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Gebremedhin A, Li Y, Shunmugam ASK, Sudheesh S, Valipour-Kahrood H, Hayden MJ, Rosewarne GM, Kaur S. Genomic selection for target traits in the Australian lentil breeding program. FRONTIERS IN PLANT SCIENCE 2024; 14:1284781. [PMID: 38235201 PMCID: PMC10791954 DOI: 10.3389/fpls.2023.1284781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 12/07/2023] [Indexed: 01/19/2024]
Abstract
Genomic selection (GS) uses associations between markers and phenotypes to predict the breeding values of individuals. It can be applied early in the breeding cycle to reduce the cross-to-cross generation interval and thereby increase genetic gain per unit of time. The development of cost-effective, high-throughput genotyping platforms has revolutionized plant breeding programs by enabling the implementation of GS at the scale required to achieve impact. As a result, GS is becoming routine in plant breeding, even in minor crops such as pulses. Here we examined 2,081 breeding lines from Agriculture Victoria's national lentil breeding program for a range of target traits including grain yield, ascochyta blight resistance, botrytis grey mould resistance, salinity and boron stress tolerance, 100-grain weight, seed size index and protein content. A broad range of narrow-sense heritabilities was observed across these traits (0.24-0.66). Genomic prediction models were developed based on 64,781 genome-wide SNPs using Bayesian methodology and genomic estimated breeding values (GEBVs) were calculated. Forward cross-validation was applied to examine the prediction accuracy of GS for these targeted traits. The accuracy of GEBVs was consistently higher (0.34-0.83) than BLUP estimated breeding values (EBVs) (0.22-0.54), indicating a higher expected rate of genetic gain with GS. GS-led parental selection using early generation breeding materials also resulted in higher genetic gain compared to BLUP-based selection performed using later generation breeding lines. Our results show that implementing GS in lentil breeding will fast track the development of high-yielding cultivars with increased resistance to biotic and abiotic stresses, as well as improved seed quality traits.
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Affiliation(s)
- Alem Gebremedhin
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | - Yongjun Li
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | | | - Shimna Sudheesh
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | | | - Matthew J. Hayden
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia
| | | | - Sukhjiwan Kaur
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia
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Song J, Mavraganis I, Shen W, Yang H, Cram D, Xiang D, Patterson N, Zou J. Transcriptome dissection of candidate genes associated with lentil seed quality traits. PLANT BIOLOGY (STUTTGART, GERMANY) 2022; 24:815-826. [PMID: 35395134 DOI: 10.1111/plb.13426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 03/29/2022] [Indexed: 06/14/2023]
Abstract
Lentils provide a rich plant-based protein source and staple food in many parts of the world. Despite numerous nutritional benefits, lentil seeds also possess undesirable elements, such as anti-nutritional factors. Understanding the genetic networks of seed metabolism is of great importance for improving the seed nutritional profile. We applied RNA sequencing analysis to survey the transcriptome of developing lentil seeds and compared this with that of the pod shells and leaves. In total, we identified 2622 genes differentially expressed among the tissues examined. Genes preferentially expressed in seeds were enriched in the Gene Ontology (GO) terms associated with development, nitrogen and carbon (N/C) metabolism and lipid synthesis. We further categorized seed preferentially expressed genes based on their involvement in storage protein production, starch accumulation, lipid and suberin metabolism, phytate, saponin and phenylpropanoid biosynthesis. The availability of transcript profile datasets on lentil seed metabolism and a roadmap of candidate genes presented here will be of great value for breeding strategies towards further improvement of lentil seed quality traits.
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Affiliation(s)
- J Song
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, Saskatchewan, Canada
| | - I Mavraganis
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, Saskatchewan, Canada
| | - W Shen
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, Saskatchewan, Canada
| | - H Yang
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, Saskatchewan, Canada
| | - D Cram
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, Saskatchewan, Canada
| | - D Xiang
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, Saskatchewan, Canada
| | - N Patterson
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, Saskatchewan, Canada
| | - J Zou
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, Saskatchewan, Canada
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Wood JA, Knights EJ, Campbell GM, Harden S, Choct M. Enzyme pre-milling treatments improved milling performance of chickpeas by targeting mechanisms of seed coat and cotyledon adhesion with various effects on dhal quality. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2022; 102:62-72. [PMID: 34031883 DOI: 10.1002/jsfa.11331] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/16/2021] [Accepted: 05/25/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Dehulling and splitting are important elements of the milling process to produce dhal from pulses. However, grain that is difficult-to-mill because of tightly adhered seed coats or cotyledons that resist separation makes it difficult to achieve high quality dhal. Milling yields are reduced, energy inputs into the milling process are increased, and the resulting dhal can be of poorer quality, chipped or abraded. RESULTS Eight enzyme pre-treatments were chosen based on the hypothesised mechanisms of seed coat and cotyledon adhesion established previously. Using a difficult-to-mill chickpea (Cicer arietinum L.) genotype, we examined the effects of these pre-treatments, over time, on laboratory-scale milling performance and dhal quality. We pioneered a texture analyser method to measure the flex of the cotyledons and the force required to cleave the cotyledons. The enzyme-induced changes ranged from negative (tough seed coat, weight loss, deleterious colour and texture, increased visual damage to cotyledons and increased kibble loss, concave cotyledons, increased flex, and changes in taste) to positive (brittle seed coat, increased seed volume, improved dehulling efficiency and splitting yield, reduced cotyledon cleavage force, and acceptable dhal quality and taste). CONCLUSION All pre-treatments improved milling performance compared to milling the raw seed, although there was considerable variation between them. Two pre-treatments showed no improvement in milling yields compared to the water control, and several pre-treatments resulted in unacceptable qualities. Three pre-treatments, endo-polygalacturonanase, α-galactosidase and cellulase, show potential for commercial milling applications and could assist pulse millers globally to achieve high quality dhal at the same time as minimising milling effort. © 2021 Society of Chemical Industry.
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Affiliation(s)
- Jennifer A Wood
- NSW Department of Primary Industries, Tamworth Agricultural Institute, Calala, NSW, Australia
| | - Edmund J Knights
- NSW Department of Primary Industries, Tamworth Agricultural Institute, Calala, NSW, Australia
| | | | - Steven Harden
- NSW Department of Primary Industries, Tamworth Agricultural Institute, Calala, NSW, Australia
| | - Mingan Choct
- University of New England, Armidale, NSW, Australia
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Tiwari M, Singh B, Min D, Jagadish SVK. Omics Path to Increasing Productivity in Less-Studied Crops Under Changing Climate-Lentil a Case Study. FRONTIERS IN PLANT SCIENCE 2022; 13:813985. [PMID: 35615121 PMCID: PMC9125188 DOI: 10.3389/fpls.2022.813985] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 04/04/2022] [Indexed: 05/08/2023]
Abstract
Conventional breeding techniques for crop improvement have reached their full potential, and hence, alternative routes are required to ensure a sustained genetic gain in lentils. Although high-throughput omics technologies have been effectively employed in major crops, less-studied crops such as lentils have primarily relied on conventional breeding. Application of genomics and transcriptomics in lentils has resulted in linkage maps and identification of QTLs and candidate genes related to agronomically relevant traits and biotic and abiotic stress tolerance. Next-generation sequencing (NGS) complemented with high-throughput phenotyping (HTP) technologies is shown to provide new opportunities to identify genomic regions and marker-trait associations to increase lentil breeding efficiency. Recent introduction of image-based phenotyping has facilitated to discern lentil responses undergoing biotic and abiotic stresses. In lentil, proteomics has been performed using conventional methods such as 2-D gel electrophoresis, leading to the identification of seed-specific proteome. Metabolomic studies have led to identifying key metabolites that help differentiate genotypic responses to drought and salinity stresses. Independent analysis of differentially expressed genes from publicly available transcriptomic studies in lentils identified 329 common transcripts between heat and biotic stresses. Similarly, 19 metabolites were common across legumes, while 31 were common in genotypes exposed to drought and salinity stress. These common but differentially expressed genes/proteins/metabolites provide the starting point for developing high-yielding multi-stress-tolerant lentils. Finally, the review summarizes the current findings from omic studies in lentils and provides directions for integrating these findings into a systems approach to increase lentil productivity and enhance resilience to biotic and abiotic stresses under changing climate.
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Affiliation(s)
- Manish Tiwari
- Department of Agronomy, Kansas State University, Manhattan, KS, United States
- *Correspondence: Manish Tiwari,
| | - Baljinder Singh
- National Institute of Plant Genome Research, New Delhi, India
| | - Doohong Min
- Department of Agronomy, Kansas State University, Manhattan, KS, United States
| | - S. V. Krishna Jagadish
- Department of Agronomy, Kansas State University, Manhattan, KS, United States
- S. V. Krishna Jagadish,
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Gela T, Ramsay L, Haile TA, Vandenberg A, Bett K. Identification of anthracnose race 1 resistance loci in lentil by integrating linkage mapping and genome-wide association study. THE PLANT GENOME 2021; 14:e20131. [PMID: 34482633 DOI: 10.1002/tpg2.20131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 06/08/2021] [Indexed: 05/24/2023]
Abstract
Anthracnose, caused byColletotrichum lentis, is a devastating disease of lentil (Lens culinaris Medik.) in western Canada. Growing resistant lentil cultivars is the most cost-effective and environmentally friendly approach to prevent seed yield losses that can exceed 70%. To identify loci conferring resistance to anthracnose race 1 in lentil, biparental quantitative trait loci (QTL) mapping of two recombinant inbred line (RIL) populations was integrated with a genome-wide association study (GWAS) using 200 diverse lentil accessions from a lentil diversity panel. A major-effect QTL (qAnt1.Lc-3) conferring resistance to race 1 was mapped to lentil chromosome 3 and colocated on the lentil physical map for both RIL populations. Clusters of candidate nucleotide-binding leucine-rich repeat (NB-LRR) and other defense-related genes were uncovered within the QTL region. A GWAS detected 14 significant single nucleotide polymorphism (SNP) markers associated with race 1 resistance on chromosomes 3, 4, 5, and 6. The most significant GWAS SNPs on chromosome 3 supported qAnt1.Lc-3 and delineated a region of 1.6 Mb containing candidate resistance genes. The identified SNP markers can be directly applied in marker-assisted selection (MAS) to accelerate the introgression of race 1 resistance in lentil breeding.
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Affiliation(s)
- Tadesse Gela
- Crop Development Centre, Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, Saskatchewan, S7N 5A8, Canada
| | - Larissa Ramsay
- Crop Development Centre, Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, Saskatchewan, S7N 5A8, Canada
| | - Teketel A Haile
- Crop Development Centre, Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, Saskatchewan, S7N 5A8, Canada
| | - Albert Vandenberg
- Crop Development Centre, Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, Saskatchewan, S7N 5A8, Canada
| | - Kirstin Bett
- Crop Development Centre, Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, Saskatchewan, S7N 5A8, Canada
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Kumar J, Sen Gupta D. Prospects of next generation sequencing in lentil breeding. Mol Biol Rep 2020; 47:9043-9053. [PMID: 33037962 DOI: 10.1007/s11033-020-05891-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Accepted: 10/03/2020] [Indexed: 11/28/2022]
Abstract
Lentil is an important food legume crop that has large and complex genome. During past years, considerable attention has been given on the use of next generation sequencing for enriching the genomic resources including identification of SSR and SNP markers, development of unigenes, transcripts, and identification of candidate genes for biotic and abiotic stresses, analysis of genetic diversity and identification of genes/ QTLs for agronomically important traits. However, in other crops including pulses, next generation sequencing has revolutionized the genomic research and helped in genomic assisted breeding rapidly and cost effectively. The present review discuss current status and future prospects of the use NGS based breeding in lentil.
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Affiliation(s)
- Jitendra Kumar
- Division of Crop Improvement, ICAR-Indian Institute of Pulses Research, Kalyanpur, Kanpur, 208024, India.
| | - Debjyoti Sen Gupta
- Division of Crop Improvement, ICAR-Indian Institute of Pulses Research, Kalyanpur, Kanpur, 208024, India
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Marzougui A, Ma Y, Zhang C, McGee RJ, Coyne CJ, Main D, Sankaran S. Advanced Imaging for Quantitative Evaluation of Aphanomyces Root Rot Resistance in Lentil. FRONTIERS IN PLANT SCIENCE 2019; 10:383. [PMID: 31057562 PMCID: PMC6477098 DOI: 10.3389/fpls.2019.00383] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 03/13/2019] [Indexed: 05/08/2023]
Abstract
Aphanomyces root rot (ARR) is a soil-borne disease that results in severe yield losses in lentil. The development of resistant cultivars is one of the key strategies to control this pathogen. However, the evaluation of disease severity is limited to visual scores that can be subjective. This study utilized image-based phenotyping approaches to evaluate Aphanomyces euteiches resistance in lentil genotypes in greenhouse (351 genotypes from lentil single plant/LSP derived collection and 191 genotypes from recombinant inbred lines/RIL using digital Red-Green-Blue/RGB and hyperspectral imaging) and field (173 RIL genotypes using unmanned aerial system-based multispectral imaging) conditions. Moderate to strong correlations were observed between RGB, multispectral, and hyperspectral derived features extracted from lentil shoots/roots and visual scores. In general, root features extracted from RGB imaging were found to be strongly associated with disease severity. With only three root traits, elastic net regression model was able to predict disease severity across and within multiple datasets (R 2 = 0.45-0.73 and RMSE = 0.66-1.00). The selected features could represent visual disease scores. Moreover, we developed twelve normalized difference spectral indices (NDSIs) that were significantly correlated with disease scores: two NDSIs for lentil shoot section - computed from wavelengths of 1170, 1160, 1270, and 1280 nm (0.12 ≤ |r| ≤ 0.24, P < 0.05) and ten NDSIs for lentil root sections - computed from wavelengths in the range of 630-670, 700-840, and 1320-1530 nm (0.10 ≤ |r| ≤ 0.50, P < 0.05). Root-derived NDSIs were more accurate in predicting disease scores with an R 2 of 0.54 (RMSE = 0.86), especially when the model was trained and tested on LSP accessions, compared to R 2 of 0.25 (RMSE = 1.64) when LSP and RIL genotypes were used as train and test datasets, respectively. Importantly, NDSIs - computed from wavelengths of 700, 710, 730, and 790 nm - had strong positive correlations with disease scores (0.35 ≤r ≤ 0.50, P < 0.0001), which was confirmed in field phenotyping with similar correlations using vegetation index with red edge wavelength (normalized difference red edge, 0.36 ≤ |r| ≤ 0.57, P < 0.0001). The adopted image-based phenotyping approaches can help plant breeders to objectively quantify ARR resistance and reduce the subjectivity in selecting potential genotypes.
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Affiliation(s)
- Afef Marzougui
- Department of Biological Systems Engineering, Washington State University, Pullman, WA, United States
| | - Yu Ma
- Department of Horticulture, Washington State University, Pullman, WA, United States
| | - Chongyuan Zhang
- Department of Biological Systems Engineering, Washington State University, Pullman, WA, United States
| | - Rebecca J. McGee
- United States Department of Agriculture-Agricultural Research Service, Grain Legume Genetics and Physiology Research Unit, Washington State University, Pullman, WA, United States
| | - Clarice J. Coyne
- United States Department of Agriculture-Agricultural Research Service, Plant Germplasm Introduction and Testing Unit, Washington State University, Pullman, WA, United States
| | - Dorrie Main
- Department of Horticulture, Washington State University, Pullman, WA, United States
| | - Sindhuja Sankaran
- Department of Biological Systems Engineering, Washington State University, Pullman, WA, United States
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