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Rawal HC, Kumar S, Mithra S V A, Solanke AU, Nigam D, Saxena S, Tyagi A, V S, Yadav NR, Kalia P, Singh NP, Singh NK, Sharma TR, Gaikwad K. High Quality Unigenes and Microsatellite Markers from Tissue Specific Transcriptome and Development of a Database in Clusterbean (Cyamopsis tetragonoloba, L. Taub). Genes (Basel) 2017; 8:genes8110313. [PMID: 29120386 PMCID: PMC5704226 DOI: 10.3390/genes8110313] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Revised: 10/23/2017] [Accepted: 11/06/2017] [Indexed: 12/23/2022] Open
Abstract
Clusterbean (Cyamopsis tetragonoloba L. Taub), is an important industrial, vegetable and forage crop. This crop owes its commercial importance to the presence of guar gum (galactomannans) in its endosperm which is used as a lubricant in a range of industries. Despite its relevance to agriculture and industry, genomic resources available in this crop are limited. Therefore, the present study was undertaken to generate RNA-Seq based transcriptome from leaf, shoot, and flower tissues. A total of 145 million high quality Illumina reads were assembled using Trinity into 127,706 transcripts and 48,007 non-redundant high quality (HQ) unigenes. We annotated 79% unigenes against Plant Genes from the National Center for Biotechnology Information (NCBI), Swiss-Prot, Pfam, gene ontology (GO) and KEGG databases. Among the annotated unigenes, 30,020 were assigned with 116,964 GO terms, 9984 with EC and 6111 with 137 KEGG pathways. At different fragments per kilobase of transcript per millions fragments sequenced (FPKM) levels, genes were found expressed higher in flower tissue followed by shoot and leaf. Additionally, we identified 8687 potential simple sequence repeats (SSRs) with an average frequency of one SSR per 8.75 kb. A total of 28 amplified SSRs in 21 clusterbean genotypes resulted in polymorphism in 13 markers with average polymorphic information content (PIC) of 0.21. We also constructed a database named ‘ClustergeneDB’ for easy retrieval of unigenes and the microsatellite markers. The tissue specific genes identified and the molecular marker resources developed in this study is expected to aid in genetic improvement of clusterbean for its end use.
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Affiliation(s)
- Hukam C Rawal
- ICAR-National Research Centre on Plant Biotechnology, New Delhi 110012, India.
| | - Shrawan Kumar
- ICAR-National Research Centre on Plant Biotechnology, New Delhi 110012, India.
| | - Amitha Mithra S V
- ICAR-National Research Centre on Plant Biotechnology, New Delhi 110012, India.
| | - Amolkumar U Solanke
- ICAR-National Research Centre on Plant Biotechnology, New Delhi 110012, India.
| | - Deepti Nigam
- ICAR-National Research Centre on Plant Biotechnology, New Delhi 110012, India.
| | - Swati Saxena
- ICAR-National Research Centre on Plant Biotechnology, New Delhi 110012, India.
| | - Anshika Tyagi
- ICAR-National Research Centre on Plant Biotechnology, New Delhi 110012, India.
| | - Sureshkumar V
- ICAR-National Research Centre on Plant Biotechnology, New Delhi 110012, India.
| | - Neelam R Yadav
- Department of Biotechnology and Molecular Biology, CCS Haryana Agricultural University, Hisar 125004, India.
| | - Pritam Kalia
- ICAR-Indian Agricultural Research Institute, New Delhi 110012, India.
| | | | | | - Tilak Raj Sharma
- ICAR-National Research Centre on Plant Biotechnology, New Delhi 110012, India.
| | - Kishor Gaikwad
- ICAR-National Research Centre on Plant Biotechnology, New Delhi 110012, India.
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Sandhu M, Sureshkumar V, Prakash C, Dixit R, Solanke AU, Sharma TR, Mohapatra T, S V AM. RiceMetaSys for salt and drought stress responsive genes in rice: a web interface for crop improvement. BMC Bioinformatics 2017; 18:432. [PMID: 28964253 PMCID: PMC5622590 DOI: 10.1186/s12859-017-1846-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Accepted: 09/21/2017] [Indexed: 11/17/2022] Open
Abstract
Background Genome-wide microarray has enabled development of robust databases for functional genomics studies in rice. However, such databases do not directly cater to the needs of breeders. Here, we have attempted to develop a web interface which combines the information from functional genomic studies across different genetic backgrounds with DNA markers so that they can be readily deployed in crop improvement. In the current version of the database, we have included drought and salinity stress studies since these two are the major abiotic stresses in rice. Results RiceMetaSys, a user-friendly and freely available web interface provides comprehensive information on salt responsive genes (SRGs) and drought responsive genes (DRGs) across genotypes, crop development stages and tissues, identified from multiple microarray datasets. ‘Physical position search’ is an attractive tool for those using QTL based approach for dissecting tolerance to salt and drought stress since it can provide the list of SRGs and DRGs in any physical interval. To identify robust candidate genes for use in crop improvement, the ‘common genes across varieties’ search tool is useful. Graphical visualization of expression profiles across genes and rice genotypes has been enabled to facilitate the user and to make the comparisons more impactful. Simple Sequence Repeat (SSR) search in the SRGs and DRGs is a valuable tool for fine mapping and marker assisted selection since it provides primers for survey of polymorphism. An external link to intron specific markers is also provided for this purpose. Bulk retrieval of data without any limit has been enabled in case of locus and SSR search. Conclusions The aim of this database is to facilitate users with a simple and straight-forward search options for identification of robust candidate genes from among thousands of SRGs and DRGs so as to facilitate linking variation in expression profiles to variation in phenotype. Database URL: http://14.139.229.201 Electronic supplementary material The online version of this article (10.1186/s12859-017-1846-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Maninder Sandhu
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi, 110012, India.,Shobhit University, Modipuram, Meerut, 250110, Uttar Pradesh, India
| | - V Sureshkumar
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi, 110012, India.,Department of Plant Molecular Biology and Bioinformatics, Tamil Nadu Agricultural University, Coimbatore, 641003, India
| | - Chandra Prakash
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi, 110012, India
| | - Rekha Dixit
- Shobhit University, Modipuram, Meerut, 250110, Uttar Pradesh, India.,Current address: Department of biotechnology, Keralverma faculty of science, Swami Vivekanand Subharti University, Meerut, 250005, Uttar Pradesh, India
| | - Amolkumar U Solanke
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi, 110012, India
| | - Tilak Raj Sharma
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi, 110012, India
| | - Trilochan Mohapatra
- Indian Council of Agricultural Research, Krishi Bhawan, New Delhi, 110001, India
| | - Amitha Mithra S V
- ICAR-National Research Centre on Plant Biotechnology, LBS Building, Pusa Campus, New Delhi, 110012, India.
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