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A new rhesus macaque assembly and annotation for next-generation sequencing analyses.

Zimin AV, Cornish AS, Maudhoo MD, Gibbs RM, Zhang X, Pandey S, Meehan DT, Wipfler K, Bosinger SE, Johnson ZP, Tharp GK, Marçais G, Roberts M, Ferguson B, Fox HS, Treangen T, Salzberg SL, Yorke JA, Norgren RB - Biol. Direct (2014)

Bottom Line: Further, we demonstrate that the new annotations provide greatly improved accuracy as compared to the current annotations of rheMac2.The MacaM assembly and annotation files provide a substantially more complete and accurate representation of the rhesus macaque genome than rheMac2 or CR_1.0 and will serve as an important resource for investigators conducting next-generation sequencing studies with nonhuman primates.This article was reviewed by Dr. Lutz Walter, Dr. Soojin Yi and Dr. Kateryna Makova.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, Nebraska 68198, USA. rnorgren@unmc.edu.

ABSTRACT

Background: The rhesus macaque (Macaca mulatta) is a key species for advancing biomedical research. Like all draft mammalian genomes, the draft rhesus assembly (rheMac2) has gaps, sequencing errors and misassemblies that have prevented automated annotation pipelines from functioning correctly. Another rhesus macaque assembly, CR_1.0, is also available but is substantially more fragmented than rheMac2 with smaller contigs and scaffolds. Annotations for these two assemblies are limited in completeness and accuracy. High quality assembly and annotation files are required for a wide range of studies including expression, genetic and evolutionary analyses.

Results: We report a new de novo assembly of the rhesus macaque genome (MacaM) that incorporates both the original Sanger sequences used to assemble rheMac2 and new Illumina sequences from the same animal. MacaM has a weighted average (N50) contig size of 64 kilobases, more than twice the size of the rheMac2 assembly and almost five times the size of the CR_1.0 assembly. The MacaM chromosome assembly incorporates information from previously unutilized mapping data and preliminary annotation of scaffolds. Independent assessment of the assemblies using Ion Torrent read alignments indicates that MacaM is more complete and accurate than rheMac2 and CR_1.0. We assembled messenger RNA sequences from several rhesus tissues into transcripts which allowed us to identify a total of 11,712 complete proteins representing 9,524 distinct genes. Using a combination of our assembled rhesus macaque transcripts and human transcripts, we annotated 18,757 transcripts and 16,050 genes with complete coding sequences in the MacaM assembly. Further, we demonstrate that the new annotations provide greatly improved accuracy as compared to the current annotations of rheMac2. Finally, we show that the MacaM genome provides an accurate resource for alignment of reads produced by RNA sequence expression studies.

Conclusions: The MacaM assembly and annotation files provide a substantially more complete and accurate representation of the rhesus macaque genome than rheMac2 or CR_1.0 and will serve as an important resource for investigators conducting next-generation sequencing studies with nonhuman primates.

Reviewers: This article was reviewed by Dr. Lutz Walter, Dr. Soojin Yi and Dr. Kateryna Makova.

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mRNA expression validation. We sequenced RNA from 60 rhesus macaque PBMC samples of differing ranks using Illumina paired end sequencing. After filtering, we mapped reads to either the MacaM (green symbols) or rheMac2 (blue symbols) assemblies using the STAR algorithm; we used CUFFLINKS to assign transcripts and determine differentially expressed genes (DEGs). (A) Number of uniquely mapping reads in individual RNA samples mapped using the MacaM and rheMac2 assemblies. Individual samples mapped by either assembly are joined by lines. (B) Percentage of total filtered reads that uniquely mapped to each assembly. (C) Number of DEGs that were identified using CUFFDIFF2.1 for dominant animals at two time points using the MacaM and rheMac2 genomes.
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Figure 4: mRNA expression validation. We sequenced RNA from 60 rhesus macaque PBMC samples of differing ranks using Illumina paired end sequencing. After filtering, we mapped reads to either the MacaM (green symbols) or rheMac2 (blue symbols) assemblies using the STAR algorithm; we used CUFFLINKS to assign transcripts and determine differentially expressed genes (DEGs). (A) Number of uniquely mapping reads in individual RNA samples mapped using the MacaM and rheMac2 assemblies. Individual samples mapped by either assembly are joined by lines. (B) Percentage of total filtered reads that uniquely mapped to each assembly. (C) Number of DEGs that were identified using CUFFDIFF2.1 for dominant animals at two time points using the MacaM and rheMac2 genomes.

Mentions: To compare the performance of the rheMac2 and MacaM genomes on a ‘real-world’ mRNA-seq dataset, we examined the effects of an acute stressor on a background of chronic stress in social-housed female rhesus macaques. Social subordination in macaques is a natural stressor that produces distinct stress-related phenotypes and chronically stressed subordinate subjects [40]. We drew blood from both dominant and subordinate animals; following this, we exposed both to an acute stressor (human intruder paradigm [41]) and then drew blood at different time points after exposure. mRNA-seq read-mapping was significantly higher with MacaM as compared to rheMac2 (mean 3.1 × 107 vs. 2.6 × 107, p <0.0001) (Figure 4A). Similarly, mRNA-seq read-mapping percentages were significantly higher using the MacaM assembly than the rheMac2 assembly (mean 85.2% vs. 70.0%, p <0.0001 (Figure 4B). When we compared mRNA expression levels with one set of animals at two time points (Figure 4C), we detected many more Differentially Expressed Genes (DEGs) with the MacM genome than with rheMac2. We observed this same pattern in 8 additional comparisons (Figure 5).


A new rhesus macaque assembly and annotation for next-generation sequencing analyses.

Zimin AV, Cornish AS, Maudhoo MD, Gibbs RM, Zhang X, Pandey S, Meehan DT, Wipfler K, Bosinger SE, Johnson ZP, Tharp GK, Marçais G, Roberts M, Ferguson B, Fox HS, Treangen T, Salzberg SL, Yorke JA, Norgren RB - Biol. Direct (2014)

mRNA expression validation. We sequenced RNA from 60 rhesus macaque PBMC samples of differing ranks using Illumina paired end sequencing. After filtering, we mapped reads to either the MacaM (green symbols) or rheMac2 (blue symbols) assemblies using the STAR algorithm; we used CUFFLINKS to assign transcripts and determine differentially expressed genes (DEGs). (A) Number of uniquely mapping reads in individual RNA samples mapped using the MacaM and rheMac2 assemblies. Individual samples mapped by either assembly are joined by lines. (B) Percentage of total filtered reads that uniquely mapped to each assembly. (C) Number of DEGs that were identified using CUFFDIFF2.1 for dominant animals at two time points using the MacaM and rheMac2 genomes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4214606&req=5

Figure 4: mRNA expression validation. We sequenced RNA from 60 rhesus macaque PBMC samples of differing ranks using Illumina paired end sequencing. After filtering, we mapped reads to either the MacaM (green symbols) or rheMac2 (blue symbols) assemblies using the STAR algorithm; we used CUFFLINKS to assign transcripts and determine differentially expressed genes (DEGs). (A) Number of uniquely mapping reads in individual RNA samples mapped using the MacaM and rheMac2 assemblies. Individual samples mapped by either assembly are joined by lines. (B) Percentage of total filtered reads that uniquely mapped to each assembly. (C) Number of DEGs that were identified using CUFFDIFF2.1 for dominant animals at two time points using the MacaM and rheMac2 genomes.
Mentions: To compare the performance of the rheMac2 and MacaM genomes on a ‘real-world’ mRNA-seq dataset, we examined the effects of an acute stressor on a background of chronic stress in social-housed female rhesus macaques. Social subordination in macaques is a natural stressor that produces distinct stress-related phenotypes and chronically stressed subordinate subjects [40]. We drew blood from both dominant and subordinate animals; following this, we exposed both to an acute stressor (human intruder paradigm [41]) and then drew blood at different time points after exposure. mRNA-seq read-mapping was significantly higher with MacaM as compared to rheMac2 (mean 3.1 × 107 vs. 2.6 × 107, p <0.0001) (Figure 4A). Similarly, mRNA-seq read-mapping percentages were significantly higher using the MacaM assembly than the rheMac2 assembly (mean 85.2% vs. 70.0%, p <0.0001 (Figure 4B). When we compared mRNA expression levels with one set of animals at two time points (Figure 4C), we detected many more Differentially Expressed Genes (DEGs) with the MacM genome than with rheMac2. We observed this same pattern in 8 additional comparisons (Figure 5).

Bottom Line: Further, we demonstrate that the new annotations provide greatly improved accuracy as compared to the current annotations of rheMac2.The MacaM assembly and annotation files provide a substantially more complete and accurate representation of the rhesus macaque genome than rheMac2 or CR_1.0 and will serve as an important resource for investigators conducting next-generation sequencing studies with nonhuman primates.This article was reviewed by Dr. Lutz Walter, Dr. Soojin Yi and Dr. Kateryna Makova.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, Nebraska 68198, USA. rnorgren@unmc.edu.

ABSTRACT

Background: The rhesus macaque (Macaca mulatta) is a key species for advancing biomedical research. Like all draft mammalian genomes, the draft rhesus assembly (rheMac2) has gaps, sequencing errors and misassemblies that have prevented automated annotation pipelines from functioning correctly. Another rhesus macaque assembly, CR_1.0, is also available but is substantially more fragmented than rheMac2 with smaller contigs and scaffolds. Annotations for these two assemblies are limited in completeness and accuracy. High quality assembly and annotation files are required for a wide range of studies including expression, genetic and evolutionary analyses.

Results: We report a new de novo assembly of the rhesus macaque genome (MacaM) that incorporates both the original Sanger sequences used to assemble rheMac2 and new Illumina sequences from the same animal. MacaM has a weighted average (N50) contig size of 64 kilobases, more than twice the size of the rheMac2 assembly and almost five times the size of the CR_1.0 assembly. The MacaM chromosome assembly incorporates information from previously unutilized mapping data and preliminary annotation of scaffolds. Independent assessment of the assemblies using Ion Torrent read alignments indicates that MacaM is more complete and accurate than rheMac2 and CR_1.0. We assembled messenger RNA sequences from several rhesus tissues into transcripts which allowed us to identify a total of 11,712 complete proteins representing 9,524 distinct genes. Using a combination of our assembled rhesus macaque transcripts and human transcripts, we annotated 18,757 transcripts and 16,050 genes with complete coding sequences in the MacaM assembly. Further, we demonstrate that the new annotations provide greatly improved accuracy as compared to the current annotations of rheMac2. Finally, we show that the MacaM genome provides an accurate resource for alignment of reads produced by RNA sequence expression studies.

Conclusions: The MacaM assembly and annotation files provide a substantially more complete and accurate representation of the rhesus macaque genome than rheMac2 or CR_1.0 and will serve as an important resource for investigators conducting next-generation sequencing studies with nonhuman primates.

Reviewers: This article was reviewed by Dr. Lutz Walter, Dr. Soojin Yi and Dr. Kateryna Makova.

Show MeSH