Evolution of moss leaf-like organs through variations in deeply conserved developmental principles
Abstract
Leaves and leaf-like organs with laminar structures and determinate growth arose multiple times independently in land plants. The cellular basis of leaf development is well characterized in flowering plants, and molecular studies have shown that the plant hormone auxin plays a central role in this process, orchestrating cellular growth and differentiation. Auxin is also crucial for the formation of phyllids, the leaf-like organs of bryophytes, yet its precise role in morphogenesis remains unclear. More broadly, whether similar developmental principles are shared across distantly related evolutionary lineages is unknown. Here, we combine live-imaging, genetics, pharmacological treatments, and modeling to investigate the cellular and molecular basis of phyllid development in the model moss Physcomitrium patens. By tracking phyllid morphogenesis from a single initial cell to full maturity, we uncover the cellular growth dynamics underlying organ development. We demonstrate that auxin spatially inhibits cell divisions and promotes cellular elongation and differentiation. However, unlike in vascular plants, moss PIN transporters do not participate in polar auxin transport during phyllid development but mainly reduce intracellular auxin concentration. These findings indicate that while auxin's role in organogenesis is conserved, its transport mechanisms have diverged across land plants. Overall, our study reveals shared principles of planar organ morphogenesis, highlighting how the repeated deployment of similar developmental strategies, with lineage-specific variations, drove the convergent evolution of leaves and leaf-like organs.
Repository Description
This repository and it's companion Zenodo repository contain all data required for the quantifications presented, as well as the files needed to run the models used in this study.
Part I: Data.zip
The dataset primarily includes raw .csv files directly exported from MorphoGraphX (the main image processing and analysis software used), as well as organized .xlsx files. Detailed instructions for data extraction are provided in the Methods section of the manuscript.
All files are organized into ten folders corresponding to the figures in the study (Fig. 1--4; Fig. S1--14), along with an additional folder containing information necessary to run the quantification scripts.
File Naming and Structure
All data were obtained from three biological replicates (time-lapse series), labeled "01", "02", and "03" (sample identity), for each genotype or treatment (WT, pinapinb, WT+NAA, pinapinb+NAA). The replicate labeled "01" corresponds to the sample shown in the figures, while "02" and "03" represent the additional replicates.
Data are further organized into subfolders named after the relevant figure panels. For example, the folder "Fig_1_H-K" contains all data (e.g., cell division, area expansion, and distance from the base for each cell) used to generate panels Fig. 1H--K. Within these folders, additional subfolders may be present, categorized by genotype or treatment (e.g., "WT"), sample identity (e.g., "01"), or quantification type (e.g., "CellDivision").
To avoid redundancy, datasets are stored only once, in the folder corresponding to the figure panel where they are first presented. For instance, data on cell division in upper WT phyllids appear in Fig. 1 to Fig. 4, Fig. S4, Fig. S9 and Fig. S12, but the original files are located only in the "Fig_1" folder.
The files labeled "DISTANCE_Absolute_BASE" contain the absolute distance of each cell from the phyllid base. These values were converted to relative distances (percentages) using the accompanying scripts.
Each individual quantification file (.csv or .xlsx) follows the naming convention:
"SampleNumber_DevelopmentTime_QuantificationType" (e.g., "01_4--4.5days_CellDivisions").
Structure of Data Files
Fig_1
Fig_1_E
Contains csv files of Merophyte size value.
Fig_1_H-K
- WT
- AreaExpansion: contains csv files of Area expansion value.
- CellDivision: contains csv files of Cell Division value.
- DISTANCE_Absolute_BASE: contains csv files of absolute distance from the phyllid base.
Fig_2
Fig_2_F.xlsx
DII/mDII value of cells from WT or pinapinb at different developmental stages specified by the name of each individual sheet.
Fig_2_G.xlsx
Measurement of phyllid shape.
- Sample_Name: Genotype_Sample number
- Label: margin cell identifier
- Distance_Base: the distance of this cell to the phyllid base
- Relative_Distance_Base: the relative distance of this cell to the phyllid base
- CellFilesFromMargins: numbers of horizontal cell files in the phyllid counted from this cell.
Fig_2_I_J.xlsx
Cell division orientation analysis of pinapinb and WT upper phyllids in the section of "Upper_pinapinb" and "Upper_WT" respectively. They were further separated by individual sample. Quantification is regarding cell division number in longitudinal and mediolateral direction at corresponding time point.
Fig_2_N
- pinapinb: contains csv files of Growth anisotropy value.
- WT: contains csv files of Growth anisotropy value.
Fig_2_M
- pinapinb
- CellDivision: contains csv files of Cell Division value.
- DISTANCE_Absolute_BASE: contains csv files of absolute distance from the phyllid base.
Fig_3
Fig_3_C_D.xlsx
Cell division orientation analysis. Same structure as in Fig_2_I_J.xlsx.
Fig_3_G_J
- pinapinb+NAA
- LongitudinalGrowth: contains csv files of Longitudinal growth value.
- MediolateralGrowth: contains csv files of Mediolateral Growth value.
- CellDivision: contains csv files of Cell Division value.
- DISTANCE_Absolute_BASE: contains csv files of absolute distance from the phyllid base.
- WT+NAA
- LongitudinalGrowth: contains csv files of Longitudinal growth value.
- MediolateralGrowth: contains csv files of Mediolateral Growth value.
- CellDivision: contains csv files of Cell Division value.
- DISTANCE_Absolute_BASE: contains csv files of absolute distance from the phyllid base.
Fig_4
Fig_4_B.csv
Phyllid measurement in mm.
Fig_4_C.csv
Phyllid measurement in cell number.
Fig_4_F.csv
Merophyte size.
Fig_4_G.xlsx
Cell volume of cells from different merophytes (3 or 4 or 5) from different samples of upper or basal phyllid specified by the name of the sheets.
Fig_4_H.csv
Cells per sector.
Fig_4_K_L
- Basal:
- AreaExpansion: contains csv files of Area expansion value.
- CellDivision: contains csv files of Cell Division value.
- DISTANCE_Absolute_BASE: contains csv files of absolute distance from the phyllid base.
Fig_S1
Fig_S1_A-C
- Fig_S1_A-C.py: python script to analyze cell trajectory.
- WT:
- Output: original plots generated by "Fig_S1_A-C.py"; "DAI": Day after initiation; "TTL": time to last division; "Total": total growth.
- 01 (same structure for 02 and 03 folders)
- Growth: contains csv files of Area expansion value.
- LongitudinalGrowth: contains csv files of Longitudinal growth value.
- MediolateralGrowth: contains csv files of Mediolateral Growth value.
- PARENT: contains csv files of cell lineage information.
Fig_S1_F-H
- WT:
- LongitudinalGrowth: contains csv files of Longitudinal growth value.
- MediolateralGrowth: contains csv files of Mediolateral Growth value.
- DISTANCE_Absolute_BASE: contains csv files of absolute distance from the phyllid base.
Fig_S3
Fig_S3_C.xlsx
DII/mDII value of cells from WT or pinapinb at different developmental stages specified by the name of each individual sheet.
r2_d2_quantification_SF_3.py
Python script for the quantification of DII/mDII along distance.
Fig_S4_S8
- pinapinb
- LongitudinalGrowth: contains csv files of Longitudinal growth value.
- MediolateralGrowth: contains csv files of Mediolateral Growth value.
- CellDivision: contains csv files of Cell Division value.
- DISTANCE_Absolute_BASE: contains csv files of absolute distance from the phyllid base.
- AreaExpansion: contains csv files of Area expansion value.
Fig_S9_S10
- WT+NAA
- LongitudinalGrowth: contains csv files of Longitudinal growth value.
- MediolateralGrowth: contains csv files of Mediolateral Growth value.
- CellDivision: contains csv files of Cell Division value.
- DISTANCE_Absolute_BASE: contains csv files of absolute distance from the phyllid base.
- AreaExpansion: contains csv files of Area expansion value.
Fig_S12-S13
- pinapinb+NAA
- LongitudinalGrowth: contains csv files of Longitudinal growth value.
- MediolateralGrowth: contains csv files of Mediolateral Growth value.
- CellDivision: contains csv files of Cell Division value.
- DISTANCE_Absolute_BASE: contains csv files of absolute distance from the phyllid base.
- AreaExpansion: contains csv files of Area expansion value.
Fig_S14
- Basal
- LongitudinalGrowth: contains csv files of Longitudinal growth value.
- MediolateralGrowth: contains csv files of Mediolateral Growth value.
- DISTANCE_Absolute_BASE: contains csv files of absolute distance from the phyllid base.
General Notes on File Formats
For .csv files not specified in the previous section:
- The first row contains numeric labels of each cell or merophyte (each label number corresponds to a cell or merophyte in the segmented mesh).
- The second row contains values of the corresponding measurement indicated by the file names.
For .xlsx files:
- Variables are specified by the headers of each row and column.
- Details of each .xlsx file have been mentioned above.
Code/Software
For quantification:
Requirements
Code requires Python (≥3.8 recommended) with the following packages:
numpy
pandas
matplotlib
scipy
jupyter
polyscope
scikit-learn
Install them with,
pip install numpy pandas matplotlib scipy jupyter polyscope scikit-learn
Running the Notebook:
Start Jupyter and Open the notebook 'data_analysis.ipynb'.
Update the code for data location variables based upon the location in your PC.
Run the first data loading cells sequentially and then run specific cell for given plot like Growth box-plot, growth versus distance trajectory, proliferation boxplot etc.
Note that the data folder structure has been simplified using a different naming system compared to earlier versions of the analysis. For this reason, one should modify the file name and path accordingly before running the codes.
Individual subsamples are distinguished by sample name prefixes in the .csv filenames.
Example structure:
data/
GenotypeOrTreatment_1(e.g. WT, pinapinb, WT+NAA, pinapinb+NAA)/
sample_01.csv
sample_02.csv
sample_03.csv
GenotypeOrTreatment_2/
sample_01.csv
sample_02.csv
sample_03.csv
Timepoint Naming Change:
Note that in previous versions of the dataset, timepoints were labeled as:
T1, T2
These have been renamed to represent days after the developmental event, and are now encoded directly in the .csv files as:
days
Please refer to the "Time_Points_Converter.csv" file to make necessary changes before running the codes.
For R2D2 quantification in Fig. S3, update the path to the .csv file (Fig_S3_data.csv) in the script r2_d2_quantification_SF_3.py, then run the script. One can choose options for genotype as 'wt' or 'pinapinb' and for stage as 'old'(3.5 days) and 'young' (2.5 days) to plot specific curve.
Each row in Fig_S3_data.csv corresponds to the signal from a single nucleus. The Sample column indicates the leaf sample, while genotype, stage, and celltype describe the biological context. The columns center_x, center_y, and center_z provide the 3D coordinates of the nucleus center, and label identifies each nucleus. Script ignores the rows labelled 'dnu' in celltype.
Fluorescence intensities are stored as follows: CH0 (DII signal) and CH1 (mDII signal). The column CH0/CH1 gives the DII/mDII ratio, and 1-ratio represents (1- DII/mDII ratio).
The script aligns samples using the 3D nuclear coordinates, computes the DII/mDII ratio as a function of distance from the leaf base, and generates the corresponding plot.
The output shows the mean CH0/CH1 ratio (X-axis), binned along the distance on the principal axis (PC1, Y-axis), illustrating the average spatial gradient across samples for each leaf and genotype.
This distance is calculated by projecting the 3D cell coordinates onto the PC1 vector of the combined cell population.
Part II: Models.zip (Zenodo)
File types
The .hpp and .cpp are C++ source files, which can be opened with any text editor. mdxm are MorphoDynamX mesh files, and mdxv are MorphoDynamX view (parameter) files, both of which can be opened with MorphoDynamX.
mdx_source.tar.gz : source code for MorphoDynamX/MorphoMechanX
The simulation models (ext folder) contains the following files:
ext/01-WT-UpperPhyllid : mature phyllid of WT.
ext/02-pinapinb-Intermediate : intermediate model of pinapinb mutant
ext/03-pinapinb : pinapinb mutant simulation
ext/04-pinapinbNAA : simulation of pinapinb mutant treated with NAA
ext/05-WT-BasalPhyllid : juvenile phyllid of WT.
To run the models, change to the directory for the specific model and type:
$ make run
MDX-2.0.3-117-Ubuntu24.04-Cuda12.8.deb : MorphoDynamX simulation software including MorphoMechanX. This version requires Cuda 12.8. Install the package with the system package manager tool (eg apt).
MDX-2.0.3-117-Ubuntu24.04.deb : Non-cuda version of MorphoDynamX simulation software including MorphoMechanX.
Once MorphoDymanX starts, the model can be run by pressing the double arrow in the top right. For more information about MorphoMechanX, please see www.MorphoMechanX.org.
A short descriptions of each model and its parameters are in the file "description.txt".
Note that only dependencies required to run MorphoDynamX are installed automatically, whereas running models requires building them. This means that the development versions of some packages that include the header files will be required in order to compile them. These packages typically end in the extension "-dev".