Home > Research > Publications & Outputs > Genome‐wide association and genomic prediction ...

Research

Links

Text available via DOI:

Keywords

View graph of relations

Genome‐wide association and genomic prediction for yield and component traits of <i>Miscanthus sacchariflorus</i>

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

Genome‐wide association and genomic prediction for yield and component traits of <i>Miscanthus sacchariflorus</i> / Njuguna, Joyce N.; Clark, Lindsay V.; Lipka, Alexander E. et al.
In: GCB Bioenergy, Vol. 15, No. 11, 30.11.2023, p. 1355-1372.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Njuguna, JN, Clark, LV, Lipka, AE, Anzoua, KG, Bagmet, L, Chebukin, P, Dwiyanti, MS, Dzyubenko, E, Dzyubenko, N, Ghimire, BK, Jin, X, Johnson, DA, Nagano, H, Peng, J, Petersen, KK, Sabitov, A, Seong, ES, Yamada, T, Yoo, JH, Yu, CY, Zhao, H, Long, SP & Sacks, EJ 2023, 'Genome‐wide association and genomic prediction for yield and component traits of <i>Miscanthus sacchariflorus</i>', GCB Bioenergy, vol. 15, no. 11, pp. 1355-1372. https://doi.org/10.1111/gcbb.13097

APA

Njuguna, J. N., Clark, L. V., Lipka, A. E., Anzoua, K. G., Bagmet, L., Chebukin, P., Dwiyanti, M. S., Dzyubenko, E., Dzyubenko, N., Ghimire, B. K., Jin, X., Johnson, D. A., Nagano, H., Peng, J., Petersen, K. K., Sabitov, A., Seong, E. S., Yamada, T., Yoo, J. H., ... Sacks, E. J. (2023). Genome‐wide association and genomic prediction for yield and component traits of <i>Miscanthus sacchariflorus</i> GCB Bioenergy, 15(11), 1355-1372. https://doi.org/10.1111/gcbb.13097

Vancouver

Njuguna JN, Clark LV, Lipka AE, Anzoua KG, Bagmet L, Chebukin P et al. Genome‐wide association and genomic prediction for yield and component traits of <i>Miscanthus sacchariflorus</i> GCB Bioenergy. 2023 Nov 30;15(11):1355-1372. Epub 2023 Sept 8. doi: 10.1111/gcbb.13097

Author

Njuguna, Joyce N. ; Clark, Lindsay V. ; Lipka, Alexander E. et al. / Genome‐wide association and genomic prediction for yield and component traits of <i>Miscanthus sacchariflorus</i>. In: GCB Bioenergy. 2023 ; Vol. 15, No. 11. pp. 1355-1372.

Bibtex

@article{a929dbd02b3a489f8a676873dcf3083c,
title = "Genome‐wide association and genomic prediction for yield and component traits of Miscanthus sacchariflorus",
abstract = "Accelerating biomass improvement is a major goal of Miscanthus breeding. The development and implementation of genomic‐enabled breeding tools, like marker‐assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of Miscanthus breeding. The present study conducted genome‐wide association (GWA) and genomic prediction of biomass yield and 14 yield‐components traits in Miscanthus sacchariflorus. We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single‐nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported Miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield‐component traits in M. sacchariflorus that may facilitate marker‐assisted breeding for biomass yield. Genomic prediction accuracy for the yield‐related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus. This study indicated that MAS and genomic prediction will likely be beneficial for conducting population‐improvement of M. sacchariflorus.",
keywords = "Miscanthus sacchariflorus, bioenergy, biomass, genome-wide association analysis, genomic prediction",
author = "Njuguna, {Joyce N.} and Clark, {Lindsay V.} and Lipka, {Alexander E.} and Anzoua, {Kossonou G.} and Larisa Bagmet and Pavel Chebukin and Dwiyanti, {Maria S.} and Elena Dzyubenko and Nicolay Dzyubenko and Ghimire, {Bimal Kumar} and Xiaoli Jin and Johnson, {Douglas A.} and Hironori Nagano and Junhua Peng and Petersen, {Karen Koefoed} and Andrey Sabitov and Seong, {Eun Soo} and Toshihiko Yamada and Yoo, {Ji Hye} and Yu, {Chang Yeon} and Hua Zhao and Long, {Stephen P.} and Sacks, {Erik J.}",
year = "2023",
month = nov,
day = "30",
doi = "10.1111/gcbb.13097",
language = "English",
volume = "15",
pages = "1355--1372",
journal = "GCB Bioenergy",
issn = "1757-1693",
publisher = "Blackwell Publishing Ltd",
number = "11",

}

RIS

TY - JOUR

T1 - Genome‐wide association and genomic prediction for yield and component traits of Miscanthus sacchariflorus

AU - Njuguna, Joyce N.

AU - Clark, Lindsay V.

AU - Lipka, Alexander E.

AU - Anzoua, Kossonou G.

AU - Bagmet, Larisa

AU - Chebukin, Pavel

AU - Dwiyanti, Maria S.

AU - Dzyubenko, Elena

AU - Dzyubenko, Nicolay

AU - Ghimire, Bimal Kumar

AU - Jin, Xiaoli

AU - Johnson, Douglas A.

AU - Nagano, Hironori

AU - Peng, Junhua

AU - Petersen, Karen Koefoed

AU - Sabitov, Andrey

AU - Seong, Eun Soo

AU - Yamada, Toshihiko

AU - Yoo, Ji Hye

AU - Yu, Chang Yeon

AU - Zhao, Hua

AU - Long, Stephen P.

AU - Sacks, Erik J.

PY - 2023/11/30

Y1 - 2023/11/30

N2 - Accelerating biomass improvement is a major goal of Miscanthus breeding. The development and implementation of genomic‐enabled breeding tools, like marker‐assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of Miscanthus breeding. The present study conducted genome‐wide association (GWA) and genomic prediction of biomass yield and 14 yield‐components traits in Miscanthus sacchariflorus. We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single‐nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported Miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield‐component traits in M. sacchariflorus that may facilitate marker‐assisted breeding for biomass yield. Genomic prediction accuracy for the yield‐related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus. This study indicated that MAS and genomic prediction will likely be beneficial for conducting population‐improvement of M. sacchariflorus.

AB - Accelerating biomass improvement is a major goal of Miscanthus breeding. The development and implementation of genomic‐enabled breeding tools, like marker‐assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of Miscanthus breeding. The present study conducted genome‐wide association (GWA) and genomic prediction of biomass yield and 14 yield‐components traits in Miscanthus sacchariflorus. We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single‐nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported Miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield‐component traits in M. sacchariflorus that may facilitate marker‐assisted breeding for biomass yield. Genomic prediction accuracy for the yield‐related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus. This study indicated that MAS and genomic prediction will likely be beneficial for conducting population‐improvement of M. sacchariflorus.

KW - Miscanthus sacchariflorus

KW - bioenergy

KW - biomass

KW - genome-wide association analysis

KW - genomic prediction

U2 - 10.1111/gcbb.13097

DO - 10.1111/gcbb.13097

M3 - Journal article

VL - 15

SP - 1355

EP - 1372

JO - GCB Bioenergy

JF - GCB Bioenergy

SN - 1757-1693

IS - 11

ER -