Evidence map›Paper›PMID 42041572›Full record

ArticleCells2026

Optimization of Preimplantation Genome Profiling Supports Genomic Selection in Cattle.

Shihui Yan, Saina Yan, Yuanweilu Cheng, Hengyuan Cui, Yang Pang, Jingfang Si, Li Jiang, Dongxiao Sun, Alfredo Pauciullo, Johannes A Lenstra and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cells, 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

12 authors.

Shihui YanState Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory of Animal Breeding, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100107, China.
Saina YanCollege of Biological Sciences, China Agricultural University, Beijing 100107, China.
Yuanweilu ChengState Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory of Animal Breeding, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100107, China.
Hengyuan CuiState Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory of Animal Breeding, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100107, China.
Yang PangState Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory of Animal Breeding, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100107, China.
Jingfang SiState Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory of Animal Breeding, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100107, China.ORCID 0009-0001-9232-3995
Li JiangState Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory of Animal Breeding, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100107, China.ORCID 0000-0002-0648-2173
Dongxiao SunState Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory of Animal Breeding, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100107, China.ORCID 0000-0002-7512-5946
Alfredo PauciulloDepartment of Agricultural, Forest and Food Science, University of Torin, 10124 Torino, Italy.ORCID 0000-0002-3140-9373
Johannes A LenstraFaculty of Veterinary Science, Utrecht University, 3584 CL Utrecht, The Netherlands.
Shenming ZengState Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory of Animal Breeding, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100107, China.
Yi ZhangState Key Laboratory of Animal Biotech Breeding, National Engineering Laboratory of Animal Breeding, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100107, China.ORCID 0000-0003-1642-5890

Funding

the earmarked fund CARS36the National Key Research and Development Program of China 2022YFD1302204
6 · The paper itself

Abstract

Preimplantation embryo genomic selection (eGS) enables selection prior to implantation and could accelerate genetic gain in cattle. A major hurdle is the limited DNA from embryo biopsies, requiring efficient whole-genome amplification (WGA) for accurate genomic analyses. However, alternative WGA methods and genotyping strategies have not been systematically compared in cattle. This study evaluated different methods for WGA (multiple displacement amplification (MDA) or multiple annealing and looping-based amplification cycles (MALBAC)) and for genotyping (single nucleotide polymorphism array (SNP-array), genotyping by targeted sequencing (GBTS), or whole-genome sequencing (WGS)) using 3-, 6-, and 9-cell bovine samples. MDA consistently outperformed MALBAC across various performance metrics, including amplification length, call rates, genome coverage (93.43-94.40% vs. 53.01-67.08%), and genotyping concordance (0.89-0.98 vs. 0.75-0.92). GBTS achieved the highest call rates, while SNP-array and GBTS showed excellent concordance and low error rates. WGS provided genome-wide data for precise aneuploidy detection. We further validated the workflow in trophectoderm biopsies and arrested embryos, generating reliable data for genomic evaluation, sex determination, and aneuploidy screening. MDA from ≥6 cells combined with GBTS or SNP-array showed a favorable balance of efficiency and accuracy for bovine eGS. This framework may facilitate the application of eGS in cattle breeding by enhancing selection intensity and accelerating genetic improvement.

Indexed as

BlastocystGenomeGenomicsAnimalsCattleFemaleGenotypeGenotyping TechniquesNucleic Acid Amplification TechniquesPolymorphism, Single NucleotideWhole Genome Sequencingbovineembryogenomic selectiongenotypingwhole-genome amplification

Identifiers

PMID42041572
PMCPMC13115129

What OpenQuestion holds

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LicenceCC BY
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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.