Using Haplotype Mapping to Uncover the Missing Heritability: A Simulation Study

Masoud Shirali; Ricardo Pong-Wong; Sara Knott; Caroline Hayward; Veronique Vitart; Igor Rudan; Harry Campbell; Nick Hastie; Alan Wright; Pau Navarro; Chris Haley

Using Haplotype Mapping to Uncover the Missing Heritability: A Simulation Study

Masoud Shirali, Ricardo Pong-Wong, Sara Knott, Caroline Hayward, Veronique Vitart, Igor Rudan, Harry Campbell, Nick Hastie, Alan Wright, Pau Navarro, Chris Haley

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

An improved regional mapping method is proposed based on haplotype information with haplotype blocks being used as analysis regions. Genomic data were simulated using circa 300K SNPs. The simulated phenotypes’ heritability was 0.30 from which 0.05 was regional heritability. Twenty different regions of genome were selected to be trait associated in the simulation. Four scenarios were used to generate regional variance with either one SNP, all SNPs, one haplotype or all haplotypes from the region being the causal variants. Regional genomic relationship matrices constructed with SNP-based or haplotype-based methods were used in a REML framework to estimate the variance explained by the region. Our results show that the proposed haplotype-based method always captures the effect of the regions, albeit with decreased performance with increasing block size in SNP-based variants. SNP-based methods often do not detect the effect of causal haplotype(s).

Original language	English
Title of host publication	proceedings of the 10th World Congress in Ganetics Applied to Livestock Production
Publication status	Unpublished - 2014

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WCGALP2014ShiraliSubmitted manuscript, 349 KB

LOCATING THE MISSING HERITABILITY OF COMPLEX TRAITS USING REGIONAL HAPLOTYPE MAPPING
Haley, C., Navarro, P., Pong-Wong, R., Shirali, M. & Knott, S.
BBSRC
1/05/12 → 30/04/15
Project: Research
HGU Core Award Apr 12 - MAr 18
Hastie, N., Adams, I., Baldock, R., Bickmore, W., Caceres, J., Dorin, J., FitzPatrick, D., Haley, C., Hill, B., Jackson, I., Jackson, A., Kudla, G., Meehan, R. & Patton, E.
MRC
1/04/12 → 31/03/18
Project: Research
ISP1: Analysis and prediction in complex animal systems
Tenesa, A., Archibald, A., Beard, P., Bishop, S., Bronsvoort, M., Burt, D., Freeman, T., Haley, C., Hocking, P., Houston, R., Hume, D., Joshi, A., Law, A., Michoel, T., Summers, K., Vernimmen, D., Watson, M., Wiener, P., Wilson, A., Woolliams, J., Ait-Ali, T., Barnett, M., Carlisle, A., Finlayson, H., Haga, I., Karavolos, M., Matika, O., Paterson, T., Paton, B., Pong-Wong, R., Robert, C. & Robertson, G.
BBSRC
1/04/12 → 31/03/17
Project: Research

Cite this

@inproceedings{191eeba0962645dd9bceccbd008beff7,

title = "Using Haplotype Mapping to Uncover the Missing Heritability: A Simulation Study",

abstract = "An improved regional mapping method is proposed based on haplotype information with haplotype blocks being used as analysis regions. Genomic data were simulated using circa 300K SNPs. The simulated phenotypes{\textquoteright} heritability was 0.30 from which 0.05 was regional heritability. Twenty different regions of genome were selected to be trait associated in the simulation. Four scenarios were used to generate regional variance with either one SNP, all SNPs, one haplotype or all haplotypes from the region being the causal variants. Regional genomic relationship matrices constructed with SNP-based or haplotype-based methods were used in a REML framework to estimate the variance explained by the region. Our results show that the proposed haplotype-based method always captures the effect of the regions, albeit with decreased performance with increasing block size in SNP-based variants. SNP-based methods often do not detect the effect of causal haplotype(s).",

author = "Masoud Shirali and Ricardo Pong-Wong and Sara Knott and Caroline Hayward and Veronique Vitart and Igor Rudan and Harry Campbell and Nick Hastie and Alan Wright and Pau Navarro and Chris Haley",

year = "2014",

language = "English",

booktitle = "proceedings of the 10th World Congress in Ganetics Applied to Livestock Production",

}

TY - GEN

T1 - Using Haplotype Mapping to Uncover the Missing Heritability: A Simulation Study

AU - Shirali, Masoud

AU - Pong-Wong, Ricardo

AU - Knott, Sara

AU - Hayward, Caroline

AU - Vitart, Veronique

AU - Rudan, Igor

AU - Campbell, Harry

AU - Hastie, Nick

AU - Wright, Alan

AU - Navarro, Pau

AU - Haley, Chris

PY - 2014

Y1 - 2014

N2 - An improved regional mapping method is proposed based on haplotype information with haplotype blocks being used as analysis regions. Genomic data were simulated using circa 300K SNPs. The simulated phenotypes’ heritability was 0.30 from which 0.05 was regional heritability. Twenty different regions of genome were selected to be trait associated in the simulation. Four scenarios were used to generate regional variance with either one SNP, all SNPs, one haplotype or all haplotypes from the region being the causal variants. Regional genomic relationship matrices constructed with SNP-based or haplotype-based methods were used in a REML framework to estimate the variance explained by the region. Our results show that the proposed haplotype-based method always captures the effect of the regions, albeit with decreased performance with increasing block size in SNP-based variants. SNP-based methods often do not detect the effect of causal haplotype(s).

AB - An improved regional mapping method is proposed based on haplotype information with haplotype blocks being used as analysis regions. Genomic data were simulated using circa 300K SNPs. The simulated phenotypes’ heritability was 0.30 from which 0.05 was regional heritability. Twenty different regions of genome were selected to be trait associated in the simulation. Four scenarios were used to generate regional variance with either one SNP, all SNPs, one haplotype or all haplotypes from the region being the causal variants. Regional genomic relationship matrices constructed with SNP-based or haplotype-based methods were used in a REML framework to estimate the variance explained by the region. Our results show that the proposed haplotype-based method always captures the effect of the regions, albeit with decreased performance with increasing block size in SNP-based variants. SNP-based methods often do not detect the effect of causal haplotype(s).

M3 - Conference contribution

BT - proceedings of the 10th World Congress in Ganetics Applied to Livestock Production

ER -

Using Haplotype Mapping to Uncover the Missing Heritability: A Simulation Study

Abstract

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LOCATING THE MISSING HERITABILITY OF COMPLEX TRAITS USING REGIONAL HAPLOTYPE MAPPING

HGU Core Award Apr 12 - MAr 18

ISP1: Analysis and prediction in complex animal systems

Cite this