Evidence map›Paper›PMID 40301257›Full record

ReviewAdvances in experimental medicine and biology2025

Computational Approaches in Spatial Transcriptomics for the Study of Mammalian Spermatogenesis.

Deina Bossa, Melanie Evans, Shreya Rajachandran, Xin Zhang, Qiqi Cao, Haiqi Chen

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In one paragraph

Review in Advances in experimental medicine and biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Deina BossaDepartment of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Melanie EvansDepartment of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Shreya RajachandranDepartment of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Xin ZhangDepartment of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Qiqi CaoDepartment of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Haiqi ChenDepartment of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA. haiqi.chen@utsouthwestern.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spermatogenesis is a complex and dynamic cellular differentiation process critical to male fertility. Although the full continuum of gene expression patterns from spermatogonial stem cells (SSCs) to spermatozoa in steady state was characterized using single-cell RNA sequencing technologies, the transcriptional dynamics of spermatogenesis within its native tissue context was largely unexplored. The recent development of spatial transcriptomics (ST) technologies has transformed male fertility research from a single-cell level to a two-dimensional spatial coordinate system and facilitated the study of spermatogenesis in the native environment of both the rodent and human testes. The spatial gene expression information generated by these ST technologies requires new computational approaches to extract novel biological insights. These requirements include, but are not limited to, spatial mapping of testicular cell types, identifying spatially variable genes, and understanding the molecular cross-talk between testicular cell types. Here, we review computational approaches that have been used to dissect mammalian spermatogenesis in the context of ST. We also highlight new computational approaches that can be leveraged to reveal novel insights into male fertility.

Indexed as

Computational BiologyGene Expression ProfilingSpermatogenesisTestisTranscriptomeAnimalsHumansMaleMammalsSingle-Cell AnalysisSpermatozoaCell-cell communicationSpatially variable genesSpatial TranscriptomicsSpermatogenesisTestis

Identifiers

What OpenQuestion holds

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Registered trials

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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.