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Items: 1 to 50 of 58

1.

Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits.

Xiang R, Berg IVD, MacLeod IM, Hayes BJ, Prowse-Wilkins CP, Wang M, Bolormaa S, Liu Z, Rochfort SJ, Reich CM, Mason BA, Vander Jagt CJ, Daetwyler HD, Lund MS, Chamberlain AJ, Goddard ME.

Proc Natl Acad Sci U S A. 2019 Sep 24;116(39):19398-19408. doi: 10.1073/pnas.1904159116. Epub 2019 Sep 9.

2.

Artificial selection causes significant linkage disequilibrium among multiple unlinked genes in Australian wheat.

Joukhadar R, Daetwyler HD, Gendall AR, Hayden MJ.

Evol Appl. 2019 Jul 18;12(8):1610-1625. doi: 10.1111/eva.12807. eCollection 2019 Sep.

3.

Extension of a haplotype-based genomic prediction model to manage multi-environment wheat data using environmental covariates.

He S, Thistlethwaite R, Forrest K, Shi F, Hayden MJ, Trethowan R, Daetwyler HD.

Theor Appl Genet. 2019 Nov;132(11):3143-3154. doi: 10.1007/s00122-019-03413-1. Epub 2019 Aug 21.

PMID:
31435703
4.

Population-dependent reproducible deviation from natural bread wheat genome in synthetic hexaploid wheat.

Jighly A, Joukhadar R, Sehgal D, Singh S, Ogbonnaya FC, Daetwyler HD.

Plant J. 2019 Nov;100(4):801-812. doi: 10.1111/tpj.14480. Epub 2019 Sep 3.

PMID:
31355965
5.

Using imputed whole-genome sequence data to improve the accuracy of genomic prediction for parasite resistance in Australian sheep.

Al Kalaldeh M, Gibson J, Duijvesteijn N, Daetwyler HD, MacLeod I, Moghaddar N, Lee SH, van der Werf JHJ.

Genet Sel Evol. 2019 Jun 26;51(1):32. doi: 10.1186/s12711-019-0476-4.

6.

Assessment of low-coverage nanopore long read sequencing for SNP genotyping in doubled haploid canola (Brassica napus L.).

Malmberg MM, Spangenberg GC, Daetwyler HD, Cogan NOI.

Sci Rep. 2019 Jun 18;9(1):8688. doi: 10.1038/s41598-019-45131-0.

7.

Accuracy of imputation to whole-genome sequence in sheep.

Bolormaa S, Chamberlain AJ, Khansefid M, Stothard P, Swan AA, Mason B, Prowse-Wilkins CP, Duijvesteijn N, Moghaddar N, van der Werf JH, Daetwyler HD, MacLeod IM.

Genet Sel Evol. 2019 Jan 17;51(1):1. doi: 10.1186/s12711-018-0443-5.

8.

Evaluation and Recommendations for Routine Genotyping Using Skim Whole Genome Re-sequencing in Canola.

Malmberg MM, Barbulescu DM, Drayton MC, Shinozuka M, Thakur P, Ogaji YO, Spangenberg GC, Daetwyler HD, Cogan NOI.

Front Plant Sci. 2018 Dec 7;9:1809. doi: 10.3389/fpls.2018.01809. eCollection 2018.

9.

1000 Bull Genomes Project to Map Simple and Complex Genetic Traits in Cattle: Applications and Outcomes.

Hayes BJ, Daetwyler HD.

Annu Rev Anim Biosci. 2019 Feb 15;7:89-102. doi: 10.1146/annurev-animal-020518-115024. Epub 2019 Dec 3.

PMID:
30508490
10.

Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation.

Yurchenko AA, Daetwyler HD, Yudin N, Schnabel RD, Vander Jagt CJ, Soloshenko V, Lhasaranov B, Popov R, Taylor JF, Larkin DM.

Sci Rep. 2018 Aug 28;8(1):12984. doi: 10.1038/s41598-018-31304-w.

11.

Genomic Prediction Using Prior Quantitative Trait Loci Information Reveals a Large Reservoir of Underutilised Blackleg Resistance in Diverse Canola (Brassica napus L.) Lines.

Fikere M, Barbulescu DM, Malmberg MM, Shi F, Koh JCO, Slater AT, MacLeod IM, Bowman PJ, Salisbury PA, Spangenberg GC, Cogan NOI, Daetwyler HD.

Plant Genome. 2018 Jul;11(2). doi: 10.3835/plantgenome2017.11.0100.

12.

Genome variants associated with RNA splicing variations in bovine are extensively shared between tissues.

Xiang R, Hayes BJ, Vander Jagt CJ, MacLeod IM, Khansefid M, Bowman PJ, Yuan Z, Prowse-Wilkins CP, Reich CM, Mason BA, Garner JB, Marett LC, Chen Y, Bolormaa S, Daetwyler HD, Chamberlain AJ, Goddard ME.

BMC Genomics. 2018 Jul 4;19(1):521. doi: 10.1186/s12864-018-4902-8.

13.

Exploitation of data from breeding programs supports rapid implementation of genomic selection for key agronomic traits in perennial ryegrass.

Pembleton LW, Inch C, Baillie RC, Drayton MC, Thakur P, Ogaji YO, Spangenberg GC, Forster JW, Daetwyler HD, Cogan NOI.

Theor Appl Genet. 2018 Sep;131(9):1891-1902. doi: 10.1007/s00122-018-3121-7. Epub 2018 Jun 2.

14.

Genomic prediction of the polled and horned phenotypes in Merino sheep.

Duijvesteijn N, Bolormaa S, Daetwyler HD, van der Werf JHJ.

Genet Sel Evol. 2018 May 22;50(1):28. doi: 10.1186/s12711-018-0398-6.

15.

Diversity and Genome Analysis of Australian and Global Oilseed Brassica napus L. Germplasm Using Transcriptomics and Whole Genome Re-sequencing.

Malmberg MM, Shi F, Spangenberg GC, Daetwyler HD, Cogan NOI.

Front Plant Sci. 2018 Apr 19;9:508. doi: 10.3389/fpls.2018.00508. eCollection 2018.

16.

Insights into population genetics and evolution of polyploids and their ancestors.

Jighly A, Lin Z, Forster JW, Spangenberg GC, Hayes BJ, Daetwyler HD.

Mol Ecol Resour. 2018 Apr 26. doi: 10.1111/1755-0998.12896. [Epub ahead of print]

PMID:
29697892
17.

Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals.

Bouwman AC, Daetwyler HD, Chamberlain AJ, Ponce CH, Sargolzaei M, Schenkel FS, Sahana G, Govignon-Gion A, Boitard S, Dolezal M, Pausch H, Brøndum RF, Bowman PJ, Thomsen B, Guldbrandtsen B, Lund MS, Servin B, Garrick DJ, Reecy J, Vilkki J, Bagnato A, Wang M, Hoff JL, Schnabel RD, Taylor JF, Vinkhuyzen AAE, Panitz F, Bendixen C, Holm LE, Gredler B, Hozé C, Boussaha M, Sanchez MP, Rocha D, Capitan A, Tribout T, Barbat A, Croiseau P, Drögemüller C, Jagannathan V, Vander Jagt C, Crowley JJ, Bieber A, Purfield DC, Berry DP, Emmerling R, Götz KU, Frischknecht M, Russ I, Sölkner J, Van Tassell CP, Fries R, Stothard P, Veerkamp RF, Boichard D, Goddard ME, Hayes BJ.

Nat Genet. 2018 Mar;50(3):362-367. doi: 10.1038/s41588-018-0056-5. Epub 2018 Feb 19.

PMID:
29459679
18.

Genetic Diversity, Population Structure and Ancestral Origin of Australian Wheat.

Joukhadar R, Daetwyler HD, Bansal UK, Gendall AR, Hayden MJ.

Front Plant Sci. 2017 Dec 12;8:2115. doi: 10.3389/fpls.2017.02115. eCollection 2017.

19.

Meta-analysis of sequence-based association studies across three cattle breeds reveals 25 QTL for fat and protein percentages in milk at nucleotide resolution.

Pausch H, Emmerling R, Gredler-Grandl B, Fries R, Daetwyler HD, Goddard ME.

BMC Genomics. 2017 Nov 9;18(1):853. doi: 10.1186/s12864-017-4263-8.

20.

Genotyping-by-sequencing through transcriptomics: implementation in a range of crop species with varying reproductive habits and ploidy levels.

Malmberg MM, Pembleton LW, Baillie RC, Drayton MC, Sudheesh S, Kaur S, Shinozuka H, Verma P, Spangenberg GC, Daetwyler HD, Forster JW, Cogan NOI.

Plant Biotechnol J. 2018 Apr;16(4):877-889. doi: 10.1111/pbi.12835. Epub 2017 Oct 13.

21.

Rapid Discovery of De Novo Deleterious Mutations in Cattle Enhances the Value of Livestock as Model Species.

Bourneuf E, Otz P, Pausch H, Jagannathan V, Michot P, Grohs C, Piton G, Ammermüller S, Deloche MC, Fritz S, Leclerc H, Péchoux C, Boukadiri A, Hozé C, Saintilan R, Créchet F, Mosca M, Segelke D, Guillaume F, Bouet S, Baur A, Vasilescu A, Genestout L, Thomas A, Allais-Bonnet A, Rocha D, Colle MA, Klopp C, Esquerré D, Wurmser C, Flisikowski K, Schwarzenbacher H, Burgstaller J, Brügmann M, Dietschi E, Rudolph N, Freick M, Barbey S, Fayolle G, Danchin-Burge C, Schibler L, Bed'Hom B, Hayes BJ, Daetwyler HD, Fries R, Boichard D, Pin D, Drögemüller C, Capitan A.

Sci Rep. 2017 Sep 13;7(1):11466. doi: 10.1038/s41598-017-11523-3.

22.

Accelerating wheat breeding for end-use quality with multi-trait genomic predictions incorporating near infrared and nuclear magnetic resonance-derived phenotypes.

Hayes BJ, Panozzo J, Walker CK, Choy AL, Kant S, Wong D, Tibbits J, Daetwyler HD, Rochfort S, Hayden MJ, Spangenberg GC.

Theor Appl Genet. 2017 Dec;130(12):2505-2519. doi: 10.1007/s00122-017-2972-7. Epub 2017 Aug 24.

PMID:
28840266
23.

Multiple-trait QTL mapping and genomic prediction for wool traits in sheep.

Bolormaa S, Swan AA, Brown DJ, Hatcher S, Moghaddar N, van der Werf JH, Goddard ME, Daetwyler HD.

Genet Sel Evol. 2017 Aug 15;49(1):62. doi: 10.1186/s12711-017-0337-y.

24.

Exome sequence genotype imputation in globally diverse hexaploid wheat accessions.

Shi F, Tibbits J, Pasam RK, Kay P, Wong D, Petkowski J, Forrest KL, Hayes BJ, Akhunova A, Davies J, Webb S, Spangenberg GC, Akhunov E, Hayden MJ, Daetwyler HD.

Theor Appl Genet. 2017 Jul;130(7):1393-1404. doi: 10.1007/s00122-017-2895-3. Epub 2017 Apr 4.

PMID:
28378053
25.

Mitigation of inbreeding while preserving genetic gain in genomic breeding programs for outbred plants.

Lin Z, Shi F, Hayes BJ, Daetwyler HD.

Theor Appl Genet. 2017 May;130(5):969-980. doi: 10.1007/s00122-017-2863-y. Epub 2017 Mar 31.

PMID:
28364262
26.

Erratum to: Detection and validation of structural variations in bovine whole-genome sequence data.

Chen L, Chamberlain AJ, Reich CM, Daetwyler HD, Hayes BJ.

Genet Sel Evol. 2017 Mar 3;49(1):31. doi: 10.1186/s12711-017-0305-6. No abstract available.

27.

Detection and validation of genomic regions associated with resistance to rust diseases in a worldwide hexaploid wheat landrace collection using BayesR and mixed linear model approaches.

Pasam RK, Bansal U, Daetwyler HD, Forrest KL, Wong D, Petkowski J, Willey N, Randhawa M, Chhetri M, Miah H, Tibbits J, Bariana H, Hayden MJ.

Theor Appl Genet. 2017 Apr;130(4):777-793. doi: 10.1007/s00122-016-2851-7. Epub 2017 Mar 2.

PMID:
28255670
28.

Evaluation of the accuracy of imputed sequence variant genotypes and their utility for causal variant detection in cattle.

Pausch H, MacLeod IM, Fries R, Emmerling R, Bowman PJ, Daetwyler HD, Goddard ME.

Genet Sel Evol. 2017 Feb 21;49(1):24. doi: 10.1186/s12711-017-0301-x.

29.

Genomic prediction of reproduction traits for Merino sheep.

Bolormaa S, Brown DJ, Swan AA, van der Werf JHJ, Hayes BJ, Daetwyler HD.

Anim Genet. 2017 Jun;48(3):338-348. doi: 10.1111/age.12541. Epub 2017 Feb 17.

PMID:
28211150
30.

Detection and validation of structural variations in bovine whole-genome sequence data.

Chen L, Chamberlain AJ, Reich CM, Daetwyler HD, Hayes BJ.

Genet Sel Evol. 2017 Jan 25;49(1):13. doi: 10.1186/s12711-017-0286-5. Erratum in: Genet Sel Evol. 2017 Mar 3;49(1):31.

31.

Improving Genetic Gain with Genomic Selection in Autotetraploid Potato.

Slater AT, Cogan NO, Forster JW, Hayes BJ, Daetwyler HD.

Plant Genome. 2016 Nov;9(3). doi: 10.3835/plantgenome2016.02.0021. Review.

32.

Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass.

Lin Z, Cogan NO, Pembleton LW, Spangenberg GC, Forster JW, Hayes BJ, Daetwyler HD.

Plant Genome. 2016 Mar;9(1). doi: 10.3835/plantgenome2015.06.0046.

33.

Detailed phenotyping identifies genes with pleiotropic effects on body composition.

Bolormaa S, Hayes BJ, van der Werf JH, Pethick D, Goddard ME, Daetwyler HD.

BMC Genomics. 2016 Mar 12;17:224. doi: 10.1186/s12864-016-2538-0.

34.

Accuracy of genotype imputation based on random and selected reference sets in purebred and crossbred sheep populations and its effect on accuracy of genomic prediction.

Moghaddar N, Gore KP, Daetwyler HD, Hayes BJ, van der Werf JH.

Genet Sel Evol. 2015 Dec 22;47:97. doi: 10.1186/s12711-015-0175-8.

35.

Rare Variants in Transcript and Potential Regulatory Regions Explain a Small Percentage of the Missing Heritability of Complex Traits in Cattle.

Gonzalez-Recio O, Daetwyler HD, MacLeod IM, Pryce JE, Bowman PJ, Hayes BJ, Goddard ME.

PLoS One. 2015 Dec 7;10(12):e0143945. doi: 10.1371/journal.pone.0143945. eCollection 2015.

36.

Design of a low-density SNP chip for the main Australian sheep breeds and its effect on imputation and genomic prediction accuracy.

Bolormaa S, Gore K, van der Werf JH, Hayes BJ, Daetwyler HD.

Anim Genet. 2015 Oct;46(5):544-56. doi: 10.1111/age.12340. Epub 2015 Sep 11.

PMID:
26360638
37.

Selection on Optimal Haploid Value Increases Genetic Gain and Preserves More Genetic Diversity Relative to Genomic Selection.

Daetwyler HD, Hayden MJ, Spangenberg GC, Hayes BJ.

Genetics. 2015 Aug;200(4):1341-8. doi: 10.1534/genetics.115.178038. Epub 2015 Jun 19.

38.

How old are quantitative trait loci and how widely do they segregate?

Kemper KE, Hayes BJ, Daetwyler HD, Goddard ME.

J Anim Breed Genet. 2015 Apr;132(2):121-34. doi: 10.1111/jbg.12152.

PMID:
25823838
39.

Assessment of genetic variation within a global collection of lentil (Lens culinaris Medik.) cultivars and landraces using SNP markers.

Lombardi M, Materne M, Cogan NO, Rodda M, Daetwyler HD, Slater AT, Forster JW, Kaur S.

BMC Genet. 2014 Dec 24;15:150. doi: 10.1186/s12863-014-0150-3.

40.

Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle.

Daetwyler HD, Capitan A, Pausch H, Stothard P, van Binsbergen R, Brøndum RF, Liao X, Djari A, Rodriguez SC, Grohs C, Esquerré D, Bouchez O, Rossignol MN, Klopp C, Rocha D, Fritz S, Eggen A, Bowman PJ, Coote D, Chamberlain AJ, Anderson C, VanTassell CP, Hulsegge I, Goddard ME, Guldbrandtsen B, Lund MS, Veerkamp RF, Boichard DA, Fries R, Hayes BJ.

Nat Genet. 2014 Aug;46(8):858-65. doi: 10.1038/ng.3034. Epub 2014 Jul 13.

PMID:
25017103
41.

Genomic prediction for rust resistance in diverse wheat landraces.

Daetwyler HD, Bansal UK, Bariana HS, Hayden MJ, Hayes BJ.

Theor Appl Genet. 2014 Aug;127(8):1795-803. doi: 10.1007/s00122-014-2341-8. Epub 2014 Jun 26.

PMID:
24965887
42.

Genomic selection for recovery of original genetic background from hybrids of endangered and common breeds.

Amador C, Hayes BJ, Daetwyler HD.

Evol Appl. 2014 Feb;7(2):227-37. doi: 10.1111/eva.12113. Epub 2013 Oct 14.

43.

An independent validation association study of carcass quality, shear force, intramuscular fat percentage and omega-3 polyunsaturated fatty acid content with gene markers in Australian lamb.

Knight MI, Daetwyler HD, Hayes BJ, Hayden MJ, Ball AJ, Pethick DW, McDonagh MB.

Meat Sci. 2014 Feb;96(2 Pt B):1025-33. doi: 10.1016/j.meatsci.2013.07.008. Epub 2013 Jul 17.

44.

Genomic prediction in animals and plants: simulation of data, validation, reporting, and benchmarking.

Daetwyler HD, Calus MP, Pong-Wong R, de Los Campos G, Hickey JM.

Genetics. 2013 Feb;193(2):347-65. doi: 10.1534/genetics.112.147983. Epub 2012 Dec 5. Review.

45.

Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation.

Daetwyler HD, Swan AA, van der Werf JH, Hayes BJ.

Genet Sel Evol. 2012 Nov 12;44:33. doi: 10.1186/1297-9686-44-33.

46.

Components of the accuracy of genomic prediction in a multi-breed sheep population.

Daetwyler HD, Kemper KE, van der Werf JH, Hayes BJ.

J Anim Sci. 2012 Oct;90(10):3375-84. doi: 10.2527/jas.2011-4557.

PMID:
23038744
47.

Comparing linkage and association analyses in sheep points to a better way of doing GWAS.

Kemper KE, Daetwyler HD, Visscher PM, Goddard ME.

Genet Res (Camb). 2012 Aug;94(4):191-203. doi: 10.1017/S0016672312000365.

PMID:
22950900
48.

Improved accuracy of genomic prediction for dry matter intake of dairy cattle from combined European and Australian data sets.

de Haas Y, Calus MP, Veerkamp RF, Wall E, Coffey MP, Daetwyler HD, Hayes BJ, Pryce JE.

J Dairy Sci. 2012 Oct;95(10):6103-12. doi: 10.3168/jds.2011-5280. Epub 2012 Aug 3.

49.

Whole-genome regression and prediction methods applied to plant and animal breeding.

de Los Campos G, Hickey JM, Pong-Wong R, Daetwyler HD, Calus MP.

Genetics. 2013 Feb;193(2):327-45. doi: 10.1534/genetics.112.143313. Epub 2012 Jun 28. Review.

50.

Whole-genome resequencing of two elite sires for the detection of haplotypes under selection in dairy cattle.

Larkin DM, Daetwyler HD, Hernandez AG, Wright CL, Hetrick LA, Boucek L, Bachman SL, Band MR, Akraiko TV, Cohen-Zinder M, Thimmapuram J, Macleod IM, Harkins TT, McCague JE, Goddard ME, Hayes BJ, Lewin HA.

Proc Natl Acad Sci U S A. 2012 May 15;109(20):7693-8. doi: 10.1073/pnas.1114546109. Epub 2012 Apr 23.

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