PANOMICS meets germplasm.
GWAS
Green systems biology
PANOMICS
crop improvement
genome editing
germplasm
multi-omics
phenotyping
plant systems biology
Journal
Plant biotechnology journal
ISSN: 1467-7652
Titre abrégé: Plant Biotechnol J
Pays: England
ID NLM: 101201889
Informations de publication
Date de publication:
07 2020
07 2020
Historique:
received:
07
12
2019
revised:
17
02
2020
accepted:
26
02
2020
pubmed:
13
3
2020
medline:
3
11
2020
entrez:
13
3
2020
Statut:
ppublish
Résumé
Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.
Identifiants
pubmed: 32163658
doi: 10.1111/pbi.13372
pmc: PMC7292548
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
1507-1525Subventions
Organisme : Austrian Science Fund FWF
ID : W1257-820
Pays : Austria
Informations de copyright
© 2020 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.
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