A mouse tissue atlas of small noncoding RNA

Small noncoding RNAs (ncRNAs) play a vital role in a broad range of biological processes both in health and disease. A comprehensive quantitative reference of small ncRNA expression would significantly advance our understanding of ncRNA roles in shaping tissue functions. Here, we systematically prof...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 117; no. 41; pp. 25634 - 25645
Main Authors Isakova, Alina, Fehlmann, Tobias, Keller, Andreas, Quake, Stephen R.
Format Journal Article
LanguageEnglish
Published Washington National Academy of Sciences 13.10.2020
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ISSN0027-8424
1091-6490
1091-6490
DOI10.1073/pnas.2002277117

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Abstract Small noncoding RNAs (ncRNAs) play a vital role in a broad range of biological processes both in health and disease. A comprehensive quantitative reference of small ncRNA expression would significantly advance our understanding of ncRNA roles in shaping tissue functions. Here, we systematically profiled the levels of five ncRNA classes (microRNA [miRNA], small nucleolar RNA [snoRNA], small nuclear RNA [snRNA], small Cajal body-specific RNA [scaRNA], and transfer RNA [tRNA] fragments) across 11 mouse tissues by deep sequencing. Using 14 biological replicates spanning both sexes, we identified that ∼30% of small ncRNAs are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. We found that some miRNAs are subject to “arm switching” between healthy tissues and that tRNA fragments are retained within tissues in both a gene- and a tissue-specific manner. Out of 11 profiled tissues, we confirmed that brain contains the largest number of unique small ncRNA transcripts, some of which were previously annotated while others are identified in this study. Furthermore, by combining these findings with single-cell chromatin accessibility (scATAC-seq) data, we were able to connect identified brain-specific ncRNAs with their cell types of origin. These results yield the most comprehensive characterization of specific and ubiquitous small RNAs in individual murine tissues to date, and we expect that these data will be a resource for the further identification of ncRNAs involved in tissue function in health and dysfunction in disease.
AbstractList We report a systematic unbiased analysis of small RNA molecule expression in 11 different tissues of the model organism mouse. We discovered uncharacterized noncoding RNA molecules and identified that ∼30% of total noncoding small RNA transcriptome are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. Distinct distribution patterns of small RNA across the body suggest the existence of tissue-specific mechanisms involved in noncoding RNA processing. Small noncoding RNAs (ncRNAs) play a vital role in a broad range of biological processes both in health and disease. A comprehensive quantitative reference of small ncRNA expression would significantly advance our understanding of ncRNA roles in shaping tissue functions. Here, we systematically profiled the levels of five ncRNA classes (microRNA [miRNA], small nucleolar RNA [snoRNA], small nuclear RNA [snRNA], small Cajal body-specific RNA [scaRNA], and transfer RNA [tRNA] fragments) across 11 mouse tissues by deep sequencing. Using 14 biological replicates spanning both sexes, we identified that ∼30% of small ncRNAs are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. We found that some miRNAs are subject to “arm switching” between healthy tissues and that tRNA fragments are retained within tissues in both a gene- and a tissue-specific manner. Out of 11 profiled tissues, we confirmed that brain contains the largest number of unique small ncRNA transcripts, some of which were previously annotated while others are identified in this study. Furthermore, by combining these findings with single-cell chromatin accessibility (scATAC-seq) data, we were able to connect identified brain-specific ncRNAs with their cell types of origin. These results yield the most comprehensive characterization of specific and ubiquitous small RNAs in individual murine tissues to date, and we expect that these data will be a resource for the further identification of ncRNAs involved in tissue function in health and dysfunction in disease.
Small noncoding RNAs (ncRNAs) play a vital role in a broad range of biological processes both in health and disease. A comprehensive quantitative reference of small ncRNA expression would significantly advance our understanding of ncRNA roles in shaping tissue functions. Here, we systematically profiled the levels of five ncRNA classes (microRNA [miRNA], small nucleolar RNA [snoRNA], small nuclear RNA [snRNA], small Cajal body-specific RNA [scaRNA], and transfer RNA [tRNA] fragments) across 11 mouse tissues by deep sequencing. Using 14 biological replicates spanning both sexes, we identified that ∼30% of small ncRNAs are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. We found that some miRNAs are subject to "arm switching" between healthy tissues and that tRNA fragments are retained within tissues in both a gene- and a tissue-specific manner. Out of 11 profiled tissues, we confirmed that brain contains the largest number of unique small ncRNA transcripts, some of which were previously annotated while others are identified in this study. Furthermore, by combining these findings with single-cell chromatin accessibility (scATAC-seq) data, we were able to connect identified brain-specific ncRNAs with their cell types of origin. These results yield the most comprehensive characterization of specific and ubiquitous small RNAs in individual murine tissues to date, and we expect that these data will be a resource for the further identification of ncRNAs involved in tissue function in health and dysfunction in disease.
Small noncoding RNAs (ncRNAs) play a vital role in a broad range of biological processes both in health and disease. A comprehensive quantitative reference of small ncRNA expression would significantly advance our understanding of ncRNA roles in shaping tissue functions. Here, we systematically profiled the levels of five ncRNA classes (microRNA [miRNA], small nucleolar RNA [snoRNA], small nuclear RNA [snRNA], small Cajal body-specific RNA [scaRNA], and transfer RNA [tRNA] fragments) across 11 mouse tissues by deep sequencing. Using 14 biological replicates spanning both sexes, we identified that ∼30% of small ncRNAs are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. We found that some miRNAs are subject to "arm switching" between healthy tissues and that tRNA fragments are retained within tissues in both a gene- and a tissue-specific manner. Out of 11 profiled tissues, we confirmed that brain contains the largest number of unique small ncRNA transcripts, some of which were previously annotated while others are identified in this study. Furthermore, by combining these findings with single-cell chromatin accessibility (scATAC-seq) data, we were able to connect identified brain-specific ncRNAs with their cell types of origin. These results yield the most comprehensive characterization of specific and ubiquitous small RNAs in individual murine tissues to date, and we expect that these data will be a resource for the further identification of ncRNAs involved in tissue function in health and dysfunction in disease.Small noncoding RNAs (ncRNAs) play a vital role in a broad range of biological processes both in health and disease. A comprehensive quantitative reference of small ncRNA expression would significantly advance our understanding of ncRNA roles in shaping tissue functions. Here, we systematically profiled the levels of five ncRNA classes (microRNA [miRNA], small nucleolar RNA [snoRNA], small nuclear RNA [snRNA], small Cajal body-specific RNA [scaRNA], and transfer RNA [tRNA] fragments) across 11 mouse tissues by deep sequencing. Using 14 biological replicates spanning both sexes, we identified that ∼30% of small ncRNAs are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. We found that some miRNAs are subject to "arm switching" between healthy tissues and that tRNA fragments are retained within tissues in both a gene- and a tissue-specific manner. Out of 11 profiled tissues, we confirmed that brain contains the largest number of unique small ncRNA transcripts, some of which were previously annotated while others are identified in this study. Furthermore, by combining these findings with single-cell chromatin accessibility (scATAC-seq) data, we were able to connect identified brain-specific ncRNAs with their cell types of origin. These results yield the most comprehensive characterization of specific and ubiquitous small RNAs in individual murine tissues to date, and we expect that these data will be a resource for the further identification of ncRNAs involved in tissue function in health and dysfunction in disease.
Author Keller, Andreas
Fehlmann, Tobias
Isakova, Alina
Quake, Stephen R.
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Cites_doi 10.1093/bioinformatics/bts635
10.1093/nar/gkw116
10.1126/science.337.6099.1159
10.1016/j.cell.2019.10.017
10.1038/ni888
10.1038/nature11247
10.1101/gad.203786.112
10.1093/nar/gkl1172
10.1261/rna.073395.119
10.18632/aging.100540
10.1186/s12864-017-4031-9
10.1101/430561
10.1126/science.aad6780
10.1093/nar/gkv1335
10.1016/j.celrep.2012.10.021
10.1242/jcs.01487
10.1038/srep39812
10.1126/science.aar3819
10.1186/1471-2164-14-298
10.1093/nar/gkv007
10.18632/oncotarget.2405
10.1080/15476286.2016.1257470
10.1016/j.cell.2007.04.040
10.1016/j.molcel.2018.06.044
10.7554/eLife.05005
10.1093/nar/gkaa323
10.1093/nar/gkt393
10.1038/nrg3074
10.1038/s41580-018-0045-7
10.1086/342408
10.1155/2014/328935
10.1261/rna.064493.117
10.1038/nrm3838
10.1016/j.cell.2018.06.052
10.3390/cells8020083
10.1093/nar/gkx851
10.1016/j.canlet.2018.02.002
10.1038/nrm3742
10.1182/blood-2012-01-153486
10.1101/gr.106849.110
10.1016/j.celrep.2019.05.031
10.1101/gr.222067.117
10.1186/s12859-018-2287-y
10.1371/journal.pone.0042248
10.1016/j.biocel.2015.07.003
10.1038/nature05453
10.1038/nbt.3947
10.15252/embj.201490493
10.1530/ERC-14-0208
10.1093/nar/gkz584
10.1016/j.cell.2018.03.006
10.1093/bioinformatics/btx814
10.1007/BF00994018
10.1093/nar/gkr688
10.3324/haematol.2011.051730
10.3389/fgene.2013.00020
10.18632/oncotarget.4695
10.1093/nar/gkz097
10.1186/1472-6750-8-69
10.1261/rna.065516.117
10.1093/bioinformatics/btt656
10.1186/s13059-014-0550-8
10.1056/NEJMoa1209026
10.1038/nature09267
10.1371/journal.pone.0124877
10.1186/s12915-014-0078-0
10.1093/nar/gkv1309
10.1038/nbt.3701
10.1101/gad.1837609
10.1074/jbc.RA118.003410
10.1016/j.gene.2018.07.057
10.1093/nar/gks1268
10.1186/1471-2164-8-166
10.1016/j.cell.2014.03.008
10.1038/s41598-017-02632-0
10.1093/nar/gky955
10.1016/S1074-7613(00)80316-7
10.1038/nrm2124
10.1038/nmeth.1682
10.1038/s41571-018-0035-x
10.1016/j.ebiom.2018.11.003
10.1093/nar/gkt1181
10.2174/138920209788185289
10.1101/gr.190595.115
ContentType Journal Article
Copyright Copyright National Academy of Sciences Oct 13, 2020
Copyright © 2020 the Author(s). Published by PNAS.
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Reviewers: J.C.M., European Molecular Biology Laboratory–European Bioinformatics Institute; and I.U., Weizmann Institute of Science.
Author contributions: A.I. and S.R.Q. designed research; A.I. performed research; A.I., T.F., and A.K. analyzed data; and A.I. and S.R.Q. wrote the paper.
Contributed by Stephen R. Quake, July 29, 2020 (sent for review February 10, 2020; reviewed by John C. Marioni and Igor Ulitsky)
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References e_1_3_4_3_2
e_1_3_4_1_2
e_1_3_4_61_2
e_1_3_4_82_2
e_1_3_4_9_2
e_1_3_4_63_2
e_1_3_4_84_2
e_1_3_4_7_2
e_1_3_4_40_2
e_1_3_4_5_2
e_1_3_4_80_2
e_1_3_4_23_2
e_1_3_4_44_2
e_1_3_4_69_2
e_1_3_4_21_2
e_1_3_4_42_2
e_1_3_4_27_2
e_1_3_4_48_2
e_1_3_4_65_2
e_1_3_4_86_2
e_1_3_4_25_2
e_1_3_4_46_2
e_1_3_4_88_2
e_1_3_4_29_2
e_1_3_4_72_2
e_1_3_4_74_2
e_1_3_4_30_2
e_1_3_4_51_2
e_1_3_4_70_2
e_1_3_4_11_2
e_1_3_4_34_2
e_1_3_4_57_2
e_1_3_4_55_2
e_1_3_4_32_2
e_1_3_4_59_2
e_1_3_4_53_2
e_1_3_4_15_2
e_1_3_4_38_2
e_1_3_4_76_2
e_1_3_4_13_2
e_1_3_4_36_2
e_1_3_4_78_2
e_1_3_4_19_2
e_1_3_4_17_2
e_1_3_4_2_2
e_1_3_4_60_2
e_1_3_4_83_2
e_1_3_4_62_2
e_1_3_4_85_2
e_1_3_4_8_2
e_1_3_4_41_2
e_1_3_4_6_2
e_1_3_4_81_2
e_1_3_4_4_2
e_1_3_4_22_2
e_1_3_4_45_2
e_1_3_4_68_2
e_1_3_4_20_2
e_1_3_4_43_2
e_1_3_4_26_2
e_1_3_4_49_2
e_1_3_4_64_2
e_1_3_4_87_2
e_1_3_4_24_2
e_1_3_4_47_2
e_1_3_4_66_2
e_1_3_4_28_2
e_1_3_4_71_2
e_1_3_4_73_2
e_1_3_4_52_2
e_1_3_4_50_2
e_1_3_4_79_2
e_1_3_4_12_2
e_1_3_4_33_2
e_1_3_4_58_2
e_1_3_4_54_2
e_1_3_4_10_2
e_1_3_4_31_2
Lin M. (e_1_3_4_67_2) 2018; 15
e_1_3_4_75_2
e_1_3_4_16_2
e_1_3_4_37_2
e_1_3_4_77_2
e_1_3_4_14_2
e_1_3_4_35_2
e_1_3_4_56_2
e_1_3_4_18_2
e_1_3_4_39_2
References_xml – ident: e_1_3_4_75_2
  doi: 10.1093/bioinformatics/bts635
– ident: e_1_3_4_33_2
  doi: 10.1093/nar/gkw116
– ident: e_1_3_4_84_2
  doi: 10.1126/science.337.6099.1159
– ident: e_1_3_4_20_2
  doi: 10.1016/j.cell.2019.10.017
– ident: e_1_3_4_56_2
  doi: 10.1038/ni888
– ident: e_1_3_4_63_2
  doi: 10.1038/nature11247
– ident: e_1_3_4_14_2
  doi: 10.1101/gad.203786.112
– ident: e_1_3_4_8_2
  doi: 10.1093/nar/gkl1172
– ident: e_1_3_4_26_2
  doi: 10.1261/rna.073395.119
– ident: e_1_3_4_48_2
  doi: 10.18632/aging.100540
– volume: 15
  start-page: 9818
  year: 2018
  ident: e_1_3_4_67_2
  article-title: Comprehensive identification of microRNA arm selection preference in lung cancer: miR-324-5p and -3p serve oncogenic functions in lung cancer
  publication-title: Oncol. Lett.
– ident: e_1_3_4_78_2
  doi: 10.1186/s12864-017-4031-9
– ident: e_1_3_4_88_2
  doi: 10.1101/430561
– ident: e_1_3_4_69_2
  doi: 10.1126/science.aad6780
– ident: e_1_3_4_70_2
  doi: 10.1093/nar/gkv1335
– ident: e_1_3_4_36_2
  doi: 10.1016/j.celrep.2012.10.021
– ident: e_1_3_4_13_2
  doi: 10.1242/jcs.01487
– ident: e_1_3_4_57_2
  doi: 10.1038/srep39812
– ident: e_1_3_4_73_2
  doi: 10.1126/science.aar3819
– ident: e_1_3_4_68_2
  doi: 10.1186/1471-2164-14-298
– ident: e_1_3_4_79_2
  doi: 10.1093/nar/gkv007
– ident: e_1_3_4_58_2
  doi: 10.18632/oncotarget.2405
– ident: e_1_3_4_4_2
  doi: 10.1080/15476286.2016.1257470
– ident: e_1_3_4_16_2
  doi: 10.1016/j.cell.2007.04.040
– ident: e_1_3_4_87_2
  doi: 10.1016/j.molcel.2018.06.044
– ident: e_1_3_4_82_2
  doi: 10.7554/eLife.05005
– ident: e_1_3_4_52_2
– ident: e_1_3_4_45_2
  doi: 10.1093/nar/gkaa323
– ident: e_1_3_4_83_2
  doi: 10.1093/nar/gkt393
– ident: e_1_3_4_3_2
  doi: 10.1038/nrg3074
– ident: e_1_3_4_6_2
  doi: 10.1038/s41580-018-0045-7
– ident: e_1_3_4_34_2
  doi: 10.1086/342408
– ident: e_1_3_4_50_2
  doi: 10.1155/2014/328935
– ident: e_1_3_4_32_2
  doi: 10.1261/rna.064493.117
– ident: e_1_3_4_11_2
  doi: 10.1038/nrm3838
– ident: e_1_3_4_28_2
  doi: 10.1016/j.cell.2018.06.052
– ident: e_1_3_4_44_2
  doi: 10.3390/cells8020083
– ident: e_1_3_4_85_2
  doi: 10.1093/nar/gkx851
– ident: e_1_3_4_72_2
  doi: 10.1016/j.canlet.2018.02.002
– ident: e_1_3_4_41_2
  doi: 10.1038/nrm3742
– ident: e_1_3_4_64_2
  doi: 10.1182/blood-2012-01-153486
– ident: e_1_3_4_10_2
  doi: 10.1101/gr.106849.110
– ident: e_1_3_4_5_2
  doi: 10.1016/j.celrep.2019.05.031
– ident: e_1_3_4_24_2
  doi: 10.1101/gr.222067.117
– ident: e_1_3_4_77_2
  doi: 10.1186/s12859-018-2287-y
– ident: e_1_3_4_55_2
  doi: 10.1371/journal.pone.0042248
– ident: e_1_3_4_38_2
  doi: 10.1016/j.biocel.2015.07.003
– ident: e_1_3_4_66_2
  doi: 10.1038/nature05453
– ident: e_1_3_4_25_2
  doi: 10.1038/nbt.3947
– ident: e_1_3_4_37_2
  doi: 10.15252/embj.201490493
– ident: e_1_3_4_60_2
  doi: 10.1530/ERC-14-0208
– ident: e_1_3_4_40_2
  doi: 10.1093/nar/gkz584
– ident: e_1_3_4_1_2
  doi: 10.1016/j.cell.2018.03.006
– ident: e_1_3_4_49_2
  doi: 10.1093/bioinformatics/btx814
– ident: e_1_3_4_62_2
  doi: 10.1007/BF00994018
– ident: e_1_3_4_47_2
  doi: 10.1093/nar/gkr688
– ident: e_1_3_4_65_2
  doi: 10.3324/haematol.2011.051730
– ident: e_1_3_4_51_2
  doi: 10.3389/fgene.2013.00020
– ident: e_1_3_4_7_2
  doi: 10.18632/oncotarget.4695
– ident: e_1_3_4_46_2
  doi: 10.1093/nar/gkz097
– ident: e_1_3_4_22_2
  doi: 10.1186/1472-6750-8-69
– ident: e_1_3_4_54_2
  doi: 10.1261/rna.065516.117
– ident: e_1_3_4_76_2
  doi: 10.1093/bioinformatics/btt656
– ident: e_1_3_4_80_2
  doi: 10.1186/s13059-014-0550-8
– ident: e_1_3_4_21_2
  doi: 10.1056/NEJMoa1209026
– ident: e_1_3_4_61_2
  doi: 10.1038/nature09267
– ident: e_1_3_4_35_2
  doi: 10.1371/journal.pone.0124877
– ident: e_1_3_4_86_2
– ident: e_1_3_4_15_2
  doi: 10.1186/s12915-014-0078-0
– ident: e_1_3_4_30_2
  doi: 10.1093/nar/gkv1309
– ident: e_1_3_4_17_2
  doi: 10.1038/nbt.3701
– ident: e_1_3_4_53_2
  doi: 10.1101/gad.1837609
– ident: e_1_3_4_27_2
  doi: 10.1074/jbc.RA118.003410
– ident: e_1_3_4_71_2
  doi: 10.1016/j.gene.2018.07.057
– ident: e_1_3_4_42_2
  doi: 10.1093/nar/gks1268
– ident: e_1_3_4_23_2
  doi: 10.1186/1471-2164-8-166
– ident: e_1_3_4_2_2
  doi: 10.1016/j.cell.2014.03.008
– ident: e_1_3_4_18_2
  doi: 10.1038/s41598-017-02632-0
– ident: e_1_3_4_29_2
  doi: 10.1093/nar/gky955
– ident: e_1_3_4_39_2
  doi: 10.1016/S1074-7613(00)80316-7
– ident: e_1_3_4_12_2
  doi: 10.1038/nrm2124
– ident: e_1_3_4_9_2
  doi: 10.1038/nmeth.1682
– ident: e_1_3_4_81_2
– ident: e_1_3_4_19_2
  doi: 10.1038/s41571-018-0035-x
– ident: e_1_3_4_43_2
  doi: 10.1016/j.ebiom.2018.11.003
– ident: e_1_3_4_31_2
  doi: 10.1093/nar/gkt1181
– ident: e_1_3_4_59_2
  doi: 10.2174/138920209788185289
– ident: e_1_3_4_74_2
  doi: 10.1101/gr.190595.115
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Snippet Small noncoding RNAs (ncRNAs) play a vital role in a broad range of biological processes both in health and disease. A comprehensive quantitative reference of...
We report a systematic unbiased analysis of small RNA molecule expression in 11 different tissues of the model organism mouse. We discovered uncharacterized...
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SubjectTerms Biological activity
Biological Sciences
Brain
Chromatin
Fragments
MicroRNAs
miRNA
Non-coding RNA
Nucleoli
Ribonucleic acid
RNA
Sexual dimorphism
snoRNA
snRNA
Tissues
Transfer RNA
tRNA
Title A mouse tissue atlas of small noncoding RNA
URI https://www.jstor.org/stable/26969638
https://www.proquest.com/docview/2453209373
https://www.proquest.com/docview/2446670656
https://pubmed.ncbi.nlm.nih.gov/PMC7568261
Volume 117
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