PreprintCited by 5Advanced Proteomics Techniques and ApplicationsCardiac Fibrosis and RemodelingCongenital heart defects research

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

A Ratiometric Catalog of Protein Isoform Shifts in the Cardiac Fetal Gene Program

Open access

Preprint — published as 10.1172/jci.insight.184309 · Paper page

Abstract

Pathological cardiac remodeling is associated with the reactivation of fetal genes, yet the extent of the heart’s fetal gene program and its impact on proteome compositions remain incompletely understood. Here, using a new proteome-wide protein ratio quantification strategy with mass spectrometry, we identify pervasive isoform usage shifts in fetal and postnatal mouse hearts, involving 145 pairs of highly homologous paralogs and alternative splicing-derived isoform proteins. Proteome-wide ratio comparisons readily rediscover hallmark fetal gene signatures in muscle contraction and glucose metabolism pathways, while revealing novel isoform usage in mitochondrial and gene expression proteins, including PPA1/PPA2, ANT1/ANT2, and PCBP1/PCBP2 switches. Paralogs with differential fetal usage tend to be evolutionarily recent, consistent with functional diversification. Alternative splicing adds another rich source of fetal isoform usage differences, involving PKM M1/M2, GLS-1 KGA/GAC, PDLIM5 long/short, and other spliceoforms. When comparing absolute protein proportions, we observe a partial reversion toward fetal gene usage in pathological hearts. In summary, we present a ratiometric catalog of paralogs and spliceoform pairs in the cardiac fetal gene program. More generally, the results demonstrate the potential of applying the proteome-wide ratio test concept to discover new regulatory modalities beyond differential gene expression.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1101/2024.04.09.588716

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

  • Global quantification of mammalian gene expression control

    Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566 · cited 1×

    “A first-pass unique iBAQ value (intensity-based absolute quantification) estimate of the absolute quantity if each protein (Schwanhäusser et al., 2011) was calculated by the sum of MS1 LFQ of all peptides confidently mappable to a unique protein, divided by the protein sequence length.”

Flagged first, then by citations

Research works printed but not linked: 119

  1. 10.1016/j.celrep.2021.108869 · DOI
  2. 10.1038/s41467-024-49874-x · DOI
  3. 10.1016/j.ymeth.2015.04.032 · DOI
  4. 10.1074/jbc.M006587200 · DOI
  5. 10.1006/viro.1996.0530 · DOI
  6. 10.1038/s41536-020-0091-6 · DOI · Paper page
  7. 10.1038/ncb1575 · DOI · Paper page
  8. 10.1126/science.1230612 · DOI · Paper page
  9. 10.1083/jcb.132.1.211 · DOI
  10. 10.1074/jbc.M110.110130 · DOI
  11. 10.1016/0014-5793(91)80820-S · DOI
  12. 10.1016/j.tibs.2017.04.001 · DOI · Paper page
  13. 10.1016/S0021-9258(17)37547-6 · DOI
  14. 10.1093/NAR/GKAA1025 · DOI · Paper page
  15. 10.1038/s41467-020-20327-5 · DOI
  16. 10.1126/science.1083995 · DOI · Paper page
  17. 10.1016/j.cell.2019.10.007 · DOI · Paper page
  18. 10.1371/journal.pone.0092903 · DOI
  19. 10.1038/s41467-024-46600-5 · DOI · Paper page
  20. 10.1016/j.celrep.2020.108087 · DOI
  21. 10.1371/journal.pcbi.1009918 · DOI
  22. 10.1016/j.devcel.2016.10.001 · DOI
  23. 10.1113/JP284137 · DOI
  24. 10.1016/j.bbadis.2013.07.023 · DOI
  25. 10.1093/bioinformatics/bts635 · DOI · Paper page
  26. 10.1038/s41598-020-75505-8 · DOI
  27. 10.1038/nprot.2009.97 · DOI
  28. 10.1016/j.devcel.2023.04.011 · DOI
  29. 10.1093/nar/gkp985 · DOI · Paper page
  30. 10.1016/S0008-6363(97)00321-0 · DOI
  31. 10.1093/nar/gkaa1087 · DOI · Paper page
  32. 10.1261/rna.780708 · DOI
  33. 10.1161/CIRCRESAHA.116.309040 · DOI
  34. 10.1016/j.devcel.2022.03.017 · DOI
  35. 10.1074/mcp.M112.024919 · DOI · Paper page
  36. 10.1016/j.tcb.2017.09.005 · DOI
  37. 10.1093/nar/gkab1028 · DOI
  38. 10.1016/j.celrep.2022.111891 · DOI
  39. 10.1128/MCB.19.3.1720 · DOI · Paper page
  40. 10.1016/j.mcpro.2022.100252 · DOI
  41. 10.1152/ajpheart.00244.2022 · DOI · Paper page
  42. 10.1016/j.xpro.2020.100138 · DOI
  43. 10.1007/s004120050389 · DOI
  44. 10.1073/pnas.2113579118 · DOI
  45. 10.1016/j.mcpro.2023.100607 · DOI
  46. 10.1016/j.mcpro.2023.100640 · DOI
  47. 10.1161/01.RES.69.5.1409 · DOI
  48. 10.1016/j.cell.2010.12.001 · DOI · Paper page
  49. 10.1074/jbc.RA119.011870 · DOI
  50. 10.1016/j.semcdb.2015.08.004 · DOI
  51. 10.3389/fcell.2024.1423553 · DOI
  52. 10.1016/j.jbc.2024.107830 · DOI
  53. 10.1152/physrev.00026.2023 · DOI
  54. 10.1152/ajpheart.1995.269.6.H1843 · DOI
  55. 10.1016/j.molcel.2019.11.010 · DOI
  56. 10.1038/nmeth.4256 · DOI
  57. 10.1038/s41467-023-39965-6 · DOI
  58. 10.1126/science.aat9528 · DOI
  59. 10.1210/me.14.3.393 · DOI
  60. 10.1254/jphs.12R04CP · DOI
  61. 10.1172/JCI73787 · DOI
  62. 10.1371/journal.pone.0005867 · DOI
  63. 10.1038/sdata.2016.15 · DOI
  64. 10.1016/j.celrep.2019.11.026 · DOI · Paper page
  65. 10.1021/acs.jproteome.3c00486 · DOI
  66. 10.1016/j.cell.2014.02.033 · DOI
  67. 10.1186/s13059-014-0550-8 · DOI · Paper page
  68. 10.1056/NEJMoa012630 · DOI
  69. 10.1016/j.simpa.2021.100163 · DOI
  70. 10.1083/jcb.111.6.2427 · DOI
  71. 10.1038/s41559-024-02398-5 · DOI
  72. 10.1002/bies.202400202 · DOI
  73. 10.1146/annurev-genet-071719-020653 · DOI
  74. 10.1093/nar/gkac958 · DOI
  75. 10.1261/rna.055939.116 · DOI
  76. 10.1016/0022-2836(89)90141-1 · DOI
  77. 10.1016/j.yjmcc.2023.04.003 · DOI
  78. 10.1016/S0021-9258(19)74066-6 · DOI
  79. 10.1016/j.semcdb.2006.11.012 · DOI
  80. 10.1016/j.tibs.2014.10.010 · DOI
  81. 10.1038/nbt.3122 · DOI
  82. 10.1016/0014-5793(80)80219-5 · DOI
  83. 10.1007/s10741-007-9034-1 · DOI
  84. 10.1161/hc4901.100526 · DOI
  85. 10.1002/1097-0134(20010501)43:2<175::AID-PROT1029>3.0.CO;2-# · DOI
  86. 10.1016/j.bbrc.2015.02.122 · DOI
  87. 10.1152/ajpheart.2001.280.4.H1814 · DOI · Paper page
  88. 10.1093/nar/gkv007 · DOI · Paper page
  89. 10.1038/s43586-024-00318-2 · DOI · Paper page
  90. 10.1074/mcp.M114.046995 · DOI
  91. 10.1016/j.cell.2018.02.030 · DOI
  92. 10.1002/jms.4354 · DOI
  93. 10.1038/emboj.2009.127 · DOI
  94. 10.1371/journal.pcbi.1010702 · DOI
  95. 10.1016/j.xgen.2024.100506 · DOI
  96. 10.1093/nar/gkac1000 · DOI · Paper page
  97. 10.1111/j.1749-6632.2009.05100.x · DOI
  98. 10.1161/JAHA.118.010378 · DOI
  99. 10.1007/s13361-016-1460-7 · DOI · Paper page
  100. 10.1093/nar/gkac1052 · DOI · Paper page
  101. 10.1016/S0021-9258(18)43355-8 · DOI
  102. 10.1093/cvr/cvaa233 · DOI
  103. 10.1038/srep35520 · DOI
  104. 10.1002/pmic.202300188 · DOI
  105. 10.1016/j.mcpro.2023.100626 · DOI
  106. 10.1074/mcp.RA117.000155 · DOI · Paper page
  107. 10.1038/s41419-019-1407-6 · DOI
  108. 10.1002/wrna.1393 · DOI
  109. 10.1016/j.yjmcc.2021.08.008 · DOI
  110. 10.1038/s41467-023-40129-9 · DOI
  111. 10.1016/j.cels.2020.06.013 · DOI
  112. 10.1242/jcs.121384 · DOI
  113. 10.1152/ajpheart.00692.2021 · DOI
  114. 10.1039/C5MB00663E · DOI
  115. 10.1016/j.humpath.2012.09.007 · DOI
  116. 10.1074/mcp.TIR119.001385 · DOI
  117. 10.1161/JAHA.119.012731 · DOI
  118. 10.1038/s41598-024-59975-8 · DOI
  119. 10.1093/bioinformatics/bty895 · DOI

Metadata

Authors
Han, Y., Binti, S., Wennersten, S. A., Pandi, B., Ng, D. C. M., Lau, E., & Lam, M. P. Y.
Affiliations
University of Colorado Anschutz (US)
Corresponding author
Lam, Maggie P. Y.
Venue
JCI Insight
Publisher
openRxiv
Published
2024-04-10
Volume
10
Issue
20
ISSN
2379-3708 (ISSN-L)
OpenAlex
W4413044285
Cited by
5
References
1
Citations by year
2026: 5
FWCI
1.27
Type
journal article
Language
en
Open access
Locations
  • JCI Insight (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed Central (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • American Heart Association (25POST1372064)
  • National Institutes of Health (1r01hl169473-01a1)
  • National Heart, Lung, and Blood Institute (R01-HL169473, R00HL144829, R01HL141278)
  • National Institute of General Medical Sciences (R01GM144456, R35GM146815)
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac Fibrosis and Remodeling
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Congenital heart defects research
Keywords
paralogs, alternative splicing, cardiac remodeling, PDLIM5, mitochondrial proteins, glucose metabolism, muscle contraction, mouse heart

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review