Comparative expression profiling reveals widespread coordinated evolution of gene expression across eukaryotes

Martin, Trevor; Fraser, Hunter B.

doi:10.1038/s41467-018-07436-y

Cited by 16 publications

(23 citation statements)

References 53 publications

(65 reference statements)

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“…Expression patterns of orthologous genes are often conserved and closely related to their function [30][31][32]. In the current study, we observed a total of 12 AGPAT genes orthologous between buffalo and cattle, suggesting that they might have a similar function in both species.…”

Section: Discussionsupporting

confidence: 49%

Novel Insight Into The Potential Role of AGPAT Gene Family in Triacylglycerols Synthesis in Buffalo

Ma¹,

Duan²,

Lu³

et al. 2021

Preprint

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Background: Acylglycerophosphate acyltransferases (AGPATs) are enzymes known to act on the second acylation step in the Kennedy (de novo) pathway to catalyze the conversion of lysophosphatidic acid (LPA) to phosphatidic acid (PA). Although AGPATs have been extensively explored by evolution, expression, and functional studies, little is known about the functional characterization of how many members of the AGPAT family are involved in the triacylglycerols (TAG) synthesis. Therefore, the objective of this study was to characterize the potential functional roles of AGPAT family members in the TAG synthesis and growth of mammary epithelial cells using comparative genomic analysis and RNA interference (RNAi) technology.Results: In the present study, a total of 13 AGPAT genes in buffalo were identified using genome-wide analysis. Among them, 12 AGPAT gene pairs were orthologous between buffalo and cattle. The comparative transcriptomic analysis and real-time quantitative reverse transcription PCR (qRT-PCR) further showed that both AGPAT1 and AGPAT6 were highly expressed in milk samples of buffalo and cattle during lactation. Notably, knockdown of AGPAT1 or AGPAT6 significantly decreased the TAG content of buffalo mammary epithelial cells (BuMEC) and bovine mammary epithelial cells (BoMEC) through regulating the mRNA expression levels of several lipogenic genes. Furthermore, the knockdown of AGPAT1 or AGPAT6 inhibited proliferation and promoted apoptosis of BuMECs; the qRT-PCR analysis of marker genes associated with cell proliferation and apoptosis supported the same conclusions. Conclusions: These findings provide new insights about the members of AGPAT family on how they regulate the TAG synthesis and growth of mammary epithelial cells in buffalo. These findings will have important implications for understanding the role of AGPAT gene for buffalo milk production performance.

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Section: Discussionsupporting

confidence: 49%

Novel Insight Into The Potential Role of AGPAT Gene Family in Triacylglycerols Synthesis in Buffalo

Ma¹,

Duan²,

Lu³

et al. 2021

Preprint

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“…Previous work suggests that biological systems evolve and function in a modular fashion, where groups of genes that share functional relationships tend to co-evolve independently of genes in other functional groups, and where genes and proteins that share function tend to be co-regulated (Hartwell et al 1999; Schlosser and Wagner 2004; Ryan et al 2012; Ge et al 2001; Martin and Fraser 2018). Consistent with this, we find the core network is modularly structured.…”

Section: Discussionmentioning

confidence: 99%

In search of a core cellular network with single cell transcriptome data in the fruit fly

Yang

Harrison

Promislow

2021

Preprint

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Background: Along with specialized functions, cells of multicellular organisms also perform essential functions common to most if not all cells. Whether diverse cells do this by using the same set of genes, interacting in a fixed coordinated fashion to execute essential functions, remains a central question in biology. Single-cell RNA-sequencing (scRNA-seq) measures gene expression of individual cells, enabling researchers to discover gene expression patterns that contribute to the diversity of cell functions. Current analyses focus primarily on identifying differentially expressed genes across cells. However, patterns of co-expression between genes are probably more indicative of biological processes than are the expression of individual genes. Using single cell transcriptome data from the fly brain, here we focus on gene co-expression to search for a core cellular network. Results: In this study, we constructed cell type-specific gene co-expression networks using single cell transcriptome data of brains from the fruit fly, Drosophila melanogaster. We detected a set of highly coordinated genes preserved across cell types in fly brains and defined this set as the core cellular network. This core is very small compared with cell type-specific gene co-expression networks and shows dense connectivity. Modules within this core are enriched for basic cellular functions, such as translation and ATP metabolic processes, and gene members of these modules have distinct evolutionary signatures. Conclusions: Overall, we demonstrated that a core cellular network exists in diverse cell types of fly brains and this core exhibits unique topological, structural, functional and evolutionary properties.

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“…First, genome data enable researchers to derive accurate, high-resolution phylogenies to probe the evolution of gene families and the genomic signatures of selection (e.g., Whitkus et al 1992 ; Clark et al 2007 ). Second, transcriptomics, proteomics, and metabolomics allow for the study of adaptation at the molecular level with a breadth not previously possible (e.g., von Mering et al 2003 ; Spirin et al 2006 ; Bedford and Hartl 2009 ; Brawand et al 2011 ; Gordon and Ruvinsky 2012 ; Martin and Fraser 2018 ; Cope et al 2020 ). Metabolomic methods are able to measure the levels of hundreds to thousands of metabolite features with a high level of accuracy ( Jones et al 2012 ).…”

Section: Introductionmentioning

confidence: 99%

Modular Evolution of the Drosophila Metabolome

Harrison

Hoffman

Samuelson

et al. 2021

Molecular Biology and Evolution

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Comparative phylogenetic studies offer a powerful approach to study the evolution of complex traits. While much effort has been devoted to the evolution of the genome and to organismal phenotypes, until now relatively little work has been done on the evolution of the metabolome, despite the fact that it is composed of the basic structural and functional building blocks of all organisms. Here we explore variation in metabolite levels across 50 million years of evolution in the genus Drosophila, employing a common garden design to measure the metabolome within and among 11 species of Drosophila. We find that both sex and age have dramatic and evolutionarily conserved effects on the metabolome. We also find substantial evidence that many metabolite pairs covary after phylogenetic correction, and that such metabolome coevolution is modular. Some of these modules are enriched for specific biochemical pathways and show different evolutionary trajectories, with some showing signs of stabilizing selection. Both observations suggest that functional relationships may ultimately cause such modularity. These coevolutionary patterns also differ between sexes and are affected by age. We explore the relevance of modular evolution to fitness by associating modules with lifespan variation measured in the same common garden. We find several modules associated with lifespan, particularly in the metabolome of older flies. Oxaloacetate levels in older females appear to coevolve with lifespan, and a lifespan-associated module in older females suggests that metabolic associations could underlie 50 million years of lifespan evolution.

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Comparative expression profiling reveals widespread coordinated evolution of gene expression across eukaryotes

Cited by 16 publications

References 53 publications

Novel Insight Into The Potential Role of AGPAT Gene Family in Triacylglycerols Synthesis in Buffalo

Novel Insight Into The Potential Role of AGPAT Gene Family in Triacylglycerols Synthesis in Buffalo

In search of a core cellular network with single cell transcriptome data in the fruit fly

Modular Evolution of the Drosophila Metabolome

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