000, Chile;
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Li H, Zhu B, Xu L, Wang Z, Xu L, Zhou P, Gao H, Guo P, Chen Y, Gao X, Zhang L, Gao H, Cai W, Xu L, Li J. Genomic Prediction Using LD-Based Haplotypes Inferred From High-Density Chip and Imputed Sequence Variants in Chinese Simmental Beef Cattle. Front Genet 2021; 12:665382. [PMID: 34394182 PMCID: PMC8358323 DOI: 10.3389/fgene.2021.665382] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 06/30/2021] [Indexed: 01/05/2023] Open
Abstract
A haplotype is defined as a combination of alleles at adjacent loci belonging to the same chromosome that can be transmitted as a unit. In this study, we used both the Illumina BovineHD chip (HD chip) and imputed whole-genome sequence (WGS) data to explore haploblocks and assess haplotype effects, and the haploblocks were defined based on the different LD thresholds. The accuracies of genomic prediction (GP) for dressing percentage (DP), meat percentage (MP), and rib eye roll weight (RERW) based on haplotype were investigated and compared for both data sets in Chinese Simmental beef cattle. The accuracies of GP using the entire imputed WGS data were lower than those using the HD chip data in all cases. For DP and MP, the accuracy of GP using haploblock approaches outperformed the individual single nucleotide polymorphism (SNP) approach (GBLUP_In_Block) at specific LD levels. Hotelling’s test confirmed that GP using LD-based haplotypes from WGS data can significantly increase the accuracies of GP for RERW, compared with the individual SNP approach (∼1.4 and 1.9% for GHBLUP and GHBLUP+GBLUP, respectively). We found that the accuracies using haploblock approach varied with different LD thresholds. The LD thresholds (r2 ≥ 0.5) were optimal for most scenarios. Our results suggested that LD-based haploblock approach can improve accuracy of genomic prediction for carcass traits using both HD chip and imputed WGS data under the optimal LD thresholds in Chinese Simmental beef cattle.
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Affiliation(s)
- Hongwei Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Bo Zhu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.,National Centre of Beef Cattle Genetic Evaluation, Beijing, China
| | - Ling Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zezhao Wang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lei Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Peinuo Zhou
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Han Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Peng Guo
- College of Computer and Information Engineering, Tianjin Agricultural University, Tianjin, China
| | - Yan Chen
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xue Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lupei Zhang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huijiang Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.,National Centre of Beef Cattle Genetic Evaluation, Beijing, China
| | - Wentao Cai
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lingyang Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Junya Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.,National Centre of Beef Cattle Genetic Evaluation, Beijing, China
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Sharifi RS, Noshahr FA, Seifdavati J, Evrigh NH, Cipriano-Salazar M, Mariezcurrena-Berasain MA. Comparison of haplotype method using for genomic prediction versus single SNP genotypes in sheep breeding programs. Small Rumin Res 2021. [DOI: 10.1016/j.smallrumres.2021.106380] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Haplotype-Based Genome-Wide Association Study and Identification of Candidate Genes Associated with Carcass Traits in Hanwoo Cattle. Genes (Basel) 2020; 11:genes11050551. [PMID: 32423003 PMCID: PMC7290854 DOI: 10.3390/genes11050551] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 04/30/2020] [Accepted: 05/05/2020] [Indexed: 12/20/2022] Open
Abstract
Hanwoo, is the most popular native beef cattle in South Korea. Due to its extensive popularity, research is ongoing to enhance its carcass quality and marbling traits. In this study we conducted a haplotype-based genome-wide association study (GWAS) by constructing haplotype blocks by three methods: number of single nucleotide polymorphisms (SNPs) in a haplotype block (nsnp), length of genomic region in kb (Len) and linkage disequilibrium (LD). Significant haplotype blocks and genes associated with them were identified for carcass traits such as BFT (back fat thickness), EMA (eye Muscle area), CWT (carcass weight) and MS (marbling score). Gene-set enrichment analysis and functional annotation of genes in the significantly-associated loci revealed candidate genes, including PLCB1 and PLCB4 present on BTA13, coding for phospholipases, which might be important candidates for increasing fat deposition due to their role in lipid metabolism and adipogenesis. CEL (carboxyl ester lipase), a bile-salt activated lipase, responsible for lipid catabolic process was also identified within the significantly-associated haplotype block on BTA11. The results were validated in a different Hanwoo population. The genes and pathways identified in this study may serve as good candidates for improving carcass traits in Hanwoo cattle.
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12
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Won S, Park JE, Son JH, Lee SH, Park BH, Park M, Park WC, Chai HH, Kim H, Lee J, Lim D. Genomic Prediction Accuracy Using Haplotypes Defined by Size and Hierarchical Clustering Based on Linkage Disequilibrium. Front Genet 2020; 11:134. [PMID: 32211021 PMCID: PMC7067973 DOI: 10.3389/fgene.2020.00134] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Accepted: 02/04/2020] [Indexed: 11/13/2022] Open
Abstract
Genomic prediction is an effective way to estimate the genomic breeding values from genetic information based on statistical methods such as best linear unbiased prediction (BLUP). The used of haplotype, clusters of linked single nucleotide polymorphism (SNP) as markers instead of individual SNPs can improve the accuracy of genomic prediction. Since the probability of a quantitative trait loci to be in strong linkage disequilibrium (LD) with a cluster of markers is higher compared to an individual marker. To make haplotypes efficient in genomic prediction, finding optimal ways to define haplotypes is essential. In this study, 770K or 50K SNP chip data was collected from Hanwoo (Korean cattle) population consisted of 3,498 cattle. Using SNP chip data, haplotype was defined in three different ways based on 1) the number of SNPs included, 2) length of haplotypes (bp), and 3) agglomerative hierarchical clustering based on LD. To compare the methods in parallel, haplotypes defined by all methods were set to have comparable sizes; 5, 10, 20 or 50 SNPs on average per haplotype. A linear mixed model using haplotype to calculated the covariance matrix was applied for testing the prediction accuracy of each haplotype size. Also, conventional SNP-based linear mixed model was tested to evaluate the performance of the haplotype sets on genomic prediction. Carcass weight (CWT), eye muscle area (EMA) and backfat thickness (BFT) were used as the phenotypes. This study reveals that using haplotypes generally showed increased accuracy compared to conventional SNP-based model for CWT and EMA, but found to be small or no increase in accuracy for BFT. LD clustering-based haplotypes specifically the five SNPs size showed the highest prediction accuracy for CWT and EMA. Meanwhile, the highest accuracy was obtained when length-based haplotypes with five SNPs were used for BFT. The maximum gain in accuracy was 1.3% from cross-validation and 4.6% from forward validation for EMA, suggesting that genomic prediction accuracy can be increased by using haplotypes. However, the improvement from using haplotypes may depend on the trait of interest. In addition, when the number of alleles generated by each haplotype defining methods was compared, clustering by LD generated the least number of alleles, thereby reducing computational costs. Therefore, finding optimal ways to define haplotypes and using the haplotype alleles as markers can improve the accuracy of genomic prediction.
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Affiliation(s)
- Sohyoung Won
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea
| | - Jong-Eun Park
- National Institute of Animal Science, RDA, Wanju, South Korea
| | - Ju-Hwan Son
- National Institute of Animal Science, RDA, Wanju, South Korea
| | - Seung-Hwan Lee
- Department of Animal Science and Biotechnology, Chungnam National University, Daejeon, South Korea
| | - Byeong Ho Park
- National Institute of Animal Science, RDA, Wanju, South Korea
| | - Mina Park
- National Institute of Animal Science, RDA, Wanju, South Korea
| | - Won-Chul Park
- National Institute of Animal Science, RDA, Wanju, South Korea
| | - Han-Ha Chai
- National Institute of Animal Science, RDA, Wanju, South Korea
| | - Heebal Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea.,Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.,eGnome, Inc, Seoul, South Korea
| | - Jungjae Lee
- Jung P&C Institute, Inc., Yongin-si, South Korea
| | - Dajeong Lim
- National Institute of Animal Science, RDA, Wanju, South Korea
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Ballesta P, Maldonado C, Pérez-Rodríguez P, Mora F. SNP and Haplotype-Based Genomic Selection of Quantitative Traits in Eucalyptus globulus. PLANTS 2019; 8:plants8090331. [PMID: 31492041 PMCID: PMC6783840 DOI: 10.3390/plants8090331] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 09/02/2019] [Accepted: 09/03/2019] [Indexed: 01/02/2023]
Abstract
Eucalyptus globulus (Labill.) is one of the most important cultivated eucalypts in temperate and subtropical regions and has been successfully subjected to intensive breeding. In this study, Bayesian genomic models that include the effects of haplotype and single nucleotide polymorphisms (SNP) were assessed to predict quantitative traits related to wood quality and tree growth in a 6-year-old breeding population. To this end, the following markers were considered: (a) ~14 K SNP markers (SNP), (b) ~3 K haplotypes (HAP), and (c) haplotypes and SNPs that were not assigned to a haplotype (HAP-SNP). Predictive ability values (PA) were dependent on the genomic prediction models and markers. On average, Bayesian ridge regression (BRR) and Bayes C had the highest PA for the majority of traits. Notably, genomic models that included the haplotype effect (either HAP or HAP-SNP) significantly increased the PA of low-heritability traits. For instance, BRR based on HAP had the highest PA (0.58) for stem straightness. Consistently, the heritability estimates from genomic models were higher than the pedigree-based estimates for these traits. The results provide additional perspectives for the implementation of genomic selection in Eucalyptus breeding programs, which could be especially beneficial for improving traits with low heritability.
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Affiliation(s)
- Paulina Ballesta
- Institute of Biological Sciences, University of Talca, 2 Norte 685, Talca 3460000, Chile.
| | - Carlos Maldonado
- Institute of Biological Sciences, University of Talca, 2 Norte 685, Talca 3460000, Chile.
| | - Paulino Pérez-Rodríguez
- Colegio de Postgraduados, Statistics and Computer Sciences, Montecillos, Edo. de México 56230, Mexico.
| | - Freddy Mora
- Institute of Biological Sciences, University of Talca, 2 Norte 685, Talca 3460000, Chile.
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14
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High-frequency marker haplotypes in the genomic selection of dairy cattle. J Appl Genet 2019; 60:179-186. [PMID: 30877657 PMCID: PMC6483952 DOI: 10.1007/s13353-019-00489-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 01/18/2019] [Accepted: 02/28/2019] [Indexed: 11/05/2022]
Abstract
The aim of this study was to predict the genomic breeding value (DGV) of production, selected conformation and reproductive traits, and somatic cell score of dairy cattle in Poland using high-frequency marker haplotypes. The dataset consisted of phenotypic, genotypic, and pedigree data of 1216 Polish Holstein-Friesian bulls. The genotypic data consisted of 54,000 single-nucleotide polymorphisms (SNPs). The data were divided into two subsets: a test dataset (n = 1064) and a validation dataset (n = 152). Genotypic data were selected using three criteria: the percentage of missing genotypes, minor allele frequency, and linkage disequilibrium. The purpose of the data selection was to identify blocks of SNPs that were then used for the construction of haplotypes. Only haplotypes with a frequency higher than 25% were selected. DGV was predicted using four variants of a linear model with random haplotype effects and deregressed breeding values as the response variables. The accuracy of genomic prediction was checked by comparing DGVs with estimated breeding values (EBVs) using two methods: Pearson’s correlations and the regression of EBV on DGV. The use of high-frequency haplotypes showed a tendency to underestimate DGVs. None of the models tested was clearly superior with regard to the traits studied. DGVs of production and conformation traits as well as somatic cell score (medium or high heritability traits) were more accurate than those estimated for fertility traits (low heritability traits).
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15
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Braz CU, Taylor JF, Bresolin T, Espigolan R, Feitosa FLB, Carvalheiro R, Baldi F, de Albuquerque LG, de Oliveira HN. Sliding window haplotype approaches overcome single SNP analysis limitations in identifying genes for meat tenderness in Nelore cattle. BMC Genet 2019; 20:8. [PMID: 30642245 PMCID: PMC6332854 DOI: 10.1186/s12863-019-0713-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 01/02/2019] [Indexed: 12/30/2022] Open
Abstract
Background Traditional single nucleotide polymorphism (SNP) genome-wide association analysis (GWAA) can be inefficient because single SNPs provide limited genetic information about genomic regions. On the other hand, using haplotypes in the statistical analysis may increase the extent of linkage disequilibrium (LD) between haplotypes and causal variants and may also potentially capture epistastic interactions between variants within a haplotyped locus, providing an increase in the power and robustness of the association studies. We performed GWAA (413,355 SNP markers) using haplotypes based on variable-sized sliding windows and compared the results to a single-SNP GWAA using Warner-Bratzler shear force measured in the longissimus thorasis muscle of 3161 Nelore bulls to ascertain the optimal window size for identifying the genomic regions that influence meat tenderness. Results The GWAA using single SNPs identified eight variants influencing meat tenderness on BTA 3, 4, 9, 10 and 11. However, thirty-three putative meat tenderness QTL were detected on BTA 1, 3, 4, 5, 8, 9, 10, 11, 15, 17, 18, 24, 25, 26 and 29 using variable-sized sliding haplotype windows. Analyses using sliding window haplotypes of 3, 5, 7, 9 and 11 SNPs identified 57, 61, 42, 39, and 21% of all thirty-three putative QTL regions, respectively; however, the analyses using the 3 and 5 SNP haplotypes, cumulatively detected 88% of the putative QTL. The genes associated with variation in meat tenderness participate in myogenesis, neurogenesis, lipid and fatty acid metabolism and skeletal muscle structure or composition processes. Conclusions GWAA using haplotypes based on variable-sized sliding windows allowed the detection of more QTL than traditional single-SNP GWAA. Analyses using smaller haplotypes (3 and 5 SNPs) detected a higher proportion of the putative QTL. Electronic supplementary material The online version of this article (10.1186/s12863-019-0713-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Camila U Braz
- Animal Science Department, São Paulo State University (Unesp), Jaboticabal, SP, 144884-900, Brazil.
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA
| | - Tiago Bresolin
- Animal Science Department, São Paulo State University (Unesp), Jaboticabal, SP, 144884-900, Brazil
| | - Rafael Espigolan
- Animal Science Department, São Paulo State University (Unesp), Jaboticabal, SP, 144884-900, Brazil
| | - Fabieli L B Feitosa
- Animal Science Department, São Paulo State University (Unesp), Jaboticabal, SP, 144884-900, Brazil
| | - Roberto Carvalheiro
- Animal Science Department, São Paulo State University (Unesp), Jaboticabal, SP, 144884-900, Brazil
| | - Fernando Baldi
- Animal Science Department, São Paulo State University (Unesp), Jaboticabal, SP, 144884-900, Brazil
| | - Lucia G de Albuquerque
- Animal Science Department, São Paulo State University (Unesp), Jaboticabal, SP, 144884-900, Brazil
| | - Henrique N de Oliveira
- Animal Science Department, São Paulo State University (Unesp), Jaboticabal, SP, 144884-900, Brazil.
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16
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17
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Karimi Z, Sargolzaei M, Robinson J, Schenkel F. Assessing haplotype-based models for genomic evaluation in Holstein cattle. CANADIAN JOURNAL OF ANIMAL SCIENCE 2018. [DOI: 10.1139/cjas-2018-0009] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
A single-nucleotide polymorphisms-based genomic relationship matrix (GSNP) discriminate less identity by state from identity by descent (IBD) alleles compared with a multi-locus haplotype-based relationship matrix (GHAP), which can better capture IBD alleles and recent relationships. We aimed to compare the prediction reliability and prediction bias of genomic best linear unbiased prediction (GBLUP) using either GSNP or GHAP in Holstein cattle. Therefore, a total of 57 traits with a wide range of heritability values were analyzed. Classical validation tests were done using a validation dataset comprised of 50k genotype records of 561–669 proven bulls born in 2010–2011 with an official estimated breeding value (EBV) in 2016 and a training set of 5314–19 678 bulls born before 2010, depending on the trait. The method for building the genomic relationship matrix (G) had significant, but small effect on observed reliability (r2GEBV) (p < 0.0001) and bias (p < 0.0001). A significant interaction between G and the level of trait heritability on r2GEBV and bias was also observed (p < 0.0001). The small gains in r2GEBV and small reductions in the bias by using GHAPBLUP were increased when predicting moderate to high-heritability traits compared with low-heritability traits.
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Affiliation(s)
- Z. Karimi
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - M. Sargolzaei
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
- Semex Alliance, Guelph, ON N1H 6J2, Canada
| | - J.A.B. Robinson
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - F.S. Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
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Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers. G3-GENES GENOMES GENETICS 2018; 8:1687-1699. [PMID: 29549092 PMCID: PMC5940160 DOI: 10.1534/g3.117.300548] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects.
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19
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Hess M, Druet T, Hess A, Garrick D. Fixed-length haplotypes can improve genomic prediction accuracy in an admixed dairy cattle population. Genet Sel Evol 2017; 49:54. [PMID: 28673233 PMCID: PMC5494768 DOI: 10.1186/s12711-017-0329-y] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Accepted: 06/26/2017] [Indexed: 01/05/2023] Open
Abstract
Background Fitting covariates representing the number of haplotype alleles rather than single nucleotide polymorphism (SNP) alleles may increase genomic prediction accuracy if linkage disequilibrium between quantitative trait loci and SNPs is inadequate. The objectives of this study were to evaluate the accuracy, bias and computation time of Bayesian genomic prediction methods that fit fixed-length haplotypes or SNPs. Genotypes at 37,740 SNPs that were common to Illumina BovineSNP50 and high-density panels were phased for ~58,000 New Zealand dairy cattle. Females born before 1 June 2008 were used for training, and genomic predictions for milk fat yield (n = 24,823), liveweight (n = 13,283) and somatic cell score (n = 24,864) were validated within breed (predominantly Holstein–Friesian, predominantly Jersey, or admixed KiwiCross) in later-born females. Covariates for haplotype alleles of five lengths (125, 250, 500 kb, 1 or 2 Mb) were generated and rare haplotypes were removed at four thresholds (1, 2, 5 or 10%), resulting in 20 scenarios tested. Genomic predictions fitting covariates for either SNPs or haplotypes were calculated by using BayesA, BayesB or BayesN. This is the first study to quantify the accuracy of genomic prediction using haplotypes across the whole genome in an admixed population. Results A correlation of 0.349 ± 0.016 between yield deviation and genomic breeding values was obtained for milk fat yield in Holstein–Friesians using BayesA fitting covariates. Genomic predictions were more accurate with short haplotypes than with SNPs but less accurate with longer haplotypes than with SNPs. Fitting only the most frequent haplotype alleles reduced computation time with little decrease in prediction accuracy for short haplotypes. Trends were similar for all traits and breeds and there was little difference between Bayesian methods. Conclusions Fitting covariates for haplotype alleles rather than SNPs can increase prediction accuracy, although it decreased drastically for long (>500 kb) haplotypes. In this population, fitting 250 kb haplotypes with a 1% frequency threshold resulted in the highest genomic prediction accuracy and fitting 125 kb haplotypes with a 10% frequency threshold improved genomic prediction accuracy with comparable computation time to fitting SNPs. This increased accuracy is likely to increase genetic gain by changing the ranking of selection candidates. Electronic supplementary material The online version of this article (doi:10.1186/s12711-017-0329-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Melanie Hess
- Iowa State University, Ames, IA, USA. .,LIC, Hamilton, New Zealand.
| | | | | | - Dorian Garrick
- Iowa State University, Ames, IA, USA.,Massey University, Palmerston North, New Zealand
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N’Diaye A, Haile JK, Cory AT, Clarke FR, Clarke JM, Knox RE, Pozniak CJ. Single Marker and Haplotype-Based Association Analysis of Semolina and Pasta Colour in Elite Durum Wheat Breeding Lines Using a High-Density Consensus Map. PLoS One 2017; 12:e0170941. [PMID: 28135299 PMCID: PMC5279799 DOI: 10.1371/journal.pone.0170941] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2016] [Accepted: 01/12/2017] [Indexed: 12/30/2022] Open
Abstract
Association mapping is usually performed by testing the correlation between a single marker and phenotypes. However, because patterns of variation within genomes are inherited as blocks, clustering markers into haplotypes for genome-wide scans could be a worthwhile approach to improve statistical power to detect associations. The availability of high-density molecular data allows the possibility to assess the potential of both approaches to identify marker-trait associations in durum wheat. In the present study, we used single marker- and haplotype-based approaches to identify loci associated with semolina and pasta colour in durum wheat, the main objective being to evaluate the potential benefits of haplotype-based analysis for identifying quantitative trait loci. One hundred sixty-nine durum lines were genotyped using the Illumina 90K Infinium iSelect assay, and 12,234 polymorphic single nucleotide polymorphism (SNP) markers were generated and used to assess the population structure and the linkage disequilibrium (LD) patterns. A total of 8,581 SNPs previously localized to a high-density consensus map were clustered into 406 haplotype blocks based on the average LD distance of 5.3 cM. Combining multiple SNPs into haplotype blocks increased the average polymorphism information content (PIC) from 0.27 per SNP to 0.50 per haplotype. The haplotype-based analysis identified 12 loci associated with grain pigment colour traits, including the five loci identified by the single marker-based analysis. Furthermore, the haplotype-based analysis resulted in an increase of the phenotypic variance explained (50.4% on average) and the allelic effect (33.7% on average) when compared to single marker analysis. The presence of multiple allelic combinations within each haplotype locus offers potential for screening the most favorable haplotype series and may facilitate marker-assisted selection of grain pigment colour in durum wheat. These results suggest a benefit of haplotype-based analysis over single marker analysis to detect loci associated with colour traits in durum wheat.
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Affiliation(s)
- Amidou N’Diaye
- Department of Plant Sciences and Crop Development Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Jemanesh K. Haile
- Department of Plant Sciences and Crop Development Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Aron T. Cory
- Department of Plant Sciences and Crop Development Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Fran R. Clarke
- Semiarid Prairie Agricultural Research Centre, Agriculture and Agri-Food Canada, Swift Current, Saskatchewan, Canada
| | - John M. Clarke
- Department of Plant Sciences and Crop Development Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Ron E. Knox
- Semiarid Prairie Agricultural Research Centre, Agriculture and Agri-Food Canada, Swift Current, Saskatchewan, Canada
| | - Curtis J. Pozniak
- Department of Plant Sciences and Crop Development Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
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21
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Sánchez-Molano E, Tsiokos D, Chatziplis D, Jorjani H, Degano L, Diaz C, Rossoni A, Schwarzenbacher H, Seefried F, Varona L, Vicario D, Nicolazzi EL, Banos G. A practical approach to detect ancestral haplotypes in livestock populations. BMC Genet 2016; 17:91. [PMID: 27342071 PMCID: PMC4921009 DOI: 10.1186/s12863-016-0405-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2016] [Accepted: 06/21/2016] [Indexed: 12/04/2022] Open
Abstract
Background The effects of different evolutionary forces are expected to lead to the conservation, over many generations, of particular genomic regions (haplotypes) due to the development of linkage disequilibrium (LD). The detection and identification of early (ancestral) haplotypes can be used to clarify the evolutionary dynamics of different populations as well as identify selection signatures and genomic regions of interest to be used both in conservation and breeding programs. The aims of this study were to develop a simple procedure to identify ancestral haplotypes segregating across several generations both within and between populations with genetic links based on whole-genome scanning. This procedure was tested with simulated and then applied to real data from different genotyped populations of Spanish, Fleckvieh, Simmental and Brown-Swiss cattle. Results The identification of ancestral haplotypes has shown coincident patterns of selection across different breeds, allowing the detection of common regions of interest on different bovine chromosomes and mirroring the evolutionary dynamics of the studied populations. These regions, mainly located on chromosomes BTA5, BTA6, BTA7 and BTA21 are related with certain animal traits such as coat colour and milk protein and fat content. Conclusion In agreement with previous studies, the detection of ancestral haplotypes provides useful information for the development and comparison of breeding and conservation programs both through the identification of selection signatures and other regions of interest, and as indicator of the general genetic status of the populations. Electronic supplementary material The online version of this article (doi:10.1186/s12863-016-0405-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Enrique Sánchez-Molano
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Scotland, UK.
| | - Dimitrios Tsiokos
- Laboratory of Agrobiotechnology and Inspection of Agricultural Products, Department of Agricultural Technology, School of Agricultural Technology, Food Technology and Nutrition, Alexander Technological Educational Institute of Thessaloniki, Thessaloniki, Greece
| | - Dimitrios Chatziplis
- Laboratory of Agrobiotechnology and Inspection of Agricultural Products, Department of Agricultural Technology, School of Agricultural Technology, Food Technology and Nutrition, Alexander Technological Educational Institute of Thessaloniki, Thessaloniki, Greece
| | | | - Lorenzo Degano
- Associazione Nazionale Allevatori Bovini di razza Pezzata Rossa Italiana, Udine, Italy
| | - Clara Diaz
- Departamento de Mejora Genética Animal, INIA, Madrid, 28040, Spain
| | - Attilio Rossoni
- Associazione Nazionale Allevatori Bovini della Razza Bruna, Verona, Italy
| | | | | | - Luis Varona
- Departamento de Anatomía, Embriología y Genética, Universidad de Zaragoza, Zaragoza, 50013, Spain.,Instituto Agroalimentario de Aragón (IA2), Zaragoza, 50013, Spain
| | - Daniele Vicario
- Associazione Nazionale Allevatori Bovini di razza Pezzata Rossa Italiana, Udine, Italy
| | - Ezequiel L Nicolazzi
- Bioinformatics core facility, Fondazione Parco Tecnologico Padano, Via Einstein, Loc. CascinaCodazza, Lodi, 26900, Italy
| | - Georgios Banos
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Scotland, UK.,SRUC,The Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG, Edinburgh, UK.,School of Veterinary Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
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Jónás D, Ducrocq V, Fouilloux MN, Croiseau P. Alternative haplotype construction methods for genomic evaluation. J Dairy Sci 2016; 99:4537-4546. [DOI: 10.3168/jds.2015-10433] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2015] [Accepted: 02/08/2016] [Indexed: 11/19/2022]
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23
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Yang S, Fresnedo-Ramírez J, Wang M, Cote L, Schweitzer P, Barba P, Takacs EM, Clark M, Luby J, Manns DC, Sacks G, Mansfield AK, Londo J, Fennell A, Gadoury D, Reisch B, Cadle-Davidson L, Sun Q. A next-generation marker genotyping platform (AmpSeq) in heterozygous crops: a case study for marker-assisted selection in grapevine. HORTICULTURE RESEARCH 2016; 3:16002. [PMID: 27257505 PMCID: PMC4879517 DOI: 10.1038/hortres.2016.2] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2015] [Revised: 01/06/2016] [Accepted: 01/08/2016] [Indexed: 05/07/2023]
Abstract
Marker-assisted selection (MAS) is often employed in crop breeding programs to accelerate and enhance cultivar development, via selection during the juvenile phase and parental selection prior to crossing. Next-generation sequencing and its derivative technologies have been used for genome-wide molecular marker discovery. To bridge the gap between marker development and MAS implementation, this study developed a novel practical strategy with a semi-automated pipeline that incorporates trait-associated single nucleotide polymorphism marker discovery, low-cost genotyping through amplicon sequencing (AmpSeq) and decision making. The results document the development of a MAS package derived from genotyping-by-sequencing using three traits (flower sex, disease resistance and acylated anthocyanins) in grapevine breeding. The vast majority of sequence reads (⩾99%) were from the targeted regions. Across 380 individuals and up to 31 amplicons sequenced in each lane of MiSeq data, most amplicons (83 to 87%) had <10% missing data, and read depth had a median of 220-244×. Several strengths of the AmpSeq platform that make this approach of broad interest in diverse crop species include accuracy, flexibility, speed, high-throughput, low-cost and easily automated analysis.
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Affiliation(s)
- Shanshan Yang
- Horticulture Section, School of Integrative Plant Science, Cornell University, Geneva, NY 14456, USA
| | | | - Minghui Wang
- Bioinformatics Facility, Cornell University, Ithaca, NY 14853, USA
| | - Linda Cote
- Institute of Biotechnology, Cornell University, Ithaca, NY 14853, USA
| | - Peter Schweitzer
- Institute of Biotechnology, Cornell University, Ithaca, NY 14853, USA
| | - Paola Barba
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA
| | - Elizabeth M Takacs
- Horticulture Section, School of Integrative Plant Science, Cornell University, Geneva, NY 14456, USA
| | - Matthew Clark
- Department of Horticultural Science, University of Minnesota, St Paul, MN 55108, USA
| | - James Luby
- Department of Horticultural Science, University of Minnesota, St Paul, MN 55108, USA
| | - David C Manns
- Department of Food Science, Cornell University, Geneva, NY 14456, USA
| | - Gavin Sacks
- Department of Food Science, Cornell University, Ithaca, NY 14853, USA
| | | | - Jason Londo
- USDA-ARS Grape Genetics Research Unit, Geneva, NY 14456, USA
| | - Anne Fennell
- Plant Science Department, South Dakota State University, Brookings, SD 57007, USA
| | - David Gadoury
- Plant Pathology and Plant-Microbe Biology Section, School of Integrative Plant Science, Cornell University, Geneva, NY 14456, USA
| | - Bruce Reisch
- Horticulture Section, School of Integrative Plant Science, Cornell University, Geneva, NY 14456, USA
| | | | - Qi Sun
- Bioinformatics Facility, Cornell University, Ithaca, NY 14853, USA
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Wientjes YCJ, Veerkamp RF, Calus MPL. Using selection index theory to estimate consistency of multi-locus linkage disequilibrium across populations. BMC Genet 2015; 16:87. [PMID: 26187501 PMCID: PMC4506610 DOI: 10.1186/s12863-015-0252-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Accepted: 07/09/2015] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND The potential of combining multiple populations in genomic prediction is depending on the consistency of linkage disequilibrium (LD) between SNPs and QTL across populations. We investigated consistency of multi-locus LD across populations using selection index theory and investigated the relationship between consistency of multi-locus LD and accuracy of genomic prediction across different simulated scenarios. In the selection index, QTL genotypes were considered as breeding goal traits and SNP genotypes as index traits, based on LD among SNPs and between SNPs and QTL. The consistency of multi-locus LD across populations was computed as the accuracy of predicting QTL genotypes in selection candidates using a selection index derived in the reference population. Different scenarios of within and across population genomic prediction were evaluated, using all SNPs or only the four neighboring SNPs of a simulated QTL. Phenotypes were simulated using different numbers of QTL underlying the trait. The relationship between the calculated consistency of multi-locus LD and accuracy of genomic prediction using a GBLUP type of model was investigated. RESULTS The accuracy of predicting QTL genotypes, i.e. the measure describing consistency of multi-locus LD, was much lower for across population scenarios compared to within population scenarios, and was lower when QTL had a low MAF compared to QTL randomly selected from the SNPs. Consistency of multi-locus LD was highly correlated with the realized accuracy of genomic prediction across different scenarios and the correlation was higher when QTL were weighted according to their effects in the selection index instead of weighting QTL equally. By only considering neighboring SNPs of QTL, accuracy of predicting QTL genotypes within population decreased, but it substantially increased the accuracy across populations. CONCLUSIONS Consistency of multi-locus LD across populations is a characteristic of the properties of the QTL in the investigated populations and can provide more insight in underlying reasons for a low empirical accuracy of across population genomic prediction. By focusing in genomic prediction models only on neighboring SNPs of QTL, multi-locus LD is more consistent across populations since only short-range LD is considered, and accuracy of predicting QTL genotypes of individuals from another population is increased.
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Affiliation(s)
- Yvonne C J Wientjes
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 6700 AH, Wageningen, The Netherlands. .,Animal Breeding and Genomics Centre, Wageningen University, 6700 AH, Wageningen, The Netherlands.
| | - Roel F Veerkamp
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 6700 AH, Wageningen, The Netherlands. .,Animal Breeding and Genomics Centre, Wageningen University, 6700 AH, Wageningen, The Netherlands.
| | - Mario P L Calus
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 6700 AH, Wageningen, The Netherlands.
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Cuyabano BCD, Su G, Lund MS. Genomic prediction of genetic merit using LD-based haplotypes in the Nordic Holstein population. BMC Genomics 2014; 15:1171. [PMID: 25539631 PMCID: PMC4367958 DOI: 10.1186/1471-2164-15-1171] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2013] [Accepted: 12/12/2014] [Indexed: 11/17/2022] Open
Abstract
Background A haplotype approach to genomic prediction using high density data in dairy cattle as an alternative to single-marker methods is presented. With the assumption that haplotypes are in stronger linkage disequilibrium (LD) with quantitative trait loci (QTL) than single markers, this study focuses on the use of haplotype blocks (haploblocks) as explanatory variables for genomic prediction. Haploblocks were built based on the LD between markers, which allowed variable reduction. The haploblocks were then used to predict three economically important traits (milk protein, fertility and mastitis) in the Nordic Holstein population. Results The haploblock approach improved prediction accuracy compared with the commonly used individual single nucleotide polymorphism (SNP) approach. Furthermore, using an average LD threshold to define the haploblocks (LD≥0.45 between any two markers) increased the prediction accuracies for all three traits, although the improvement was most significant for milk protein (up to 3.1 % improvement in prediction accuracy, compared with the individual SNP approach). Hotelling’s t-tests were performed, confirming the improvement in prediction accuracy for milk protein. Because the phenotypic values were in the form of de-regressed proofs, the improved accuracy for milk protein may be due to higher reliability of the data for this trait compared with the reliability of the mastitis and fertility data. Comparisons between best linear unbiased prediction (BLUP) and Bayesian mixture models also indicated that the Bayesian model produced the most accurate predictions in every scenario for the milk protein trait, and in some scenarios for fertility. Conclusions The haploblock approach to genomic prediction is a promising method for genomic selection in animal breeding. Building haploblocks based on LD reduced the number of variables without the loss of information. This method may play an important role in the future genomic prediction involving while genome sequences.
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Affiliation(s)
| | - Guosheng Su
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Denmark.
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26
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Brard S, Ricard A. Is the use of formulae a reliable way to predict the accuracy of genomic selection? J Anim Breed Genet 2014; 132:207-17. [PMID: 25377121 DOI: 10.1111/jbg.12123] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2014] [Accepted: 09/16/2014] [Indexed: 11/28/2022]
Abstract
We studied four formulae used to predict the accuracy of genomic selection prior to genotyping. The objectives of our study were to investigate the impact of the parameters of each formula on the values of accuracy calculated using these formulae, and to check whether the accuracies reported in the literature are in agreement with the formulae. First, we computed the marginal distribution of accuracy (by integration) for each parameter of all four formulae: heritability h(2) , reference population size T, number of markers M and number of effective segments in the genome Me . Then, we collected 145 accuracies and corresponding parameters reported in 13 publications on genomic selection (mainly in dairy cattle), and performed analysis of variance to test the differences between observed and predicted accuracy with effects of formulae and parameters. The variation of accuracy for different values of each parameter indicated that two parameters, T and Me, had a significant impact and that considerable differences existed between the formulae (mean accuracies differed by up to 0.20 point). The results of our meta-analysis showed a big formula effect on the accuracies predicted using each formula, and also a significant effect of the value obtained for Me calculated from Ne (effective population size). Each formula can therefore be demonstrated to be optimal depending on the assumption used for Me . In conclusion, no rules can be applied to predict the reliability of genomic selection using these formulae.
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Affiliation(s)
- S Brard
- INRA, GenPhySE (Génétique, Physiologie et Systèmes d'Elevage), Castanet-Tolosan, France; Université de Toulouse, INP, ENSAT, GenPhySE (Génétique, Physiologie et Systèmes d'Elevage), Castanet-Tolosan, France; Université de Toulouse, INP, ENVT, GenPhySE (Génétique, Physiologie et Systèmes d'Elevage), Toulouse, France
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27
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Wu Y, Fan H, Wang Y, Zhang L, Gao X, Chen Y, Li J, Ren H, Gao H. Genome-wide association studies using haplotypes and individual SNPs in Simmental cattle. PLoS One 2014; 9:e109330. [PMID: 25330174 PMCID: PMC4203724 DOI: 10.1371/journal.pone.0109330] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2014] [Accepted: 09/10/2014] [Indexed: 01/05/2023] Open
Abstract
Recent advances in high-throughput genotyping technologies have provided the opportunity to map genes using associations between complex traits and markers. Genome-wide association studies (GWAS) based on either a single marker or haplotype have identified genetic variants and underlying genetic mechanisms of quantitative traits. Prompted by the achievements of studies examining economic traits in cattle and to verify the consistency of these two methods using real data, the current study was conducted to construct the haplotype structure in the bovine genome and to detect relevant genes genuinely affecting a carcass trait and a meat quality trait. Using the Illumina BovineHD BeadChip, 942 young bulls with genotyping data were introduced as a reference population to identify the genes in the beef cattle genome significantly associated with foreshank weight and triglyceride levels. In total, 92,553 haplotype blocks were detected in the genome. The regions of high linkage disequilibrium extended up to approximately 200 kb, and the size of haplotype blocks ranged from 22 bp to 199,266 bp. Additionally, the individual SNP analysis and the haplotype-based analysis detected similar regions and common SNPs for these two representative traits. A total of 12 and 7 SNPs in the bovine genome were significantly associated with foreshank weight and triglyceride levels, respectively. By comparison, 4 and 5 haplotype blocks containing the majority of significant SNPs were strongly associated with foreshank weight and triglyceride levels, respectively. In addition, 36 SNPs with high linkage disequilibrium were detected in the GNAQ gene, a potential hotspot that may play a crucial role for regulating carcass trait components.
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Affiliation(s)
- Yang Wu
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, China
| | - Huizhong Fan
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, China
| | - Yanhui Wang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, China
| | - Lupei Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, China
| | - Xue Gao
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, China
| | - Yan Chen
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, China
| | - Junya Li
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, China
| | - HongYan Ren
- Department of life sciences, National Natural Science Foundation of China, Beijing, China
- * E-mail: (HG); (HR)
| | - Huijiang Gao
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, China
- * E-mail: (HG); (HR)
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28
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Meuwissen THE, Odegard J, Andersen-Ranberg I, Grindflek E. On the distance of genetic relationships and the accuracy of genomic prediction in pig breeding. Genet Sel Evol 2014; 46:49. [PMID: 25158793 PMCID: PMC4237822 DOI: 10.1186/1297-9686-46-49] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2013] [Accepted: 06/24/2014] [Indexed: 11/29/2022] Open
Abstract
Background With the advent of genomic selection, alternative relationship matrices are used in animal breeding, which vary in their coverage of distant relationships due to old common ancestors. Relationships based on pedigree (A) and linkage analysis (GLA) cover only recent relationships because of the limited depth of the known pedigree. Relationships based on identity-by-state (G) include relationships up to the age of the SNP (single nucleotide polymorphism) mutations. We hypothesised that the latter relationships were too old, since QTL (quantitative trait locus) mutations for traits under selection were probably more recent than the SNPs on a chip, which are typically selected for high minor allele frequency. In addition, A and GLA relationships are too recent to cover genetic differences accurately. Thus, we devised a relationship matrix that considered intermediate-aged relationships and compared all these relationship matrices for their accuracy of genomic prediction in a pig breeding situation. Methods Haplotypes were constructed and used to build a haplotype-based relationship matrix (GH), which considers more intermediate-aged relationships, since haplotypes recombine more quickly than SNPs mutate. Dense genotypes (38 453 SNPs) on 3250 elite breeding pigs were combined with phenotypes for growth rate (2668 records), lean meat percentage (2618), weight at three weeks of age (7387) and number of teats (5851) to estimate breeding values for all animals in the pedigree (8187 animals) using the aforementioned relationship matrices. Phenotypes on the youngest 424 to 486 animals were masked and predicted in order to assess the accuracy of the alternative genomic predictions. Results Correlations between the relationships and regressions of older on younger relationships revealed that the age of the relationships increased in the order A, GLA, GH and G. Use of genomic relationship matrices yielded significantly higher prediction accuracies than A. GH and G, differed not significantly, but were significantly more accurate than GLA. Conclusions Our hypothesis that intermediate-aged relationships yield more accurate genomic predictions than G was confirmed for two of four traits, but these results were not statistically significant. Use of estimated genotype probabilities for ungenotyped animals proved to be an efficient method to include the phenotypes of ungenotyped animals.
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Affiliation(s)
- Theo H E Meuwissen
- Institute of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway.
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29
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Jacquin L, Elsen JM, Gilbert H. Using haplotypes for the prediction of allelic identity to fine-map QTL: characterization and properties. Genet Sel Evol 2014; 46:45. [PMID: 25022866 PMCID: PMC4223544 DOI: 10.1186/1297-9686-46-45] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2013] [Accepted: 05/20/2014] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Numerous methods have been developed over the last decade to predict allelic identity at unobserved loci between pairs of chromosome segments along the genome. These loci are often unobserved positions tested for the presence of quantitative trait loci (QTL). The main objective of this study was to understand from a theoretical standpoint the relation between linkage disequilibrium (LD) and allelic identity prediction when using haplotypes for fine mapping of QTL. In addition, six allelic identity predictors (AIP) were also compared in this study to determine which one performed best in theory and application. RESULTS A criterion based on a simple measure of matrix distance was used to study the relation between LD and allelic identity prediction when using haplotypes. The consistency of this criterion with the accuracy of QTL localization, another criterion commonly used to compare AIP, was evaluated on a set of real chromosomes. For this set of chromosomes, the criterion was consistent with the mapping accuracy of a simulated QTL with either low or high effect. As measured by the matrix distance, the best AIP for QTL mapping were those that best captured LD between a tested position and a QTL. Moreover the matrix distance between a tested position and a QTL was shown to decrease for some AIP when LD increased. However, the matrix distance for AIP with continuous predictions in the [0,1] interval was algebraically proven to decrease less rapidly up to a lower bound with increasing LD in the simplest situations, than the discrete predictor based on identity by state between haplotypes (IBS hap), for which there was no lower bound. The expected LD between haplotypes at a tested position and alleles at a QTL is a quantity that increases naturally when the tested position gets closer to the QTL. This behavior was demonstrated with pig and unrelated human chromosomes. CONCLUSIONS When the density of markers is high, and therefore LD between adjacent loci can be assumed to be high, the discrete predictor IBS hap is recommended since it predicts allele identity correctly when taking LD into account.
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Affiliation(s)
- Laval Jacquin
- INRA, GenPhySE (Génétique, Physiologie et Systèmes d'Elevage), F-31326, Castanet-Tolosan, France.
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30
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Genome-wide association study of temperament and tenderness using different Bayesian approaches in a Nellore–Angus crossbred population. Livest Sci 2014. [DOI: 10.1016/j.livsci.2013.12.012] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Edriss V, Fernando RL, Su G, Lund MS, Guldbrandtsen B. The effect of using genealogy-based haplotypes for genomic prediction. Genet Sel Evol 2013; 45:5. [PMID: 23496971 PMCID: PMC3655921 DOI: 10.1186/1297-9686-45-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2012] [Accepted: 02/13/2013] [Indexed: 11/10/2022] Open
Abstract
Background Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. Methods A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. Results About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Conclusions Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy.
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Affiliation(s)
- Vahid Edriss
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele DK-8830, Denmark.
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Fine-mapping quantitative trait loci with a medium density marker panel: efficiency of population structures and comparison of linkage disequilibrium linkage analysis models. Genet Res (Camb) 2013; 94:223-34. [PMID: 22950902 PMCID: PMC3487687 DOI: 10.1017/s0016672312000407] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Recently, a Haley–Knott-type regression method using combined linkage disequilibrium and linkage analyses (LDLA) was proposed to map quantitative trait loci (QTLs). Chromosome of 5 and 25 cM with 0·25 and 0·05 cM, respectively, between markers were simulated. The differences between the LDLA approaches with regard to QTL position accuracy were very limited, with a significantly better mean square error (MSE) with the LDLA regression (LDLA_reg) in sparse map cases; the contrary was observed, but not significantly, in dense map situations. The computing time required for the LDLA variance components (LDLA_vc) model was much higher than the LDLA_reg model. The precision of QTL position estimation was compared for four numbers of half-sib families, four different family sizes and two experimental designs (half-sibs, and full- and half-sibs). Regarding the number of families, MSE values were lowest for 15 or 50 half-sib families, differences not being significant. We observed that the greater the number of progenies per sire, the more accurate the QTL position. However, for a fixed population size, reducing the number of families (e.g. using a small number of large full-sib families) could lead to less accuracy of estimated QTL position.
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Legarra A, Ducrocq V. Computational strategies for national integration of phenotypic, genomic, and pedigree data in a single-step best linear unbiased prediction. J Dairy Sci 2012; 95:4629-45. [PMID: 22818478 DOI: 10.3168/jds.2011-4982] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2011] [Accepted: 04/03/2012] [Indexed: 11/19/2022]
Abstract
The single-step genomic BLUP (SSGBLUP) is a method that can integrate pedigree and genotypes at molecular markers in an optimal way. However, its present form (regular SSGBLUP) has a high computational cost (cubic in the number of genotyped animals) and may need extensive rewriting of genetic evaluation software. In this work, we propose several strategies to implement the single step in a simpler manner. The first one expands the single-step mixed-model equations to obtain equivalent equations from which the regular (including pedigree and records only) mixed-model equations are a subset. These new equations (unsymmetric extended SSGBLUP) have low computational cost, but require a nonsymmetric solver such as the biconjugate gradient stabilized method or successive underrelaxation, which is a variant of successive overrelaxation, with a relaxation factor lower than 1. In addition, we show a new derivation of the single-step method, which includes, as an extra effect, deviations from strictly polygenic breeding values. As a result, the same set of equations as above is obtained. We show that, whereas the new derivation shows apparent problems of nonpositive definiteness for certain covariance matrices, a proper equivalent model including imaginary effects always exists, leading always to the regular SSGBLUP mixed model equations. The system of equations can be solved (iterative SSGBLUP) by iterating between a pedigree and records evaluation and a genomic evaluation (each one solved by any iterative or direct method), whereas global iteration can use a block version of successive underrelaxation, which ensures convergence. The genomic evaluation can explicitly include marker or haplotype effects and possibly involve nonlinear (e.g., Bayesian by Markov chain Monte Carlo) methods. In a simulated example with 28,800 individuals and 1,800 genotyped individuals, all methods converged quickly to the same solutions. Using existing efficient methods with limited memory requirements to compute the products Gt and A(22)t for any t (where G and A(22) are genomic and pedigree relationships for genotyped animals, and t is a vector), all strategies can be converted to iteration on data procedures for which the total number of operations is linear in the number of animals + number of genotyped animals × number of markers.
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Affiliation(s)
- A Legarra
- INRA, UR 631 SAGA, F-31326 Castanet Tolosan, France.
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34
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Calus MPL, Veerkamp RF. Accuracy of multi-trait genomic selection using different methods. Genet Sel Evol 2011; 43:26. [PMID: 21729282 PMCID: PMC3146811 DOI: 10.1186/1297-9686-43-26] [Citation(s) in RCA: 190] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2011] [Accepted: 07/05/2011] [Indexed: 01/22/2023] Open
Abstract
Background Genomic selection has become a very important tool in animal genetics and is rapidly emerging in plant genetics. It holds the promise to be particularly beneficial to select for traits that are difficult or expensive to measure, such as traits that are measured in one environment and selected for in another environment. The objective of this paper was to develop three models that would permit multi-trait genomic selection by combining scarcely recorded traits with genetically correlated indicator traits, and to compare their performance to single-trait models, using simulated datasets. Methods Three (SNP) Single Nucleotide Polymorphism based models were used. Model G and BCπ0 assumed that contributed (co)variances of all SNP are equal. Model BSSVS sampled SNP effects from a distribution with large (or small) effects to model SNP that are (or not) associated with a quantitative trait locus. For reasons of comparison, model A including pedigree but not SNP information was fitted as well. Results In terms of accuracies for animals without phenotypes, the models generally ranked as follows: BSSVS > BCπ0 > G > > A. Using multi-trait SNP-based models, the accuracy for juvenile animals without any phenotypes increased up to 0.10. For animals with phenotypes on an indicator trait only, accuracy increased up to 0.03 and 0.14, for genetic correlations with the evaluated trait of 0.25 and 0.75, respectively. Conclusions When the indicator trait had a genetic correlation lower than 0.5 with the trait of interest in our simulated data, the accuracy was higher if genotypes rather than phenotypes were obtained for the indicator trait. However, when genetic correlations were higher than 0.5, using an indicator trait led to higher accuracies for selection candidates. For different combinations of traits, the level of genetic correlation below which genotyping selection candidates is more effective than obtaining phenotypes for an indicator trait, needs to be derived considering at least the heritabilities and the numbers of animals recorded for the traits involved.
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Affiliation(s)
- Mario P L Calus
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Lelystad, The Netherlands.
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35
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Calus MP, Mulder HA, Veerkamp RF. Estimating genomic breeding values and detecting QTL using univariate and bivariate models. BMC Proc 2011; 5 Suppl 3:S5. [PMID: 21624175 PMCID: PMC3103204 DOI: 10.1186/1753-6561-5-s3-s5] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Background Genomic selection is particularly beneficial for difficult or expensive to measure traits. Since multi-trait selection is an important tool to deal with such cases, an important question is what the added value is of multi-trait genomic selection. Methods The simulated dataset, including a quantitative and binary trait, was analyzed with four univariate and bivariate linear models to predict breeding values for juvenile animals. Two models estimated variance components with REML using a numerator (A), or SNP based relationship matrix (G). Two SNP based Bayesian models included one (BayesA) or two distributions (BayesC) for estimated SNP effects. The bivariate BayesC model sampled QTL probabilities for each SNP conditional on both traits. Genotypes were permuted 2,000 times against phenotypes and pedigree, to obtain significance thresholds for posterior QTL probabilities. Genotypes were permuted rather than phenotypes, to retain relationships between pedigree and phenotypes, such that polygenic effects could still be estimated. Results Correlations between estimated breeding values (EBV) of different SNP based models, for juvenile animals, were greater than 0.93 (0.87) for the quantitative (binary) trait. Estimated genetic correlation was 0.71 (0.66) for model G (A). Accuracies of breeding values of SNP based models were for both traits highest for BayesC and lowest for G. Accuracies of breeding values of bivariate models were up to 0.08 higher than for univariate models. The bivariate BayesC model detected 14 out of 32 QTL for the quantitative trait, and 8 out of 22 for the binary trait. Conclusions Accuracy of EBV clearly improved for both traits using bivariate compared to univariate models. BayesC achieved highest accuracies of EBV and was also one of the methods that found most QTL. Permuting genotypes against phenotypes and pedigree in BayesC provided an effective way to derive significance thresholds for posterior QTL probabilities.
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Affiliation(s)
- Mario Pl Calus
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Lelystad, Netherlands.
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Zhang H, Liu SH, Zhang Q, Zhang YD, Wang SZ, Wang QG, Wang YX, Tang ZQ, Li H. Fine-mapping of quantitative trait loci for body weight and bone traits and positional cloning of the RB1 gene in chicken. J Anim Breed Genet 2011; 128:366-75. [PMID: 21906182 DOI: 10.1111/j.1439-0388.2011.00927.x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Previously, a quantitative trait locus (QTL) that affects body weight (BW) at 4-12 weeks of age and carcass weight at 12 weeks of age had been mapped on chicken chromosome 1. After including more markers and individuals, the confidence interval was narrowed down to approximately 5.5 Mbps and located this QTL near a microsatellite marker (ADL328). This QTL is the same as the QTL for 12 bone traits, including metatarsus length and metatarsus circumference at 4, 6, 8, 10 and 12 weeks of age and keel length and metatarsus claw weight at 12 weeks of age, that was identified using the same population. In the current study, 1010 individuals from the Northeast Agricultural University F(2) resource population were used and 14 single-nucleotide polymorphism (SNPs) around ADL328 were developed to construct haplotypes, and an association analysis was performed to fine-map the QTL. The haplotypes were constructed on the basis of a sliding 'window', with three SNP markers included in each 'window'. The association analysis results indicated that the haplotypes in 'windows' 6-12 were significantly associated with BW and bone traits and suggested that the QTL for BW and bone traits was located between SNP8 and SNP14 or was in linkage disequilibrium with this region. The interval from SNP8 to SNP14 was approximately 400 kbps. This region contained five RefSeq genes (RB1, P2RY5, FNDC3A, MLNR and CAB39L) on the University of California Santa Cruz website. The RB1 gene was selected as a candidate gene and five SNPs were identified in the gene. The association results indicated that the RB1 gene was a major gene for BW and bone traits. The SNPs g.39692 G>A and g.77260 A>G in RB1 gene might be two quantitative trait nucleotides for BW and bone traits.
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Affiliation(s)
- H Zhang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
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Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley. PLoS One 2010; 5:e14079. [PMID: 21124933 PMCID: PMC2989918 DOI: 10.1371/journal.pone.0014079] [Citation(s) in RCA: 85] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2010] [Accepted: 10/21/2010] [Indexed: 12/30/2022] Open
Abstract
Genome-wide association studies (GWAS) may benefit from utilizing haplotype information for making marker-phenotype associations. Several rationales for grouping single nucleotide polymorphisms (SNPs) into haplotype blocks exist, but any advantage may depend on such factors as genetic architecture of traits, patterns of linkage disequilibrium in the study population, and marker density. The objective of this study was to explore the utility of haplotypes for GWAS in barley (Hordeum vulgare) to offer a first detailed look at this approach for identifying agronomically important genes in crops. To accomplish this, we used genotype and phenotype data from the Barley Coordinated Agricultural Project and constructed haplotypes using three different methods. Marker-trait associations were tested by the efficient mixed-model association algorithm (EMMA). When QTL were simulated using single SNPs dropped from the marker dataset, a simple sliding window performed as well or better than single SNPs or the more sophisticated methods of blocking SNPs into haplotypes. Moreover, the haplotype analyses performed better 1) when QTL were simulated as polymorphisms that arose subsequent to marker variants, and 2) in analysis of empirical heading date data. These results demonstrate that the information content of haplotypes is dependent on the particular mutational and recombinational history of the QTL and nearby markers. Analysis of the empirical data also confirmed our intuition that the distribution of QTL alleles in nature is often unlike the distribution of marker variants, and hence utilizing haplotype information could capture associations that would elude single SNPs. We recommend routine use of both single SNP and haplotype markers for GWAS to take advantage of the full information content of the genotype data.
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Including copy number variation in association studies to predict genotypic values. Genet Res (Camb) 2010; 92:115-25. [PMID: 20515515 DOI: 10.1017/s0016672310000091] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
The objective of this study was to investigate, both empirically and deterministically, the ability to explain genetic variation resulting from a copy number polymorphism (CNP) by including the CNP, either by its genotype or by a continuous derivation thereof, alone or together with a nearby single nucleotide polymorphism (SNP) in the model. This continuous measure of a CNP genotype could be a raw hybridization measurement, or a predicted CNP genotype. Results from simulations showed that the linkage disequilibrium (LD) between an SNP and CNP was lower than LD between two SNPs, due to the higher mutation rate at the CNP loci. The model R(2) values from analysing the simulated data were very similar to the R(2) values predicted with the deterministic formulae. Under the assumption that x copies at a CNP locus lead to the effect of x times the effect of 1 copy, including a continuous measure of a CNP locus in the model together with the genotype of a nearby SNP increased power to explain variation at the CNP locus, even when the continuous measure explained only 15% of the variation at the CNP locus.
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Pryce J, Bolormaa S, Chamberlain A, Bowman P, Savin K, Goddard M, Hayes B. A validated genome-wide association study in 2 dairy cattle breeds for milk production and fertility traits using variable length haplotypes. J Dairy Sci 2010; 93:3331-45. [DOI: 10.3168/jds.2009-2893] [Citation(s) in RCA: 118] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2009] [Accepted: 03/11/2010] [Indexed: 11/19/2022]
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Veerkamp RF, Verbyla KL, Mulder HA, Calus MPL. Simultaneous QTL detection and genomic breeding value estimation using high density SNP chips. BMC Proc 2010; 4 Suppl 1:S9. [PMID: 20380763 PMCID: PMC2857851 DOI: 10.1186/1753-6561-4-s1-s9] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The simulated dataset of the 13th QTL-MAS workshop was analysed to i) detect QTL and ii) predict breeding values for animals without phenotypic information. Several parameterisations considering all SNP simultaneously were applied using Gibbs sampling. RESULTS Fourteen QTL were detected at the different time points. Correlations between estimated breeding values were high between models, except when the model was used that assumed that all SNP effects came from one distribution. The model that used the selected 14 SNP found associated with QTL, gave close to unity correlations with the full parameterisations. CONCLUSIONS Nine out of 18 QTL were detected, however the six QTL for inflection point were missed. Models for genomic selection were indicated to be fairly robust, e.g. with respect to accuracy of estimated breeding values. Still, it is worthwhile to investigate the number QTL underlying the quantitative traits, before choosing the model used for genomic selection.
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Affiliation(s)
- Roel F Veerkamp
- Animal Breeding and Genomics Centre, ASG Wageningen UR, PO Box 65, 8200 AB Lelystad, The Netherlands .
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Mulder HA, Calus MPL, Veerkamp RF. Prediction of haplotypes for ungenotyped animals and its effect on marker-assisted breeding value estimation. Genet Sel Evol 2010; 42:10. [PMID: 20307301 PMCID: PMC2861017 DOI: 10.1186/1297-9686-42-10] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2009] [Accepted: 03/22/2010] [Indexed: 11/10/2022] Open
Abstract
Background In livestock populations, missing genotypes on a large proportion of animals are a major problem to implement the estimation of marker-assisted breeding values using haplotypes. The objective of this article is to develop a method to predict haplotypes of animals that are not genotyped using mixed model equations and to investigate the effect of using these predicted haplotypes on the accuracy of marker-assisted breeding value estimation. Methods For genotyped animals, haplotypes were determined and for each animal the number of haplotype copies (nhc) was counted, i.e. 0, 1 or 2 copies. In a mixed model framework, nhc for each haplotype were predicted for ungenotyped animals as well as for genotyped animals using the additive genetic relationship matrix. The heritability of nhc was assumed to be 0.99, allowing for minor genotyping and haplotyping errors. The predicted nhc were subsequently used in marker-assisted breeding value estimation by applying random regression on these covariables. To evaluate the method, a population was simulated with one additive QTL and an additive polygenic genetic effect. The QTL was located in the middle of a haplotype based on SNP-markers. Results The accuracy of predicted haplotype copies for ungenotyped animals ranged between 0.59 and 0.64 depending on haplotype length. Because powerful BLUP-software was used, the method was computationally very efficient. The accuracy of total EBV increased for genotyped animals when marker-assisted breeding value estimation was compared with conventional breeding value estimation, but for ungenotyped animals the increase was marginal unless the heritability was smaller than 0.1. Haplotypes based on four markers yielded the highest accuracies and when only the nearest left marker was used, it yielded the lowest accuracy. The accuracy increased with increasing marker density. Accuracy of the total EBV approached that of gene-assisted BLUP when 4-marker haplotypes were used with a distance of 0.1 cM between the markers. Conclusions The proposed method is computationally very efficient and suitable for marker-assisted breeding value estimation in large livestock populations including effects of a number of known QTL. Marker-assisted breeding value estimation using predicted haplotypes increases accuracy especially for traits with low heritability.
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Affiliation(s)
- Han A Mulder
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, PO Box 65, 8200 AB Lelystad, The Netherlands.
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