Evidence map›Paper›PMID 38473873›Full record

ArticleInternational journal of molecular sciences2024

Transcriptome-Wide Association Study Reveals Potentially Candidate Genes Responsible for Milk Production Traits in Buffalo.

Kelong Wei, Ying Lu, Xiaoya Ma, Anqian Duan, Xingrong Lu, Hamdy Abdel-Shafy, Tingxian Deng

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
2.8field-weighted citation impact, top 11% of its field
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, 2 syntheses or guidelines pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Genome-wide association study identifies significant SNPs for milk production and stature traits in Karan Fries cattle.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
  4. Article
  5. 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

7 authors at 2 institutions in 2 countries.

Kelong WeiGuangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
Ying LuGuangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
Xiaoya MaGuangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
Anqian DuanGuangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
Xingrong LuGuangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
Hamdy Abdel-ShafyDepartment of Animal Production, Faculty of Agriculture, Cairo University, Giza 12613, Egypt.ORCID 0000-0003-3282-3899
Tingxian DengGuangxi Provincial Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.ORCID 0000-0002-7442-6739
Guangxi Buffalo Research Institute · CNCairo University · EG

Funding

National Natural Science Foundation of China 32160779Natural Science Foundation of Guangxi Zhuang Autonomous Region 2020GXNSFDA297032
6 · The paper itself

Abstract

Identifying key causal genes is critical for unraveling the genetic basis of complex economic traits, yet it remains a formidable challenge. The advent of large-scale sequencing data and computational algorithms, such as transcriptome-wide association studies (TWASs), offers a promising avenue for identifying potential causal genes. In this study, we harnessed the power of TWAS to identify genes potentially responsible for milk production traits, including daily milk yield (MY), fat percentage (FP), and protein percentage (PP), within a cohort of 100 buffaloes. Our approach began by generating the genotype and expression profiles for these 100 buffaloes through whole-genome resequencing and RNA sequencing, respectively. Through comprehensive genome-wide association studies (GWAS), we pinpointed a total of seven and four single nucleotide polymorphisms (SNPs) significantly associated with MY and FP traits, respectively. By using TWAS, we identified 55, 71, and 101 genes as significant signals for MY, FP, and PP traits, respectively. To delve deeper, we conducted protein-protein interaction (PPI) analysis, revealing the categorization of these genes into distinct PPI networks. Interestingly, several TWAS-identified genes within the PPI network played a vital role in milk performance. These findings open new avenues for identifying potentially causal genes underlying important traits, thereby offering invaluable insights for genomics and breeding in buffalo populations.

Indexed as

BuffaloesMilkAnimalsGenome-Wide Association StudyGenotypeHumansPhenotypePolymorphism, Single NucleotideTranscriptomebuffalocausal genesGWASmilk production traitsTWAS

Identifiers

PMID38473873
PMCPMC10932178
OpenAlexW4392097497

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.