2021
DOI: 10.1016/j.tplants.2021.06.008
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How noncoding open chromatin regions shape soybean domestication

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Cited by 3 publications
(1 citation statement)
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“…In contrast to human or model plants (e.g., Arabidopsis), there are many databases with abundant sequencing data for understanding the function of noncoding regions, such as the human ENCODE (https://www.encodeproject.org accessed on 1 May 2024) and the Arabidopsis Cistrome database [20]. Although soybean also has abundant DNA resequencing data characterizing the single nucleotide polymorph (SNP) or structural variation (SV) at the genomic level, for example, the recently published soybean PAN-genome data [21], few high-throughput sequencing data (e.g., ATAC-seq) [22][23][24] have been aimed at finding these functional non-coding elements (e.g., motifs) in the soybean genome. Compared to the ChIP-seq method [14], a traditional strategy for discovering new motifs, DAP-seq [15] is able to select the DNA fragments directly bound by the recombinant TF in vitro, which showed some advantage over the ChIP-seq in finding motifs.…”
Section: Discussionmentioning
confidence: 99%
“…In contrast to human or model plants (e.g., Arabidopsis), there are many databases with abundant sequencing data for understanding the function of noncoding regions, such as the human ENCODE (https://www.encodeproject.org accessed on 1 May 2024) and the Arabidopsis Cistrome database [20]. Although soybean also has abundant DNA resequencing data characterizing the single nucleotide polymorph (SNP) or structural variation (SV) at the genomic level, for example, the recently published soybean PAN-genome data [21], few high-throughput sequencing data (e.g., ATAC-seq) [22][23][24] have been aimed at finding these functional non-coding elements (e.g., motifs) in the soybean genome. Compared to the ChIP-seq method [14], a traditional strategy for discovering new motifs, DAP-seq [15] is able to select the DNA fragments directly bound by the recombinant TF in vitro, which showed some advantage over the ChIP-seq in finding motifs.…”
Section: Discussionmentioning
confidence: 99%