Table 1.
Reference list for omics-driven research on peanut seed development.
| Re-sequencing data were employed for SNP genotyping to construct high-resolution genetic maps, identify quantitative trait loci (QTL), or conduct genome-wide association studies (GWAS) focusing on seed-related traits | |||||
|---|---|---|---|---|---|
| Omics technology | Traits/application | Reference | Omics Data | Traits | Reference |
| SLAF-seq | Yield-related Traits/QTL | Wang et al., 2018b | BSA-seq | Sucrose content/QTL | Guo et al., 2023 |
| SLAF-seq | Seed weight/QTL | Zhang et al., 2019 | BSA-seq | Red testa/QTL | Zhang et al., 2022b |
| SLAF-seq | Seed weight/QTL | Zhao et al., 2022 | ddRAD-seq | Yield-related traits/GWAS | Wang et al., 2019; |
| SLAF-seq | Oleic and Linoleic Acid/QTL | Hu et al., 2018 | ddRAD-seq | Fatty acid components/GWAS | Zhang et al., 2021 |
| WGS-seq | Quality traits/QTL | Sun et al., 2022 | Axiom_Arachis2 SNP array | Seed weight/GWAS | Zhao et al., 2022 |
| WGS-seq | Sucrose content/QTL | Wang et al., 2024 | WGS-seq | Yield-related traits/GWAS | Zhou et al., 2021 |
| WGS-seq | Purple testa/QTL | Zhao et al., 2020b | WGS-seq | Fatty acid components/GWAS | Zhou et al., 2022 |
| ddRAD-seq | Trans-resveratrol content/QTL | Luo et al., 2021 | Axiom_Arachis2 SNP array | Fatty acid components/GWAS | Otyama et al., 2022 |
| ddRAD-seq | Oil content/QTL | Liu et al., 2020c | SLAF-seq | Seed weight/GWAS | Zhang et al., 2017 |
| Transcriptome, Protome, Metabolome data or multi-omics data joint analysis were employed for seed development or seed-related traits | |||||
| RNA-seq | SD | Clevenger et al., 2016 | RNA-seq | Sucrose content | Li et al., 2021a |
| RNA-seq | SD | Gupta et al., 2016 | RNA-seq | Seed coat color | Wan et al., 2016 |
| RNA-seq | SD | Yin et al., 2013 | RNA-seq | Seed coat color | Huang et al., 2020 |
| RNA-seq | SD | Zhang et al., 2012 | Proteomic | SD and lipid metabolism | Wang et al., 2016; |
| RNA-seq | SD | Chen et al., 2013 | Proteomic | SD and allergen proteins | Li et al., 2020 |
| RNA-seq | SD | Zhu et al., 2014 | RNA-seq and DNA Methylation | Oil content | Liu et al., 2022; |
| RNA-seq | SD | Zhang et al., 2016 | Methylation | SD and seed size | Li et al., 2023 |
| RNA-seq | SD | Chen et al., 2016a | CircRNAs | SD and seed size | Feng et al., 2019 |
| RNA-seq | SD | Zhao et al., 2020a | miRNA | SD | Chen et al., 2019a |
| RNA-seq | SD | Chen et al., 2019b | miRNA | SD | Ma et al., 2018 |
| RNA-seq | SD | Yu et al., 2015 | Metabolomics | Seed coat color | Zhang et al., 2022a |
| RNA-seq | SD | Liu et al., 2020a | Metabolomics | SD | Kefale et al., 2023 |
| RNA-seq | SD | Li et al., 2017 | Metabolomics | SD | Li et al., 2022 |
| RNA-seq | SD | Yang et al., 2020 | QTL-seq and RNA-seq | Pod length | Lv et al., 2024 |
| RNA-seq | Seed size | Wu et al., 2022 | QTL-seq and RNA-seq | Seed weight | Wang et al., 2022 |
| RNA-seq | Seed size | Li et al., 2021b | Metabolomics-Transcriptomics joint analysis | Seed coat color | Xue et al., 2021 |
| RNA-seq | Seed size and Oil content | Guo et al., 2022 | Metabolomics-Transcriptomics joint analysis | Seed coat color | Hu et al., 2021 |
| RNA-seq | Oil Content | Wang et al., 2018a | Metabolomics-Transcriptomics joint analysis | Seed coat color | Wang et al., 2022 |
| RNA-seq | Seed size and oil content | Yang et al., 2023 | Metabolomics-Transcriptomics joint analysis | SD | Li et al., 2022 |
| RNA-seq | Oleic acid content | Liu et al., 2018 | Metabolomics-Transcriptomics joint analysis | Pod size | Lv et al., 2022 |
| Lipidomics and proteomicsjoint analysis | Oleic acid content | Liu et al., 2020 | |||
WGS-seq, Whole genome resequencing; BSA-seq, Bulked segregant analysis based on deep sequencing; SLAF-seq, Specific locus amplified fragment sequencing; ddRAD-seq, Double digest restriction-site associated sequencing; SD, Seed developmental.