Strategies for imputation to whole genome sequence using a single or multi-breed reference population in cattle

BMC Genomics

Volumn 15, Issue 1, 2014, Pages

  Brøndum, Rasmus F ^a   Guldbrandtsen, Bernt ^a   Sahana, Goutam ^a   Lund, Mogens S ^a   Su, Guosheng ^a  

^a AARHUS UNIVERSITY   (Denmark)

Author keywords

Allele frequency; Cross validation; Imputation; Next generation sequencing; Pre phasing

Indexed keywords

ARTICLE; AUTOSOME; BROWN SWISS CATTLE; BULL (MAMMAL); CATTLE BREED; CONTROLLED STUDY; GENE FREQUENCY; GENE SEQUENCE; GENETIC CORRELATION; GENETIC VARIABILITY; GENOME ANALYSIS; GENOME SIZE; HOLSTEIN CATTLE; IMPUTATION; JERSEY CATTLE; MATHEMATICAL MODEL; MEASUREMENT ACCURACY; NONHUMAN; NORDIC RED CATTLE; PROBABILITY; REFERENCE DATABASE; SEQUENCE ANALYSIS; SINGLE NUCLEOTIDE POLYMORPHISM; VALIDATION PROCESS; ANIMAL; BOVINE; BREEDING; COMPUTER PROGRAM; DNA SEQUENCE; GENETICS; GENOME; GENOTYPING TECHNIQUE; HIGH THROUGHPUT SEQUENCING; MALE; PROCEDURES; STANDARD; STANDARDS;

BOS;

ANIMALS; BREEDING; CATTLE; GENE FREQUENCY; GENOME; GENOTYPING TECHNIQUES; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; MALE; POLYMORPHISM, SINGLE NUCLEOTIDE; REFERENCE STANDARDS; SEQUENCE ANALYSIS, DNA; SOFTWARE;

EID: 84906822558     PISSN: None     EISSN: 14712164     Source Type: Journal    
DOI: 10.1186/1471-2164-15-728     Document Type: Article

References (30)

1. Meuwissen TH, Hayes BJ, Goddard ME. Prediction of total genetic value using genome-wide dense marker maps. Genetics 2001, 157:1819-1829.
2. Matukumalli LK, Lawley CT, Schnabel RD, Taylor JF, Allan MF, Heaton MP, O'Connell J, Moore SS, Smith TPL, Sonstegard TS, Van Tassell CP. Development and characterization of a high density SNP genotyping assay for cattle. PLoS One 2009, 4:e5350.
3. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, McCarthy MI, Ramos EM, Cardon LR, Chakravarti A, Cho JH, Guttmacher AE, Kong A, Kruglyak L, Mardis E, Rotimi CN, Slatkin M, Valle D, Whittemore AS, Boehnke M, Clark AG, Eichler EE, Gibson G, Haines JL, Mackay TFC, McCarroll SA, Visscher PM. Finding the missing heritability of complex diseases. Nature 2009, 461:747-753.
4. Abecasis GR, Altshuler D, Auton A, Brooks LD, Durbin RM, Gibbs RA, Hurles ME, McVean GA. A map of human genome variation from population-scale sequencing. Nature 2010, 467:1061-1073.
5. Daetwyler HD, Capitan A, Pausch H, Stothard P, van Binsbergen R, Brøndum RF, Liao X, Grohs C, Jung S, Baur A, Esquerre´ D, Gollnick N, Legrain S, Laurent P, Djari A, Rossignol M-N, Klopp C, Rocha D, Fritz S, Eggen A, Bowman P, Coote D, Chamberlain A, VanTassel CP, Hulsegge I, Goddard M, Guldbrandtsen B, Lund MS, Veerkamp R, Boichard D, et al. Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle. Nat Genet 2014, 46:858-865.
6. Brøndum RF, Ma P, Lund MS, Su G. Short communication: Genotype imputation within and across Nordic cattle breeds. J Dairy Sci 2012, 95:6795-6800.
7. Dassonneville R, Brøndum RF, Druet T, Fritz S, Guillaume F, Guldbrandtsen B, Lund MS, Ducrocq V, Su G. Effect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations. J Dairy Sci 2011, 94:3679-3686.
8. Hoze´ C, Fouilloux M-N, Venot E, Guillaume F, Dassonneville R, Fritz S, Ducrocq V, Phocas F, Boichard D, Croiseau P. High-density marker imputation accuracy in sixteen French cattle breeds. Genet Sel Evol 2013, 45:33.
9. Hayes BJ, Bowman PJ, Daetwyler HD, Kijas JW, van der Werf JHJ. Accuracy of genotype imputation in sheep breeds. Anim Genet 2012, 43:72-80.
10. Zhang Z, Druet T. Marker imputation with low-density marker panels in Dutch Holstein cattle. J Dairy Sci 2010, 93:5487-5494.
11. Berry DP, McClure MC, Mullen MP. Within- and across-breed imputation of high-density genotypes in dairy and beef cattle from medium- and low-density genotypes. J Anim Breed Genet 2013, 131:165-172.
12. De Roos APW, Hayes BJ, Spelman RJ, Goddard ME. Linkage disequilibrium and persistence of phase in Holstein-Friesian, Jersey and Angus cattle. Genetics 2008, 179:1503-1512.
13. Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet 2012, 44:955-959.
14. Delaneau O, Zagury J-F, Marchini J. Improved whole-chromosome phasing for disease and population genetic studies. Nat Methods 2013, 10:5-6.
15. Browning BL, Browning SR. A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am J Hum Genet 2009, 84:210-223.
16. Ma P, Brøndum RF, Zhang Q, Lund MS, Su G. Comparison of different methods for imputing genome-wide marker genotypes in Swedish and Finnish Red Cattle. J Dairy Sci 2013, 96:4666-4677.
17. Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 2009, 5:e1000529.
18. Sargolzaei M, Chesnais JP, Schenkel FS. FImpute - An efficient imputation algorithm for dairy cattle populations. J Anim Sci 2011, 89(E-Suppl 1):333. J Dairy Sci Vol 94, E-Suppl 1.
19. Howie B, Marchini J, Stephens M. Genotype imputation with thousands of genomes. G3 (Bethesda) 2011, 1:457-470.
20. Li H, Ruan J, Durbin R. Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res 2008, 18:1851-1858.
21. Zimin AV, Delcher AL, Florea L, Kelley DR, Schatz MC, Puiu D, Hanrahan F, Pertea G, Van Tassell CP, Sonstegard TS, Marc¸ais G, Roberts M, Subramanian P, Yorke JA, Salzberg SL. A whole-genome assembly of the domestic cow. Bos taurus Genome Biol 2009, 10:R42.
22. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009, 25:1754-1760.
23. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. The sequence alignment/map format and SAMtools. Bioinformatics 2009, 25:2078-2079.
24. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010, 20:1297-1303.
25. Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 2001, 29:308-311.
26. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST, McVean G, Durbin R. The variant call format and VCFtools. Bioinformatics 2011, 27:2156-2158.
27. Su G, Brøndum RF, Ma P, Guldbrandtsen B, Aamand GP, Lund MS. Comparison of genomic predictions using medium-density (∼54,000) and high-density (∼777,000) single nucleotide polymorphism marker panels in Nordic Holstein and Red Dairy Cattle populations. J Dairy Sci 2012, 95:4657-4665.
28. Gao H, Su G, Janss L, Zhang Y, Lund MS. Model comparison on genomic predictions using high-density markers for different groups of bulls in the Nordic Holstein population. J Dairy Sci 2013, 96:4678-4687.
29. Kadri NK. Methods For Association Mapping Using Multiple Population Data 2014, Aarhus University, Department of Molecular Biology and Genetics, PhD thesis.
30. Browning BL, Browning SR. Improving the accuracy and efficiency of identity-by-descent detection in population data. Genetics 2013, 194:459-471.