Evidence map›Paper›PMID 34116424›Full record

ReviewCurrent opinion in plant biology2021

Potentials of single-cell genomics in deciphering cellular phenotypes.

Abbas Shojaee, Michelle Saavedra, Shao-Shan Carol Huang

Abstract readReview
In one paragraph

Review in Current opinion in plant biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Trafficking and localization ofCommunicative & integrative biology · 2022
    Article
  5. Cell types as species: Exploring a metaphor.Frontiers in plant science · 2022
    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

3 authors.

Abbas ShojaeeCenter for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, United States.
Michelle SaavedraCenter for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, United States.
Shao-Shan Carol HuangCenter for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, United States. Electronic address: s.c.huang@nyu.edu.

Funding

Sequence, chromatin, and cellular contexts of transcription factor- DNA interaction and functionR35GM138143 · NIGMS · NEW YORK UNIVERSITY · PI Shao-shan Carol Huang · 2020 to 2026
$2.4M
NIGMS NIH HHS R35 GM138143
6 · The paper itself

Abstract

Single-cell genomics, particularly single-cell transcriptome profiling by RNA sequencing have transformed the possibilities to relate genes to functions, structures, and eventually phenotypes. We can now observe changes in each cell's transcriptome and among its neighborhoods, interrogate the sequence of transcriptional events, and assess their influence on subsequent events. This paradigm shift in biology enables us to infer causal relationships in these events with high accuracy. Here we review the latest single-cell studies in plants that uncover how cellular phenotypes emerge as a result of the transcriptome process such as waves of expression, trajectories of development and responses to the environment, and spatial information. With an eye on the advances made in animal and human studies, we further highlight some of the needed areas for future research and development, including computational methods.

Indexed as

Computational BiologySingle-Cell AnalysisAnimalsGenomicsPhenotypeSequence Analysis, RNACausal inferenceChromatin accessibilityExpression wavesMulti-omicsPlant biologyPseudotimeRNA sequencingSingle cellSpatial transcriptomics

Identifiers

PMID34116424
PMCPMC8545747

What OpenQuestion holds

Textmetadata
LicenceTDM
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.