AsianScientist (Jul. 20, 2026) – Wheat is a staple crop for more than a third of the world’s population and supplies a large share of the calories and proteins that people live on. Improving wheat, though, has always involved a lot of field work and fundamental research. A breeder can see that one wheat variety yields well or shrugs off drought, but not which cells, in which tissue, at which stage in the plant’s life, actually produce the trait. Spatial omics is starting to improve this process.
The limitation lies in the traditional transcriptomics methods themselves. Bulk RNA-sequencing reads the molecular profile in a tissue sample, but only by grinding the tissue up. You learn what is present but lose all trace of where it was expressed or which cell it came from. The location of a cell is not trivial: its position in a leaf, root or grain often determines what it does.
“Desirable traits—such as drought tolerance, disease resistance, and grain size—can be determined through conventional sequencing approaches,” said Professor Rajeev Varshney of Murdoch University. “However, the picture painted is quite broad.”
Spatial omics preserves the tissue intact and reveals which gene is switched on, in which cell, in which part of the plant. This represents a shift in resolution from knowing that a wheat variety’s genes raise yield to seeing which cells, in which parts and at which stage, drive it.
Spatial omics work on the developing wheat spike has exposed molecular gradients that appear before any structure forms, helping explain why some florets set grain while others fail. Mapping the grain itself has revealed which of wheat’s three sub-genomes does the work for specific gene functions.
A genome too big for one lab
The details of sub-genomes also explains why wheat research has lagged rice and most other crops. Wheat genome contains approximately 17 billion bases, significantly larger than that of rice, and it is hexaploid—three complete sub-genomes in one plant species. A draft reference wheat genome sequence was not available until 2017.
The tissue is challenging to handle. Stiff cell walls hinder precise sectioning, and central vacuoles can occupy up to 90% of a cell’s volume. Experiments are costly, and the datasets are enormous. As Professor Zhong-Hua Chen of Adelaide University points out, no single lab—or even a handful working together—can bear the cost alone.
This is the impetus driving the Wheat Spatial Omics Consortium (WSOC), launched in November 2025 under the wider STOC Plant initiative. Co-led by Adelaide University alongside BGI-Research, Xianghu Laboratory, and Murdoch University, it now brings together more than 30 institutions across nine countries.
The membership was assembled for its versatility, with some groups bringing genome assemblies and the bioinformatics to handle them, while others conduct field-breeding programmes with access to both elite wheat varieties and rare landraces—stores of stress-tolerance traits that have been lost in modern varieties. The sequencing technology and the AI that converts extensive atlases into breeding predictions are sourced from elsewhere. Together, the WSOC are constructing a unified, standardised spatial omics reference across the entire wheat life cycle, including plants under stresses, which any breeder can access.
Putting the tools in more hands
None of this would be feasible without the technology that brought single-cell resolution to plants. MGI’s Stereo-seq technology, one of the leading spatial omics technologies, pushed spatial transcriptomics to single-cell and even sub-cellular resolution across large tissue areas, routinely resolving a thousand or more genes in a single cell.
Additionally, running it on MGI’s own sequencing platforms has helped bring the cost of each experiment down. The technology has since reached labs across Singapore, Japan, Korea, India and Australia. MGI has also taken on the less glamorous work of widening access: supporting the STOC Plant initiative that was initiated by BGI-Research, and funding grants that put the equipment into more labs across the Asia-Pacific.
“We believe spatial omics can provide a new level of biological understanding that helps researchers develop more resilient and sustainable crop varieties,” says Dr Xin Liu, Senior Vice President of MGI.
Heat, drought and new diseases are eroding wheat yields just as demand climbs, and conventional breeding has not kept pace. Ultimately, this increased understanding can support food security under global climate change.
A recent roadmap for wheat spatial omics led by Prof. Chen, Prof. Varshney and three other senior authors was published in Nature Genetics in April 2026. They are clear about the obstacles that remain—imaging that is not yet sharp enough; analysis tools still built for animal and human tissue rather than plant; and predictive models that lean on AI. Spatial data, paired with gene editing and precision phenotyping, should sharpen wheat breeding decisions and cut the years it takes to develop a variety. Furthermore, an open atlas allows any national wheat breeding programme and any university lab with no sequencing centre in developing countries to, work from the same data as the best-resourced research institutes.
MGI is betting that the future of crop improvement lies where spatial omics, AI, genomics and precision breeding meet.
Contact the MGI team at https://global-mgitech.com/contact/ to find out more about how STOmics solutions powered by Stereo-seq technology can support your work.
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Source: MGI Technologies; Image: Unsplash
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