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Functional Genomics Approaches for Improving Abiotic Stress Tolerance in Crop Plants

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Plant Sciences".

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 7986

Special Issue Editors


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Guest Editor
USDA-ARS, Cereal Crops Research Unit, Madison, WI 53726, USA
Interests: plant genomics; crop plant

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Guest Editor
Thünen Institute of Forest Genetics, Sieker Landstrasse 2, D-22927 Grosshansdorf, Germany
Interests: plant molecular biology; bioinformatics; functional genome research; tree genomics and transcriptomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In this Special Issue, contributions are invited wherein functional genomic approaches such as transcriptomics, proteomics, and metabolomics are used to identify networks of genes associated with abiotic stresses in crop plants. Omic studies that involve combinations of two or more stresses such as drought and heat, drought and salinity, and other stress combinations are strongly encouraged. Investigations on single abiotic stresses that utilize two or more omic strategies to identify key genes will be suitable for this issue. Studies using GWAS to identify genomic regions associated with stresses should include the genetic analysis of one or more genes underlying a major QTL region. The genetic analysis could be performed using mutant collections, RNAi, CRISPR, and overexpression lines.

Dr. Ramamurthy Mahalingam
Dr. Birgit Kersten
Guest Editors

Manuscript Submission Information

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Keywords

  • Abiotic stress
  • Combined stress
  • Gene networks
  • Genetic analysis
  • GWAS
  • Metabolomics
  • Proteomics
  • Transcriptomics

Published Papers (2 papers)

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Research

14 pages, 3426 KiB  
Article
An Efficient Agrobacterium-Mediated Transformation Method for Hybrid Poplar 84K (Populus alba × P. glandulosa) Using Calli as Explants
by Shuang-Shuang Wen, Xiao-Lan Ge, Rui Wang, Hai-Feng Yang, Yu-E. Bai, Ying-Hua Guo, Jin Zhang, Meng-Zhu Lu, Shu-Tang Zhao and Liu-Qiang Wang
Int. J. Mol. Sci. 2022, 23(4), 2216; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms23042216 - 17 Feb 2022
Cited by 26 | Viewed by 5172
Abstract
A highly efficient Agrobacterium-mediated transformation method is needed for the molecular study of model tree species such as hybrid poplar 84K (Populus alba × P. glandulosa cv. ‘84K’). In this study, we report a callus-based transformation method that exhibits high efficiency [...] Read more.
A highly efficient Agrobacterium-mediated transformation method is needed for the molecular study of model tree species such as hybrid poplar 84K (Populus alba × P. glandulosa cv. ‘84K’). In this study, we report a callus-based transformation method that exhibits high efficiency and reproducibility. The optimized callus induction medium (CIM1) induced the development of calli from leaves with high efficiency, and multiple shoots were induced from calli growing on the optimized shoot induction medium (SIM1). Factors affecting the transformation frequency of calli were optimized as follows: Agrobacterium concentration sets at an OD600 of 0.6, Agrobacterium infective suspension with an acetosyringone (AS) concentration of 100 µM, infection time of 15 min, cocultivation duration of 2 days and precultivation duration of 6 days. Using this method, transgenic plants are obtained within approximately 2 months with a transformation frequency greater than 50%. Polymerase chain reaction (PCR), reverse transcription-PCR (RT-PCR) and β-galactosidase (GUS) histochemical staining analyses confirmed the successful generation of stable transformants. Additionally, the calli from leaves were subcultured and used to obtain new explants; the high transformation efficiency was still maintained in subcultured calli after 6 cycles. This method provides a reference for developing effective transformation protocols for other poplar species. Full article
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9 pages, 372 KiB  
Article
LegumeSSRdb: A Comprehensive Microsatellite Marker Database of Legumes for Germplasm Characterization and Crop Improvement
by Naveen Duhan and Rakesh Kaundal
Int. J. Mol. Sci. 2021, 22(21), 11350; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms222111350 - 21 Oct 2021
Cited by 5 | Viewed by 2050
Abstract
Microsatellites, or simple sequence repeats (SSRs), are polymorphic loci that play a major role as molecular markers for genome analysis and plant breeding. The legume SSR database is a webserver which contains simple sequence repeats (SSRs) from genomes of 13 legume species. A [...] Read more.
Microsatellites, or simple sequence repeats (SSRs), are polymorphic loci that play a major role as molecular markers for genome analysis and plant breeding. The legume SSR database is a webserver which contains simple sequence repeats (SSRs) from genomes of 13 legume species. A total of 3,706,276 SSRs are present in the database, 698,509 of which are genic SSRs, and 3,007,772 are non-genic. This webserver is an integrated tool to perform end-to-end marker selection right from generating SSRs to designing and validating primers, visualizing the results and blasting the genomic sequences at one place without juggling between several resources. The user-friendly web interface allows users to browse SSRs based on the genomic region, chromosome, motif type, repeat motif sequence, frequency of motif, and advanced searches allow users to search based on chromosome location range and length of SSR. Users can give their desired flanking region around repeat and obtain the sequence, they can explore the genes in which the SSRs are present or the genes between which the SSRs are bound design custom primers, and perform in silico validation using PCR. An SSR prediction pipeline is implemented where the user can submit their genomic sequence to generate SSRs. This webserver will be frequently updated with more species, in time. We believe that legumeSSRdb would be a useful resource for marker-assisted selection and mapping quantitative trait loci (QTLs) to practice genomic selection and improve crop health. The database can be freely accessed at http://bioinfo.usu.edu/legumeSSRdb/. Full article
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