Gene Expression, Single Nucleotide Variant and Fusion Transcript Discovery in Archival Material from Breast Tumors
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{"title"=>"Gene expression, single nucleotide variant and fusion transcript discovery in archival material from breast tumors", "type"=>"journal", "authors"=>[{"first_name"=>"Nadine", "last_name"=>"Norton", "scopus_author_id"=>"56231551800"}, {"first_name"=>"Zhifu", "last_name"=>"Sun", "scopus_author_id"=>"7404240192"}, {"first_name"=>"Yan W.", "last_name"=>"Asmann", "scopus_author_id"=>"6505913007"}, {"first_name"=>"Daniel J.", "last_name"=>"Serie", "scopus_author_id"=>"57197834076"}, {"first_name"=>"Brian M.", "last_name"=>"Necela", "scopus_author_id"=>"6506798970"}, {"first_name"=>"Aditya", "last_name"=>"Bhagwate", "scopus_author_id"=>"56079363300"}, {"first_name"=>"Jin", "last_name"=>"Jen", "scopus_author_id"=>"7101875673"}, {"first_name"=>"Bruce W.", "last_name"=>"Eckloff", "scopus_author_id"=>"6602368942"}, {"first_name"=>"Krishna R.", "last_name"=>"Kalari", "scopus_author_id"=>"14828017500"}, {"first_name"=>"Kevin J.", "last_name"=>"Thompson", "scopus_author_id"=>"35335411600"}, {"first_name"=>"Jennifer M.", "last_name"=>"Carr", "scopus_author_id"=>"37046749200"}, {"first_name"=>"Jennifer M.", "last_name"=>"Kachergus", "scopus_author_id"=>"6505997179"}, {"first_name"=>"Xochiquetzal J.", "last_name"=>"Geiger", "scopus_author_id"=>"6507807661"}, {"first_name"=>"Edith A.", "last_name"=>"Perez", "scopus_author_id"=>"55416105700"}, {"first_name"=>"E. Aubrey", "last_name"=>"Thompson", "scopus_author_id"=>"56562355200"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pmid"=>"24278466", "pui"=>"372438043", "scopus"=>"2-s2.0-84896730409", "doi"=>"10.1371/journal.pone.0081925", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "sgr"=>"84896730409"}, "id"=>"62d76a41-d3da-311c-8f22-0afdfd91741d", "abstract"=>"Advantages of RNA-Seq over array based platforms are quantitative gene expression and discovery of expressed single nucleotide variants (eSNVs) and fusion transcripts from a single platform, but the sensitivity for each of these characteristics is unknown. We measured gene expression in a set of manually degraded RNAs, nine pairs of matched fresh-frozen, and FFPE RNA isolated from breast tumor with the hybridization based, NanoString nCounter (226 gene panel) and with whole transcriptome RNA-Seq using RiboZeroGold ScriptSeq V2 library preparation kits. We performed correlation analyses of gene expression between samples and across platforms. We then specifically assessed whole transcriptome expression of lincRNA and discovery of eSNVs and fusion transcripts in the FFPE RNA-Seq data. For gene expression in the manually degraded samples, we observed Pearson correlations of >0.94 and >0.80 with NanoString and ScriptSeq protocols, respectively. Gene expression data for matched fresh-frozen and FFPE samples yielded mean Pearson correlations of 0.874 and 0.783 for NanoString (226 genes) and ScriptSeq whole transcriptome protocols respectively, p<2x10-16 . Specifically for lincRNAs, we observed superb Pearson correlation (0.988) between matched fresh-frozen and FFPE pairs. FFPE samples across NanoString and RNA-Seq platforms gave a mean Pearson correlation of 0.838. In FFPE libraries, we detected 53.4% of high confidence SNVs and 24% of high confidence fusion transcripts. Sensitivity of fusion transcript detection was not overcome by an increase in depth of sequencing up to 3-fold (increase from ~56 to ~159 million reads). Both NanoString and ScriptSeq RNA-Seq technologies yield reliable gene expression data for degraded and FFPE material. The high degree of correlation between NanoString and RNA-Seq platforms suggests discovery based whole transcriptome studies from FFPE material will produce reliable expression data. The RiboZeroGold ScriptSeq protocol performed particularly well for lincRNA expression from FFPE libraries, but detection of eSNV and fusion transcripts was less sensitive.", "link"=>"http://www.mendeley.com/research/gene-expression-single-nucleotide-variant-fusion-transcript-discovery-archival-material-breast-tumor", "reader_count"=>35, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Researcher"=>9, "Student > Ph. D. Student"=>11, "Other"=>7, "Student > Master"=>5, "Student > Bachelor"=>1, "Lecturer"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Researcher"=>9, "Student > Ph. D. Student"=>11, "Other"=>7, "Student > Master"=>5, "Student > Bachelor"=>1, "Lecturer"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>7, "Agricultural and Biological Sciences"=>17, "Medicine and Dentistry"=>9, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>9}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>17}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>7}}, "reader_count_by_country"=>{"Australia"=>1, "Spain"=>1}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1293441"], "description"=>"<p>(A) % reads mapped to genome, genes and exon junctions, B) Venn diagram of fusion transcript detection, (C) Number SNV calls, (D) Correlation of FFPE library insert size with sensitivity for single nucleotide variant detection.</p>", "links"=>[], "tags"=>["mapped", "fusion", "esnv"], "article_id"=>860702, "categories"=>["Biological Sciences"], "users"=>["Nadine Norton", "Zhifu Sun", "Yan W. Asmann", "Daniel J. Serie", "Brian M. Necela", "Aditya Bhagwate", "Jin Jen", "Bruce W. Eckloff", "Krishna R. Kalari", "Kevin J. Thompson", "Jennifer M. Carr", "Jennifer M. Kachergus", "Xochiquetzal J. Geiger", "Edith A. Perez", "E. Aubrey Thompson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0081925.g003", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_RNA_Seq_Mapped_Reads_Fusion_and_eSNV_statistics_By_Protocol_/860702", "title"=>"RNA-Seq Mapped Reads, Fusion and eSNV statistics By Protocol.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-22 03:03:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/1293439"], "description"=>"<p>Log<sub>2</sub> gene expression for FFPE technical replicate with (A) NanoString platform and (B) RiboZeroGold ScriptSeq; (C) Gene expression correlation of nine FFPE samples across nanoString and RiboZeroGold ScriptSeq protocols. Gene expression correlation of nine fresh-frozen (FROZ) RNA samples across (D) nanoString and ScriptSeq, (E) nanoString and TruSeq and (F) RiboZeroGold ScriptSeq and TruSeq.</p>", "links"=>[], "tags"=>["replicates", "cross-platform"], "article_id"=>860700, "categories"=>["Biological Sciences"], "users"=>["Nadine Norton", "Zhifu Sun", "Yan W. Asmann", "Daniel J. Serie", "Brian M. Necela", "Aditya Bhagwate", "Jin Jen", "Bruce W. Eckloff", "Krishna R. Kalari", "Kevin J. Thompson", "Jennifer M. Carr", "Jennifer M. Kachergus", "Xochiquetzal J. Geiger", "Edith A. Perez", "E. Aubrey Thompson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0081925.g002", "stats"=>{"downloads"=>1, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Technical_Replicates_and_Cross_Platform_Correlations_/860700", "title"=>"Technical Replicates and Cross-Platform Correlations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-22 03:03:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/1293437"], "description"=>"<p>Nanostring correlation for (A) undegraded RNA against the same manually degraded sample (RIN=2.0); (B) log<sub>2</sub> fold change between two high quality RNAs and the same two samples when manually degraded (RIN 2.0); (C) nine matched fresh-frozen and FFPE pairs. ScriptSeq correlation for (D) undegraded RNA against the same manually degraded sample (RIN=2.0); (E) log<sub>2</sub> fold change between two high quality RNAs and the same two samples when manually degraded (RIN 2.0); (F) nine matched fresh-frozen and FFPE pairs.</p>", "links"=>[], "tags"=>["correlations", "scriptseq", "truseq"], "article_id"=>860698, "categories"=>["Biological Sciences"], "users"=>["Nadine Norton", "Zhifu Sun", "Yan W. Asmann", "Daniel J. Serie", "Brian M. Necela", "Aditya Bhagwate", "Jin Jen", "Bruce W. Eckloff", "Krishna R. Kalari", "Kevin J. Thompson", "Jennifer M. Carr", "Jennifer M. Kachergus", "Xochiquetzal J. Geiger", "Edith A. Perez", "E. Aubrey Thompson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0081925.g001", "stats"=>{"downloads"=>0, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Gene_Expression_correlations_with_Nanostring_ScriptSeq_And_TruSeq_platforms_/860698", "title"=>"Gene Expression correlations with Nanostring, ScriptSeq And TruSeq platforms.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-22 03:03:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/1293442", "https://ndownloader.figshare.com/files/1293443", "https://ndownloader.figshare.com/files/1293444", "https://ndownloader.figshare.com/files/1293445", "https://ndownloader.figshare.com/files/1293446", "https://ndownloader.figshare.com/files/1293447", "https://ndownloader.figshare.com/files/1293448", "https://ndownloader.figshare.com/files/1293449"], "description"=>"<div><p>Advantages of RNA-Seq over array based platforms are quantitative gene expression and discovery of expressed single nucleotide variants (eSNVs) and fusion transcripts from a single platform, but the sensitivity for each of these characteristics is unknown. We measured gene expression in a set of manually degraded RNAs, nine pairs of matched fresh-frozen, and FFPE RNA isolated from breast tumor with the hybridization based, NanoString nCounter (226 gene panel) and with whole transcriptome RNA-Seq using RiboZeroGold ScriptSeq V2 library preparation kits. We performed correlation analyses of gene expression between samples and across platforms. We then specifically assessed whole transcriptome expression of lincRNA and discovery of eSNVs and fusion transcripts in the FFPE RNA-Seq data. For gene expression in the manually degraded samples, we observed Pearson correlations of >0.94 and >0.80 with NanoString and ScriptSeq protocols, respectively. Gene expression data for matched fresh-frozen and FFPE samples yielded mean Pearson correlations of 0.874 and 0.783 for NanoString (226 genes) and ScriptSeq whole transcriptome protocols respectively, p<2x10<sup>-16</sup>. Specifically for lincRNAs, we observed superb Pearson correlation (0.988) between matched fresh-frozen and FFPE pairs. FFPE samples across NanoString and RNA-Seq platforms gave a mean Pearson correlation of 0.838. In FFPE libraries, we detected 53.4% of high confidence SNVs and 24% of high confidence fusion transcripts. Sensitivity of fusion transcript detection was not overcome by an increase in depth of sequencing up to 3-fold (increase from ~56 to ~159 million reads). Both NanoString and ScriptSeq RNA-Seq technologies yield reliable gene expression data for degraded and FFPE material. The high degree of correlation between NanoString and RNA-Seq platforms suggests discovery based whole transcriptome studies from FFPE material will produce reliable expression data. The RiboZeroGold ScriptSeq protocol performed particularly well for lincRNA expression from FFPE libraries, but detection of eSNV and fusion transcripts was less sensitive.</p> </div>", "links"=>[], "tags"=>["nucleotide", "variant", "fusion", "transcript", "archival"], "article_id"=>860703, "categories"=>["Biological Sciences"], "users"=>["Nadine Norton", "Zhifu Sun", "Yan W. Asmann", "Daniel J. Serie", "Brian M. Necela", "Aditya Bhagwate", "Jin Jen", "Bruce W. Eckloff", "Krishna R. Kalari", "Kevin J. Thompson", "Jennifer M. Carr", "Jennifer M. Kachergus", "Xochiquetzal J. Geiger", "Edith A. Perez", "E. Aubrey Thompson"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0081925.s001", "https://dx.doi.org/10.1371/journal.pone.0081925.s002", "https://dx.doi.org/10.1371/journal.pone.0081925.s003", "https://dx.doi.org/10.1371/journal.pone.0081925.s004", "https://dx.doi.org/10.1371/journal.pone.0081925.s005", "https://dx.doi.org/10.1371/journal.pone.0081925.s006", "https://dx.doi.org/10.1371/journal.pone.0081925.s007", "https://dx.doi.org/10.1371/journal.pone.0081925.s008"], "stats"=>{"downloads"=>16, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Gene_Expression_Single_Nucleotide_Variant_and_Fusion_Transcript_Discovery_in_Archival_Material_from_Breast_Tumors_/860703", "title"=>"Gene Expression, Single Nucleotide Variant and Fusion Transcript Discovery in Archival Material from Breast Tumors", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-11-22 03:03:47"}

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Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[269, 466, 588, 697, 800, 896, 988, 1076, 1165, 1254, 1340, 1417]}, {"subject_area"=>"/Biology and life sciences/Biochemistry", "average_usage"=>[266, 468, 593, 703, 804, 903, 993, 1084, 1171, 1256, 1339, 1422, 1492]}, {"subject_area"=>"/Biology and life sciences/Computational biology", "average_usage"=>[295, 511, 651, 775, 882, 992, 1100, 1201, 1304, 1400, 1486, 1570, 1650]}, {"subject_area"=>"/Biology and life sciences/Genetics", "average_usage"=>[284, 491, 620, 738, 843, 945, 1043, 1137, 1225, 1315, 1400, 1479, 1555]}]}
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