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Related Experiment Video

Updated: Sep 15, 2025

Isolate Cell-Type-Specific RNAs from Snap-Frozen Heterogeneous Tissue Samples without Cell Sorting

Isolate Cell-Type-Specific RNAs from Snap-Frozen Heterogeneous Tissue Samples without Cell Sorting

Published on: December 8, 2021

Transcriptome sequencing reveals significant RNA variation in human sperm samples.

Weiming Chen^1,2, Lei Yu^3,4, Zhenyu Jia^5,6

¹Guizhou university medical school, South Jiaxiu Rd, Guiyang city, Guizhou province, China.

BMC Research Notes

|July 12, 2025

Summary

Investigating sperm RNA profiles is crucial for understanding male infertility and epigenetic impacts. This study provides valuable transcriptome data to advance research in this area.

Keywords:

Asthenospermia RNA-seq Sperm

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Last Updated: Sep 15, 2025

Isolate Cell-Type-Specific RNAs from Snap-Frozen Heterogeneous Tissue Samples without Cell Sorting

Isolate Cell-Type-Specific RNAs from Snap-Frozen Heterogeneous Tissue Samples without Cell Sorting

Published on: December 8, 2021

RiboTag Immunoprecipitation in the Germ Cells of the Male Mouse

RiboTag Immunoprecipitation in the Germ Cells of the Male Mouse

Published on: March 4, 2020

Enhanced Crosslinking Immunoprecipitation eCLIP Method for Efficient Identification of Protein-bound RNA in Mouse Testis

Enhanced Crosslinking Immunoprecipitation eCLIP Method for Efficient Identification of Protein-bound RNA in Mouse Testis

Published on: May 10, 2019

Area of Science:

Reproductive Biology
Genomics
Molecular Biology

Background:

Sperm RNA profiles are vital for understanding male fertility and epigenetic inheritance.
The role of RNA quantity and quality in sperm biology remains poorly understood.
Investigating sperm RNA can shed light on male infertility linked to RNA disorders.

Purpose of the Study:

To analyze the transcriptome of spermatozoa from men with normal and reduced sperm motility.
To assess the RNA integrity and quantity in sperm samples.
To make valuable RNA sequencing data publicly available for further research.

Main Methods:

Collected 83 semen samples, including those with asthenospermia (reduced sperm motility).
Performed transcriptome sequencing on 37 successfully processed samples.
Classified samples based on RNA Integrity Number (RIN) and 28S/18S ratio.

Main Results:

Successfully sequenced RNA from 37 semen samples.
Identified 15 high-quality samples (RIN > 6) and 22 intermediate-quality samples (RIN 5-6).
Publicly deposited RNA sequencing data in the GSA-Human database (accession numbers HRA006250, HRA006906).

Conclusions:

The study provides crucial, publicly accessible sperm RNA sequencing data.
This data can aid in developing algorithms for analyzing post-spermatogenesis RNA.
Potential for discovering new molecular markers for asthenospermia is highlighted.