Multi-omics approach to the systems biology to understand cotton fiber development

The highly polarized cotton fiber cell that emerges from the seed coat surface is the foundation of a multi-billion-dollar global textile industry. At present, the ability to predict and control fiber traits is limited by our lack of understanding regarding the primary controls governing the rate, duration, and patterns of fiber cell growth. To shed light on the mechanisms and create predictive control networks, we conducted quantitative “-omics” profiling of RNA, protein, protein complexes, and cell wall polysaccharides as a function of measured fiber traits at an unprecedented temporal resolution from 5-24 days post-anthesis.

A gene co-expression network using about 50,000 reliable transcript profiles was constructed and the network analysis, with the daily sampling over a 20-day interval, revealed unexpected oscillations and compositions of molecular phenotypes across fiber development. Further we integrated the time-series transcriptome analysis with proteomic data to reconstruct gene regulatory network models and analyzed as a function of fiber phenotypes and cell wall architectures to present candidate network modules of cellular and molecular control. The results revealed the transition to secondary cell wall synthesis is not clearly associated with a decreased growth rate. These also enabled us to identify a network module that predicts systems level control of 2º cell wall synthesis. The module is correlated with the dynamic change of cellulose contents during fiber development and includes proteins mainly involve in cell wall biosynthesis and modification, including cellulose synthetases, glycoside hydrolases, and glycosyltransferases. We are currently organizing the data from our multi-omics approach so that it is findable and useful to the plant community with the goal of accelerating the genetic engineering of cotton fiber traits.