Dataset Information

Assessment and improvement of Indian-origin rhesus macaque and Mauritian-origin cynomolgus macaque genome annotations using deep transcriptome sequencing data.

ABSTRACT:

Background

The genome annotations of rhesus (Macaca mulatta) and cynomolgus (Macaca fascicularis) macaques, two of the most common non-human primate animal models, are limited.

Methods

We analyzed large-scale macaque RNA-based next-generation sequencing (RNAseq) data to identify un-annotated macaque transcripts.

Results

For both macaque species, we uncovered thousands of novel isoforms for annotated genes and thousands of un-annotated intergenic transcripts enriched with non-coding RNAs. We also identified thousands of transcript sequences which are partially or completely 'missing' from current macaque genome assemblies. We showed that many newly identified transcripts were differentially expressed during SIV infection of rhesus macaques or during Ebola virus infection of cynomolgus macaques.

Conclusions

For two important macaque species, we uncovered thousands of novel isoforms and un-annotated intergenic transcripts including coding and non-coding RNAs, polyadenylated and non-polyadenylated transcripts. This resource will greatly improve future macaque studies, as demonstrated by their applications in infectious disease studies.

SUBMITTER: Peng X

PROVIDER: S-EPMC4176519 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Until recently, few genomic reagents specific for non-human primate research have been available. To address this need, we have constructed a macaque-specific high-density oligonucleotide microarray by using highly fragmented low-pass sequence contigs from the rhesus genome project together with the detailed sequence and exon structure of the human genome. Using this method, we designed oligonucleotide probes to over 17,000 distinct rhesus/human gene orthologs and increased by four-fold the number of available genes relative to our first-generation expressed sequence tag (EST)-derived array.We constructed a database containing 248,000 exon sequences from 23,000 human RefSeq genes and compared each human exon with its best matching sequence in the January 2005 version of the rhesus genome project list of 486,000 DNA contigs. Best matching rhesus exon sequences for each of the 23,000 human genes were then concatenated in the proper order and orientation to produce a rhesus "virtual transcriptome." Microarray probes were designed, one per gene, to the region closest to the 3' untranslated region (UTR) of each rhesus virtual transcript. Each probe was compared to a composite rhesus/human transcript database to test for cross-hybridization potential yielding a final probe set representing 18,296 rhesus/human gene orthologs, including transcript variants, and over 17,000 distinct genes. We hybridized mRNA from rhesus brain and spleen to both the EST- and genome-derived microarrays. Besides four-fold greater gene coverage, the genome-derived array also showed greater mean signal intensities for genes present on both arrays. Genome-derived probes showed 99.4% identity when compared to 4,767 rhesus GenBank sequence tag site (STS) sequences indicating that early stage low-pass versions of complex genomes are of sufficient quality to yield valuable functional genomic information when combined with finished genome information from a closely related species.The number of different genes represented on microarrays for unfinished genomes can be greatly increased by matching known gene transcript annotations from a closely related species with sequence data from the unfinished genome. Signal intensity on both EST- and genome-derived arrays was highly correlated with probe distance from the 3' UTR, information often missing from ESTs yet present in early-stage genome projects.