Single-cell RNA sequencing uncovers dynamic roadmap and cell-cell communication during buffalo spermatogenesis

Huang, Liangfeng; Zhang, Pengfei; Huang, Xingchen; Yang, Wenxuan; Liu, Runfeng; Sun, Qinqiang; Lu, Yangqing; Zhang, Ming; Fu, Qiang

doi:10.1016/j.isci.2022.105733

Cited by 21 publications

(11 citation statements)

References 140 publications

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“…In our dataset, in T2D islets, we find that PLCE1 expression increases in α1 and α2 (mature α-cells) and decreases further from the already very low expression level in mature β1 cells confirming previous results and highlighting this phospholipase as a potential candidate for β-cell dysfunction in T2D. Pappalysin-2 (PAPPA2), an enzyme that cleaves and inactivates IGFBP proteins, is upregulated in α-cells during gestation (50). In our study, we observe that PAPPA2 is expressed in α-cells and may participate in the transition of AB/β-cells into α-cells by suppressing the effects of IGFBPs since IGFBP1 has been reported to promote α-to β-cell transdifferentiation (51).…”

Section: Discussionsupporting

confidence: 90%

Human Pancreatic α-Cell Heterogeneity and Trajectory Inference Analysis Using Integrated Single Cell- and Single Nucleus-RNA Sequencing Platforms

Kang,

Lee,

Varela

et al. 2023

Preprint

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Prior studies have shown that pancreatic α-cells can transdifferentiate into β-cells, and that β-cells de-differentiate and are prone to acquire an α-cell phenotype in type 2 diabetes (T2D). However, the specific human α-cell and β-cell subtypes that are involved in α-to-β-cell and β-to-α-cell transitions are unknown. Here, we have integrated single cell RNA sequencing (scRNA-seq) and single nucleus RNA-seq (snRNA-seq) of isolated human islets and human islet grafts and provide additional insight into α-β cell fate switching. Using this approach, we make seven novel observations. 1) There are five differentGCG-expressing human α-cell subclusters [α1, α2, α-β-transition 1 (AB-Tr1), α-β-transition 2 (AB-Tr2), and α-β (AB) cluster] with different transcriptome profiles in human islets from non-diabetic donors. 2) The AB subcluster displays multihormonal gene expression, inferred mostly from snRNA-seq data suggesting identification by pre-mRNA expression. 3) The α1, α2, AB-Tr1, and AB-Tr2 subclusters are enriched in genes specific for α-cell function while AB cells are enriched in genes related to pancreatic progenitor and β-cell pathways; 4) Trajectory inference analysis of extracted α- and β-cell clusters and RNA velocity/PAGA analysis suggests a bifurcate transition potential for AB towards both α- and β-cells. 5) Gene commonality analysis identifiesZNF385D, TRPM3, CASR, MEG3andHDAC9as signature for trajectories moving towards β-cells andSMOC1, PLCE1, PAPPA2, ZNF331, ALDH1A1, SLC30A8, BTG2, TM4SF4, NR4A1andPSCK2as signature for trajectories moving towards α-cells. 6) Remarkably, in contrast to the eventsin vitro, the AB subcluster is not identifiedin vivoin human islet grafts and trajectory inference analysis suggests only unidirectional transition from α-to-β-cellsin vivo. 7) Analysis of scRNA-seq datasets from adult human T2D donor islets reveals a clear unidirectional transition from β-to-α-cells compatible with dedifferentiation or conversion into α-cells. Collectively, these studies show that snRNA-seq and scRNA-seq can be leveraged to identify transitions in the transcriptional status among human islet endocrine cell subpopulationsin vitro,in vivo, in non-diabetes and in T2D. They reveal the potential gene signatures for common trajectories involved in interconversion between α- and β-cells and highlight the utility and power of studying single nuclear transcriptomes of human isletsin vivo. Most importantly, they illustrate the importance of studying human islets in their naturalin vivosetting.

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Section: Discussionsupporting

confidence: 90%

Human Pancreatic α-Cell Heterogeneity and Trajectory Inference Analysis Using Integrated Single Cell- and Single Nucleus-RNA Sequencing Platforms

Kang,

Lee,

Varela

et al. 2023

Preprint

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“…Lineage tracing of the formation and maintenance of the spermatogonial population may uncover the mechanisms that direct clonality within the spermatogonial population and whether a decrease in clonal diversity accompanies infertility. We anticipate that transcriptomic resources, like those presented here, will facilitate continued explorations of the mechanisms that regulate the development, maintenance, and break down of the zebrafish testis and serve as an evolutionary comparison point for studies of fertility in other vertebrates (Green et al 2018, Guo et al 2018, Jung et al 2019, Guo et al 2020, Lau et al 2020, Yu et al 2021, Nie et al 2022, Garcia-Alonso et al 2022, Liu et al 2022, Huang et al 2023).…”

Section: Discussionmentioning

confidence: 99%

Germ cells do not progress through spermatogenesis in the infertile zebrafish testis

Sposato,

Llewellyn,

Weber

et al. 2023

Preprint

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Vertebrate spermatogonial stem cells maintain sperm production over the lifetime of an animal but fertility declines with age. While morphological studies have greatly informed our understanding of typical spermatogenesis, the molecular and cellular mechanisms underlying spermatogenesis are not yet understood, particularly with respect to the onset of fertility. We used single-cell RNA sequencing to generate a developmental atlas of the zebrafish testis. Using 5 timepoints across the adult life of a zebrafish, we described cellular profiles in the testis during and after fertility. While all germ cell stages of spermatogenesis are detected in testes from fertile adult zebrafish, testes from older infertile males only contained spermatogonia and a reduced population of spermatocytes. These remaining germ cells are transcriptionally distinct from fertile spermatogonia. Immune cells including macrophages and lymphocytes drastically increase in abundance in infertile testes. Our developmental atlas reveals the cellular changes as the testis ages and defines a molecular roadmap for the regulation of male fertility.

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“…Here, we hypothesise that an integrated single-cell atlas of the set of publicly-available adult human testes samples (comprising data from 9 different studies 10,15,16,20,[22][23][24][25][26] ) would increase the resolution at which we view the molecular identity of the undifferentiated compartment and the origin and progression of the spermatogenic trajectory. Combined with a comparative analysis of spermatogonia across human development (using embryonic, foetal and both pre-and peri-pubertal samples from 7 different studies 10,16,23,25,[27][28][29] ) and against two primate (rhesus 5,20 and cynomolgus macaque 30 ), and five non-primate mammalian species (mouse [31][32][33][34] , rat 35 , pig 36 , sheep 37 , and buffalo 38 ), here we aim to characterise the heterogeneity of undifferentiated human spermatogonia and provide insight into the nature of the putative SSC populations. In doing so, we propose new hypotheses about the mechanisms of SSC regulation.…”

Section: Introductionmentioning

confidence: 99%

Human spermatogonial stem cells retain states with a foetal-like signature

Bush,

Nikola,

Han

et al. 2024

Preprint

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Spermatogenesis involves a complex process of cellular differentiation maintained by spermatogonial stem cells (SSCs). Being critical to male reproduction, it is generally assumed that spermatogenesis starts and ends in equivalent transcriptional states in related species. Based on single-cell gene expression profiling it has been proposed that undifferentiated human spermatogonia can be sub-classified into four heterogenous subtypes, termed states 0, 0A, 0B, and 1. To increase the resolution of the undifferentiated compartment and trace the origin of the spermatogenic trajectory, we re-analysed the single-cell (sc)RNA-seq libraries of 34 post-pubescent human testes to generate an integrated atlas of germ cell differentiation. We then used this atlas to perform comparative analyses of the putative SSC transcriptome both across human development (using 28 foetal and pre-pubertal scRNA-seq libraries) and across species (including data from sheep, pig, buffalo, rhesus and cynomolgus macaque, rat and mouse). Alongside its detailed characterisation, we show that the transcriptional heterogeneity of the undifferentiated spermatogonial cell compartment varies not only between species but across development. Our findings associate 'state 0B' with a suppressive transcriptomic program that, in adult humans, acts to functionally oppose proliferation and maintain cells in a ready-to-react state. Consistent with this conclusion, we show that human foetal germ cells - which are mitotically arrested - can be characterised solely as state 0B. While germ cells with a state 0B signature are also present in foetal mouse (and are likely conserved at this stage throughout mammals), they are not maintained into adulthood. We conjecture that in rodents, the foetal-like state 0B differentiates at birth into the renewing SSC population, whereas in humans it is maintained as a reserve population, supporting testicular homeostasis over a longer reproductive life while reducing mutagenic load. Together, these results suggest that SSCs adopt differing evolutionary strategies across species to ensure fertility and genome integrity over vastly differing life histories and reproductive timeframes.

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Single-cell RNA sequencing uncovers dynamic roadmap and cell-cell communication during buffalo spermatogenesis

Cited by 21 publications

References 140 publications

Human Pancreatic α-Cell Heterogeneity and Trajectory Inference Analysis Using Integrated Single Cell- and Single Nucleus-RNA Sequencing Platforms

Human Pancreatic α-Cell Heterogeneity and Trajectory Inference Analysis Using Integrated Single Cell- and Single Nucleus-RNA Sequencing Platforms

Germ cells do not progress through spermatogenesis in the infertile zebrafish testis

Human spermatogonial stem cells retain states with a foetal-like signature

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