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Whole-genome DNA methylation profile of female Gobiocypris rarus brains at three age stages.

Code ↔ Paper

2 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 2 matches
  1. [1] § Methods › Genomic feature annotation ↔ scripts/03_figures/plot_Figure2.R, lines 1–50 · score 0.71 · Down2k, Up2k, mRNA, CDS, Islands
  2. [2] § Data Overview › Genomic feature-specific methylation patterns ↔ scripts/03_figures/plot_Figure2.R, lines 1–50 · score 0.66 · Down2k, Up2k, mRNA, CDS, islands, months

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

R · 140 lines · 2.8 KB · no license · 2 matches

  1. # ==========================
  2. # Figure 2: Feature methylation (NO statistics)
  3. # ==========================
  5. library(tidyverse)
  6. library(patchwork)
  8. # ==========================
  9. # 1. Input
  10. # ==========================
  11. file_feature <- file.path(
  12. data_processed_dir,
  13. "feature_methylation_matrix.tsv"
  14. )
  16. df <- read_tsv(file_feature)
  18. # ==========================
  19. # 2. Factor levels
  20. # ==========================
  21. df <- df %>%
  22. mutate(
  23. Age_group = factor(
  24. Age_group,
  25. levels = c("8 months","44 months","74 months")
  26. ),
  27. Feature = factor(
  28. Feature,
  29. levels = c("Up2k","CDS","mRNA","Down2k","CpG island","Repeat")
  30. )
  31. )
  33. # ==========================
  34. # 3. Long format
  35. # ==========================
  36. df_long <- df %>%
  37. pivot_longer(
  38. cols = c(`mCG%`,`mCHG%`,`mCHH%`),
  39. names_to = "Context",
  40. values_to = "Methylation"
  41. )
  43. # ==========================
  44. # 4. Colors
  45. # ==========================
  46. cols <- c(
  47. "8 months" = "#3C5488",
  48. "44 months" = "#00A087",
  49. "74 months" = "#E64B35"
  50. )
  52. # ==========================
  53. # 5. Plot function
  54. # ==========================
  55. plot_context <- function(context_name){
  57. data_sub <- df_long %>% filter(Context == context_name)
  59. pd <- position_dodge(0.35)
  61. ggplot(data_sub,
  62. aes(Feature, Methylation,
  63. color = Age_group,
  64. shape = Age_group)) +
  66. stat_summary(
  67. fun = mean,
  68. geom = "point",
  69. size = 3.2,
  70. position = pd
  71. ) +
  73. stat_summary(
  74. fun.data = mean_sdl,
  75. fun.args = list(mult = 1),
  76. geom = "errorbar",
  77. width = 0.1,
  78. linewidth = 0.25,
  79. alpha = 0.7,
  80. position = pd
  81. ) +
  83. scale_color_manual(values = cols) +
  84. scale_shape_manual(values = c(16,17,15)) +
  86. theme_classic(base_size = 8.5) +
  88. theme(
  89. axis.text.x = element_text(angle = 25, hjust = 1, size = 8),
  90. axis.text.y = element_text(size = 8),
  91. axis.title.y = element_text(size = 9, face = "bold"),
  92. legend.position = "bottom",
  93. legend.title = element_blank(),
  94. legend.text = element_text(size = 8),
  95. plot.title = element_text(hjust = 0.5, size = 10, face="bold"),
  96. plot.margin = margin(4,6,4,6)
  97. ) +
  98. labs(
  99. title = gsub("^m|%","",context_name),
  100. y = "Mean methylation (%)",
  101. x = NULL
  102. )
  103. }
  105. # ==========================
  106. # 6. Generate panels
  107. # ==========================
  108. p1 <- plot_context("mCG%")
  109. p2 <- plot_context("mCHG%")
  110. p3 <- plot_context("mCHH%")
  112. # ==========================
  113. # 7. Save
  114. # ==========================
  115. final_plot <-
  116. (p1 + p2 + p3) +
  117. plot_layout(ncol = 3, guides = "collect") +
  118. plot_annotation(tag_levels = "a")
  120. final_plot <- final_plot &
  121. theme(
  122. plot.tag = element_text(size = 12, face = "bold"),
  123. plot.tag.position = c(0.01,0.98),
  124. legend.position="bottom",
  125. legend.key.width = unit(0.6,"cm"),
  126. legend.direction="horizontal"
  127. )
  129. final_plot
  131. ggsave(
  132. "Figure2.tiff",
  133. final_plot,
  134. width=180,
  135. height=110,
  136. units="mm",
  137. dpi=600,
  138. compression="lzw",
  139. device = ragg::agg_tiff
  140. )

plot_Figure2.R at commit fc883fd, no license · at the source

Overview

Authors: Yongfeng He1,2, Xinhua Zou1,3, Menghan Wu1,3, Jianwei Wang1
ORCID iDs: Xinhua Zou
  1. Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
  2. State Key Laboratory of Breeding Biotechnology and Sustainable Aquaculture, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
  3. University of Chinese Academy of Sciences, Beijing, China
Institutions: Chinese Academy of Sciences (China); Institute of Hydrobiology (China); University of Chinese Academy of Sciences (China)
Journal: Scientific data, volume 13, issue 1, article 895
Dates: received 10 July 2025; accepted 14 April 2026; published online 17 April 2026
Type: Data paper · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41597-026-07270-8 · PMID 41997990 · PMCID PMC13272678 · OpenAlex W7154730081
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: genetics / omics (modality), methods / tools (subfield)
Methods: Smoothing, state filtering, decompositions
Keywords: DNA methylation, Predictive markers
MeSH: Aging*, Brain*, Cyprinidae*, DNA Methylation*, Animals, Female, Genome, Whole Genome Sequencing (* major topic)
Topic: Epigenetics and DNA Methylation (Molecular Biology, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: National Natural Science Foundation of China (National Science Foundation of China) (32473164)
Citations: not cited yet (Europe PMC); 20 references in the paper

Abstract

Gobiocypris rarus is an endemic cyprinid fish in China with a lifespan of up to nine years under artificial breeding conditions and is widely used in biological and toxicological studies. However, genome-wide DNA methylation profiles across adult aging stages in this species remain limited. In this study, brain samples from 27 female individuals at three representative adult stages (8, 44, and 74 months) were subjected to whole-genome bisulfite sequencing (WGBS). After quality filtering to remove low-quality reads, adaptor sequences, and ambiguous bases, an average of 41.36 Gb clean bases per sample was obtained. Three methylation contexts (CG, CHG, and CHH) were identified, with average methylation proportions of 79.95 ± 1.01%, 1.19 ± 0.14% and 1.13 ± 0.10%, respectively. This dataset provides a high-resolution brain methylome resource across representative adult stages of rare minnow and enables future comparative and integrative epigenetic analyses in teleost species.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above, with 2 matches between paragraphs and lines of code.

He-Yongfeng/rare_minnow_brain_methylome_analysis

License: none: the authors keep all their rights
State: the link answers, verified on 29 September 2026
Evidence: files inventoried
Commit: fc883fd7448f39edd87ca36a34253cd589baa621, 19 March 2026
Languages: R (9)
Size: 13 files, 9 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: data.table (3 files), patchwork (3 files), tidyverse (3 files), ggplot2 (2 files)
Availability: 1 check, the latest on 29 September 2026: the link answers
  • 29 September 2026: the link answers
10 files
At the source: github.com/He-Yongfeng/rare_minnow_brain_methylome_analysis

Zenodo 19108131

License: CC-BY-4.0
State: the link answers, verified on 29 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: data.table (3 files), patchwork (3 files), tidyverse (3 files), ggplot2 (2 files)
Availability: 1 check, the latest on 29 September 2026: the link answers (HTTP 200)
  • 29 September 2026: the link answers (HTTP 200)
10 files
At the source:

Code availability

Data processing relied on SOAPnuke and BSMAP. Downstream statistical analyses and visualization were performed in R (version 4.5.2). All analysis scripts are available on GitHub (https://github.com/He-Yongfeng/rare_minnow_brain_methylome_analysis) and archived in Zenodo (10.5281/zenodo.19108131).

Reproduced under the paper's license (CC BY), from the paper cited above.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 18 scripts, each with its path and the digest of its content;
  • 2 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability

The cleaned WGBS sequencing reads are available in the NCBI Sequence Read Archive (SRA) under accession number SRP598880, associated with BioProject PRJNA128812317. Processed methylation data have been deposited in Figshare and are publicly available at 10.6084/m9.figshare.31769062. All files can be accessed and downloaded without restriction.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 2 keywords, 8 MeSH terms, 1 funder, 16 references.

Cite

This paper

He, Y., Zou, X., Wu, M., & Wang, J. (2026). Whole-genome DNA methylation profile of female Gobiocypris rarus brains at three age stages. Scientific data, 13(1), 895. https://doi.org/10.1038/s41597-026-07270-8

BibTeX

@article{he2026whole,
author = {He, Yongfeng and Zou, Xinhua and Wu, Menghan and Wang, Jianwei},
title = {{Whole-genome DNA methylation profile of female Gobiocypris rarus brains at three age stages}},
journal = {Scientific data},
year = {2026},
month = apr,
volume = {13},
number = {1},
pages = {895},
publisher = {Nature Publishing Group},
issn = {2052-4463},
doi = {10.1038/s41597-026-07270-8},
url = {https://doi.org/10.1038/s41597-026-07270-8},
pmid = {41997990},
pmcid = {PMC13272678}
}

RIS

TY - JOUR
AU - He, Yongfeng
AU - Zou, Xinhua
AU - Wu, Menghan
AU - Wang, Jianwei
TI - Whole-genome DNA methylation profile of female Gobiocypris rarus brains at three age stages
T2 - Scientific data
J2 - Sci Data
PY - 2026
DA - 2026/04/17
VL - 13
IS - 1
SP - 895
SN - 2052-4463
PB - Nature Publishing Group
DO - 10.1038/s41597-026-07270-8
UR - https://doi.org/10.1038/s41597-026-07270-8
LA - en
ER -

CSL-JSON

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