Evidence map›Paper›PMID 35205423›Full record

ReviewGenes2022

A Primer for Single-Cell Sequencing in Non-Model Organisms.

James M Alfieri, Guosong Wang, Michelle M Jonika, Clare A Gill, Heath Blackmon, Giridhar N Athrey

Abstract readReview
In one paragraph

Review in Genes, 2022. 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. Review
  3. Article
  4. Review
  5. Review
  6. Understanding developmental system drift.Development (Cambridge, England) · 2024
    Review
  7. Review
  8. Article
  9. Review
  10. Article
  11. Fourth Report on Chicken Genes and Chromosomes 2022.Cytogenetic and genome research · 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

6 authors.

James M AlfieriDepartment of Biology, Texas A&M University, College Station, TX 77843, USA.
Guosong WangDepartment of Animal Science, Texas A&M University, College Station, TX 77843, USA.
Michelle M JonikaDepartment of Biology, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0002-1170-6418
Clare A GillDepartment of Animal Science, Texas A&M University, College Station, TX 77843, USA.
Heath BlackmonDepartment of Biology, Texas A&M University, College Station, TX 77843, USA.
Giridhar N AthreyInterdisciplinary Program in Ecology and Evolutionary Biology, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0002-5295-9884

Funding

Integrating theory, genomics, and comparative approaches to break barriers to the understanding of genome structure and sex chromosome evolution.R35GM138098 · NIGMS · TEXAS A&M UNIVERSITY · PI BLACKMON, HEATH · 2020 to 2024
$1.8M
NIGMS NIH HHS R35 GM138098
6 · The paper itself

Abstract

Single-cell sequencing technologies have led to a revolution in our knowledge of the diversity of cell types, connections between biological levels of organization, and relationships between genotype and phenotype. These advances have mainly come from using model organisms; however, using single-cell sequencing in non-model organisms could enable investigations of questions inaccessible with typical model organisms. This primer describes a general workflow for single-cell sequencing studies and considerations for using non-model organisms (limited to multicellular animals). Importantly, single-cell sequencing, when further applied in non-model organisms, will allow for a deeper understanding of the mechanisms between genotype and phenotype and the basis for biological variation.

Indexed as

PhenotypeAnimalsGenotypeanimal scienceecologyevolutionnon-model organismsingle-cell sequencing

Identifiers

PMID35205423
PMCPMC8872538

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.