For this task,

• process new and old experimental data sets from the Ravi Palanivelu lab
• confer with Palanivelu lab personnel to understand and document the samples
• track code and key data files using this repository: https://bitbucket.org/hotpollen/pistil-rna-seq/src/main/

About the data:

As of summer 2023, there are now three collections of sequencing data that we got from the Ravi Palanivelu lab. These collections correspond to "batches" of RNA samples that were sent to GeneWiz/Azenta for library synthesis and subsequent sequencing.

For two of these batches, the RP lab created the biological material for samples, extracted RNA, and then sent the RNA boxes to Azenta (formerly GeneWiz), the sequencing company. For one of these batches, the so-called "library synthesis pilot," the RP lab synthesized the libraries themselves and then sent the libraries to Azenta.

Once the sequencing data are complete, the company sent links to an ftp site containing the data files to the RP lab, who downloaded them or asked us to download them. We then obtained the sequence data and deployed them to the Charlotte HPC file system for the next steps - data processing, in which we generate files for visualization in IGB and, also, "counts" files for statistical analysis libraries developed for RNA-Seq data.

The three data collections are:

1) 2021 Kelsie Pryze's unpollinated pistil heat stress experiment, azenta id: 30-681594536

These data are from an experiment done by Kelse Pryze in which she tested the effects of heat stress on un-pollinated tomato pistils dissected from emasculated flowers from four tomato varieties: Heinz, Malintka, Tamaulipas, and Nagcarlang. All sample types have three replicates per sample type represented in the sequencing data, except for Tamaulipas, which has two. KP provided a detailed description of exactly how the samples were generated. The biological material were created in 2021, in the summer and early spring.

The data files also included three data files from a different experiment investigating the transcriptome of dissected, unpollinated ovary tissue. We processed these data alongside the fastq files from the un-pollinated pistils because they were all sequenced at the same time, in the same lot of RNAs sent to the sequencing provider. However, for visualization, we will probably want to present them in ways that will make it super clear that the biological material were created separately from the un-pollinated pistils.

Rob Reid downloaded the data onto the UNCC cluster and saved it here: /projects/tomato_genome/rnaseq/ravi-2022-fullrun/30-681594536.

We then began processing these data in 2023, using the high performance computing cluster at UNC Charlotte. You can identify these samples on our file system by looking for their Azenta identifier - 30-681594536. Also, in our various pipelines and Jira records, we have been referring to these data by the date we got them from the RP Lab: the "Ravi 2022" dataset.

KP provided documentation describing these samples. We will place these files in a "Documentation" folder in the git repository. However, as you will see from the documentation in the repository, the samples themselves were generated during the summer and early spring of 2021.

When we deploy these data to the genome browser for visualization, we will probably use a study name that describes the data and makes it easy for RP Lab personnel and others to recognize them in the browser or other settings.

2) self-pollinated stigma+style heat stress experiment, Azenta id 30-804059537

We have been referring to this experimental data set as "KP-2023", referring to the experimenter Kelsie Pryze and the date when we obtained the experimental data sequence files.

The original sequence files are downloaded to this location on the UNC Charlotte cluster computing system: /projects/tomato_genome/rnaseq/30-804059537-kelsie

This experiment included sample types testing two temperature conditions, three treatment durations, four varieties, and one tissue type. These were:

• temperature conditions: 37 degrees C (heat stress) and 25 degrees C (control)
• treatment durations: 0 hours (no heat stress applied), 3 hours, and 8 hours
• four varieties: Heinz, Malintka, Nagcarlang, Tamaulipas
• tissue type: dissected stigma and style tissue from self-pollinated flowers

There were three replicates per sample type. The zero-hour samples however included three 25 degrees C samples and no 37 degrees C samples.

Number of samples: (2 conditions * 4 varieties * 2 treatment durations * 3 replications) + (1 condition * 4 * 1 treatment duration (0 hours) * 3 replications ) = 60 samples

3) self-pollinated and unpollinated Tamaulipas library preparation pilot experiment, Azenta id 30-605730043

This experiment performed by Kelsie Pryze involved creating libraries for sequencing using RNAs from pollinated and upollinated samples from Tamaulipas plants.

The data from this experiment are stored on the UNC Charlotte cluster in: /projects/tomato_genome/rnaseq/ravi-tamaulipas
Rob downloaded these data from the sequencing provider on or around December 15, 2021. (This is the date that Rob created a Google Doc describing the files available from the sequencing provider's data transfer ftp site.)

Note: We need to confirm if that the sequences obtained from the unpollinated pistils were from the same experiment as (1) above. If yes, which "replicate" were they? This will influence how we label the data in IGB.

To-do for each experimental data set:

• Run nf-core/rnaseq pipeline with both the SL5/2022 and SL4/2019 target genome assemblies using "reverse" strandedness parameter.
• Check the multi-qc report. Re-run the processing as necessary.
• Rename BAM files to not included "sorted" in the name.
• Create scaled coverage graphs.
• Create junction files.
• Migrate data to an on-line location for IGB visualization.
• Create annots.xml metadata file with visualization parameters for each dataset; add the data collection to the makeAnnotsXml.py script
• Add the "counts" data files to the repository for statistical analysis
• Add documentation for each sequence collection to the git repository
• Perform data checking to catch any record-keeping errors that may have occurred

Attached:

• Azenta (sequencing provider) data report for KP 2023 data, with numbers of sequences produced
• Quote from Azenta indicating strand-specific RNA-Seq, 2x150 bp paired end sequencing

Contact:

• Kelsey Pryze - kelseypryze@email.arizona.edu