Evidence map›Paper›PMID 42252190›Full record

ReviewThe Journal of reproduction and development2026

Genomic evaluation and gene expression analysis of preimplantation embryos for enhancing cattle breeding and in vitro embryo production.

Takashi Fujii

Abstract readReview
In one paragraph

Review in The Journal of reproduction and development, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Takashi FujiiFaculty of Agriculture, Iwate University, Iwate 020-8550, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic selection using genomic estimated breeding values (GEBVs) based on single nucleotide polymorphism (SNP) genotyping has been widely adopted for efficient breeding of cattle. Recent advances in DNA analysis technologies have enabled comprehensive SNP genotyping using a small number of cells. Implementation of a preimplantation genomic selection (PGS) system, wherein GEBVs are calculated from a limited number of embryonic cells, can further enhance breeding efficiency through the selective production of genetically superior animals by embryo transfer. In addition, the use of bovine embryos produced by in vitro fertilization (IVF) has increased worldwide in recent years. However, the implantation potential of bovine IVF embryos is lower than that of in vivo-derived (IVD) embryos, and aberrant epigenetic modifications and gene expression are considered major contributing factors to the reduced developmental competence of bovine IVF embryos. Therefore, the differences in the gene expression characteristics of bovine IVD and IVF embryos need to be better understood for improved bovine in vitro production (IVP) systems. This review outlines the development and applications of PGS systems using bovine blastocysts, elongating conceptuses, and demi-embryos derived from blastomere separation. It also discusses the utility of gene expression profiling as a method for evaluating the quality of bovine preimplantation embryos, which may contribute to improvements in bovine IVP systems.

Indexed as

BlastocystBreedingFertilization in VitroAnimalsCattleEmbryo Culture TechniquesEmbryo TransferFemaleGene Expression ProfilingGene Expression Regulation, DevelopmentalGenomicsPolymorphism, Single NucleotidePregnancyBovineEmbryoGene expressionGenomic evaluationPreimplantation genomic selection

Identifiers

PMID42252190
PMCPMC13441460

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.