Prediction of the coding sequences of unidentified human genes. XX. The complete sequences of 100 new cDNA clones from brain which code for large proteins in vitro.

To accumulate information on the coding sequences of unidentified genes, we have carried out a sequencing project of human cDNA clones which encode large proteins. We herein present the entire sequences of 100 cDNA clones of unidentified human genes, named KIAA1776 and KIAA1780-KIAA1878, from size-fractionated cDNA libraries derived from human fetal brain, adult whole brain, hippocampus and amygdala. Most of the cDNA clones to be entirely sequenced were selected as cDNAs which were shown to have coding potentiality by in vitro transcription/translation experiments, and some clones were chosen by using computer-assisted analysis of terminal sequences of cDNAs. Three of these clones (fibrillin2/KIAA1776, MEGF10/KIAA1780 and MEGF11/KIAA1781) were isolated as genes encoding proteins with multiple EGF-like domains by motif-trap screening. The average sizes of the inserts and corresponding open reading frames of eDNA clones analyzed here reached 4.7 kb and 2.4 kb (785 amino acid residues), respectively. From the results of homology and motif searches against the public databases, the functional categories of the predicted gene products of 54 genes were determined; 93% of these predicted gene products (50 gene products) were classified as proteins related to cell signaling/communication, nucleic acid management, or cell structure/motility. To collect additional information on these genes, their expression profiles were also studied in 10 human tissues, 8 brain regions, spinal cord, fetal brain and fetal liver by reverse transcription-coupled polymerase chain reaction, products of which were quantified by enzyme-linked immunosorbent assay.

• Publication year

  2001

• Venue

  DNA Research

• Publication date

  Unknown publication date

• Fields of study

  Biology, Medicine

• Identifiers
  DOI 10.1093/DNARES/8.2.85PMID 11347906
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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