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Amelia F. Alessi

Researcher at Johns Hopkins University

Publications -  9
Citations -  410

Amelia F. Alessi is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Cell fate determination & Caenorhabditis elegans. The author has an hindex of 6, co-authored 8 publications receiving 274 citations. Previous affiliations of Amelia F. Alessi include University of Michigan.

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The Caenorhabditis elegans HEN1 Ortholog, HENN-1, Methylates and Stabilizes Select Subclasses of Germline Small RNAs

TL;DR: The worm HEN1 ortholog, HENN-1 (HEN of Nematode), is required for methylation of piRNAs and some endogenous and exogenous small interfering RNAs, and these findings support a model wherein methylation status of a metazoan small RNA is dictated by the Argonaute to which it binds.
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FUS Regulates Activity of MicroRNA-Mediated Gene Silencing

TL;DR: F fused in sarcoma (FUS), an RNA-binding protein linked to neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), interacts with the core miRISC component AGO2 and is required for optimal microRNA-mediated gene silencing.
Journal ArticleDOI

The full-length transcriptome of C. elegans using direct RNA sequencing.

TL;DR: N nanopore-based direct RNA sequencing is applied to characterize the developmental polyadenylated transcriptome of C. elegans, providing support for 23,865 splice isoforms across 14,611 genes, without the need for computational reconstruction of gene models and determining that poly(A) tail lengths of transcripts vary across development, as do the strengths of previously reported correlations between poly( A) tail length and expression level.
Posted ContentDOI

The full-length transcriptome of C. elegans using direct RNA sequencing

TL;DR: N nanopore-based direct RNA sequencing is applied to characterize the developmental polyadenylated transcriptome of C. elegans, providing support for 20,902 splice isoforms across 14,115 genes, without the need for computational reconstruction of gene models and determining that poly(A) tail lengths of transcripts vary across development, as do the strengths of previously reported correlations between poly( A) tail length and expression level.