Natural Variation in Fish Transcriptomes: Comparative Analysis of the Fathead Minnow (Pimephales promelas) and Zebrafish (Danio rerio)
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{"title"=>"Natural Variation in Fish Transcriptomes: Comparative Analysis of the Fathead Minnow (Pimephales promelas) and Zebrafish (Danio rerio)", "type"=>"journal", "authors"=>[{"first_name"=>"Rong-Lin", "last_name"=>"Wang"}, {"first_name"=>"David C.", "last_name"=>"Bencic"}, {"first_name"=>"Natàlia", "last_name"=>"Garcia-Reyero"}, {"first_name"=>"Edward J.", "last_name"=>"Perkins"}, {"first_name"=>"Daniel L.", "last_name"=>"Villeneuve"}, {"first_name"=>"Gerald T.", "last_name"=>"Ankley"}, {"first_name"=>"Adam D.", "last_name"=>"Biales"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"1932-6203", "pui"=>"600717140", "doi"=>"10.1371/journal.pone.0114178", "sgr"=>"84916631011", "scopus"=>"2-s2.0-84916631011", "isbn"=>"1932-6203", "pmid"=>"25493933"}, "id"=>"4232217d-1dde-3520-bebb-eac9f423cb61", "abstract"=>"Fathead minnow and zebrafish are among the most intensively studied fish species in environmental toxicogenomics. To aid the assessment and interpretation of subtle transcriptomic effects from treatment conditions of interest, better characterization and understanding are needed for natural variation in gene expression among fish individuals from lab cultures. Leveraging the transcriptomics data from a number of our toxicogenomics studies conducted over the years, we conducted a meta-analysis of nearly 600 microarrays generated from the ovary tissue of untreated, reproductively mature fathead minnow and zebrafish samples. As expected, there was considerable batch-to-batch transcriptomic variation; this \"batch-effect\" appeared to differentially impact subsets of fish transcriptomes in a nonsystematic way. Temporally more closely spaced batches tended to share a greater transcriptomic similarity among one another. The overall level of within-batch variation was quite low in fish ovary tissue, making it a suitable system for studying chemical stressors with subtle biological effects. The observed differences in the within-batch variability of gene expression, at the levels of both individual genes and pathways, were probably both technical and biological. This suggests that biological interpretation and prioritization of genes and pathways targeted by experimental conditions should take into account both their intrinsic variability and the size of induced transcriptional changes. There was significant conservation of both the genomes and transcriptomes between fathead minnow and zebrafish. The high degree of conservation offers promising opportunities in not only studying fish molecular responses to environmental stressors by a comparative biology approach, but also effective sharing of a large amount of existing public transcriptomics data for developing toxicogenomics applications.", "link"=>"http://www.mendeley.com/research/natural-variation-fish-transcriptomes-comparative-analysis-fathead-minnow-pimephales-promelas-zebraf-3", "reader_count"=>21, "reader_count_by_academic_status"=>{"Librarian"=>1, "Student > Doctoral Student"=>1, "Researcher"=>4, "Student > Ph. D. Student"=>6, "Other"=>3, "Student > Master"=>4, "Student > Bachelor"=>2}, "reader_count_by_user_role"=>{"Librarian"=>1, "Student > Doctoral Student"=>1, "Researcher"=>4, "Student > Ph. D. Student"=>6, "Other"=>3, "Student > Master"=>4, "Student > Bachelor"=>2}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Environmental Science"=>2, "Biochemistry, Genetics and Molecular Biology"=>4, "Agricultural and Biological Sciences"=>12, "Social Sciences"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>12}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}, "Environmental Science"=>{"Environmental Science"=>2}}, "reader_count_by_country"=>{"Canada"=>1, "United Kingdom"=>1, "India"=>1}, "group_count"=>1}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1832454"], "description"=>"<p>A total of 84 (three outliers excluded) KEGG pathways were calculated for their average intensities (A), and 53 (two outliers excluded) pathways for their average CVs (B), based on a combined total of 6617 orthologous genes. To be included, each pathway must have at least five orthologs and a p-value of ≤0.1 for the correlation of the intensities or CVs of its member genes as estimated within a batch. The CCs were 0.86 and 0.80 for the average intensity and average CV by pathway respectively, with the both p-values = 0. The p-values of normality test of error distribution for linear regressions were 0.045 and 0.585 respectively.</p>", "links"=>[], "tags"=>["interpretation", "differentially impact subsets", "transcriptome", "zebrafish", "gene expression", "variability", "variation", "Conservation", "stressors", "fathead", "pathway", "fish ovary tissue", "transcriptomics data", "toxicogenomic", "fathead minnow"], "article_id"=>1266624, "categories"=>["Biological Sciences"], "users"=>["Rong-Lin Wang", "David C. Bencic", "Natàlia Garcia-Reyero", "Edward J. Perkins", "Daniel L. Villeneuve", "Gerald T. Ankley", "Adam D. Biales"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0114178.g004", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Interspecific_correlation_by_average_intensity_and_average_coefficient_of_variation_of_individual_pathways_/1266624", "title"=>"Interspecific correlation by average intensity and average coefficient of variation of individual pathways.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-12-10 02:44:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1832467", "https://ndownloader.figshare.com/files/1832468", "https://ndownloader.figshare.com/files/1832469", "https://ndownloader.figshare.com/files/1832470", "https://ndownloader.figshare.com/files/1832471", "https://ndownloader.figshare.com/files/1832472", "https://ndownloader.figshare.com/files/1832473", "https://ndownloader.figshare.com/files/1832474", "https://ndownloader.figshare.com/files/1832475", "https://ndownloader.figshare.com/files/1832476", "https://ndownloader.figshare.com/files/1832477", "https://ndownloader.figshare.com/files/1832478"], "description"=>"<div><p>Fathead minnow and zebrafish are among the most intensively studied fish species in environmental toxicogenomics. To aid the assessment and interpretation of subtle transcriptomic effects from treatment conditions of interest, better characterization and understanding are needed for natural variation in gene expression among fish individuals from lab cultures. Leveraging the transcriptomics data from a number of our toxicogenomics studies conducted over the years, we conducted a meta-analysis of nearly 600 microarrays generated from the ovary tissue of untreated, reproductively mature fathead minnow and zebrafish samples. As expected, there was considerable batch-to-batch transcriptomic variation; this “batch-effect” appeared to differentially impact subsets of fish transcriptomes in a nonsystematic way. Temporally more closely spaced batches tended to share a greater transcriptomic similarity among one another. The overall level of within-batch variation was quite low in fish ovary tissue, making it a suitable system for studying chemical stressors with subtle biological effects. The observed differences in the within-batch variability of gene expression, at the levels of both individual genes and pathways, were probably both technical and biological. This suggests that biological interpretation and prioritization of genes and pathways targeted by experimental conditions should take into account both their intrinsic variability and the size of induced transcriptional changes. There was significant conservation of both the genomes and transcriptomes between fathead minnow and zebrafish. The high degree of conservation offers promising opportunities in not only studying fish molecular responses to environmental stressors by a comparative biology approach, but also effective sharing of a large amount of existing public transcriptomics data for developing toxicogenomics applications.</p></div>", "links"=>[], "tags"=>["interpretation", "differentially impact subsets", "transcriptome", "zebrafish", "gene expression", "variability", "variation", "Conservation", "stressors", "fathead", "pathway", "fish ovary tissue", "transcriptomics data", "toxicogenomic", "fathead minnow"], "article_id"=>1266637, "categories"=>["Biological Sciences"], "users"=>["Rong-Lin Wang", "David C. Bencic", "Natàlia Garcia-Reyero", "Edward J. Perkins", "Daniel L. Villeneuve", "Gerald T. Ankley", "Adam D. Biales"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0114178.s001", "https://dx.doi.org/10.1371/journal.pone.0114178.s002", "https://dx.doi.org/10.1371/journal.pone.0114178.s003", "https://dx.doi.org/10.1371/journal.pone.0114178.s004", "https://dx.doi.org/10.1371/journal.pone.0114178.s005", "https://dx.doi.org/10.1371/journal.pone.0114178.s006", "https://dx.doi.org/10.1371/journal.pone.0114178.s007", "https://dx.doi.org/10.1371/journal.pone.0114178.s008", "https://dx.doi.org/10.1371/journal.pone.0114178.s009", "https://dx.doi.org/10.1371/journal.pone.0114178.s010", "https://dx.doi.org/10.1371/journal.pone.0114178.s011", "https://dx.doi.org/10.1371/journal.pone.0114178.s012"], "stats"=>{"downloads"=>22, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Natural_Variation_in_Fish_Transcriptomes_Comparative_Analysis_of_the_Fathead_Minnow_Pimephales_promelas_and_Zebrafish_Danio_rerio_/1266637", "title"=>"Natural Variation in Fish Transcriptomes: Comparative Analysis of the Fathead Minnow (<i>Pimephales promelas</i>) and Zebrafish (<i>Danio rerio</i>)", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-12-10 02:44:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1832452"], "description"=>"<p>The within-batch intensities (A) and coefficients of variation (CV; B) were based on 6617 orthologous genes. The orthologs were represented by 9311 zebrafish (DRE) and 6950 fathead minnow (PPR) probes. The intensity and CV of an ortholog with duplicated probes were probe means. The correlation coefficients over the orthologs for the two metrics were 0.49 and 0.33 respectively, with the both p-values = 0.</p>", "links"=>[], "tags"=>["interpretation", "differentially impact subsets", "transcriptome", "zebrafish", "gene expression", "variability", "variation", "Conservation", "stressors", "fathead", "pathway", "fish ovary tissue", "transcriptomics data", "toxicogenomic", "fathead minnow"], "article_id"=>1266622, "categories"=>["Biological Sciences"], "users"=>["Rong-Lin Wang", "David C. Bencic", "Natàlia Garcia-Reyero", "Edward J. Perkins", "Daniel L. Villeneuve", "Gerald T. Ankley", "Adam D. Biales"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0114178.g003", "stats"=>{"downloads"=>1, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Interspecific_correlation_by_within_batch_intensity_and_coefficient_of_variation_of_orthologs_/1266622", "title"=>"Interspecific correlation by within-batch intensity and coefficient of variation of orthologs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-12-10 02:44:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1832448"], "description"=>"<p>A total of 136 pathways (eight outliers excluded) were included for fathead minnow (A) and 144 pathways for zebrafish (B). The CCs were −0.68 and −0.70 respectively, with both p-values = 0. The p-values of normality test of error distribution for linear regressions were 0.094 (no significant departure from normality) and 0 (significant non-normality) respectively.</p>", "links"=>[], "tags"=>["interpretation", "differentially impact subsets", "transcriptome", "zebrafish", "gene expression", "variability", "variation", "Conservation", "stressors", "fathead", "pathway", "fish ovary tissue", "transcriptomics data", "toxicogenomic", "fathead minnow"], "article_id"=>1266618, "categories"=>["Biological Sciences"], "users"=>["Rong-Lin Wang", "David C. Bencic", "Natàlia Garcia-Reyero", "Edward J. Perkins", "Daniel L. Villeneuve", "Gerald T. Ankley", "Adam D. Biales"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0114178.g002", "stats"=>{"downloads"=>0, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Intraspecific_correlation_between_the_average_CV_and_average_intensity_by_KEGG_pathways_/1266618", "title"=>"Intraspecific correlation between the average CV and average intensity by KEGG pathways.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-12-10 02:44:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1832457"], "description"=>"<p>The DEGs were identified in paired comparisons of N–1 batches against a batch designated as a common reference. N is the total number of batches in a factor. The comparisons were made in conjunction with the analysis of within-batch effects involving 250 permutations. There were little variations in between-batch effects among permutations so their calculations were made only from the first permutation. DRE, zebrafish; PPR, fathead minnow.</p><p>Between-batch variation as measured by average number of DEGs (standard deviations where N>3).</p>", "links"=>[], "tags"=>["interpretation", "differentially impact subsets", "transcriptome", "zebrafish", "gene expression", "variability", "variation", "Conservation", "stressors", "fathead", "pathway", "fish ovary tissue", "transcriptomics data", "toxicogenomic", "fathead minnow"], "article_id"=>1266627, "categories"=>["Biological Sciences"], "users"=>["Rong-Lin Wang", "David C. Bencic", "Natàlia Garcia-Reyero", "Edward J. Perkins", "Daniel L. Villeneuve", "Gerald T. Ankley", "Adam D. Biales"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0114178.t003", "stats"=>{"downloads"=>2, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Between_batch_variation_as_measured_by_average_number_of_DEGs_standard_deviations_where_N_gt_3_/1266627", "title"=>"Between-batch variation as measured by average number of DEGs (standard deviations where N>3).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-12-10 02:44:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1832456"], "description"=>"<p>The DEGs were identified in paired comparisons of N batches against a simulated reference made up of the batch means of their respective factors. DRE, zebrafish; PPR, fathead minnow.</p><p>Between-batch variation as measured by average number of DEGs (standard deviations where N>3).</p>", "links"=>[], "tags"=>["interpretation", "differentially impact subsets", "transcriptome", "zebrafish", "gene expression", "variability", "variation", "Conservation", "stressors", "fathead", "pathway", "fish ovary tissue", "transcriptomics data", "toxicogenomic", "fathead minnow"], "article_id"=>1266626, "categories"=>["Biological Sciences"], "users"=>["Rong-Lin Wang", "David C. Bencic", "Natàlia Garcia-Reyero", "Edward J. Perkins", "Daniel L. Villeneuve", "Gerald T. Ankley", "Adam D. Biales"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0114178.t002", "stats"=>{"downloads"=>0, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Between_batch_variation_as_measured_by_average_number_of_DEGs_standard_deviations_where_N_gt_3_/1266626", "title"=>"Between-batch variation as measured by average number of DEGs (standard deviations where N>3).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-12-10 02:44:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1832459"], "description"=>"<p>The CVs were calculated for each probe by individual batches under the Experiment factor and averaged over all batches. Further averaging these CVs across the entire transcriptome yielded an overall CV of 0.056 for fathead minnow (PPR) and 0.051 for zebrafish (DRE). The total number of orthologous genes identified between Agilent 015064 and 019597 was 6617, represented by 9311 and 6950 unique probes respectively. The PPR probes mapped to their EST sequences and ESTs to NCBI databases by BLAST all had a minimum E-value of E-06.</p><p>Within-batch variation as measured by coefficient of variation (CV).</p>", "links"=>[], "tags"=>["interpretation", "differentially impact subsets", "transcriptome", "zebrafish", "gene expression", "variability", "variation", "Conservation", "stressors", "fathead", "pathway", "fish ovary tissue", "transcriptomics data", "toxicogenomic", "fathead minnow"], "article_id"=>1266629, "categories"=>["Biological Sciences"], "users"=>["Rong-Lin Wang", "David C. Bencic", "Natàlia Garcia-Reyero", "Edward J. Perkins", "Daniel L. Villeneuve", "Gerald T. Ankley", "Adam D. Biales"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0114178.t005", "stats"=>{"downloads"=>3, "page_views"=>111, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Within_batch_variation_as_measured_by_coefficient_of_variation_CV_/1266629", "title"=>"Within-batch variation as measured by coefficient of variation (CV).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-12-10 02:44:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1832444"], "description"=>"<p>Coefficients of variation (CV) were computed at various intensities of 15208 fathead minnow probes (A) and 21495 zebrafish probes (B).</p>", "links"=>[], "tags"=>["interpretation", "differentially impact subsets", "transcriptome", "zebrafish", "gene expression", "variability", "variation", "Conservation", "stressors", "fathead", "pathway", "fish ovary tissue", "transcriptomics data", "toxicogenomic", "fathead minnow"], "article_id"=>1266614, "categories"=>["Biological Sciences"], "users"=>["Rong-Lin Wang", "David C. Bencic", "Natàlia Garcia-Reyero", "Edward J. Perkins", "Daniel L. Villeneuve", "Gerald T. Ankley", "Adam D. Biales"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0114178.g001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Estimation_of_within_batch_variation_/1266614", "title"=>"Estimation of within-batch variation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-12-10 02:44:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1832458"], "description"=>"<p>There were 250 permutations conducted under individual factors. Between-batch variation was controlled statistically in these analyses. PPR, fathead minnow; DRE, zebrafish.</p><p>Within-batch variation as measured by the maximum (% of transcriptome) and minimum number of DEGs per permutation.</p>", "links"=>[], "tags"=>["interpretation", "differentially impact subsets", "transcriptome", "zebrafish", "gene expression", "variability", "variation", "Conservation", "stressors", "fathead", "pathway", "fish ovary tissue", "transcriptomics data", "toxicogenomic", "fathead minnow"], "article_id"=>1266628, "categories"=>["Biological Sciences"], "users"=>["Rong-Lin Wang", "David C. Bencic", "Natàlia Garcia-Reyero", "Edward J. Perkins", "Daniel L. Villeneuve", "Gerald T. Ankley", "Adam D. Biales"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0114178.t004", "stats"=>{"downloads"=>3, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Within_batch_variation_as_measured_by_the_maximum_of_transcriptome_and_minimum_number_of_DEGs_per_permutation_/1266628", "title"=>"Within-batch variation as measured by the maximum (% of transcriptome) and minimum number of DEGs per permutation.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-12-10 02:44:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1832455"], "description"=>"<p>Sample sizes were indicated in parenthesis.</p><p>BPA, bisphenol-A; EE2, 17a-ethynyl estradiol; FAD, fadrozole; FIP, fipronil; FLU, flutamide; GEM, Gemfibrozil; KTC, ketoconazole; PRO, prochloraz; RDX, hexahydro-1,3,5-trinitro-1,3,5-triazine; TRB, 17 -trenbolone; TNT, 2,4,6-trinitrotoluene; TRI, trilostane; VIN, vinclozolin; WLSSD, effluent from Western Lake Superior Sanitary District; RNA Date not determined: 11111, 55555; RNA Person not determined: DDD, YYY.</p><p>Factors and batches (N) by which fathead minnow (PPR) and zebrafish (DRE) microarray samples were organized.</p>", "links"=>[], "tags"=>["interpretation", "differentially impact subsets", "transcriptome", "zebrafish", "gene expression", "variability", "variation", "Conservation", "stressors", "fathead", "pathway", "fish ovary tissue", "transcriptomics data", "toxicogenomic", "fathead minnow"], "article_id"=>1266625, "categories"=>["Biological Sciences"], "users"=>["Rong-Lin Wang", "David C. Bencic", "Natàlia Garcia-Reyero", "Edward J. Perkins", "Daniel L. Villeneuve", "Gerald T. Ankley", "Adam D. Biales"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0114178.t001", "stats"=>{"downloads"=>5, "page_views"=>34, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Factors_and_batches_N_by_which_fathead_minnow_PPR_and_zebrafish_DRE_microarray_samples_were_organized_/1266625", "title"=>"Factors and batches (N) by which fathead minnow (PPR) and zebrafish (DRE) microarray samples were organized.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-12-10 02:44:48"}

PMC Usage Stats | Further Information

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Relative Metric

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