Dataset Information

Gene characterization index: assessing the depth of gene annotation.

ABSTRACT: We introduce the Gene Characterization Index, a bioinformatics method for scoring the extent to which a protein-encoding gene is functionally described. Inherently a reflection of human perception, the Gene Characterization Index is applied for assessing the characterization status of individual genes, thus serving the advancement of both genome annotation and applied genomics research by rapid and unbiased identification of groups of uncharacterized genes for diverse applications such as directed functional studies and delineation of novel drug targets.The scoring procedure is based on a global survey of researchers, who assigned characterization scores from 1 (poor) to 10 (extensive) for a sample of genes based on major online resources. By evaluating the survey as training data, we developed a bioinformatics procedure to assign gene characterization scores to all genes in the human genome. We analyzed snapshots of functional genome annotation over a period of 6 years to assess temporal changes reflected by the increase of the average Gene Characterization Index. Applying the Gene Characterization Index to genes within pharmaceutically relevant classes, we confirmed known drug targets as high-scoring genes and revealed potentially interesting novel targets with low characterization indexes. Removing known drug targets and genes linked to sequence-related patent filings from the entirety of indexed genes, we identified sets of low-scoring genes particularly suited for further experimental investigation.The Gene Characterization Index is intended to serve as a tool to the scientific community and granting agencies for focusing resources and efforts on unexplored areas of the genome. The Gene Characterization Index is available from http://cisreg.ca/gci/.

SUBMITTER: Kemmer D

PROVIDER: S-EPMC2194620 | biostudies-literature | 2008 Jan

REPOSITORIES: biostudies-literature

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Gene characterization index: assessing the depth of gene annotation.

Kemmer Danielle D Podowski Raf M RM Yusuf Dimas D Brumm Jochen J Cheung Warren W Wahlestedt Claes C Lenhard Boris B Wasserman Wyeth W WW

PloS one 20080123 1

<h4>Background</h4>We introduce the Gene Characterization Index, a bioinformatics method for scoring the extent to which a protein-encoding gene is functionally described. Inherently a reflection of human perception, the Gene Characterization Index is applied for assessing the characterization status of individual genes, thus serving the advancement of both genome annotation and applied genomics research by rapid and unbiased identification of groups of uncharacterized genes for diverse applicat ...[more]

PMID: 18213364

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Project description:Genome sequencing of Anopheles gambiae was completed more than ten years ago and has accelerated research on malaria transmission. However, annotation needs to be refined and verified experimentally, as most predicted transcripts have been identified by comparative analysis with genomes from other species. The mosquito midgut-the first organ to interact with Plasmodium parasites-mounts effective antiplasmodial responses that limit parasite survival and disease transmission. High-throughput Illumina sequencing of the midgut transcriptome was used to identify new genes and transcripts, contributing to the refinement of An. gambiae genome annotation.We sequenced ~223 million reads from An. gambiae midgut cDNA libraries generated from susceptible (G3) and refractory (L35) mosquito strains. Mosquitoes were infected with either Plasmodium berghei or Plasmodium falciparum, and midguts were collected after the first or second Plasmodium infection. In total, 22,889 unique midgut transcript models were generated from both An. gambiae strain sequences combined, and 76% are potentially novel. Of these novel transcripts, 49.5% aligned with annotated genes and appear to be isoforms or pre-mRNAs of reference transcripts, while 50.5% mapped to regions between annotated genes and represent novel intergenic transcripts (NITs). Predicted models were validated for midgut expression using qRT-PCR and microarray analysis, and novel isoforms were confirmed by sequencing predicted intron-exon boundaries. Coding potential analysis revealed that 43% of total midgut transcripts appear to be long non-coding RNA (lncRNA), and functional annotation of NITs showed that 68% had no homology to current databases from other species. Reads were also analyzed using de novo assembly and predicted transcripts compared with genome mapping-based models. Finally, variant analysis of G3 and L35 midgut transcripts detected 160,742 variants with respect to the An. gambiae PEST genome, and 74% were new variants. Intergenic transcripts had a higher frequency of variation compared with non-intergenic transcripts.This in-depth Illumina sequencing and assembly of the An. gambiae midgut transcriptome doubled the number of known transcripts and tripled the number of variants known in this mosquito species. It also revealed existence of a large number of lncRNA and opens new possibilities for investigating the biological function of many newly discovered transcripts.

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Gene characterization index: assessing the depth of gene annotation.

Publications

Gene characterization index: assessing the depth of gene annotation.

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