1
|
Yadav RK, Tripathi MK, Tiwari S, Tripathi N, Asati R, Patel V, Sikarwar RS, Payasi DK. Breeding and Genomic Approaches towards Development of Fusarium Wilt Resistance in Chickpea. Life (Basel) 2023; 13:life13040988. [PMID: 37109518 PMCID: PMC10144025 DOI: 10.3390/life13040988] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 03/27/2023] [Accepted: 03/29/2023] [Indexed: 04/29/2023] Open
Abstract
Chickpea is an important leguminous crop with potential to provide dietary proteins to both humans and animals. It also ameliorates soil nitrogen through biological nitrogen fixation. The crop is affected by an array of biotic and abiotic factors. Among different biotic stresses, a major fungal disease called Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceris (FOC), is responsible for low productivity in chickpea. To date, eight pathogenic races of FOC (race 0, 1A, and 1B/C, 2-6) have been reported worldwide. The development of resistant cultivars using different conventional breeding methods is very time consuming and depends upon the environment. Modern technologies can improve conventional methods to solve these major constraints. Understanding the molecular response of chickpea to Fusarium wilt can help to provide effective management strategies. The identification of molecular markers closely linked to genes/QTLs has provided great potential for chickpea improvement programs. Moreover, omics approaches, including transcriptomics, metabolomics, and proteomics give scientists a vast viewpoint of functional genomics. In this review, we will discuss the integration of all available strategies and provide comprehensive knowledge about chickpea plant defense against Fusarium wilt.
Collapse
Affiliation(s)
- Rakesh Kumar Yadav
- Department of Genetics & Plant Breeding, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior 474002, India
| | - Manoj Kumar Tripathi
- Department of Genetics & Plant Breeding, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior 474002, India
- Department of Plant Molecular Biology & Biotechnology, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior 474002, India
| | - Sushma Tiwari
- Department of Genetics & Plant Breeding, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior 474002, India
- Department of Plant Molecular Biology & Biotechnology, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior 474002, India
| | - Niraj Tripathi
- Directorate of Research Services, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur 482004, India
| | - Ruchi Asati
- Department of Genetics & Plant Breeding, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior 474002, India
| | - Vinod Patel
- Department of Genetics & Plant Breeding, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior 474002, India
| | - R S Sikarwar
- Department of Genetics & Plant Breeding, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior 474002, India
| | | |
Collapse
|
2
|
Obala J, Saxena RK, Singh VK, Kumar CVS, Saxena KB, Tongoona P, Sibiya J, Varshney RK. Development of sequence-based markers for seed protein content in pigeonpea. Mol Genet Genomics 2018; 294:57-68. [PMID: 30173295 DOI: 10.1007/s00438-018-1484-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 08/22/2018] [Indexed: 12/30/2022]
Abstract
Pigeonpea is an important source of dietary protein to over a billion people globally, but genetic enhancement of seed protein content (SPC) in the crop has received limited attention for a long time. Use of genomics-assisted breeding would facilitate accelerating genetic gain for SPC. However, neither genetic markers nor genes associated with this important trait have been identified in this crop. Therefore, the present study exploited whole genome re-sequencing (WGRS) data of four pigeonpea genotypes (~ 12X coverage) to identify sequence-based markers and associated candidate genes for SPC. By combining a common variant filtering strategy on available WGRS data with knowledge of gene functions in relation to SPC, 108 sequence variants from 57 genes were identified. These genes were assigned to 19 GO molecular function categories with 56% belonging to only two categories. Furthermore, Sanger sequencing confirmed presence of 75.4% of the variants in 37 genes. Out of 30 sequence variants converted into CAPS/dCAPS markers, 17 showed high level of polymorphism between low and high SPC genotypes. Assay of 16 of the polymorphic CAPS/dCAPS markers on an F2 population of the cross ICP 5529 (high SPC) × ICP 11605 (low SPC), resulted in four of the CAPS/dCAPS markers significantly (P < 0.05) co-segregated with SPC. In summary, four markers derived from mutations in four genes will be useful for enhancing/regulating SPC in pigeonpea crop improvement programs.
Collapse
Affiliation(s)
- Jimmy Obala
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
- University of KwaZulu-Natal, African Center for Crop Improvement, Scottsville, Pietermaritzburg, 3209, South Africa
| | - Rachit K Saxena
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - Vikas K Singh
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - C V Sameer Kumar
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - K B Saxena
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - Pangirayi Tongoona
- University of KwaZulu-Natal, African Center for Crop Improvement, Scottsville, Pietermaritzburg, 3209, South Africa
| | - Julia Sibiya
- University of KwaZulu-Natal, African Center for Crop Improvement, Scottsville, Pietermaritzburg, 3209, South Africa
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India.
| |
Collapse
|
3
|
Recent Perspective of Next Generation Sequencing: Applications in Molecular Plant Biology and Crop Improvement. ACTA ACUST UNITED AC 2016. [DOI: 10.1007/s40011-016-0770-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
|
4
|
Doddamani D, Khan AW, Katta MAVSK, Agarwal G, Thudi M, Ruperao P, Edwards D, Varshney RK. CicArVarDB: SNP and InDel database for advancing genetics research and breeding applications in chickpea. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2015; 2015:bav078. [PMID: 26289427 PMCID: PMC4541373 DOI: 10.1093/database/bav078] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2014] [Accepted: 07/22/2015] [Indexed: 11/12/2022]
Abstract
Molecular markers are valuable tools for breeders to help accelerate crop improvement. High throughput sequencing technologies facilitate the discovery of large-scale variations such as single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs). Sequencing of chickpea genome along with re-sequencing of several chickpea lines has enabled the discovery of 4.4 million variations including SNPs and InDels. Here we report a repository of 1.9 million variations (SNPs and InDels) anchored on eight pseudomolecules in a custom database, referred as CicArVarDB that can be accessed at http://cicarvardb.icrisat.org/. It includes an easy interface for users to select variations around specific regions associated with quantitative trait loci, with embedded webBLAST search and JBrowse visualisation. We hope that this database will be immensely useful for the chickpea research community for both advancing genetics research as well as breeding applications for crop improvement. Database URL:http://cicarvardb.icrisat.org.
Collapse
Affiliation(s)
- Dadakhalandar Doddamani
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India
| | - Aamir W Khan
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India
| | - Mohan A V S K Katta
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India
| | - Gaurav Agarwal
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India
| | - Mahendar Thudi
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India
| | - Pradeep Ruperao
- School of Agriculture and Food Sciences, University of Queensland, St Lucia, Queensland, Australia 4072, School of Plant Biology, The University of Western Australia, Perth, Western Australia, Australia 6009 and
| | - David Edwards
- School of Plant Biology, The University of Western Australia, Perth, Western Australia, Australia 6009 and Institute of Agriculture, The University of Western Australia, Perth, Western Australia, Australia 6009
| | - Rajeev K Varshney
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India, School of Plant Biology, The University of Western Australia, Perth, Western Australia, Australia 6009 and
| |
Collapse
|
5
|
Kujur A, Bajaj D, Upadhyaya HD, Das S, Ranjan R, Shree T, Saxena MS, Badoni S, Kumar V, Tripathi S, Gowda CLL, Sharma S, Singh S, Tyagi AK, Parida SK. A genome-wide SNP scan accelerates trait-regulatory genomic loci identification in chickpea. Sci Rep 2015; 5:11166. [PMID: 26058368 PMCID: PMC4461920 DOI: 10.1038/srep11166] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2015] [Accepted: 05/18/2015] [Indexed: 01/09/2023] Open
Abstract
We identified 44844 high-quality SNPs by sequencing 92 diverse chickpea accessions belonging to a seed and pod trait-specific association panel using reference genome- and de novo-based GBS (genotyping-by-sequencing) assays. A GWAS (genome-wide association study) in an association panel of 211, including the 92 sequenced accessions, identified 22 major genomic loci showing significant association (explaining 23-47% phenotypic variation) with pod and seed number/plant and 100-seed weight. Eighteen trait-regulatory major genomic loci underlying 13 robust QTLs were validated and mapped on an intra-specific genetic linkage map by QTL mapping. A combinatorial approach of GWAS, QTL mapping and gene haplotype-specific LD mapping and transcript profiling uncovered one superior haplotype and favourable natural allelic variants in the upstream regulatory region of a CesA-type cellulose synthase (Ca_Kabuli_CesA3) gene regulating high pod and seed number/plant (explaining 47% phenotypic variation) in chickpea. The up-regulation of this superior gene haplotype correlated with increased transcript expression of Ca_Kabuli_CesA3 gene in the pollen and pod of high pod/seed number accession, resulting in higher cellulose accumulation for normal pollen and pollen tube growth. A rapid combinatorial genome-wide SNP genotyping-based approach has potential to dissect complex quantitative agronomic traits and delineate trait-regulatory genomic loci (candidate genes) for genetic enhancement in crop plants, including chickpea.
Collapse
Affiliation(s)
- Alice Kujur
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Deepak Bajaj
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Hari D Upadhyaya
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, Andhra Pradesh, India
| | - Shouvik Das
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Rajeev Ranjan
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Tanima Shree
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Maneesha S Saxena
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Saurabh Badoni
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Vinod Kumar
- National Research Centre on Plant Biotechnology (NRCPB), New Delhi 110012, India
| | - Shailesh Tripathi
- Division of Genetics, Indian Agricultural Research Institute (IARI), New Delhi 110012, India
| | - C L L Gowda
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, Andhra Pradesh, India
| | - Shivali Sharma
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, Andhra Pradesh, India
| | - Sube Singh
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, Andhra Pradesh, India
| | - Akhilesh K Tyagi
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Swarup K Parida
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| |
Collapse
|
6
|
Kujur A, Bajaj D, Upadhyaya HD, Das S, Ranjan R, Shree T, Saxena MS, Badoni S, Kumar V, Tripathi S, Gowda CLL, Sharma S, Singh S, Tyagi AK, Parida SK. Employing genome-wide SNP discovery and genotyping strategy to extrapolate the natural allelic diversity and domestication patterns in chickpea. FRONTIERS IN PLANT SCIENCE 2015; 6:162. [PMID: 25873920 PMCID: PMC4379880 DOI: 10.3389/fpls.2015.00162] [Citation(s) in RCA: 69] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Accepted: 03/01/2015] [Indexed: 05/19/2023]
Abstract
The genome-wide discovery and high-throughput genotyping of SNPs in chickpea natural germplasm lines is indispensable to extrapolate their natural allelic diversity, domestication, and linkage disequilibrium (LD) patterns leading to the genetic enhancement of this vital legume crop. We discovered 44,844 high-quality SNPs by sequencing of 93 diverse cultivated desi, kabuli, and wild chickpea accessions using reference genome- and de novo-based GBS (genotyping-by-sequencing) assays that were physically mapped across eight chromosomes of desi and kabuli. Of these, 22,542 SNPs were structurally annotated in different coding and non-coding sequence components of genes. Genes with 3296 non-synonymous and 269 regulatory SNPs could functionally differentiate accessions based on their contrasting agronomic traits. A high experimental validation success rate (92%) and reproducibility (100%) along with strong sensitivity (93-96%) and specificity (99%) of GBS-based SNPs was observed. This infers the robustness of GBS as a high-throughput assay for rapid large-scale mining and genotyping of genome-wide SNPs in chickpea with sub-optimal use of resources. With 23,798 genome-wide SNPs, a relatively high intra-specific polymorphic potential (49.5%) and broader molecular diversity (13-89%)/functional allelic diversity (18-77%) was apparent among 93 chickpea accessions, suggesting their tremendous applicability in rapid selection of desirable diverse accessions/inter-specific hybrids in chickpea crossbred varietal improvement program. The genome-wide SNPs revealed complex admixed domestication pattern, extensive LD estimates (0.54-0.68) and extended LD decay (400-500 kb) in a structured population inclusive of 93 accessions. These findings reflect the utility of our identified SNPs for subsequent genome-wide association study (GWAS) and selective sweep-based domestication trait dissection analysis to identify potential genomic loci (gene-associated targets) specifically regulating important complex quantitative agronomic traits in chickpea. The numerous informative genome-wide SNPs, natural allelic diversity-led domestication pattern, and LD-based information generated in our study have got multidimensional applicability with respect to chickpea genomics-assisted breeding.
Collapse
Affiliation(s)
- Alice Kujur
- National Institute of Plant Genome Research (NIPGR)New Delhi, India
| | - Deepak Bajaj
- National Institute of Plant Genome Research (NIPGR)New Delhi, India
| | - Hari D. Upadhyaya
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Telangana, India
| | - Shouvik Das
- National Institute of Plant Genome Research (NIPGR)New Delhi, India
| | - Rajeev Ranjan
- National Institute of Plant Genome Research (NIPGR)New Delhi, India
| | - Tanima Shree
- National Institute of Plant Genome Research (NIPGR)New Delhi, India
| | | | - Saurabh Badoni
- National Institute of Plant Genome Research (NIPGR)New Delhi, India
| | - Vinod Kumar
- National Research Centre on Plant Biotechnology (NRCPB)New Delhi, India
| | - Shailesh Tripathi
- Division of Genetics, Indian Agricultural Research Institute (IARI)New Delhi, India
| | - C. L. L. Gowda
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Telangana, India
| | - Shivali Sharma
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Telangana, India
| | - Sube Singh
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Telangana, India
| | | | - Swarup K. Parida
- National Institute of Plant Genome Research (NIPGR)New Delhi, India
| |
Collapse
|
7
|
Ruperao P, Edwards D. Bioinformatics: identification of markers from next-generation sequence data. Methods Mol Biol 2015; 1245:29-47. [PMID: 25373747 DOI: 10.1007/978-1-4939-1966-6_3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
With the advent of sequencing technology, next-generation sequencing (NGS) technology has dramatically revolutionized plant genomics. NGS technology combined with new software tools enables the discovery, validation, and assessment of genetic markers on a large scale. Among different markers systems, simple sequence repeats (SSRs) and Single nucleotide polymorphisms (SNPs) are the markers of choice for genetics and plant breeding. SSR markers have been a choice for large-scale characterization of germplasm collections, construction of genetic maps, and QTL identification. Similarly, SNPs are the most abundant genetic variations with higher frequencies throughout the genome of plant species. This chapter discusses various tools available for genome assembly and widely focuses on SSR and SNP marker discovery.
Collapse
Affiliation(s)
- Pradeep Ruperao
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, QLD, Australia
| | | |
Collapse
|
8
|
Abstract
The detection and analysis of genetic variation plays an important role in plant breeding and this role is increasing with the continued development of genome sequencing technologies. Molecular genetic markers are important tools to characterize genetic variation and assist with genomic breeding. Processing and storing the growing abundance of molecular marker data being produced requires the development of specific bioinformatics tools and advanced databases. Molecular marker databases range from species specific through to organism wide and often host a variety of additional related genetic, genomic, or phenotypic information. In this chapter, we will present some of the features of plant molecular genetic marker databases, highlight the various types of marker resources, and predict the potential future direction of crop marker databases.
Collapse
|
9
|
Bedada G, Westerbergh A, Müller T, Galkin E, Bdolach E, Moshelion M, Fridman E, Schmid KJ. Transcriptome sequencing of two wild barley (Hordeum spontaneum L.) ecotypes differentially adapted to drought stress reveals ecotype-specific transcripts. BMC Genomics 2014; 15:995. [PMID: 25408241 PMCID: PMC4251939 DOI: 10.1186/1471-2164-15-995] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Accepted: 11/04/2014] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Wild barley is adapted to highly diverse environments throughout its geographical distribution range. Transcriptome sequencing of differentially adapted wild barley ecotypes from contrasting environments contributes to the identification of genes and genetic variation involved in abiotic stress tolerance and adaptation. RESULTS Two differentially adapted wild barley ecotypes from desert (B1K2) and Mediterranean (B1K30) environments were analyzed for drought stress response under controlled conditions. The desert ecotype lost more water under both irrigation and drought, but exhibited higher relative water content (RWC) and better water use efficiency (WUE) than the coastal ecotype. We sequenced normalized cDNA libraries from drought-stressed leaves of both ecotypes with the 454 platform to identify drought-related transcripts. Over half million reads per ecotype were de novo assembled into 20,439 putative unique transcripts (PUTs) for B1K2, 21,494 for B1K30 and 28,720 for the joint assembly. Over 50% of PUTs of each ecotype were not shared with the other ecotype. Furthermore, 16% (3,245) of B1K2 and 17% (3,674) of B1K30 transcripts did not show orthologous sequence hits in the other wild barley ecotype and cultivated barley, and are candidates of ecotype-specific transcripts. Over 800 unique transcripts from each ecotype homologous to over 30 different stress-related genes were identified. We extracted 1,017 high quality SNPs that differentiated the two ecotypes. The genetic distance between the desert ecotype and cultivated barley was 1.9-fold higher than between the Mediterranean ecotype and cultivated barley. Moreover, the desert ecotype harbored a larger proportion of non-synonymous SNPs than the Mediterranean ecotype suggesting different demographic histories of these ecotypes. CONCLUSIONS The results indicate a strong physiological and genomic differentiation between the desert and Mediterranean wild barley ecotypes and a closer relationship of the Mediterranean to cultivated barley. A significant number of novel transcripts specific to wild barley were identified. The higher SNP density and larger proportion of SNPs with functional effects in the desert ecotype suggest different demographic histories and effects of natural selection in Mediterranean and desert wild barley. The data are a valuable genomic resource for an improved genome annotation, transcriptome studies of drought adaptation and a source of new genetic markers for future barley improvement.
Collapse
MESH Headings
- Adaptation, Physiological/genetics
- Base Sequence
- Biological Evolution
- Conserved Sequence
- Crops, Agricultural/genetics
- Crops, Agricultural/physiology
- Droughts
- Ecotype
- Gene Expression Regulation, Plant
- Gene Ontology
- Genes, Plant
- Hordeum/genetics
- Molecular Sequence Annotation
- Plant Leaves/genetics
- Plant Transpiration/genetics
- Polymorphism, Single Nucleotide/genetics
- RNA, Messenger/genetics
- RNA, Messenger/metabolism
- Recombination, Genetic/genetics
- Reference Standards
- Sequence Analysis, RNA
- Soil/chemistry
- Species Specificity
- Stress, Physiological/genetics
- Transcription Factors/metabolism
- Transcriptome/genetics
- Water/metabolism
Collapse
Affiliation(s)
- Girma Bedada
- />Department of Plant Biology, Uppsala BioCenter, Linnean Centre of Plant Biology in Uppsala, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
| | - Anna Westerbergh
- />Department of Plant Biology, Uppsala BioCenter, Linnean Centre of Plant Biology in Uppsala, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
| | - Thomas Müller
- />Institute for Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Fruwirthstrasse 21, D-70599 Stuttgart, Germany
| | - Eyal Galkin
- />Institute of Plant Science and Genetics, The Hebrew University of Jerusalem, Rehovot, Israel
| | - Eyal Bdolach
- />Institute of Plant Science and Genetics, The Hebrew University of Jerusalem, Rehovot, Israel
| | - Menachem Moshelion
- />Institute of Plant Science and Genetics, The Hebrew University of Jerusalem, Rehovot, Israel
| | - Eyal Fridman
- />Institute of Plant Science and Genetics, The Hebrew University of Jerusalem, Rehovot, Israel
| | - Karl J Schmid
- />Department of Plant Biology, Uppsala BioCenter, Linnean Centre of Plant Biology in Uppsala, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
- />Institute for Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Fruwirthstrasse 21, D-70599 Stuttgart, Germany
| |
Collapse
|
10
|
Dalton-Morgan J, Hayward A, Alamery S, Tollenaere R, Mason AS, Campbell E, Patel D, Lorenc MT, Yi B, Long Y, Meng J, Raman R, Raman H, Lawley C, Edwards D, Batley J. A high-throughput SNP array in the amphidiploid species Brassica napus shows diversity in resistance genes. Funct Integr Genomics 2014; 14:643-55. [PMID: 25147024 DOI: 10.1007/s10142-014-0391-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2014] [Revised: 08/02/2014] [Accepted: 08/11/2014] [Indexed: 11/25/2022]
Abstract
Single-nucleotide polymorphisms (SNPs)are molecular markers based on nucleotide variation and can be used for genotyping assays across populations and to track genomic inheritance. SNPs offer a comprehensive genotyping alternative to whole-genome sequencing for both agricultural and research purposes including molecular breeding and diagnostics, genome evolution and genetic diversity analyses, genetic mapping, and trait association studies. Here genomic SNPs were discovered between four cultivars of the important amphidiploid oilseed species Brassica napus and used to develop a B. napus Infinium™ array containing 5,306 SNPs randomly dispersed across the genome. Assay success was high, with >94 % of these producing a reproducible, polymorphic genotype in the 1,070 samples screened. Although the assay was designed to B. napus, successful SNP amplification was achieved in the B. napus progenitor species, Brassica rapa and Brassica oleracea, and to a lesser extent in the related species Brassica nigra. Phylogenetic analysis was consistent with the expected relationships between B. napus individuals. This study presents an efficient custom SNP assay development pipeline in the complex polyploid Brassica genome and demonstrates the utility of the array for high-throughput genotyping in a number of related Brassica species. It also demonstrates the utility of this assay in genotyping resistance genes on chromosome A7, which segregate amongst the 1,070 samples.
Collapse
Affiliation(s)
- Jessica Dalton-Morgan
- Centre for Integrative Legume Research and School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
11
|
Abstract
The demand for rapid and accurate diagnosis of plant diseases has risen in the last decade. On-site diagnosis of single or multiple pathogens using portable devices is the first step in this endeavour. Despite extensive attempts to develop portable devices for pathogen detection, current technologies are still restricted to detecting known pathogens with limited detection accuracy. Developing new detection techniques for rapid and accurate detection of multiple plant pathogens and their associated variants is essential. Recent single DNA sequencing technologies are a promising new avenue for developing future portable devices for plant pathogen detection. In this review, we detail the current progress in portable devices and technologies used for detecting plant pathogens, the current position of emerging sequencing technologies for analysis of plant genomics, and the future of portable devices for rapid pathogen diagnosis.
Collapse
Affiliation(s)
- Amir Sanati Nezhad
- McGill University and Genome Quebec Innovation Centre, Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada.
| |
Collapse
|
12
|
Azam S, Rathore A, Shah TM, Telluri M, Amindala B, Ruperao P, Katta MAVSK, Varshney RK. An integrated SNP mining and utilization (ISMU) pipeline for next generation sequencing data. PLoS One 2014; 9:e101754. [PMID: 25003610 PMCID: PMC4086967 DOI: 10.1371/journal.pone.0101754] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2014] [Accepted: 06/11/2014] [Indexed: 12/30/2022] Open
Abstract
Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.
Collapse
Affiliation(s)
- Sarwar Azam
- Centre of Excellence in Genomics, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Abhishek Rathore
- Centre of Excellence in Genomics, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Trushar M. Shah
- Centre of Excellence in Genomics, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Mohan Telluri
- Centre of Excellence in Genomics, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - BhanuPrakash Amindala
- Centre of Excellence in Genomics, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Pradeep Ruperao
- Centre of Excellence in Genomics, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia
| | - Mohan A. V. S. K. Katta
- Centre of Excellence in Genomics, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Rajeev K. Varshney
- Centre of Excellence in Genomics, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
- * E-mail:
| |
Collapse
|
13
|
Comprehensive transcriptome assembly of Chickpea (Cicer arietinum L.) using sanger and next generation sequencing platforms: development and applications. PLoS One 2014; 9:e86039. [PMID: 24465857 PMCID: PMC3900451 DOI: 10.1371/journal.pone.0086039] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2013] [Accepted: 12/03/2013] [Indexed: 11/19/2022] Open
Abstract
A comprehensive transcriptome assembly of chickpea has been developed using 134.95 million Illumina single-end reads, 7.12 million single-end FLX/454 reads and 139,214 Sanger expressed sequence tags (ESTs) from >17 genotypes. This hybrid transcriptome assembly, referred to as Cicer arietinumTranscriptome Assembly version 2 (CaTA v2, available at http://data.comparative-legumes.org/transcriptomes/cicar/lista_cicar-201201), comprising 46,369 transcript assembly contigs (TACs) has an N50 length of 1,726 bp and a maximum contig size of 15,644 bp. Putative functions were determined for 32,869 (70.8%) of the TACs and gene ontology assignments were determined for 21,471 (46.3%). The new transcriptome assembly was compared with the previously available chickpea transcriptome assemblies as well as to the chickpea genome. Comparative analysis of CaTA v2 against transcriptomes of three legumes - Medicago, soybean and common bean, resulted in 27,771 TACs common to all three legumes indicating strong conservation of genes across legumes. CaTA v2 was also used for identification of simple sequence repeats (SSRs) and intron spanning regions (ISRs) for developing molecular markers. ISRs were identified by aligning TACs to the Medicago genome, and their putative mapping positions at chromosomal level were identified using transcript map of chickpea. Primer pairs were designed for 4,990 ISRs, each representing a single contig for which predicted positions are inferred and distributed across eight linkage groups. A subset of randomly selected ISRs representing all eight chickpea linkage groups were validated on five chickpea genotypes and showed 20% polymorphism with average polymorphic information content (PIC) of 0.27. In summary, the hybrid transcriptome assembly developed and novel markers identified can be used for a variety of applications such as gene discovery, marker-trait association, diversity analysis etc., to advance genetics research and breeding applications in chickpea and other related legumes.
Collapse
|
14
|
DeWoody JA, Abts KC, Fahey AL, Ji Y, Kimble SJA, Marra NJ, Wijayawardena BK, Willoughby JR. Of contigs and quagmires: next‐generation sequencing pitfalls associated with transcriptomic studies. Mol Ecol Resour 2013; 13:551-8. [PMID: 23615313 DOI: 10.1111/1755-0998.12107] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2012] [Revised: 03/13/2013] [Accepted: 03/14/2013] [Indexed: 12/15/2022]
Affiliation(s)
- J. Andrew DeWoody
- Department of Biological Sciences Purdue University West Lafayette IN 47907 USA
- Department of Forestry & Natural Resources Purdue University West Lafayette IN 47907 USA
| | - Kendra C. Abts
- Department of Forestry & Natural Resources Purdue University West Lafayette IN 47907 USA
| | - Anna L. Fahey
- Department of Forestry & Natural Resources Purdue University West Lafayette IN 47907 USA
| | - Yanzhu Ji
- Department of Forestry & Natural Resources Purdue University West Lafayette IN 47907 USA
| | - Steven J. A. Kimble
- Department of Forestry & Natural Resources Purdue University West Lafayette IN 47907 USA
| | - Nicholas J. Marra
- Department of Forestry & Natural Resources Purdue University West Lafayette IN 47907 USA
| | | | - Janna R. Willoughby
- Department of Forestry & Natural Resources Purdue University West Lafayette IN 47907 USA
| |
Collapse
|
15
|
Gschloessl B, Beyne E, Audiot P, Bourguet D, Streiff R. De novo transcriptomic resources for two sibling species of moths: Ostrinia nubilalis and O. scapulalis. BMC Res Notes 2013; 6:73. [PMID: 23445568 PMCID: PMC3599821 DOI: 10.1186/1756-0500-6-73] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2012] [Accepted: 02/20/2013] [Indexed: 11/10/2022] Open
Abstract
Background This study aimed at enhancing the transcriptomic resources for two sibling species of moths, Ostrinia scapulalis (Adzuki bean borer) and Ostrinia nubilalis (European corn borer), as a foundation for future researches on their divergence history. Previous works on these species had shown that their genetic divergence was low, while they were reproductively isolated in natura and specialized on different host plants. Comparative genomic resources will help facilitate the understanding of the mechanisms involved in this isolation and adaptation to the host plants. Despite their fundamental interest, these species still lack the genomic resources to thoroughly identify candidate genes for functions of interest. We present here a high throughput sequencing and de novo transcriptome assembly for these two sibling species in line with this objective of comparative genomics. Results Based on 322,504 and 307,622 reads of 454 sequencing for O. scapulalis and O. nubilalis respectively, we reconstructed 11,231 and 10,773 transcripts, of which 40% were functionally annotated by BLAST analyzes. We determined the level of completeness of both assemblies as well as the recovery level of published Ostrinia genomic resources. Gene ontology (GO) of common and species-specific de novo transcripts did not reveal GO terms significantly enriched in one or the other species. By applying stringent homology searches on transcripts common to O. scapulalis and O. nubilalis, we identified a set of homologous transcripts, with a mean nucleotide identity value of 98.1%. In this set, the most divergent transcripts revealed candidate genes involved in developmental, sensorial and pathogen defense processes. Conclusions This data greatly increases the genomic resources of Ostrinia species and constitute a solid skeleton for future comparative analyzes of expression or diversity, despite we show that the transcriptomes for both species have not been assembled at full completion. In addition, we provide a set of homologous transcripts together with their annotation as a source of candidate genes for comparative analyzes.
Collapse
Affiliation(s)
- Bernhard Gschloessl
- Centre de Biologie pour Gestion des Populations UMR INRA-IRD-CIRAD-Montpellier SupAgro, Campus International de Baillarguet, Montferrier-sur-Lez Cedex 34988, France.
| | | | | | | | | |
Collapse
|
16
|
Edwards D, Batley J, Snowdon RJ. Accessing complex crop genomes with next-generation sequencing. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2013; 126:1-11. [PMID: 22948437 DOI: 10.1007/s00122-012-1964-x] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2012] [Accepted: 08/08/2012] [Indexed: 05/02/2023]
Abstract
Many important crop species have genomes originating from ancestral or recent polyploidisation events. Multiple homoeologous gene copies, chromosomal rearrangements and amplification of repetitive DNA within large and complex crop genomes can considerably complicate genome analysis and gene discovery by conventional, forward genetics approaches. On the other hand, ongoing technological advances in molecular genetics and genomics today offer unprecedented opportunities to analyse and access even more recalcitrant genomes. In this review, we describe next-generation sequencing and data analysis techniques that vastly improve our ability to dissect and mine genomes for causal genes underlying key traits and allelic variation of interest to breeders. We focus primarily on wheat and oilseed rape, two leading examples of major polyploid crop genomes whose size or complexity present different, significant challenges. In both cases, the latest DNA sequencing technologies, applied using quite different approaches, have enabled considerable progress towards unravelling the respective genomes. Our ability to discover the extent and distribution of genetic diversity in crop gene pools, and its relationship to yield and quality-related traits, is swiftly gathering momentum as DNA sequencing and the bioinformatic tools to deal with growing quantities of genomic data continue to develop. In the coming decade, genomic and transcriptomic sequencing, discovery and high-throughput screening of single nucleotide polymorphisms, presence-absence variations and other structural chromosomal variants in diverse germplasm collections will give detailed insight into the origins, domestication and available trait-relevant variation of polyploid crops, in the process facilitating novel approaches and possibilities for genomics-assisted breeding.
Collapse
Affiliation(s)
- David Edwards
- Australian Centre for Plant Functional Genomics, School of Agriculture and Food Sciences, University of Queensland, Brisbane, QLD 4072, Australia
| | | | | |
Collapse
|
17
|
Lai K, Duran C, Berkman PJ, Lorenc MT, Stiller J, Manoli S, Hayden MJ, Forrest KL, Fleury D, Baumann U, Zander M, Mason AS, Batley J, Edwards D. Single nucleotide polymorphism discovery from wheat next-generation sequence data. PLANT BIOTECHNOLOGY JOURNAL 2012; 10:743-9. [PMID: 22748104 DOI: 10.1111/j.1467-7652.2012.00718.x] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Single nucleotide polymorphisms (SNPs) are the most abundant type of molecular genetic marker and can be used for producing high-resolution genetic maps, marker-trait association studies and marker-assisted breeding. Large polyploid genomes such as wheat present a challenge for SNP discovery because of the potential presence of multiple homoeologs for each gene. AutoSNPdb has been successfully applied to identify SNPs from Sanger sequence data for several species, including barley, rice and Brassica, but the volume of data required to accurately call SNPs in the complex genome of wheat has prevented its application to this important crop. DNA sequencing technology has been revolutionized by the introduction of next-generation sequencing, and it is now possible to generate several million sequence reads in a timely and cost-effective manner. We have produced wheat transcriptome sequence data using 454 sequencing technology and applied this for SNP discovery using a modified autoSNPdb method, which integrates SNP and gene annotation information with a graphical viewer. A total of 4,694,141 sequence reads from three bread wheat varieties were assembled to identify a total of 38 928 candidate SNPs. Each SNP is within an assembly complete with annotation, enabling the selection of polymorphism within genes of interest.
Collapse
Affiliation(s)
- Kaitao Lai
- School of Agriculture and Food Science, University of Queensland, Brisbane, QLD, Australia
| | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
18
|
Hiremath PJ, Kumar A, Penmetsa RV, Farmer A, Schlueter JA, Chamarthi SK, Whaley AM, Carrasquilla-Garcia N, Gaur PM, Upadhyaya HD, Kavi Kishor PB, Shah TM, Cook DR, Varshney RK. Large-scale development of cost-effective SNP marker assays for diversity assessment and genetic mapping in chickpea and comparative mapping in legumes. PLANT BIOTECHNOLOGY JOURNAL 2012; 10:716-32. [PMID: 22703242 PMCID: PMC3465799 DOI: 10.1111/j.1467-7652.2012.00710.x] [Citation(s) in RCA: 125] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2011] [Revised: 04/05/2012] [Accepted: 04/25/2012] [Indexed: 05/20/2023]
Abstract
A set of 2486 single nucleotide polymorphisms (SNPs) were compiled in chickpea using four approaches, namely (i) Solexa/Illumina sequencing (1409), (ii) amplicon sequencing of tentative orthologous genes (TOGs) (604), (iii) mining of expressed sequence tags (ESTs) (286) and (iv) sequencing of candidate genes (187). Conversion of these SNPs to the cost-effective and flexible throughput Competitive Allele Specific PCR (KASPar) assays generated successful assays for 2005 SNPs. These marker assays have been designated as Chickpea KASPar Assay Markers (CKAMs). Screening of 70 genotypes including 58 diverse chickpea accessions and 12 BC(3) F(2) lines showed 1341 CKAMs as being polymorphic. Genetic analysis of these data clustered chickpea accessions based on geographical origin. Genotyping data generated for 671 CKAMs on the reference mapping population (Cicer arietinum ICC 4958 × Cicer reticulatum PI 489777) were compiled with 317 unpublished TOG-SNPs and 396 published markers for developing the genetic map. As a result, a second-generation genetic map comprising 1328 marker loci including novel 625 CKAMs, 314 TOG-SNPs and 389 published marker loci with an average inter-marker distance of 0.59 cM was constructed. Detailed analyses of 1064 mapped loci of this second-generation chickpea genetic map showed a higher degree of synteny with genome of Medicago truncatula, followed by Glycine max, Lotus japonicus and least with Vigna unguiculata. Development of these cost-effective CKAMs for SNP genotyping will be useful not only for genetics research and breeding applications in chickpea, but also for utilizing genome information from other sequenced or model legumes.
Collapse
Affiliation(s)
- Pavana J Hiremath
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Patancheru, India
- Osmania UniversityHyderabad, India
| | - Ashish Kumar
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Patancheru, India
| | | | - Andrew Farmer
- National Center for Genome Resources (NCGR)Santa Fe, NM, USA
| | | | - Siva K Chamarthi
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Patancheru, India
| | | | | | - Pooran M Gaur
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Patancheru, India
| | - Hari D Upadhyaya
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Patancheru, India
| | | | - Trushar M Shah
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Patancheru, India
| | | | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)Patancheru, India
- Generation Challenge Program (GCP)Mexico DF, Mexico
- *Correspondence (Tel +91 40 30713305; fax +91 40 30713074/3075; email )
| |
Collapse
|
19
|
Egan AN, Schlueter J, Spooner DM. Applications of next-generation sequencing in plant biology. AMERICAN JOURNAL OF BOTANY 2012; 99:175-85. [PMID: 22312116 DOI: 10.3732/ajb.1200020] [Citation(s) in RCA: 140] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
The last several years have seen revolutionary advances in DNA sequencing technologies with the advent of next-generation sequencing (NGS) techniques. NGS methods now allow millions of bases to be sequenced in one round, at a fraction of the cost relative to traditional Sanger sequencing. As costs and capabilities of these technologies continue to improve, we are only beginning to see the possibilities of NGS platforms, which are developing in parallel with online availability of a wide range of biological data sets and scientific publications and allowing us to address a variety of questions not possible before. As techniques and data sets continue to improve and grow, we are rapidly moving to the point where every organism, not just select "model organisms", is open to the power of NGS. This volume presents a brief synopsis of NGS technologies and the development of exemplary applications of such methods in the fields of molecular marker development, hybridization and introgression, transcriptome investigations, phylogenetic and ecological studies, polyploid genetics, and applications for large genebank collections.
Collapse
Affiliation(s)
- Ashley N Egan
- East Carolina University, Department of Biology, Howell Science Complex N303a, Mailstop 551, Greenville, North Carolina 27858, USA.
| | | | | |
Collapse
|