Evidence map›Paper›PMID 29454799›Full record

ReviewAnimal reproduction science2018

Identification of genomic variants causing sperm abnormalities and reduced male fertility.

Jeremy F Taylor, Robert D Schnabel, Peter Sutovsky

Open access · hybridAbstract readReview
In one paragraph

Review in Animal reproduction science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 9% 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Assessing Bovine Male Fertility in a Technological Age.Advances in anatomy, embryology, and cell biology · 2025
    Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Localization and in silico-based functional analysis of miR-202 in bull testis.Reproduction in domestic animals = Zuchthygiene · 2022
    Article
  14. Article
  15. Article
  16. Use of Agriculturally Important Animals as Models in Biomedical Research.Advances in experimental medicine and biology · 2022
    Review
  17. Article
  18. Article
  19. Article
  20. 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

3 authors at 1 institution in 1 country.

Jeremy F TaylorDivision of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA. Electronic address: taylorjerr@missouri.edu.
Robert D SchnabelDivision of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
Peter SutovskyDivision of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
University of Missouri · US

Funding

Linking Fertility-Associated Gene Polymorphisms to Aberrant Sperm PhenotypesR01HD084353 · NICHD · UNIVERSITY OF MISSOURI-COLUMBIA · PI SUTOVSKY, PETER SUTOVSKY · 2016 to 2020
$1.7M
NICHD NIH HHS R01 HD084353
6 · The paper itself

Abstract

Whole genome sequencing has identified millions of bovine genetic variants; however, there is currently little understanding about which variants affect male fertility. It is imperative that we begin to link detrimental genetic variants to sperm phenotypes via the analysis of semen samples and measurement of fertility for bulls with alternate genotypes. Artificial insemination (AI) bulls provide a useful model system because of extensive fertility records, measured as sire conception rates (SCR). Genetic variants with moderate to large effects on fertility can be identified by sequencing the genomes of fertile and subfertile or infertile sires identified with high or low SCR as adult AI bulls or yearling bulls that failed Breeding Soundness Evaluation. Variants enriched in frequency in the sequences of subfertile/infertile bulls, particularly those likely to result in the loss of protein function or predicted to be severely deleterious to genes involved in sperm protein structure and function, semen quality or sperm morphology can be designed onto genotyping assays for validation of their effects on fertility. High throughput conventional and image-based flow cytometry, proteomics and cell imaging can be used to establish the functional effects of variants on sperm phenotypes. Integrating the genetic, fertility and sperm phenotype data will accelerate biomarker discovery and validation, improve routine semen testing in bull studs and identify new targets for cost-efficient AI dose optimization approaches such as semen nanopurification. This will maximize semen output from genetically superior sires and will increase the fertility of cattle. Better understanding of the relationships between male genotype and sperm phenotype may also yield new diagnostic tools and treatments for human male and idiopathic infertility.

Indexed as

Gene Expression RegulationGenetic VariationAnimalsCattleInfertility, MaleMalePhenotypeSelection, GeneticSpermatozoaSperm MotilityTeratozoospermiaWhole Genome SequencingBull fertilityCandidate genesGenome-wide association studyGenomic selectionNanopurificationQuantitative trait loci

Identifiers

PMID29454799
PMCPMC6503949
OpenAlexW2791908562

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.