Omics of Model Plants

Agrawal, P. K.; Babu, B. Kalyana; Saini, Neeru

doi:10.1007/978-81-322-2172-2_1

Cited by 5 publications

(6 citation statements)

References 185 publications

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“…The omics tools including high-throughput genome-scale genotyping platforms such as whole-genome resequencing, proteomics, and metabolomics offer better prospects for gene identification and exploration of molecular mechanisms. This information can be used to develop ideal genotypes suitable for varying climatic conditions [75].…”

Section: Implications Of Bioinformatics In Plant Omicsmentioning

confidence: 99%

“…The NGS is very popular tool for the identification of housekeeping genes in crop plants. Many tools such as Genome Analyzer, the Applied Biosystems SOLiD System, Roche/454 FLX, and the Illumina/Solexa are commercially available for NGS [76]. NGS can be utilized for whole-genome sequencing, isolation of transcription factor binding sites, and expression of noncoding RNA and targeted resequencing [77].…”

Section: Plant Genome Sequencingmentioning

confidence: 99%

“…Many tools such as Genome Analyzer, the Applied Biosystems SOLiD System, Roche/454 FLX, and the Illumina/Solexa are commercially available for NGS [76]. NGS can be utilized for whole-genome sequencing, isolation of transcription factor binding sites, and expression of noncoding RNA and targeted resequencing [77]. Various software packages are available to assemble sequences, for example, Phred/Phrap/Consed [78], GAP4 [79], and chromaseq [80].…”

Section: Plant Genome Sequencingmentioning

confidence: 99%

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Bioinformatics: A Way Forward to Explore “Plant Omics”

Rahman¹,

Shaheen²,

Rahman³

et al. 2016

Bioinformatics - Updated Features and Applications

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"ioinformatics, a computer-assisted science aiming at managing a huge volume of genomic data, is an emerging discipline that combines the power of computers, mathematical algorithms, and statistical concepts to solve multiple genetic/biological puzzles. This science has progressed parallel to the evolution of genome-sequencing tools, for example, the next-generation sequencing technologies, that resulted in arranging and analyzing the genome-sequencing information of large genomes. Synergism of plant omics and bioinformatics set a firm foundation for deducing ancestral karyotype of multiple plant families, predicting genes, etc. Second, the huge genomic data can be assembled to acquire maximum information from a voluminous omics data. The science of bioinformatics is handicapped due to lack of appropriate computational procedures in assembling sequencing reads of the homologs occurring in complex genomes like cotton n = x = , wheat n = x = , etc., and shortage of multidisciplinary-oriented trained manpower. In addition, the rapid expansion of sequencing data restricts the potential of acquisitioning, storing, distributing, and analyzing the genomic information. In future, inventions of high-tech computational tools and skills together with improved biological expertise would provide better insight into the genomes, and this information would be helpful in sustaining crop productivities on this planet.

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Section: Implications Of Bioinformatics In Plant Omicsmentioning

confidence: 99%

Section: Plant Genome Sequencingmentioning

confidence: 99%

Section: Plant Genome Sequencingmentioning

confidence: 99%

See 1 more Smart Citation

Bioinformatics: A Way Forward to Explore “Plant Omics”

Rahman¹,

Shaheen²,

Rahman³

et al. 2016

Bioinformatics - Updated Features and Applications

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show abstract

“…Advances in omics have increased our understanding of complex mechanisms regulating plant growth and development [24][25][26][27][28][29]. Multiple approaches including, transcriptomics [30][31][32], genomics [33,34], phenomics [35,36], and proteomics [37,38] have been used for uncovering flowering mechanism in plants.…”

Section: Introductionmentioning

confidence: 99%

Transcriptomic Insight into Underground Floral Differentiation in Erythronium japonicum

Wang

Zhang

Shen

et al. 2022

BioMed Research International

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Erythronium japonicum Decne (Liliaceae) flowers in early spring after overwintering. Its sexual reproduction process includes an underground development process of floral organs, but the underlying molecular mechanisms are obscure. The present study is aimed at exploring the transcriptional changes and key genes involved at underground floral developmental stages, including flower primordium differentiation, perianth differentiation, stamen differentiation, and pistil differentiation in E. japonicum. Multistage high-quality transcriptomic data resulted in identifying putative candidate genes for underground floral differentiation in E. japonicum. A total of 174,408 unigenes were identified, 28,508 of which were differentially expressed genes (DEGs) at different floral developmental stages, while only 44 genes were identified with conserved regulation between different stages. Further annotation of DEGs resulted in the identification of 270 DEGs specific to floral differentiation. In addition, ELF3, PHD, cullin 1, SE14, ZSWIM3, GIGNATEA, and SERPIN B were identified as potential candidate genes involved in the regulation of floral differentiation. Besides, we explored transcription factors with differential regulation at different developmental stages and identified bHLH, FAR1, mTERF, MYB-related, NAC, Tify, and WRKY TFs for their potential involvement in the underground floral differentiation process. Together, these results laid the foundation for future molecular works to improve our understanding of the underground floral differentiation process and its genetic regulation in E. japonicum.

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“…The use of different "omics" technologies and their integration have taken off in recent years (Misra et al, 2018;Wani & Raza, 2019). It has led to the understanding of essential plant processes regarding development (Agrawal et al, 2015;Gapper et al, 2014;Hennig, 2007) and responses to changes in plants' internal and/or external environments (Debnath et al, 2011;Ruotolo et al, 2018). For example, metabolomics and transcriptomics analyses have been applied to study alterations in metabolic systems of field grown rice (Izawa et al, 2011) and barley (Kogel et al, 2010), and in transgenic Arabidopsis plants presenting increased leaf growth (Gonzalez et al, 2010).…”

Section: The Direct Combination Of Two "Omics" In An Unsupervised Manmentioning

confidence: 99%

Metabolomics and transcriptomics analyses of sugarcane variety SP80-3280 throughout development in the field

Wijma¹

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Omics of Model Plants

Cited by 5 publications

References 185 publications

Bioinformatics: A Way Forward to Explore “Plant Omics”

Bioinformatics: A Way Forward to Explore “Plant Omics”

Transcriptomic Insight into Underground Floral Differentiation in Erythronium japonicum

Metabolomics and transcriptomics analyses of sugarcane variety SP80-3280 throughout development in the field

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