Evidence map›Paper›PMID 36642776›Full record

ReviewMolecular biology reports2023

Allelic to genome wide perspectives of swine genetic variation to litter size and its component traits.

Sakshi Vaishnav, Anuj Chauhan, Argana Ajay, Babu Lal Saini, Subodh Kumar, Amit Kumar, Bharat Bhushan, Gyanendra Kumar Gaur

Abstract readReview
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In one paragraph

Review in Molecular biology reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Research on the Historical Dynamics of Baicheng Oil Chicken Populations.Animals : an open access journal from MDPI · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. 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

8 authors.

Sakshi VaishnavIndian Veterinary Research Institute, Bareilly, India.
Anuj ChauhanIndian Veterinary Research Institute, Bareilly, India. dranujivri@gmail.com.ORCID http://orcid.org/0000-0002-5971-0950
Argana AjayIndian Veterinary Research Institute, Bareilly, India.
Babu Lal SainiIndian Veterinary Research Institute, Bareilly, India.
Subodh KumarIndian Veterinary Research Institute, Bareilly, India.
Amit KumarIndian Veterinary Research Institute, Bareilly, India.
Bharat BhushanIndian Veterinary Research Institute, Bareilly, India.
Gyanendra Kumar GaurIndian Veterinary Research Institute, Bareilly, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Litter size is a complex and sex limited trait that depends on various biological, managemental and environmental factors. Owing to its low heritability it is inefficaciously selected by traditional methods. However, due to higher heritability of ovulation rate and embryo survival, selection based on component traits of litter size is advocated. QTL analysis and candidate gene approach are among the various supplementary/alternate strategies for selection of litter size. QTL analysis is aimed at identifying genomic regions affecting trait of interest significantly. Candidate gene approach necessitates identification of genes potentially affecting the trait. There are various genes that significantly affect litter size and its component traits viz. ESR, LEP, BF, IGFBP, RBP4, PRLR, CTNNAL1, WNT10B, TCF12, DAZ, and RNF4. These genes affect litter size in a complex interacting manner. Lately, genome wide association study (GWAS) have been utilized to unveil the genetic and biological background of litter traits, and elucidate the genes governing litter size. Favorable SNPs in these genes have been identified and offers a scope for inclusion in selection programs thereby increasing breeding efficiency and profit in pigs. The review provides a comprehensive coverage of investigations carried out globally to unravel the genetic variation in litter size and its component traits in pigs, both at allelic and genome wide level. It offers a current perspective on different strategies including the profiling of candidate genes, QTLs, and genome wide association studies as an aid to efficient selection for litter size and its component traits.

Indexed as

Genome-Wide Association StudyQuantitative Trait LociAnimalsFemaleGenetic VariationLitter SizePhenotypePolymorphism, Single NucleotidePregnancySwineCandidate gene approachGenome wide association studyLitter sizeNumber born aliveQTL analysisTotal number born

Identifiers

What OpenQuestion holds

Textmetadata
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.