THE UNIGENE-BASED SKELETAL MUSCLE TRANSCRIPTIONAL PROFILE
Released July, 9th, 1999
The human skeletal muscle trancriptional
profile. To analyze
activity of the skeletal muscle human tissue, the number of ESTs
each UniGene entry, found in the considered cDNA libraries were counted,
on the assumption that the larger is the number of skeletal muscle ESTs
per entry, the more active should be in the tissue the corresponding gene.
This number represents the best available estimate of the abundance of each
individual transcript in the skeletal muscle mRNA population and it is
here as "level of expression" of each gene. The relative contribution
of a given gene to the skeletal muscle transcriptional activity is
by the ratio between the number of ESTs corresponding to that gene
and the total number of ESTs corresponding to all the genes included
in the data set.
Expression of skeletal muscle genes in other tissues. The
presence of skeletal muscle genes
in other human tissues was assessed by considering each UniGene entry
belonging to the data set and by recording in which additional tissues
the ESTs reported in that particular entry were found.
Data retrieval. The retrieval of UniGene entries belonging to
most copious not normalized nor subtracted cDNA libraries from normal
adult skeletal muscle (Lib.24, Lib.272 and Lib.500) produced a
set of 4,080 putative unique human genes.
The catalogue of these 4,080 genes, including both the
gene transcripts and transcripts expressed as well in other tissues,
provides the best representation of the transcriptome of the
according to available information.
The catalogue of 4,080 genes or ESTs
reported in UniGene as belonging
to cDNA libraries from skeletal muscle is provided. Each entry is shown
with UniGene ID, gene description, estimated level of expression in
skeletal muscle and information on expression in additional human
Reference Bortoluzzi S., d'Alessi F., Romualdi C., Danieli G.A.,
"The Human Adult Skeletal Muscle Transcriptional Profile reconstructed
by a novel computational approach", Genome Research 10: 344-349 2000.
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