Capturing Wheat Phenotypes at the Genome Level
Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.
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Frontiers Media
2022-07-04
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Subjects: | Quantitative trait locus mapping, CRISPR/Cas9, QTL cloning, Wheat, Abiotic-stress tolerance, Disease resistance, Genome-wide association, Genomic selection, |
Online Access: | http://hdl.handle.net/10261/286919 http://dx.doi.org/10.13039/501100011011 http://dx.doi.org/10.13039/501100001659 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/100000199 http://dx.doi.org/10.13039/501100000268 http://dx.doi.org/10.13039/501100000980 http://dx.doi.org/10.13039/100005825 http://dx.doi.org/10.13039/100000001 https://api.elsevier.com/content/abstract/scopus_id/85134628015 |
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Quantitative trait locus mapping CRISPR/Cas9 QTL cloning Wheat Abiotic-stress tolerance Disease resistance Genome-wide association Genomic selection Quantitative trait locus mapping CRISPR/Cas9 QTL cloning Wheat Abiotic-stress tolerance Disease resistance Genome-wide association Genomic selection |
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Quantitative trait locus mapping CRISPR/Cas9 QTL cloning Wheat Abiotic-stress tolerance Disease resistance Genome-wide association Genomic selection Quantitative trait locus mapping CRISPR/Cas9 QTL cloning Wheat Abiotic-stress tolerance Disease resistance Genome-wide association Genomic selection Hussain, Babar Akpınar, Bala Anı Alaux, Michael Algharib, Ahmed M. Sehgal, Deepmala Ali, Zulfiqar Aradottir, Gudbjorg I. Batley, Jacqueline Bellec, Arnaud Bentley, Alison R. Cagirici, Halise B. Cattivelli, Luigi Choulet, Fred Cockram, James Desiderio, Francesca Devaux, Pierre Dogramaci, Munevver Dorado, Gabriel Dreisigacker, Susanne Edwards, David El-Hassouni, Khaoula Eversole, Kellye Fahima, Tzion Figueroa, Melania Gálvez, Sergio Gill, Kulvinder S. Govta, Liubov Gul, Alvina Hensel, Goetz Hernández Molina, Pilar Crespo-Herrera, Leonardo Abdiel Ibrahim, Amir Kilian, Benjamin Korzun, Viktor Krugman, Tamar Li, Yinghui Liu, Shuyu Mahmoud, Amer F. Morgounov, Alexey Muslu, Tugdem Naseer, Faiza Ordon, Frank Paux, Etienne Perovic, Dragan Reddy, Gadi V. P. Reif, Jochen C. Reynolds, Matthew Roychowdhury, Rajib Rudd, Jackie Sen, Taner Z. Sukumaran, Sivakumar Özdemir, Bahar Soğutmaz Tiwari, Vijay Kumar Ullah, Naimat Unver, Turgay Yazar, Selami Appels, Rudi Budak, Hikmet Capturing Wheat Phenotypes at the Genome Level |
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Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence. |
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Department of Agriculture (US) |
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Department of Agriculture (US) Hussain, Babar Akpınar, Bala Anı Alaux, Michael Algharib, Ahmed M. Sehgal, Deepmala Ali, Zulfiqar Aradottir, Gudbjorg I. Batley, Jacqueline Bellec, Arnaud Bentley, Alison R. Cagirici, Halise B. Cattivelli, Luigi Choulet, Fred Cockram, James Desiderio, Francesca Devaux, Pierre Dogramaci, Munevver Dorado, Gabriel Dreisigacker, Susanne Edwards, David El-Hassouni, Khaoula Eversole, Kellye Fahima, Tzion Figueroa, Melania Gálvez, Sergio Gill, Kulvinder S. Govta, Liubov Gul, Alvina Hensel, Goetz Hernández Molina, Pilar Crespo-Herrera, Leonardo Abdiel Ibrahim, Amir Kilian, Benjamin Korzun, Viktor Krugman, Tamar Li, Yinghui Liu, Shuyu Mahmoud, Amer F. Morgounov, Alexey Muslu, Tugdem Naseer, Faiza Ordon, Frank Paux, Etienne Perovic, Dragan Reddy, Gadi V. P. Reif, Jochen C. Reynolds, Matthew Roychowdhury, Rajib Rudd, Jackie Sen, Taner Z. Sukumaran, Sivakumar Özdemir, Bahar Soğutmaz Tiwari, Vijay Kumar Ullah, Naimat Unver, Turgay Yazar, Selami Appels, Rudi Budak, Hikmet |
format |
artículo de revisión |
topic_facet |
Quantitative trait locus mapping CRISPR/Cas9 QTL cloning Wheat Abiotic-stress tolerance Disease resistance Genome-wide association Genomic selection |
author |
Hussain, Babar Akpınar, Bala Anı Alaux, Michael Algharib, Ahmed M. Sehgal, Deepmala Ali, Zulfiqar Aradottir, Gudbjorg I. Batley, Jacqueline Bellec, Arnaud Bentley, Alison R. Cagirici, Halise B. Cattivelli, Luigi Choulet, Fred Cockram, James Desiderio, Francesca Devaux, Pierre Dogramaci, Munevver Dorado, Gabriel Dreisigacker, Susanne Edwards, David El-Hassouni, Khaoula Eversole, Kellye Fahima, Tzion Figueroa, Melania Gálvez, Sergio Gill, Kulvinder S. Govta, Liubov Gul, Alvina Hensel, Goetz Hernández Molina, Pilar Crespo-Herrera, Leonardo Abdiel Ibrahim, Amir Kilian, Benjamin Korzun, Viktor Krugman, Tamar Li, Yinghui Liu, Shuyu Mahmoud, Amer F. Morgounov, Alexey Muslu, Tugdem Naseer, Faiza Ordon, Frank Paux, Etienne Perovic, Dragan Reddy, Gadi V. P. Reif, Jochen C. Reynolds, Matthew Roychowdhury, Rajib Rudd, Jackie Sen, Taner Z. Sukumaran, Sivakumar Özdemir, Bahar Soğutmaz Tiwari, Vijay Kumar Ullah, Naimat Unver, Turgay Yazar, Selami Appels, Rudi Budak, Hikmet |
author_sort |
Hussain, Babar |
title |
Capturing Wheat Phenotypes at the Genome Level |
title_short |
Capturing Wheat Phenotypes at the Genome Level |
title_full |
Capturing Wheat Phenotypes at the Genome Level |
title_fullStr |
Capturing Wheat Phenotypes at the Genome Level |
title_full_unstemmed |
Capturing Wheat Phenotypes at the Genome Level |
title_sort |
capturing wheat phenotypes at the genome level |
publisher |
Frontiers Media |
publishDate |
2022-07-04 |
url |
http://hdl.handle.net/10261/286919 http://dx.doi.org/10.13039/501100011011 http://dx.doi.org/10.13039/501100001659 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/100000199 http://dx.doi.org/10.13039/501100000268 http://dx.doi.org/10.13039/501100000980 http://dx.doi.org/10.13039/100005825 http://dx.doi.org/10.13039/100000001 https://api.elsevier.com/content/abstract/scopus_id/85134628015 |
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dig-ias-es-10261-2869192024-05-14T20:50:18Z Capturing Wheat Phenotypes at the Genome Level Hussain, Babar Akpınar, Bala Anı Alaux, Michael Algharib, Ahmed M. Sehgal, Deepmala Ali, Zulfiqar Aradottir, Gudbjorg I. Batley, Jacqueline Bellec, Arnaud Bentley, Alison R. Cagirici, Halise B. Cattivelli, Luigi Choulet, Fred Cockram, James Desiderio, Francesca Devaux, Pierre Dogramaci, Munevver Dorado, Gabriel Dreisigacker, Susanne Edwards, David El-Hassouni, Khaoula Eversole, Kellye Fahima, Tzion Figueroa, Melania Gálvez, Sergio Gill, Kulvinder S. Govta, Liubov Gul, Alvina Hensel, Goetz Hernández Molina, Pilar Crespo-Herrera, Leonardo Abdiel Ibrahim, Amir Kilian, Benjamin Korzun, Viktor Krugman, Tamar Li, Yinghui Liu, Shuyu Mahmoud, Amer F. Morgounov, Alexey Muslu, Tugdem Naseer, Faiza Ordon, Frank Paux, Etienne Perovic, Dragan Reddy, Gadi V. P. Reif, Jochen C. Reynolds, Matthew Roychowdhury, Rajib Rudd, Jackie Sen, Taner Z. Sukumaran, Sivakumar Özdemir, Bahar Soğutmaz Tiwari, Vijay Kumar Ullah, Naimat Unver, Turgay Yazar, Selami Appels, Rudi Budak, Hikmet Department of Agriculture (US) National Institute of Food and Agriculture (US) National Science Foundation (US) Junta de Andalucía European Commission Biotechnology and Biological Sciences Research Council (UK) Two Blades Foundation Grains Research and Development Corporation (Australia) Ministry of Science and Higher Education of the Russian Federation German Research Foundation Czech Science Foundation Government of Norway Quantitative trait locus mapping CRISPR/Cas9 QTL cloning Wheat Abiotic-stress tolerance Disease resistance Genome-wide association Genomic selection Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence. HB was funded by USDA-NIFA SBIRI and SBIRII. PH and SG were funded by project P18-RT-992 from Junta de Andalucía (Andalusian Regional Government), Spain (Co-funded by FEDER). JC was funded by BBSRC grant BB/P010741/1. MF is supported by the 2Blades Foundation and Grains Research and Development Corporation (project CSP1801-013RTX/9176010). VK is supported by the Ministry of Science and Higher Education of the Russian Federation (grant no. 075-15-2019-1881). GH was supported by funding of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—EXC-2048/1—project ID 390686111 and grants 426557363 and 458717903, the European Regional Development Fund (Project ID ZS/2018/06/93171), and the Czech Science Foundation (CZ.02.1.01./0.0/0.0/16_019/0000827, SPP 813103381). BK thanks the Government of Norway (QZA-14/0005) for funding the initiative of “Adapting Agriculture to Climate Change: Collecting, Protecting and Preparing Crop Wild Relatives” (https://www.cwrdiversity.org/project/pre-breeding/). Peer reviewed 2023-01-17T08:39:18Z 2023-01-17T08:39:18Z 2022-07-04 artículo de revisión http://purl.org/coar/resource_type/c_dcae04bc Frontiers in Plant Science 13: 851079 (2022) http://hdl.handle.net/10261/286919 10.3389/fpls.2022.851079 1664-462X http://dx.doi.org/10.13039/501100011011 http://dx.doi.org/10.13039/501100001659 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/100000199 http://dx.doi.org/10.13039/501100000268 http://dx.doi.org/10.13039/501100000980 http://dx.doi.org/10.13039/100005825 http://dx.doi.org/10.13039/100000001 35860541 2-s2.0-85134628015 https://api.elsevier.com/content/abstract/scopus_id/85134628015 en Publisher's version Hussain, Babar; Akpınar, Bala Anı; Alaux, Michael; Algharib, Ahmed M.; Sehgal, Deepmala; Ali, Zulfiqar; Aradottir, Gudbjorg I.; Batley, Jacqueline; Bellec, Arnaud; Bentley, Alison R.; Cagirici, Halise B.; Cattivelli, Luigi; Choulet, Fred; Cockram, James; Desiderio, Francesca; Devaux, Pierre; Dogramaci, Munevver; Dorado, Gabriel; Dreisigacker, Susanne; Edwards, David; El-Hassouni, Khaoula; Eversole, Kellye; Fahima, Tzion; Figueroa, Melania; Gálvez, Sergio; Gill, Kulvinder S.; Govta, Liubov; Gul, Alvina; Hensel, Goetz; Hernández Rodríguez, Pilar; Crespo-Herrera, Leonardo Abdiel; Ibrahim, Amir; Kilian, Benjamin; Korzun, Viktor; Krugman, Tamar; Li, Yinghui; Liu, Shuyu; Mahmoud, Amer F.; Morgounov, Alexey; Muslu, Tugdem; Naseer, Faiza; Ordon, Frank; Paux, Etienne; Perovic, Dragan; Reddy, Gadi V. P.; Reif, Jochen C.; Reynolds, Matthew; Roychowdhury, Rajib; Rudd, Jackie; Sen, Taner Z.; Sukumaran, Sivakumar; Özdemir, Bahar Soğutmaz; Tiwari, Vijay Kumar; Ullah, Naimat; Unver, Turgay; Yazar, Selami; Appels, Rudi; Budak, Hikmet; 2022; Data_Sheet_1_Capturing Wheat Phenotypes at the Genome Level.docx [Dataset]; Figshare; https://doi.org/10.3389/fpls.2022.851079.s001 https://doi.org/10.3389/fpls.2022.851079 Sí open application/pdf Frontiers Media |