Penghao Wang

1. Barley PanTs Supplementary Data1-8_10-14.xlsx
Ten Datasets referred to in the main text (Supplementary Data 1-10), presented in tabular format as separate sheets in a joint Excel formatted file.
Supplementary Data 1: Basic statistics of the RTDs
Supplementary Data 2: Ordering of genotypes incorporated into the linear pan-genome.
Supplementary Data 3: Gene categories of GsRTD
Supplementary Data 4: Alternative splicing events for highly expressed transcripts from core-single-copy genes (average TPM > 10)
Supplementary Data 5: Gene copy number variation cluster significantly correlated with the gene expression.
Supplementary Data 6: C-repeat/DRE-Binding Factor (CBF) genes identifier in GsRTD and their location in the genome
Supplementary Data 7: Genotypes with the 141Mb 7H inversion and non-inversion
Supplementary Data 8: Differentially expressed genes in the 7H inversion.
Supplementary Data 10: Detailed example of a split pattern in Golden Promise
Supplementary Data 11: Barley cv. Morex Expression Atlas Metadata
Supplementary Data 12: GA-Pathway gene expression in PanTs experiment
Supplementary Data 13: Yield and agro data for Ga2ox3-7
Supplementary Data 14: Statistics GA2ox and 7

2. Supplementary Data9.csv A csv file containing genotype-specific co-expression network results (modules and community assignments) with annotation and MorexV3 gene IDs.

3. Supplementary Data15.txt This tab delimited text file is too large for inclusion in the main Supplementary Data file and contains the details of how genes/transcripts from the genotype specific RTDs map onto genes in PanBaRT20.

This dataset comprises cross-species phenotype data for barley, oat, lupin, and chickpea. The collected data consisted of RNA-seq from Lupin and phenotype data from barley, oat and chickpea, which included many key agronomic traits, such as flowering time, plant height, grain yield, grain plumpness, growing index and tolerant index. The phenotype data were collected from 2014 to 2025 from various trials across Western Australia, including data from approximately 900 barley, 600 oat and 500 chickpea accessions. This dataset is a combination of outputs from multiple GRDC-funded projects: UMU2404-010RTX, UMU2404-010RTX, UMU2302-007RSX, UMU1606-002RMX, UMU1406-002RTX, UMU1903-004RTX, UMU2303-003RTX and UMU2306-008RSX.

Phenotype and genotype data collected from the GRDC-funded project UMU2303-003RTX (Developing genetic tools to facilitate breeder use and deployment of high value acid soils tolerant chickpea germplasm). The genotype data consisted of approximately 4,300 high-quality SNP markers of 520 chickpea accessions. The phenotype data, including the tolerance index, plant growth data and yield-related traits, were collected from multiple trials across Australia from 2023 to 2025.

RNA-seq data from leaf tissues of Narrow-leaf Lupin isogenic lines (WD_Bi and WD_Sw) derived from the cross of 83A:275 (domesticated narrow-leafed lupin) and P27255 (wild narrow-leafed lupin) were selected to identify candidate alkaloid regulators Leaf tissues of the WD_Bi and WD_Sw were used for RNA extraction by Triture RNA extraction mix. The mRNA sequencing was performed on an Illumina Novaseq 6000 platform, and 150 bp paired-end reads were generated.

Phenotype and genotype data of 308 barley accessions from a worldwide collection. The genotype data consists of over 30,000 high-quality SNPs across approximately 300 accessions. The phenotype data were collected from 308 barley accessions from a worldwide collection, which includes stomatal density, origin, row-type and growing habit. The data were outputs of the GRDC-funded project UMU2302-007RSX (Reducing stomatal density in barley to improve drought tolerance).

This dataset contains detailed analysis of crop foliar fertilisers that will provide new knowledge for the creation of improved application technologies and formulations to improve the efficiency of plant uptake and utilisation of foliar applied nutrients. This is the output of the GRDC-funded project: Synchrotron Postdoctoral Fellow no. 4: Plants - Novel foliar fertilisers and nutrition trait diversity of grains (UMU2001_001RTX). The study involves determining the background levels of zinc in a collection of wheat grains var. Scepter from the NVT sites across Australian agricultural regions; elemental analysis of wheat grains treated with zinc-foliar fertilizers and elemental mapping analysis using the X-ray fluorescence microscopy (XFM) beamline at the Australian Synchrotron (AS) facilities of treated grains. Wheat grain samples from NVT sites across Australia for over 5 years were collected and analysed for zinc concentrations. Novel foliar fertilizers containing silica mesoporous nanoparticles and lipid chelators namely ionophores were produced and compared against conventional forms of Zn sich ZnSO4 on wheat plants under controlled conditions. Grains from treated wheat plants were harvested and studied at the XFM beamline at the AS facilities. Data collected at the XFM beamline were collected and stored at the AS premises. Data analysis by remote access from Murdoch University to the AS's raw data is ongoing. GEOPIXE is the software installed at AS that is used remotely to conduct data analysis by generating elemental maps of wheat grains collected at the XFM. SigmaPlot software is used for statistical analysis. Methods of metadata analysis, production of foliar formulations, and data analysis using the GEOPIXE software are in preparation for publication.

This dataset is the output of the GRDC funded project (DAW2205-004RTX). The project involving a collaboration between Western Australia Department of Primary Industries and Regional Development (DPIRD), Murdoch University and Agriculture Victoria aims to initiate and lay the foundation of research and breeding for acid soil tolerance in chickpea. Under this one-year initiation phase, the project team will screen and genotype targeted germplasm collection and structured populations from crosses of cultivated varieties with wild relatives known to exhibit tolerance to soil acidity. The project will identify confirmed sources of inherent tolerance, bulk up seed for future research, fine tune phenotyping methodology under lab/glasshouse conditions and develop genetic (genomic) information that chickpea pre-breeders and breeders will use in developing varieties that would sustain yield potential of new chickpea varieties on acidic soils.