Focused identification of germplasm strategy (FIGS): a strategic approach for trait-enhanced pre-breeding

Genebanks maintain a rich source of variation for resistance against many pests and diseases and tolerance to abiotic stresses. However, identifying appropriate germplasm from the collection is frequently impeded by incomplete phenotyping of voluminous collections. The focused identification of germ...

Full description

Saved in:
Bibliographic Details
Published in:Genetic resources and crop evolution 2024, Vol.71 (1), p.1-16
Main Authors: Sunitha, N. C., Prathibha, M. D., Thribhuvan, R., Lokeshkumar, B. M., Basavaraj, P. S., Lohithaswa, H. C., Anilkumar, C.
Format: Article
Language:English
Subjects:
Agriculture
Biomedical and Life Sciences
Breeding
Data science
Genomics
Germplasm
Information processing
Life Sciences
Natural selection
Pests
Phenotypes
Phenotyping
Plant Genetics and Genomics
Plant Physiology
Plant Sciences
Plant Systematics/Taxonomy/Biogeography
Review Paper
Strategy
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Genebanks maintain a rich source of variation for resistance against many pests and diseases and tolerance to abiotic stresses. However, identifying appropriate germplasm from the collection is frequently impeded by incomplete phenotyping of voluminous collections. The focused identification of germplasm strategy (FIGS) helps to overcome the limitations of phenotyping genebank collections for a target trait. FIGS utilizes a priory information of the evolutionary relationship between trait and environment and helps to phenotype only those accessions with a high probability of having new allelic variation for the target trait. FIGS selects only those accessions that are likely to have evolved in the environments under natural selection pressure. Further, crop genomics and data analytics models can be trained with different filters to identify the best subset with novel alleles. A combination of genomics and data science with FIGS has the potential to improve the efficiency and precision of identifying the best accession to use in pre-breeding for target traits. This review discusses in detail the rationale, importance, strategies, integration with genomics, and applications of FIGS for pre-breeding programs.
ISSN:0925-9864
1573-5109
DOI:10.1007/s10722-023-01669-7