Evidence map›Paper›PMID 30755158›Full record

ArticleBMC genomics2019

Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data.

C Farkas, F Fuentes-Villalobos, B Rebolledo-Jaramillo, F Benavides, A F Castro, R Pincheira

Abstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Impact ofInternational journal of molecular medicine · 2022
    Article
  2. Article
  3. Characterization ofFrontiers in genetics · 2021
    Article
  4. 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

6 authors.

C FarkasLaboratorio de Transducción de Señales y Cáncer. Departamento de Bioquímica y Biología Molecular. Facultad Cs. Biológicas, Universidad de Concepción, Concepción, Chile.
F Fuentes-VillalobosLaboratorio de Transducción de Señales y Cáncer. Departamento de Bioquímica y Biología Molecular. Facultad Cs. Biológicas, Universidad de Concepción, Concepción, Chile.
B Rebolledo-JaramilloFacultad de Medicina Clínica Alemana, Universidad del Desarrollo, Santiago, Chile.
F BenavidesDepartment of Epigenetics and Molecular Carcinogenesis, M.D. Anderson Cancer Center, Smithville, TX, USA.
A F CastroLaboratorio de Transducción de Señales y Cáncer. Departamento de Bioquímica y Biología Molecular. Facultad Cs. Biológicas, Universidad de Concepción, Concepción, Chile.
R PincheiraLaboratorio de Transducción de Señales y Cáncer. Departamento de Bioquímica y Biología Molecular. Facultad Cs. Biológicas, Universidad de Concepción, Concepción, Chile. ropincheira@udec.cl.ORCID http://orcid.org/0000-0003-4277-5245

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
DHHS/NCI Cancer Center Support Grant P30 CA016672FONDECYT 1151031FONDECYT 1160731NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

backgroundGenetically engineered mice (GEM) are essential tools for understanding gene function and disease modeling. Historically, gene targeting was first done in embryonic stem cells (ESCs) derived from the 129 family of inbred strains, leading to a mixed background or congenic mice when crossed with C57BL/6 mice. Depending on the number of backcrosses and breeding strategies, genomic segments from 129-derived ESCs can be introgressed into the C57BL/6 genome, establishing a unique genetic makeup that needs characterization in order to obtain valid conclusions from experiments using GEM lines. Currently, SNP genotyping is used to detect the extent of 129-derived ESC genome introgression into C57BL/6 recipients; however, it fails to detect novel/rare variants.

resultsHere, we present a computational pipeline implemented in the Galaxy platform and in BASH/R script to determine genetic introgression of GEM using next generation sequencing data (NGS), such as whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-Seq. The pipeline includes strategies to uncover variants linked to a targeted locus, genome-wide variant visualization, and the identification of potential modifier genes. Although these methods apply to congenic mice, they can also be used to describe variants fixed by genetic drift. As a proof of principle, we analyzed publicly available RNA-Seq data from five congenic knockout (KO) lines and our own RNA-Seq data from the Sall2 KO line. Additionally, we performed target validation using several genetics approaches.

conclusionsWe revealed the impact of the 129-derived ESC genome introgression on gene expression, predicted potential modifier genes, and identified potential phenotypic interference in KO lines. Our results demonstrate that our new approach is an effective method to determine genetic introgression of GEM.

Indexed as

Genetic BackgroundAnimalsAnimals, Genetically ModifiedComputational BiologyCyclin-Dependent Kinase Inhibitor p21DNA-Binding ProteinsEmbryonic Stem CellsExome SequencingGene Expression RegulationGenes, ModifierHigh-Throughput Nucleotide SequencingIntracellular Signaling Peptides and ProteinsMiceMice, 129 StrainMice, CongenicMice, Inbred C57BLCdkn1a protein, mouseCyclin-Dependent Kinase Inhibitor p21DNA-Binding ProteinsIntracellular Signaling Peptides and ProteinsSall2 protein, mouseTranscription FactorsAngCdkn1aCongenic mouseGenetic backgroundGenetic interactionsGenomic variationKnockout mouseModifier genesqPCR validationRNA-Seq variant callingSall2Sequencing

Identifiers

PMID30755158
PMCPMC6373082

What OpenQuestion 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 OpenQuestion graph.