A gene expression atlas of embryonic neurogenesis in<i>Drosophila</i>reveals complex spatiotemporal regulation of lncRNAs

McCorkindale, Alexandra L.; Wahle, Philipp; Jungreis, Irwin; Menzel, Peter; Shukla, Chinmay; Abreu, Rúben Lopes Pereira; Irizarry, Rafael A.; Meyer, Irmtraud M.; Kellis, M; Rinn, John L.; Zinzen, Robert P.

doi:10.1101/483461

Cited by 8 publications

(15 citation statements)

References 62 publications

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“…In brief, D. melanogaster embryos were collected at the specified time points and the cell populations comprising neuroblasts, neurons, and glia were sorted after staining by FACS using primary directed and fluorescent secondary antibodies against the endogenous markers prospero (pros), elav, and repo, respectively. The specificity of the antibodies for the three cell types has been confirmed in [36]. The early collection bin at 6-8 h AEL comprises neuroblast proliferation and diversification into neurons and glia, whereas the late collection bin at 18-22 h AEL marks the end of embryogenesis with fully differentiated neurons and glia.…”

Section: Small Rna Sequencing Of Neural Cell Types During Embryogenesismentioning

confidence: 83%

“…In this study, we create smallRNA-Seq libraries for neuroblasts, neurons and glia cells at 6-8 h after egg laying (AEL) and 18-22 h AEL using the DIV-MARIS protocol, which is described in detail in [36]. In brief, D. melanogaster embryos were collected at the specified time points and the cell populations comprising neuroblasts, neurons, and glia were sorted after staining by FACS using primary directed and fluorescent secondary antibodies against the endogenous markers prospero (pros), elav, and repo, respectively.…”

Section: Small Rna Sequencing Of Neural Cell Types During Embryogenesismentioning

confidence: 99%

“…It is thus of key interest to investigate how the differential expression of microRNAs affects the mRNA levels of their target genes. To this end, we combine the in silico assessment of our small transcriptome data with the standard transcriptome sequencing data from [36], which were obtained using the same DIV-MARIS protocol. As before, we measure the differential expression of protein-coding genes between the marker-positive and marker-negative FACS fractions, between the three neural cell types as well as the early and late developmental stage ( Supplementary Figures 3 and 5).…”

Section: Effect Of Differential Microrna Expression On Their Target Gmentioning

confidence: 99%

“…Ideally, however, one would like to perform transcriptome-wide studies of microRNAs and their target genes in a tissue-or cell type-specific manner, in order to get an unbiased and more accurate view of their potential function during embryonic development. As there is little known so far about the cell type-specific expression and regulatory function of microRNAs during early neurogenesis, we analyze the spatiotemporal expression of microRNAs and their target genes during Drosophila melanogaster neurogenesis at two time points using the DIV-MARIS protocol introduced in [36], which is adapted from MARIS [37], and uses marker-based fluorescence sorting of individual embryonic cells, followed by RNA extraction and sequencing. For this purpose, we create dedicated sequencing libraries for small RNA transcripts at two developmental stages and from three different cell types.…”

Section: Introductionmentioning

confidence: 99%

“…For this purpose, we create dedicated sequencing libraries for small RNA transcripts at two developmental stages and from three different cell types. The combination of these smallRNA-Seq data sets and the standard RNA-Seq data sets from [36] allows us to simultaneously study the expression patterns of both microRNAs and their target genes. Subsequent in silico analysis allows us to identify the major cell type-specific microRNAs and their putative regulatory roles in Drosophila neurogenesis in a quantitative manner and with unprecedented spatiotemporal resolution.…”

Section: Introductionmentioning

confidence: 99%

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Transcriptional dynamics of microRNAs and their targets during Drosophila neurogenesis

et al. 2019

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During Drosophila melanogaster embryogenesis, tight regulation of gene expression in time and space is required for the orderly emergence of specific cell types. While the general importance of microRNAs in regulating eukaryotic gene expression has been well-established, their role in early neurogenesis remains to be addressed. In this survey, we investigate the transcriptional dynamics of microRNAs and their target transcripts during neurogenesis of Drosophila melanogaster. To this end, we use the recently developed DIV-MARIS protocol, a method for enriching specific cell types from the Drosophila embryo in vivo, to sequence cell type-specific transcriptomes. We generate dedicated small and total RNA-seq libraries for neuroblasts, neurons and glia cells at early (6–8 h after egg laying (AEL)) and late (18–22 h AEL) stage. This allows us to directly compare these transcriptomes and investigate the potential functional roles of individual microRNAs with spatiotemporal resolution genome-wide, which is beyond the capabilities of existing in situ hybridization methods. Overall, we identify 74 microRNAs that are significantly differentially expressed between the three cell types and the two developmental stages. In all cell types, predicted target genes of down-regulated microRNAs show a significant enrichment of Gene Ontology terms related to neurogenesis. We also investigate how microRNAs regulate the transcriptome by targeting transcription factors and find many candidate microRNAs with putative roles in neurogenesis. Our survey highlights the roles of microRNAs as regulators of differentiation and glioneurognesis in the fruit fly and provides distinct starting points for dedicated functional follow-up studies.

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Section: Small Rna Sequencing Of Neural Cell Types During Embryogenesismentioning

confidence: 83%

Section: Small Rna Sequencing Of Neural Cell Types During Embryogenesismentioning

confidence: 99%

Section: Effect Of Differential Microrna Expression On Their Target Gmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Transcriptional dynamics of microRNAs and their targets during Drosophila neurogenesis

et al. 2019

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The physiological function of long-noncoding RNAs

Chen

2020

Non-coding RNA Research

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The physiological processes of cells and organisms are regulated by various biological macromolecules, including long-noncoding RNAs (lncRNAs), which cannot be translated into protein and are different from small-noncoding RNAs on their length. In animals, lncRNAs are involved in development, metabolism, reproduction, aging and other life events by cis or trans effects. For many functional lncRNAs, there is growing evidence that they play different roles on cellular level and organismal level. On the other hand, many annotated lncRNAs are not essential and could be transcription noises. In this minireview, we investigate the physiological function of lncRNAs in cells and focus on their functions and functional mechanisms on the organismal level. The studies on lncRNAs using different classic animal models such as worms and flies are summarized and discussed in this article.

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SARS-CoV-2 gene content and COVID-19 mutation impact by comparing 44 Sarbecovirus genomes

2021

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Despite its clinical importance, the SARS-CoV-2 gene set remains unresolved, hindering dissection of COVID-19 biology. We use comparative genomics to provide a high-confidence protein-coding gene set, characterize evolutionary constraint, and prioritize functional mutations. We select 44 Sarbecovirus genomes at ideally-suited evolutionary distances, and quantify protein-coding evolutionary signatures and overlapping constraint. We find strong protein-coding signatures for ORFs 3a, 6, 7a, 7b, 8, 9b, and a novel alternate-frame gene, ORF3c, whereas ORFs 2b, 3d/3d-2, 3b, 9c, and 10 lack protein-coding signatures or convincing experimental evidence of protein-coding function. Furthermore, we show no other conserved protein-coding genes remain to be discovered. Mutation analysis suggests ORF8 contributes to within-individual fitness but not person-to-person transmission. Cross-strain and within-strain evolutionary pressures agree, except for fewer-than-expected within-strain mutations in nsp3 and S1, and more-than-expected in nucleocapsid, which shows a cluster of mutations in a predicted B-cell epitope, suggesting immune-avoidance selection. Evolutionary histories of residues disrupted by spike-protein substitutions D614G, N501Y, E484K, and K417N/T provide clues about their biology, and we catalog likely-functional co-inherited mutations. Previously reported RNA-modification sites show no enrichment for conservation. Here we report a high-confidence gene set and evolutionary-history annotations providing valuable resources and insights on SARS-CoV-2 biology, mutations, and evolution.

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A gene expression atlas of embryonic neurogenesis inDrosophilareveals complex spatiotemporal regulation of lncRNAs

Cited by 8 publications

References 62 publications

Transcriptional dynamics of microRNAs and their targets during Drosophila neurogenesis

Transcriptional dynamics of microRNAs and their targets during Drosophila neurogenesis

The physiological function of long-noncoding RNAs

SARS-CoV-2 gene content and COVID-19 mutation impact by comparing 44 Sarbecovirus genomes

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