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Creators/Authors contains: "Subramanian, Krishnamurthy"

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  1. Van De Peer, Yves (Ed.)
    Abstract Analyses in a number of organisms have shown that duplicated genes are less likely to be essential than singletons. This implies that genes can often compensate for the loss of their paralogs. However, it is unclear why the loss of some duplicates can be compensated by their paralogs, whereas the loss of other duplicates cannot. Surprisingly, initial analyses in mice did not detect differences in the essentiality of duplicates and singletons. Only subsequent analyses, using larger gene knockout data sets and controlling for a number of confounding factors, did detect significant differences. Previous studies have not taken into account the tissues in which duplicates are expressed. We hypothesized that in complex organisms, in order for a gene’s loss to be compensated by one or more of its paralogs, such paralogs need to be expressed in at least the same set of tissues as the lost gene. To test our hypothesis, we classified mouse duplicates into two categories based on the expression patterns of their paralogs: “compensable duplicates” (those with paralogs expressed in all the tissues in which the gene is expressed) and “noncompensable duplicates” (those whose paralogs are not expressed in all the tissues where the gene is expressed). In agreement with our hypothesis, the essentiality of noncompensable duplicates is similar to that of singletons, whereas compensable duplicates exhibit a substantially lower essentiality. Our results imply that duplicates can often compensate for the loss of their paralogs, but only if they are expressed in the same tissues. Indeed, the compensation ability is more dependent on expression patterns than on protein sequence similarity. The existence of these two kinds of duplicates with different essentialities, which has been overlooked by prior studies, may have hindered the detection of differences between singletons and duplicates. 
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  2. Saitou, Naruya (Ed.)
    Abstract We present the Codon Statistics Database, an online database that contains codon usage statistics for all the species with reference or representative genomes in RefSeq (over 15,000). The user can search for any species and access two sets of tables. One set lists, for each codon, the frequency, the Relative Synonymous Codon Usage, and whether the codon is preferred. Another set of tables lists, for each gene, its GC content, Effective Number of Codons, Codon Adaptation Index, and frequency of optimal codons. Equivalent tables can be accessed for (1) all nuclear genes, (2) nuclear genes encoding ribosomal proteins, (3) mitochondrial genes, and (4) chloroplast genes (if available in the relevant assembly). The user can also search for any taxonomic group (e.g., “primates”) and obtain a table comparing all the species in the group. The database is free to access without registration at http://codonstatsdb.unr.edu. 
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