Transcript isoforms of Reep6 have distinct functions in the retina is a research paper published in Human Molecular Genetics (2021). On theSindex it has a DataRank of 0.522. It has been cited 11 times, with 10 citing works in its 1-hop citation network.
Abstract Much of the complexity of the eukaryotic cell transcriptome is due to the alternative splicing of mRNA. However, knowledge on how transcriptome complexity is translated into functional complexity remains limited. For example, although different isoforms of a gene may show distinct temporal and spatial expression patterns, it is largely unknown whether these isoforms encode proteins with distinct functions matching their expression pattern. In this report, we investigated the function and relationship of the two isoforms of Reep6, namely Reep6.1 and Reep6.2, in rod photoreceptor cells. These two isoforms result from the alternative splicing of exon 5 and show mutually exclusive expression patterns. Reep6.2 is the canonical isoform that is expressed in non-retinal tissues, whereas Reep6.1 is the only expressed isoform in the adult retina. The Reep6.1 isoform-specific knockout mouse, Reep6E5/E5, is generated by deleting exon 5 and a homozygous deletion phenotypically displayed a rod degeneration phenotype comparable to a Reep6 full knockout mouse, indicating that the Reep6.1 isoform is essential for the rod photoreceptor cell survival. Consistent with the results obtained from a loss-of-function experiment, overexpression of Reep6.2 failed to rescue the rod degeneration phenotype of Reep6 knockout mice whereas overexpression of Reep6.1 does lead to rescue. These results demonstrate that, consistent with the expression pattern of the isoform, Reep6.1 has rod-specific functions that cannot be substituted by its canonical isoform. Our findings suggested that a strict regulation of splicing is required for the maintenance of photoreceptor cells.
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Base Score Contribution
0.373
From this paper's citation signal
Citation Network Contribution
0.150
From 7 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 71% comes from its base citations and 29% from the citation network (7 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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