FertilityOnline

FertilityOnline consolidates literature-curated functional genes and genetic variant information to support analysis of genetic determinants of human spermatogenesis and male infertility.


Key Features:

  • Integrated Database: Combines literature-curated functional genes involved in spermatogenesis with genetic variant information for human genes and integrates these data with SpermatogenesisOnline 1.0.
  • Functional Annotation and Genetic Variants: Provides detailed functional annotations and genetic variant data to facilitate identification and interpretation of potential disease-causing mutations.
  • Cross-species Knowledge Integration: Bridges knowledge between human and animal model data to aid interpretation of gene function in spermatogenesis.
  • Clinical Mutation Identification: Has been used to identify novel causative mutations in proteins such as synaptonemal complex central element protein 1 (SYCE1) and stromal antigen 3 (STAG3) implicated in azoospermia.

Scientific Applications:

  • Genetic basis analysis of spermatogenesis: Supports discovery and prioritization of candidate genes underlying male infertility.
  • Clinical variant interpretation: Enables identification and contextualization of disease-causing mutations in infertile men, including mutations in SYCE1 and STAG3 associated with azoospermia.
  • Comparative functional analysis: Facilitates comparison of gene function between humans and animal models to inform spermatogenesis research.

Methodology:

Curated literature on functional genes during spermatogenesis and integrated these data into the SpermatogenesisOnline 1.0 database.

Topics

Details

Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Added:
6/7/2022
Last Updated:
11/24/2024

Operations

Publications

Gao J, Zhang H, Jiang X, Ali A, Zhao D, Bao J, Jiang L, Iqbal F, Shi Q, Zhang Y. FertilityOnline: A Straightforward Pipeline for Functional Gene Annotation and Disease Mutation Discovery. Genomics, Proteomics & Bioinformatics. 2021;20(3):455-465. doi:10.1016/j.gpb.2021.08.010. PMID:34954426. PMCID:PMC9801063.

PMID: 34954426
PMCID: PMC9801063
Funding: - National Key R&D Program of China: 2016YFC1000600, 2017YFC1001500, 2018YFC1003700, 2018YFC1004700 - National Natural Science Foundation of China: 31630050, 31771668, 31871514, 31890780, 82071709 - Fundamental Research Funds for the Central Universities: YD2070002006 - National Key Research and Development Program of China: 2016YFC1000600, 2017YFC1001500, 2018YFC1003700, 2018YFC1004700