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Increased alignment sensitivity improves the usage of genome alignments for comparative gene annotation

Sharma, Virag, Hiller, Michael·2017·Nucleic Acids Research
DOI 10.1093/nar/gkx554PMC PMC5737078
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Figure 1. Alignment parameter sensitivity is crucial to align exons to their orthologous genomic locus. (A) UCSC genome browser screenshot showing the CATSPERD (cation channel sperm associated auxiliary subunit delta) gene locus in the human genome and genome alignments (chains of co-linear local alignments) to opossum computed with three different parameter sets (see text). Several exons of this gene only align to the opossum ortholog with more sensitive parameters (blue boxes) or using a subsequent round of highly sensitive alignments in addition (red boxes). (B–D) Three examples of local alignments covering exons of CATSPERD. Exonic bases are in upper case, intronic bases are in lower case.
Figure 1. Alignment parameter sensitivity is crucial to align exons to their orthologous genomic locus. (A) UCSC genome browser screenshot showing the CATSPERD (cation channel sperm associated auxiliary subunit delta) gene locus in the human genome and genome alignments (chains of co-linear local alignments) to opossum computed with three different parameter sets (see text). Several exons of this gene only align to the opossum ortholog with more sensitive parameters (blue boxes) or using a subsequent round of highly sensitive alignments in addition (red boxes). (B–D) Three examples of local alignments covering exons of CATSPERD. Exonic bases are in upper case, intronic bases are in lower case.CC BY-NC · PubMed Central
Figure 2. Sensitive alignment parameters can uncover thousands of new alignments between exons of orthologous genes. The figure compares the number of exons that align between orthologous genes for nine species at various evolutionary distances to human (axis at the bottom). Three alignment parameter sets were tested that differ in their sensitivity. The Y-axis shows the percent increase relative to the number of aligning exons with parameter set 1. The absolute number of aligning exons with parameter set 1 is given below the black dots, the absolute increase obtained with parameter set 2 and 3 is given alongside or above the black dots.
Figure 2. Sensitive alignment parameters can uncover thousands of new alignments between exons of orthologous genes. The figure compares the number of exons that align between orthologous genes for nine species at various evolutionary distances to human (axis at the bottom). Three alignment parameter sets were tested that differ in their sensitivity. The Y-axis shows the percent increase relative to the number of aligning exons with parameter set 1. The absolute number of aligning exons with parameter set 1 is given below the black dots, the absolute increase obtained with parameter set 2 and 3 is given alongside or above the black dots.CC BY-NC · PubMed Central
Figure 3. Highly sensitive alignment parameters detect additional alignments between human and non-mammalian vertebrates. UCSC genome browser screenshots compare the UCSC 100-way alignment (27) with our 144-vertebrate alignment for two genomic loci (A and B). Aligning sequence is visualized by black and grey boxes. The darker the color of the box, the higher is the sequence similarity in the alignment. Double horizontal lines indicate sequence that does not align between the reference (human) and the query species. Yellow background indicates regions where exon alignments can only be detected with sensitive parameters in our 144-way alignment. Orange background indicates additional non-exonic conserved regions. For visualization, only a subset of all 70 non-mammalian vertebrates is shown. (C) Representative additional exon alignment between human and frog that was only detected with highly-sensitive parameters (marked with a star in B).
Figure 3. Highly sensitive alignment parameters detect additional alignments between human and non-mammalian vertebrates. UCSC genome browser screenshots compare the UCSC 100-way alignment (27) with our 144-vertebrate alignment for two genomic loci (A and B). Aligning sequence is visualized by black and grey boxes. The darker the color of the box, the higher is the sequence similarity in the alignment. Double horizontal lines indicate sequence that does not align between the reference (human) and the query species. Yellow background indicates regions where exon alignments can only be detected with sensitive parameters in our 144-way alignment. Orange background indicates additional non-exonic conserved regions. For visualization, only a subset of all 70 non-mammalian vertebrates is shown. (C) Representative additional exon alignment between human and frog that was only detected with highly-sensitive parameters (marked with a star in B).CC BY-NC · PubMed Central
Figure 4. Comparative gene annotation in 143 vertebrate genomes. The X-axis shows the proportion of human exons (red circles) and genes for which CESAR annotated at least one exon (blue triangle) in 73 mammals (A) and 70 non-mammalian vertebrates (B). Species in blue font are not contained in the UCSC 100-way or primate alignment.
Figure 4. Comparative gene annotation in 143 vertebrate genomes. The X-axis shows the proportion of human exons (red circles) and genes for which CESAR annotated at least one exon (blue triangle) in 73 mammals (A) and 70 non-mammalian vertebrates (B). Species in blue font are not contained in the UCSC 100-way or primate alignment.CC BY-NC · PubMed Central
Figure 5. Increased alignment sensitivity detects thousands of additional conserved exons and hundreds of conserved genes between evolutionarily distant species. The figure shows the absolute number of exons (A) and genes (B) that are additionally annotated using our 144-vertebrate alignment, compared to the UCSC 100-way alignment. Only species for which the same assembly is included in both genome alignments are shown. Major clades are highlighted. Wallaby, parrot, scarlet macaw and spiny softshell turtle that have rather incomplete and fragmented genome assemblies are the only species were fewer exons or genes are annotated in our alignment. The reason is that fragmented assemblies result in short and low-scoring co-linear alignments that can be discarded by our more stringent filtering thresholds (see Methods). Manual inspection shows that such short co-linear alignments include paralogous gene alignments that would lead to incorrect gene annotations (Supplementary Figure S1). Given that our approach provides a consistent improvement in comparative gene annotation, better genome assemblies should substantially improve the gene annotation of these four species.
Figure 5. Increased alignment sensitivity detects thousands of additional conserved exons and hundreds of conserved genes between evolutionarily distant species. The figure shows the absolute number of exons (A) and genes (B) that are additionally annotated using our 144-vertebrate alignment, compared to the UCSC 100-way alignment. Only species for which the same assembly is included in both genome alignments are shown. Major clades are highlighted. Wallaby, parrot, scarlet macaw and spiny softshell turtle that have rather incomplete and fragmented genome assemblies are the only species were fewer exons or genes are annotated in our alignment. The reason is that fragmented assemblies result in short and low-scoring co-linear alignments that can be discarded by our more stringent filtering thresholds (see Methods). Manual inspection shows that such short co-linear alignments include paralogous gene alignments that would lead to incorrect gene annotations (Supplementary Figure S1). Given that our approach provides a consistent improvement in comparative gene annotation, better genome assemblies should substantially improve the gene annotation of these four species.CC BY-NC · PubMed Central

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Citations

Cites

Research works printed but not linked: 31

  1. 2010, Computational methods for ab initio and comparative gene finding, Methods Mol. Biol., 609, 269, 10.1007/978-1-60327-241-4_16 · DOI
  2. 1997, Prediction of complete gene structures in human genomic DNA, J. Mol. Biol., 268, 78, 10.1006/jmbi.1997.0951 · DOI
  3. 2000, GeneID in Drosophila, Genome Res., 10, 511, 10.1101/gr.10.4.511 · DOI
  4. 2003, Gene prediction with a hidden Markov model and a new intron submodel, Bioinformatics, 19, ii215
  5. 2004, GeneWise and genomewise, Genome Res., 14, 988, 10.1101/gr.1865504 · DOI · Paper page
  6. 2004, Proc. 8th Int’l Conf. on Research in Computational Molecular Biology, 177
  7. 2006, Using multiple alignments to improve gene prediction, J. Comput. Biol., 13, 379, 10.1089/cmb.2006.13.379 · DOI
  8. 2008, Direct mapping and alignment of protein sequences onto genomic sequence, Bioinformatics, 24, 2438, 10.1093/bioinformatics/btn460 · DOI
  9. 2008, MAKER: an easy-to-use annotation pipeline designed for emerging model organism genomes, Genome Res., 18, 188, 10.1101/gr.6743907 · DOI
  10. 2006, Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources, BMC Bioinformatics, 7, 62, 10.1186/1471-2105-7-62 · DOI · Paper page
  11. 2008, Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments, Genome Biol., 9, R7, 10.1186/gb-2008-9-1-r7 · DOI
  12. 2007, Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures, Nature, 450, 219, 10.1038/nature06340 · DOI
  13. 2007, Comparative genomics search for losses of long-established genes on the human lineage, PLoS Comput. Biol., 3, e247, 10.1371/journal.pcbi.0030247 · DOI · Paper page
  14. 2008, Using native and syntenically mapped cDNA alignments to improve de novo gene finding, Bioinformatics, 24, 637, 10.1093/bioinformatics/btn013 · DOI · Paper page
  15. 2005, Distribution and intensity of constraint in mammalian genomic sequence, Genome Res., 15, 901, 10.1101/gr.3577405 · DOI · Paper page
  16. 2016, Coding exon-structure aware realigner (CESAR) utilizes genome alignments for accurate comparative gene annotation, Nucleic Acids Res., 44, e103, 10.1093/nar/gkw210 · DOI · Paper page
  17. 2003, Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes, Proc. Natl. Acad. Sci. U.S.A., 100, 11484, 10.1073/pnas.1932072100 · DOI · Paper page
  18. 2013, Computational methods to detect conserved non-genic elements in phylogenetically isolated genomes: application to zebrafish, Nucleic Acids Res., 41, e151, 10.1093/nar/gkt557 · DOI · Paper page
  19. 2011, Ensembl BioMarts: a hub for data retrieval across taxonomic space, Database, 2011, bar030
  20. 2016, Ensembl comparative genomics resources, Database, 2016, bav096, 10.1093/database/bav096 · DOI
  21. 2004, Aligning multiple genomic sequences with the threaded blockset aligner, Genome Res., 14, 708, 10.1101/gr.1933104 · DOI · Paper page
  22. 2011, PHAST and RPHAST: phylogenetic analysis with space/time models, Brief. Bioinform., 12, 41, 10.1093/bib/bbq072 · DOI · Paper page
  23. 2016, The UCSC Genome Browser database: 2017 update, Nucleic Acids Res., 45, D626
  24. 2015, The UCSC Genome Browser database: 2015 update, Nucleic Acids Res., 43, D670, 10.1093/nar/gku1177 · DOI
  25. 2016, The UCSC Genome Browser database: 2016 update, Nucleic Acids Res., 44, D717, 10.1093/nar/gkv1275 · DOI
  26. 2017, chainCleaner improves genome alignment specificity and sensitivity, Bioinformatics, 33, 1596, 10.1093/bioinformatics/btx024 · DOI
  27. 2014, Track data hubs enable visualization of user-defined genome-wide annotations on the UCSC Genome Browser, Bioinformatics, 30, 1003, 10.1093/bioinformatics/btt637 · DOI
  28. 2004, Reconstructing large regions of an ancestral mammalian genome in silico, Genome Res., 14, 2412, 10.1101/gr.2800104 · DOI
  29. 2006, Reconstructing contiguous regions of an ancestral genome, Genome Res., 16, 1557, 10.1101/gr.5383506 · DOI
  30. 2005, A model of the statistical power of comparative genome sequence analysis, PLoS Biol., 3, e10, 10.1371/journal.pbio.0030010 · DOI
  31. 2011, Locating protein-coding sequences under selection for additional, overlapping functions in 29 mammalian genomes, Genome Res., 21, 1916, 10.1101/gr.108753.110 · DOI

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Metadata

Authors
Sharma, V., & Hiller, M.
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2017-06-21
Volume
45
Issue
14
Pages
8369-8377
ISSN
  • 0305-1048
  • 1362-4962
DOI
10.1093/nar/gkx554
PMC
PMC5737078
Cited by
72
References
3
Language
en
Licence
creativecommons.org/licenses/by-nc/4.0/ (vor)

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