Evidence map›Paper›PMID 25431420›Full record

ReviewJournal of biosciences2014

Functional genomics of tomato: opportunities and challenges in post-genome NGS era.

Rahul Kumar, Ashima Khurana

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of biosciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Application of CRISPR/Cas9-Mediated Gene Editing in Tomato.Methods in molecular biology (Clifton, N.J.) · 2019
    Article
  7. Article
  8. Article
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Rahul KumarRepository of Tomato Genomics Resources, Department of Plant Sciences, School of Life Sciences, University of Hyderabad, Hyderabad 500 046, India.
Ashima Khurana

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Tomato Genome Sequencing Project represented a landmark venture in the history of sequencing projects where both Sanger's and next-generation sequencing (NGS) technologies were employed, and a highly accurate and one of the best assembled plant genomes along with a draft of the wild relative, Solanum pimpinellifolium, were released in 2012. However, the functional potential of the major portion of this newly generated resource is still undefined. The very first challenge before scientists working on tomato functional biology is to exploit this high-quality reference sequence for tapping of the wealth of genetic variants for improving agronomic traits in cultivated tomatoes. The sequence data generated recently by 150 Tomato Genome Consortium would further uncover the natural alleles present in different tomato genotypes. Therefore, we found it relevant to have a fresh outlook on tomato functional genomics in the context of application of NGS technologies in its post-genome sequencing phase. Herein, we provide an overview how NGS technologies vis-a-vis available reference sequence have assisted each other for their mutual improvement and how their combined use could further facilitate the development of other 'omics' tools, required to propel the Solanaceae research. Additionally, we highlight the challenges associated with the application of these cutting-edge technologies.

Indexed as

Genome, PlantGenomicsChromosome MappingDNA Mutational AnalysisEpigenomicsGene Expression ProfilingGenetic VariationHigh-Throughput Nucleotide SequencingProteomicsSequence Analysis, DNASolanum lycopersicum

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.