This DATA_README.txt file was generated on 2022-05-26 by Sonal Shree GENERAL INFORMATION 1. Title of Dataset: Raw data for the paper titled- Dynamic Instability of Dendrite Tips Generates the Highly Branched Morphologies of Sensory Neurons. 2. Author Information Corresponding Investigator Name: Prof Jonathon Howard Institution: Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT 06511 Email: joe.howard@yale.edu Co-investigator 1 Name: Dr Sonal Shree Institution: Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT 06511 Co-investigator 2 Name: Dr Sabyasachi Sutradhar Institution: Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT 06511 Co-investigator 3 Name: Dr Olivier Trottier Institution: Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT 06511 Co-investigator 4 Name: Prof Yuhai Tu Institution: Tsinghua-Peking Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, 100084 Beijing, China Co-investigator 5 Name: Prof Xin Liang Institution: IBM T.J. Watson Research Center, Yorktown Heights, NY 10598 3. Date of data collection: 2016-2021 4. Geographic location of data collection: New Haven, CT, USA 5. Funding sources that supported the collection of the data:NIH 6. Recommended citation for this dataset: Shree et al. (2022), Sci. Adv. Data from: DATA & FILE OVERVIEW DYNAMICS DATA: (i) DYNAMICAL RAW DATA: Files:(18-20_hr_RAW_DATA.zip, 24_hr_RAW_DATA.zip, 48_hr_RAW_DATA.zip 96_hr_RAW_DATA.zip) This dataset were generated to understand the Drosophila class IV dendritic arbor morphologies emerged from the stochastic dynamics of centric tips. To do so, we have collected time-lapse movies of dendritic arbor growth at different developmental stages (18 hr, 24 hr, 48 hr and 96 After Egg Laying)using a spinning disk confocal microscope for 20-30 minutes with 4-6 second time intervals. These movies were stabilized using ImageJ and then based on their separation from neighboring dendrites and the signal-to-noise ratio individual terminal dendrites through out the arbor were isolated. All files with name "*_RAW_DATA.zip" contains the time lapse movies of dendritic tips (at the specified developmental stage) that used to track the dendritic length as a function of time using an in house developed MATLAB Software 'TipTrack' (Uploaded by Sabyasachi Sutradhar:https://doi.org/10.5061/dryad.fbg79cnx9). The pre collision tips and post collision tip Are separated to measure the dynamical properties before and after tip collisions. (ii) DYNAMICAL PARAMETERS (MATLAB files): Files: 18HrFreeTipDynamicsParameters.mat, 18HrRetractingTipDynamicsParameters.mat, 24HrFreeTipDynamicsParameters.mat, 48HrFreeTipDynamicsParameters.mat, 48HrRetractingTipDynamicsParameters.mat, 96HrFreeTipDynamicsParameters.mat To analyze the raw traces we used a method called segment maximization as described in Shree et al., Sci Advances, 2022 using MATLAB. Matlab file in .mat format is uploaded here. File with name TipDynamics Parameters store all the information extracted ( eg. Velocities, and transition rates) from the tracks. .mat file contains the following variables: The RAW traces are stores in a variable named ÔTRACKÕ. This is a structure of length N (number of traces) and each structure the following fields: time: (column vector) Contains the time points in minutes length: (column vector) length of the branch at all times in micron. xy: (cell) xy coordinates of the centerline of the branch at each time(micron) tip: (cell) the xy coordinate of the tip locations at each time bbox: Bounding box of ROI of the branch (micron) soma: location of the soma (micron) smooth: median filtered length (micron) Segmax: time and length coordinates after segment maximization ThreshMerge: time and length coordinates after segment maximization state: the state of the tip (growing==+1, paused==0 and shrinking==-1) I segmented the individual traces by using Ôsegment maximization methodÕ and then the segmentation information (time and length coordinates) are store in two separate variables Ti_Segmax and Xi_Segmax. Vi_Segmax is the velocity information. After merge these information are stored in Ti_ThreshMerge, Xi_ ThreshMerge and Vi_ThreshMerge respectively. The velocity distribution of all the tracks are fitted with a central Gaussian and two log normal distributions (in positive and negative values of velocity) iteratively. The fitting information, such as the fitting parameters, are stored in ÔGaussLognormalFitÕ. This is a structure and please type ÔGaussLognormalFitÕ in the workspace to reveal all the values stored in it. I calculated the two intersection values in the positive and negative velocity region and store them in Thresh_intersection. Using these two thresholds, finally I merge consecutive segments and count number of transitions from one state to another (such as, Ngs, Ngp etc) and divided them with respective time values (for eg. kgs=Ngs/Tg ) to get the Transition matrix. The transition matrix Transition_Matrix_ThreshMerge is ordered in the following way: G -> G G -> P G ->S P -> G P -> P P -> S S->G S ->P S -> S (iii) Branching DATA: Files: Branchingdata.xlsx To determine branching events, time-lapse movies of duration 20-30 minutes were analyzed manually using ImageJ. A new protrusion of length >0.25 micron was scored as a new branch. The total branching rate (min-1) was calculated by dividing the total number of branching events by the total time. The specific branching rate (?m-1min-1) was calculated as the total branching rate divided by the total branch length. The spatial distribution of all branching events was plotted using MATLAB with the soma at the origin (x=0,\ y=0). STATIC DATA Files: Static_Data.zip, Branch__Angles.xlsx,internal_branch_elongation_analysis.xlsx (i) Static Data: Contains the maximally projected and stitched and manually segmented images of individual neurons at different developmental stages are store here. The images are taken using a spinning disk confocal microscope. (ii)Branch angle: The angle of between two daughter branches were measured using the angle tool of ImageJ (zero angle defined as in the direction of the mother) at different developmental stages (the raw data is provided in Static_data.zip). The angle distribution graph was plotted using Prism. (iii)Internal Branch elongation: To study the possible role that the elongation of internal branches in arbor growth, we imaged the same dorsal neurons (A3, A4, and A5) every 24 hrs. Larvae were mounted and imaged as described but without the use of anesthetics. Their movement was minimized by imaging at 4 ¡C for 2-5 mins. They were then returned to the apple-agar plate in the Darwin Chamber. The larvae were imaged using 20X and 40X objectives. For image analysis, the same neurons at 24 & 48 hr, and 48 & 96hr were segmented and aligned using ImageJ to identify conserved non-terminal internal branches in the proximal region. The fractional increases in branches and segment lengths were defined as: Fractional length change=[Final length-Initial length]/Initiallength 2. Data file list: DYNAMICS DATA: DYNAMICAL RAW DATA: 1. 18-20_hr_RAW_DATA.zip 2. 24_hr_RAW_DATA.zip 3. 48_hr_RAW_DATA.zip 4. 96_hr_RAW_DATA.zip DYNAMICAL PARAMETERS (MATLAB files) 5. 18HrFreeTipDynamicsParameters.mat 6. 18HrRetractingTipDynamicsParameters.mat 7. 24HrFreeTipDynamicsParameters.mat 8. 48HrFreeTipDynamicsParameters.mat 9. 48HrRetractingTipDynamicsParameters.mat 10.96HrFreeTipDynamicsParameters.mat Branching DATA: 11. Branchingdata.xlsx STATIC DATA: 12. Static_Data.zip 13. Branch__Angles.xlsx 14.internal_branch_elongation_analysis.xlsx 3. Datafile specific information: DYNAMICS DATA: DYNAMICAL RAW DATA: 1. 18-20_hr_RAW_DATA.zip: Contains RAW individual tip movies before and after tip collision at 18-20 hr. 2. 24_hr_RAW_DATA.zip: Contains RAW individual tip movies before tip collision at 24 hr. 3. 48_hr_RAW_DATA.zip: Contains RAW individual tip movies before and after tip collision at 48 hr. 4. 96_hr_RAW_DATA.zip: Contains RAW individual tip movies before tip collision at 96 hr. DYNAMICAL PARAMETERS (MATLAB files) 5. 18HrFreeTipDynamicsParameters.mat : Contains dynamical parameters such as growth/shrink velocity and transition rates analyzed from pre-contact data at 18-20 hr. 6. 18HrRetractingTipDynamicsParameters.mat : Contains dynamical parameters such as growth/shrink velocity and transition rates analyzed from post-contact data at 18-20 hr. 7. 24HrFreeTipDynamicsParameters.mat: Contains dynamical parameters such as growth/shrink velocity and transition rates analyzed from pre-contact data at 24 hr. 8. 48HrFreeTipDynamicsParameters.mat: Contains dynamical parameters such as growth/shrink velocity and transition rates analyzed from pre-contact data at 48hr. 9. 48HrRetractingTipDynamicsParameters.mat: Contains dynamical parameters such as growth/shrink velocity and transition rates analyzed from post-contact data at 48 hr. 10.96HrFreeTipDynamicsParameters.mat: Contains dynamical parameters such as growth/shrink velocity and transition rates analyzed from pre-contact data at 96 hr. Branching DATA: 11. Branchingdata.xlsx: Contains the calculation of branching rate per minute per micron at different developmental stages STATIC DATA: 12. Static_Data.zip: Contains segmented individual neurons at different developmental stages. 13. Branch__Angles.xlsx: Contains angle between two daughter branches at different developmental stages. 14. internal_branch_elongation_analysis.xlsx: Different sheets contains specified developmental stages of internal branch elongation.