Evidence map›Paper›PMID 26846165›Full record

ArticleBMC genomics2016

Comparative transcriptomics and comprehensive marker resource development in mulberry.

Bushra Saeed, Vinay K Baranwal, Paramjit Khurana

Abstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Diversity of endophytic bacteria of mulberry (Frontiers in microbiology · 2022
    Article
  5. Metabolomics Response to Drought Stress inPlants (Basel, Switzerland) · 2021
    Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
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

3 authors.

Bushra SaeedDepartment of Plant Molecular Biology, University of Delhi South Campus, New Delhi, 110021, India. bushra.saeed1@gmail.com.
Vinay K BaranwalDepartment of Plant Molecular Biology, University of Delhi South Campus, New Delhi, 110021, India. vinaydu@gmail.com.
Paramjit KhuranaDepartment of Plant Molecular Biology, University of Delhi South Campus, New Delhi, 110021, India. param@genomeindia.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh potential of Morus laevigata and Morus serrata has been proposed in the breeding programs for Morus sp. However, due to the lack of dense molecular markers this goal is still in its nascent stage and not yet realized. We thus, sequenced the transcriptomes of these two wild Morus species and utilized the data for marker development.

resultsWe generated 87.0 and 80.3 Mb of transcriptome data from M. laevigata and M. serrata, respectively. The transcriptomes from M. laevigata and M. serrata, were assembled into 95,181 and 85,269 transcripts, respectively, and annotated. We identified around 24,049 Simple Sequence Repeats (SSRs), 1,201,326 Single Nucleotide Polymorphisms (SNPs) and 67,875 Insertion-Deletions (InDels). The variants having a higher impact were also identified and their effect was further investigated.

conclusionsThe transcriptome resource from the wildly growing mulberry species developed in this study can find wide applicability in gene identification and/or characterization. It can also contribute immensely in the existing mulberry improvement programs.

Indexed as

Gene Expression ProfilingGenetic MarkersTranscriptomeComputational BiologyDatabases, GeneticGene Expression Regulation, PlantGene OntologyGenotypeHigh-Throughput Nucleotide SequencingMicrosatellite RepeatsMolecular Sequence AnnotationMorusPolymorphism, Single NucleotideStress, PhysiologicalGenetic Markers

Identifiers

PMID26846165
PMCPMC4743097

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Registered trials

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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.