Varies of the genomics datasets were either integrated directly or following a re-analyzed procedure.
Category | NCBI/NGDC Project number1 | Sequencing Data Type | Re-analyzed By | Ref Genome(s) | Fully/Partially Integrated |
---|---|---|---|---|---|
Chen et al. 2021 (PNAS)2 | PRJNA558072 | ChIP-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Partially |
Cho et al. 2013 (Plos One)3 | PRJNA185754 | smRNA-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
Fan et al. 2021 (Plant Genome)4 | PRJNA626495 | smRNA-seq | Zhixia Xiao | Gmax_Wm82_a4v1 | Fully |
HML unpublished data (Huang) | PRJNA657378 | ATAC-seq, ChIP-seq, DAP-seq, RNA-seq | NA | Gmax_Wm82_a4v1 | Fully |
HML unpublished data (Yung) | PRJNA753632 | ChIP-seq, RNA-seq | NA | Gmax_Wm82_a4v1 | Fully |
Hossain et al. 2016 (New Phytologist)5 | PRJNA354570 | WGBS | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
Huang et al. 2021 (Genomics) 6 | PRJNA716521 | ChIP-seq, RNA-seq | NA | Gsoja_W05v1 | Fully |
Ji et al. 2019 (The Plant Cell)7 | PRJNA369414 | RNA-seq, smRNA-seq, WGBS | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
Jo et al. 2020 (PNAS)8 | PRJNA395064, PRJNA395160, PRJNA590535, PRJNA590536, PRJNA590537 | ChIP-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
Kim et al. 2015 (Plant Physiology)9 | PRJNA264602 | WGBS | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
Lin et al. 2017 (PNAS)10 | PRJNA140453, PRJNA140081, PRJNA165677, PRJNA151265, PRJNA165675, PRJNA165677, PRJNA178372 | RNA-seq, smRNA-seq, WGBS | Qianwen Wang | Gmax_Wm82_a4v1 | Partially |
Lu et al. 2019 (Nature Plants)11 | PRJNA527732 | ATAC-seq, ChIP-seq, RNA-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Partially |
Niyikiza et al. 2020 (The Plant Journal)12 | PRJNA560858 | RNA-seq, WGBS | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
Pelletier et al. 2017 (PNAS)13 | PRJNA389820 | ChIP-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Partially |
PRJNA248218 (smRNA) | PRJNA248218 | smRNA-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
PRJNA248303 (smRNA) | PRJNA248303 | smRNA-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
PRJNA248316 (smRNA) | PRJNA248316 | smRNA-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
PRJNA248403 (smRNA) | PRJNA248403 | smRNA-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
PRJNA395060 (ABI3) | PRJNA395060 | ChIP-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
PRJNA395102 (bZIP67) | PRJNA395102 | ChIP-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
PRJNA472968 (Histone modification) | PRJNA472968 | ChIP-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
PRJNA558071 (AGL62) | PRJNA558071 | ChIP-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
PRJNA638945 (WRI1) | PRJNA638945 | ChIP-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
PRJNA637947 (GRF5) | PRJNA639847 | ChIP-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
PRJNA638949 (HB22) | PRJNA638949 | ChIP-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
Rambani et al. 2020 (New Phytologist)14 | PRJNA534066 | RNA-seq, WGBS | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
Song et al. 2013 (Molecular Plant)15 | PRJNA156279, PRJNA156281, PRJNA156283 | WGBS, smRNA-seq, RNA-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Partially |
Wang et al. 2020 (Genomics)16 | PRJAN629642, PRJAN629646, PRJAN626514 | ChIP-seq, RNA-seq | NA | Gmax_Wm82_a4v1 | Fully |
Wang et al. 2021 (The Plant Cell)17 | PRJNA657728 | ATAC-seq, ChIP-seq, RNA-seq, WGBS | Qianwen Wang | Gmax_Wm82_a4v1, Gsoja_W05v1 | Partially |
Lin et al. (Plant Physiology)18 | Public Dataset | RNA-seq | NA | Gmax_Wm82_a2v1, Gsoja_W05v1 | Partially |
Xie et al. 2019 (NC)19 | PRJNA48670 | RNA-seq | NA | Gsoja_W05v1 | Fully |
Huang et al. 2021 (Genes)20 | PRJNA7165217 | ATAC-seq, ChIP-seq, RNA-seq | NA | Gsoja_W05v1 | Fully |
Liu et al. 2018 (PCE)21 | PRJNA432861 | RNA-seq | Qianwen Wang | Gmax_Wm82_a4v1 | Fully |
Shen et al. 2019 (SCI CHINA LIFE SCI)22 | PRJCA000902 | smRNA-seq, RNA-seq | Qianwen Wang | Gmax_ZH13_v2 | Fully |
Chen M, Lin JY, Wu X, et al. Comparative analysis of embryo proper and suspensor transcriptomes in plant embryos with different morphologies. Proc Natl Acad Sci U S A. 2021;118(6). doi:10.1073/pnas.2024704118 ↩︎
Cho YB, Jones SI, Vodkin L. The Transition from Primary siRNAs to Amplified Secondary siRNAs That Regulate Chalcone Synthase During Development of Glycine max Seed Coats. Freitag M, ed. PLoS One. 2013;8(10):e76954. doi:10.1371/journal.pone.0076954 ↩︎
Fan K, Wong‐Bajracharya J, Lin X, et al. Differentially expressed microRNAs that target functional genes in mature soybean nodules. Plant Genome. 2021;14(2):1-14. doi:10.1002/tpg2.20103 ↩︎
Hossain MS, Kawakatsu T, Kim K Do, et al. Divergent cytosine DNA methylation patterns in single-cell, soybean root hairs. New Phytol. 2017;214(2):808-819. doi:10.1111/nph.14421 ↩︎
Huang M, Zhang L, Zhou L, et al. An expedient survey and characterization of the soybean JAGGED 1 (GmJAG1) transcription factor binding preference in the soybean genome by modified ChIPmentation on soybean protoplasts. Genomics. 2021;113(1):344-355. doi:10.1016/j.ygeno.2020.12.026 ↩︎
Ji L, Mathioni SM, Johnson S, et al. Genome-Wide Reinforcement of DNA Methylation Occurs during Somatic Embryogenesis in Soybean. Plant Cell. 2019;31(10):2315-2331. doi:10.1105/tpc.19.00255 ↩︎
Jo L, Pelletier JM, Hsu SW, Baden R, Goldberg RB, Harada JJ. Combinatorial interactions of the LEC1 transcription factor specify diverse developmental programs during soybean seed development. Proc Natl Acad Sci U S A. 2020;117(2):1223-1232. doi:10.1073/pnas.1918441117 ↩︎
Kim K Do, El Baidouri M, Abernathy B, et al. A Comparative Epigenomic Analysis of Polyploidy-Derived Genes in Soybean and Common Bean. Plant Physiol. 2015;168(4):1433-1447. doi:10.1104/pp.15.00408 ↩︎
Lin J-Y, Le BH, Chen M, et al. Similarity between soybean and Arabidopsis seed methylomes and loss of non-CG methylation does not affect seed development. Proc Natl Acad Sci. 2017;114(45):E9730-E9739. doi:10.1073/pnas.1716758114 ↩︎
Lu Z, Marand AP, Ricci WA, Ethridge CL, Zhang X, Schmitz RJ. The prevalence, evolution and chromatin signatures of plant regulatory elements. Nat Plants. 2019;5(12):1250-1259. doi:10.1038/s41477-019-0548-z ↩︎
Niyikiza D, Piya S, Routray P, et al. Interactions of gene expression, alternative splicing, and DNA methylation in determining nodule identity. Plant J. 2020;103(5):1744-1766. doi:10.1111/tpj.14861 ↩︎
Pelletier JM, Kwong RW, Park S, et al. LEC1 sequentially regulates the transcription of genes involved in diverse developmental processes during seed development. Proc Natl Acad Sci U S A. 2017;114(32):E6710-E6719. doi:10.1073/pnas.1707957114 ↩︎
Rambani A, Pantalone V, Yang S, et al. Identification of introduced and stably inherited DNA methylation variants in soybean associated with soybean cyst nematode parasitism. New Phytol. 2020;227(1):168-184. doi:10.1111/nph.16511 ↩︎
Song Q-X, Lu X, Li Q-T, et al. Genome-Wide Analysis of DNA Methylation in Soybean. Mol Plant. 2013;6(6):1961-1974. doi:10.1093/mp/sst123 ↩︎
Wang Q, Yung W, Wang Z, Lam H. The histone modification H3K4me3 marks functional genes in soybean nodules. Genomics. 2020;112(6):5282-5294. doi:10.1016/j.ygeno.2020.09.052 ↩︎
Wang L, Jia G, Jiang X, Cao S, Chen ZJ, Song Q. Altered chromatin architecture and gene expression during polyploidization and domestication of soybean. Plant Cell. Published online March 17, 2021:1-17. doi:10.1093/plcell/koab081 ↩︎
Lin X, Lin W, Ku Y-S, et al. Analysis of Soybean Long Non-Coding RNAs Reveals a Subset of Small Peptide-Coding Transcripts. Plant Physiol. 2020;182(3):1359-1374. doi:10.1104/pp.19.01324 ↩︎
Xie M, Chung CYL, Li MW, et al. A reference-grade wild soybean genome. Nat Commun. 2019;10(1):1-12. doi:10.1038/s41467-019-09142-9 ↩︎
Huang MK, Zhang L, Zhou LM, Yung WS, Li MW, Lam HM. Genomic features of open chromatin regions (Ocrs) in wild soybean and their effects on gene expressions. Genes. 2021;12(5). doi:10.3390/genes12050640 ↩︎
Liu A, Xiao Z, Li MW, et al. Transcriptomic reprogramming in soybean seedlings under salt stress. Plant Cell Environ. 2019;42(1):98-114. doi:10.1111/pce.13186 ↩︎
Shen Y, Du H, Liu Y, et al. Update soybean Zhonghuang 13 genome to a golden reference. Sci China Life Sci. 2019;62(9):1257-1260. doi:10.1007/s11427-019-9822-2 ↩︎