Bioinformatics for plant and agricultural discoveries in the age of multiomics: A review and case study of maize nodal root growth under water deficit.
Juexin WangSen SidharthShuai ZengYuexu JiangYen On ChanZhen LyuTyler McCubbinRachel MertzRobert E SharpTrupti JoshiPublished in: Physiologia plantarum (2022)
Advances in next-generation sequencing and other high-throughput technologies have facilitated multiomics research, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, and phenomics. The resultant emerging multiomics data have brought new challenges as well as opportunities, as seen in the plant and agriculture science domains. We reviewed several bioinformatic and computational methods, models, and platforms, and we have highlighted some of our in-house developed efforts aimed at multiomics data analysis, integration, and management issues faced by the research community. A case study using multiomics datasets generated from our studies of maize nodal root growth under water deficit stress demonstrates the power of these datasets and some other publicly available tools. This analysis also sheds light on the landscape of such applied bioinformatic tools currently available for plant and crop science studies and introduces emerging trends and how they may affect the future.
Keyphrases
- data analysis
- single cell
- climate change
- high throughput
- rna seq
- public health
- mass spectrometry
- lymph node
- healthcare
- neoadjuvant chemotherapy
- mental health
- heavy metals
- copy number
- gene expression
- cell wall
- squamous cell carcinoma
- current status
- big data
- dna methylation
- machine learning
- human health
- heat stress
- radiation therapy
- label free