Genetic Augmentation of Legume Crops Using Genomic Resources and Genotyping Platforms for Nutritional Food Security

Overview

Journal Plants (Basel)

Date 2022 Jul 27

PMID 35890499

Authors

Romesh K Salgotra

Charles Neal Stewart Jr

Affiliations

Soon will be listed here.

Abstract

Recent advances in next generation sequencing (NGS) technologies have led the surge of genomic resources for the improvement legume crops. Advances in high throughput genotyping (HTG) and high throughput phenotyping (HTP) enable legume breeders to improve legume crops more precisely and efficiently. Now, the legume breeder can reshuffle the natural gene combinations of their choice to enhance the genetic potential of crops. These genomic resources are efficiently deployed through molecular breeding approaches for genetic augmentation of important legume crops, such as chickpea, cowpea, pigeonpea, groundnut, common bean, lentil, pea, as well as other underutilized legume crops. In the future, advances in NGS, HTG, and HTP technologies will help in the identification and assembly of superior haplotypes to tailor the legume crop varieties through haplotype-based breeding. This review article focuses on the recent development of genomic resource databases and their deployment in legume molecular breeding programmes to secure global food security.

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References

Yan L, Hofmann N, Li S, Ferreira M, Song B, Jiang G . Identification of QTL with large effect on seed weight in a selective population of soybean with genome-wide association and fixation index analyses. BMC Genomics. 2017; 18(1):529. PMC: 5508781. DOI: 10.1186/s12864-017-3922-0. View

Kongjaimun A, Kaga A, Tomooka N, Somta P, Shimizu T, Shu Y . An SSR-based linkage map of yardlong bean (Vigna unguiculata (L.) Walp. subsp. unguiculata Sesquipedalis Group) and QTL analysis of pod length. Genome. 2012; 55(2):81-92. DOI: 10.1139/g11-078. View

Chandra A, Kumar A, Bharati A, Joshi R, Agrawal A, Kumar S . Microbial-assisted and genomic-assisted breeding: a two way approach for the improvement of nutritional quality traits in agricultural crops. 3 Biotech. 2019; 10(1):2. PMC: 6879687. DOI: 10.1007/s13205-019-1994-z. View

Doddamani D, Katta M, Khan A, Agarwal G, Shah T, Varshney R . CicArMiSatDB: the chickpea microsatellite database. BMC Bioinformatics. 2014; 15:212. PMC: 4230034. DOI: 10.1186/1471-2105-15-212. View

Srivastava R, Singh M, Bajaj D, Parida S . A High-Resolution InDel (Insertion-Deletion) Markers-Anchored Consensus Genetic Map Identifies Major QTLs Governing Pod Number and Seed Yield in Chickpea. Front Plant Sci. 2016; 7:1362. PMC: 5025440. DOI: 10.3389/fpls.2016.01362. View

Hwang E, Song Q, Jia G, Specht J, Hyten D, Costa J . A genome-wide association study of seed protein and oil content in soybean. BMC Genomics. 2014; 15:1. PMC: 3890527. DOI: 10.1186/1471-2164-15-1. View

Akohoue F, Achigan-Dako E, Sneller C, Van Deynze A, Sibiya J . Genetic diversity, SNP-trait associations and genomic selection accuracy in a west African collection of Kersting's groundnut [Macrotyloma geocarpum(Harms) Maréchal & Baudet]. PLoS One. 2020; 15(6):e0234769. PMC: 7326195. DOI: 10.1371/journal.pone.0234769. View

Varshney R, Kudapa H, Roorkiwal M, Thudi M, Pandey M, Saxena R . Advances in genetics and molecular breeding of three legume crops of semi-arid tropics using next-generation sequencing and high-throughput genotyping technologies. J Biosci. 2012; 37(5):811-20. DOI: 10.1007/s12038-012-9228-0. View

Chen Z, Ly Vu J, Ly Vu B, Buitink J, Leprince O, Verdier J . Genome-Wide Association Studies of Seed Performance Traits in Response to Heat Stress in Uncover as a Regulator of Seed Germination Plasticity. Front Plant Sci. 2021; 12:673072. PMC: 8213093. DOI: 10.3389/fpls.2021.673072. View

10.

Kumar V, Rani A, Rawal R . Deployment of gene specific marker in development of kunitz trypsin inhibitor free soybean genotypes. Indian J Exp Biol. 2014; 51(12):1125-9. View

11.

Duran Y, Fratini R, Garcia P, de la Vega M . An intersubspecific genetic map of Lens. Theor Appl Genet. 2003; 108(7):1265-73. DOI: 10.1007/s00122-003-1542-3. View

12.

Wu L, Fredua-Agyeman R, Hwang S, Chang K, Conner R, McLaren D . Mapping QTL associated with partial resistance to Aphanomyces root rot in pea (Pisum sativum L.) using a 13.2 K SNP array and SSR markers. Theor Appl Genet. 2021; 134(9):2965-2990. DOI: 10.1007/s00122-021-03871-6. View

13.

Perseguini J, Oblessuc P, Rosa J, Gomes K, Chiorato A, Carbonell S . Genome-Wide Association Studies of Anthracnose and Angular Leaf Spot Resistance in Common Bean (Phaseolus vulgaris L.). PLoS One. 2016; 11(3):e0150506. PMC: 4773255. DOI: 10.1371/journal.pone.0150506. View

14.

Pazhamala L, Saxena R, Singh V, SameerKumar C, Kumar V, Sinha P . Genomics-assisted breeding for boosting crop improvement in pigeonpea (Cajanus cajan). Front Plant Sci. 2015; 6:50. PMC: 4330709. DOI: 10.3389/fpls.2015.00050. View

15.

Mahajan R, Zargar S, Singh R, Salgotra R, Farhat S, Sonah H . Population Structure Analysis and Selection of Core Set among Common Bean Genotypes from Jammu and Kashmir, India. Appl Biochem Biotechnol. 2016; 182(1):16-28. DOI: 10.1007/s12010-016-2307-1. View

16.

Wu X, Cortes A, Blair M . Genetic differentiation of grain, fodder and pod vegetable type cowpeas (Vigna unguiculata L.) identified through single nucleotide polymorphisms from genotyping-by-sequencing. Mol Hortic. 2023; 2(1):8. PMC: 10514946. DOI: 10.1186/s43897-022-00028-x. View

17.

Hale B, Ferrie A, Chellamma S, Samuel J, Phillips G . Androgenesis-Based Doubled Haploidy: Past, Present, and Future Perspectives. Front Plant Sci. 2022; 12:751230. PMC: 8777211. DOI: 10.3389/fpls.2021.751230. View

18.

Vos P, Hogers R, Bleeker M, Reijans M, van de Lee T, Hornes M . AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res. 1995; 23(21):4407-14. PMC: 307397. DOI: 10.1093/nar/23.21.4407. View

19.

Boutet G, Alves Carvalho S, Falque M, Peterlongo P, Lhuillier E, Bouchez O . SNP discovery and genetic mapping using genotyping by sequencing of whole genome genomic DNA from a pea RIL population. BMC Genomics. 2016; 17:121. PMC: 4758021. DOI: 10.1186/s12864-016-2447-2. View

20.

Pandey M, Roorkiwal M, Singh V, Ramalingam A, Kudapa H, Thudi M . Emerging Genomic Tools for Legume Breeding: Current Status and Future Prospects. Front Plant Sci. 2016; 7:455. PMC: 4852475. DOI: 10.3389/fpls.2016.00455. View