Differential gene expression patterns during gametophyte development provide insights into sex differentiation in the dioicous kelp Saccharina japonica

Abstract Background In brown algae, dioicy is the prevalent sexual system, and phenotypic differences between male and female gametophytes have been found in many dioicous species. Saccharina japonica show remarkable sexual dimorphism in gametophytes before gametogenesis. A higher level of phenotypic differentiation was also found in female and male gametes after gametogenesis. However, the patterns of differential gene expression throughout gametophyte development and how these changes might relate to sex-specific fitness at the gamete stage in S. japonica are not well known. Results In this study, differences in gene expression between male and female gametophytes in different developmental stages were investigated using comparative transcriptome analysis. Among the 20,151 genes expressed in the haploid gametophyte generation, 37.53% were sex-biased. The abundance of sex-biased genes in mature gametophytes was much higher than that in immature gametophytes, and more male-biased than female-biased genes were observed in the mature stage. The predicted functions of most sex-biased genes were closely related to the sex-specific characteristics of gametes, including cell wall biosynthesis, sperm motility, and sperm and egg recognition. In addition, 51 genes were specifically expressed in males in both stages, showing great potential as candidate male sex-determining region (SDR) genes. Conclusions This study describes a thorough investigation into differential gene expression between male and female gametophytes in the dioicous kelp S. japonica. A large number of sex-biased genes in mature gametophytes may be associated with the divergence of phenotypic traits and physiological functions between female gametes (eggs) and male gametes (sperm) during sexual differentiation. These genes may mainly come from new sex-biased genes that have recently evolved in the S. japonica lineage. The duplication of sex-biased genes was detected, which may increase the number of sex-biased genes after gametogenesis in S. japonica to some extent. The excess of male-biased genes over female-biased genes in the mature stage may reflect the different levels of sexual selection across sexes. This study deepens our understanding of the regulation of sex development and differentiation in the dioicous kelp S. japonica.

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Differential gene expression patterns in spermatozoa from teratospermic and normospermic domestic cats

Animal Reproduction Science ◽

10.1016/j.anireprosci.2021.106698 ◽

2021 ◽

Vol 226 ◽

pp. 106698

Author(s):

Audra A. Huffmeyer ◽

Budhan S. Pukazhenthi ◽

Robert K. Wayne

Keyword(s):

Gene Expression ◽

Differential Gene Expression ◽

Expression Patterns ◽

Gene Expression Patterns ◽

Domestic Cats ◽

Differential Gene

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Altered Levels of Histone Deacetylase OsHDT1 Affect Differential Gene Expression Patterns in Hybrid Rice

PLoS ONE ◽

10.1371/journal.pone.0021789 ◽

2011 ◽

Vol 6 (7) ◽

pp. e21789 ◽

Cited By ~ 30

Author(s):

Chen Li ◽

Limin Huang ◽

Caiguo Xu ◽

Yu Zhao ◽

Dao-Xiu Zhou

Keyword(s):

Gene Expression ◽

Histone Deacetylase ◽

Differential Gene Expression ◽

Hybrid Rice ◽

Expression Patterns ◽

Gene Expression Patterns ◽

Differential Gene

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RankerGUI: A Computational Framework to Compare Differential Gene Expression Profiles Using Rank Based Statistics

International Journal of Molecular Sciences ◽

10.3390/ijms20236098 ◽

2019 ◽

Vol 20 (23) ◽

pp. 6098 ◽

Cited By ~ 1

Author(s):

Amarinder Singh Thind ◽

Kumar Parijat Tripathi ◽

Mario Rosario Guarracino

Keyword(s):

Gene Expression ◽

Differential Expression ◽

Differential Gene Expression ◽

Web Application ◽

Cellular Response ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Experimental Conditions ◽

Differential Gene

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.

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