Leveraging breeding programs and genomic data in Norway spruce (Picea abies L. Karst) for GWAS analysis. Chen, Z., Zan, Y., Milesi, P., Zhou, L., Chen, J., Li, L., Cui, B., Niu, S., Westin, J., Karlsson, B., García-Gil, M. R., Lascoux, M., & Wu, H. X. Genome Biology, 22(1):179, June, 2021. Paper doi abstract bibtex 8 downloads Genome-wide association studies (GWAS) identify loci underlying the variation of complex traits. One of the main limitations of GWAS is the availability of reliable phenotypic data, particularly for long-lived tree species. Although an extensive amount of phenotypic data already exists in breeding programs, accounting for its high heterogeneity is a great challenge. We combine spatial and factor-analytics analyses to standardize the heterogeneous data from 120 field experiments of 483,424 progenies of Norway spruce to implement the largest reported GWAS for trees using 134 605 SNPs from exome sequencing of 5056 parental trees.
@article{chen_leveraging_2021,
title = {Leveraging breeding programs and genomic data in {Norway} spruce ({Picea} abies {L}. {Karst}) for {GWAS} analysis},
volume = {22},
issn = {1474-760X},
url = {https://doi.org/10.1186/s13059-021-02392-1},
doi = {10.1186/s13059-021-02392-1},
abstract = {Genome-wide association studies (GWAS) identify loci underlying the variation of complex traits. One of the main limitations of GWAS is the availability of reliable phenotypic data, particularly for long-lived tree species. Although an extensive amount of phenotypic data already exists in breeding programs, accounting for its high heterogeneity is a great challenge. We combine spatial and factor-analytics analyses to standardize the heterogeneous data from 120 field experiments of 483,424 progenies of Norway spruce to implement the largest reported GWAS for trees using 134 605 SNPs from exome sequencing of 5056 parental trees.},
number = {1},
urldate = {2021-10-14},
journal = {Genome Biology},
author = {Chen, Zhi-Qiang and Zan, Yanjun and Milesi, Pascal and Zhou, Linghua and Chen, Jun and Li, Lili and Cui, BinBin and Niu, Shihui and Westin, Johan and Karlsson, Bo and García-Gil, Maria Rosario and Lascoux, Martin and Wu, Harry X.},
month = jun,
year = {2021},
keywords = {Budburst stage, Frost damage, Genome-wide association study, MAP3K gene, Norway spruce, Wood quality},
pages = {179},
}
Downloads: 8
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One of the main limitations of GWAS is the availability of reliable phenotypic data, particularly for long-lived tree species. Although an extensive amount of phenotypic data already exists in breeding programs, accounting for its high heterogeneity is a great challenge. 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