Biochemical and functional analysis of a 9-nt RNA sequence that affects translation efficiency in eukaryotic cells is a research paper published in Proceedings of the National Academy of Sciences (2004). On theSindex it has a DataRank of 2.4. It has been cited 48 times, with 40 citing works in its 1-hop citation network.
We previously identified an internal ribosome entry site (IRES) within the 5′ leader of the mRNA encoding the Gtx homeodomain protein and showed that shorter nonoverlapping segments of this 5′ leader could enhance the translation of a second cistron in a dicistronic mRNA. One of these segments was 9 nt in length, and when multiple copies of this IRES module were linked together, IRES activity was greatly enhanced. To further expand the potential uses of these synthetic constructs and facilitate analyses of the mechanism by which they affect translation, we show here that an IRES containing five linked copies of the 9-nt sequence can also enhance translation in the 5′ leader of a monocistronic mRNA. Moreover, a search for interactions of the IRES module with cellular factors revealed specific binding to 40S ribosomal subunits but not to other cellular components. Based on the results of earlier studies suggesting that this sequence could bind to a complementary segment of 18S rRNA, we tested various sequences for possible links between the length of the complementary match, their binding to ribosomes, and their influence on translational efficiency. We found that the length of the complementary match was directly correlated with the ability of RNA probes to bind to ribosomes. In addition, translation was maximally enhanced (≈8-fold) by a 7-nt segment of the 9-nt element; the enhancement declined progressively as the complementary stretches became progressively longer or shorter. The results suggest that the Gtx 9-nt sequence affects translation efficiency by a mechanism that involves base pairing to 18S rRNA.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.584
From this paper's citation signal
Citation Network Contribution
1.8
From 37 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 24% comes from its base citations and 76% from the citation network (37 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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