Genevia RNA-seq Bioinformatics Grant

Announcing the winner

The winner of our RNA-Seq Bioinformatics Grant 2022 has been announced on 15 Sep 2022.

Winner: Dr. Melanie Flint, Reader in Cancer Research at the University of Brighton

Application title: Use of RNA seq and TMT mass spectrometry to characterise the effect of stress and glucocorticoid receptor antagonism on breast cancer metastasis to the brain.

Dr. Flint's research proposal addresses an intriguing and understudied aspect of cancer progression. Furthermore, the planned research builds on markedly multi-disciplinary work involving research into the endocrine system, nervous system and cancer biology. We deem Dr. Flint's research proposal a particularly fitting match for the background and expertise of Genevia Technologies' bioinformatics team.

We congratulate Dr. Flint and look forward to an interesting expression analysis project.

We wish to thank all applicants for their grant submissions and interest in our service. We can only say the quantity and quality of applications made this decision an extremely difficult one for us.

Statistics on RNA-Seq Bioinformatics Grant applications

We received 44 applications for the grant, with a high overall quality. The applications ranged from topics such as crop protection to molecular studies on various diseases, including several types of cancer.

14 applications involved mouse samples, 12 human, and 3 mouse and human samples. 15 applications involved other animals, plants or microbes.

25 applications were for bulk RNA-seq data, 13 for single-cell RNA-seq data, 3 for small RNA-seq data and 3 for other data (e.g., metatranscriptomics).

37 applications were from European universities, 6 from North American and one from an Asian university. The number one country by number of applications was UK (10 applications), and number one university was the University of Cambridge (4 applications).

We are very pleased with the interest researchers across biology and medicine have shown towards our service, and look forward to organizing another grant call in the near future.

See the original grant call below.

Genevia RNA-seq Bioinformatics Grant (16,400 EUR)

Are you planning an RNA-sequencing experiment? Apply for our bioinformatics grant to win end-to-end bioinformatics support for your next project.

Genevia RNA-seq Bioinformatics Grant is aimed at supporting academic researchers in planning a transcriptomic sequencing experiment, getting the data thoroughly analyzed and the findings published.

Genevia Technologies has been providing bioinformatics services for scientists in over 70 universities during the last 10 years. In accordance with our mission to support researchers in embracing new computational technologies, we decided the time had come to launch our first grant call.

We wish to raise awarness of the importance of consulting bioinformaticians when planning experiments. Besides the main awardee, five additional applicants will win a consultation service for sequencing experiment design.

Grant call


Key information

  • Fully tailored bioinformatics support from experiment design to publication-ready results (value 16,400 EUR / 18,400 USD)

  • For bulk, single-cell and or small RNA-seq data

  • For academic research only

  • Apply on this page before the extended deadline of August 14th, 2022


Eligibility criteria

You are eligible to apply for the grant if you are

  • a researcher in a university or other non-profit research institution,
  • planning to run a bulk, single-cell or small RNA-sequencing experiment within October 2022 to March 2023

We welcome all organisms (for the analysis, that is — applicants must be Homo sapiens.)


What the grant covers

The grant covers our standard 3-month bioinformatics service for data from a transcriptomic sequencing experiment such as bulk mRNA, single-cell RNA or small RNA sequencing. The service includes 112,5 hours of work which will be allocated to:

  • Experiment design consultation to determine parameters such as the number of replicates and sequencing depth
  • A computational analysis plan tailored to answer your research questions
  • Quality control and preprocessing of the raw sequencing output
  • Exploratory analysis to visualize trends and patterns in the data
  • Downstream analyses such as differential expression analysis, pathway analysis, transcriptome assembly (for de novo RNA-seq), cell type identification and trajectory analyses (for single-cell RNA-seq), miRNA target analyses (for small RNA-seq) and other applicable analyses (learn more)
  • Customizing and polishing figures for a manuscript
  • A project report including method descriptions to use in a manuscript
  • Manuscript review to help in reporting computational results and methods
  • Help with addressing reviewer comments

Throughout the project, you will have a dedicated post-doc level bioinformatics project manager with significant experience in transcriptomics. The project manager will be available in regular teleconferences to report the progress, agree on next steps and to discuss and interpret the results with you.

The grant also covers all required computation costs and software licenses from our end. The awardee is not obliged to purchase any services from Genevia Technologies.

Please note that the grant does not cover the sequencing experiments.

Watch the video to learn more about how the service works:


How to apply

To apply, fill out the application form on this page (scroll down).

The extended submission deadline is August 14th, 2022


Selecting and announcing the winner

The applications are reviewed and ranked based on estimated quality, novelty and impact.

The winner will be announced on this website and informed personally on September 15th, 2022.


What else can I win?

An additional five applicants will be awarded a free consultation service for planning an experiment / computational analyses (value 750 EUR / 825 USD).

Also, all eligible applicants are gifted an RNA-seq themed coffee mug.

(Actual appeareance of transcripto-mugs may differ.)


What if I am not eligible for the grant?

If you wish to discuss your bioinformatics needs or suggest a topic for our next bioinformatics grant, leave us a message.

We encourage you to notify friends and colleagues who may be eligible!


What is the catch?

There is one catch. If you win, we will publish your name, application title (from the form below) and a short interview (a couple general questions about you and your research) on our website. We hope you are OK with this!


Apply for Genevia RNA-Seq Bioinformatics Grant

The deadline for submitting applications has passed.

Contact us

For questions about this grant, contact us at . For other inquiries about our service, you may use the form below.

RNA sequencing data analysis

RNA sequencing data analysis brings to light the intricate mechanisms of gene regulation.

TRANSCRIPTOME-WIDE ANALYSES OF GENE EXPRESSION are extremely popular among researchers studying gene regulation in biological systems ranging from single cells to tissues and complex microbiomes. RNA-seq data allows for a wide range of analyses to address countless research questions across the fields of biology and biomedicine.

Read more

Learn more

We have been analyzing transcriptomic data from the days of microarrays to the age of single-cell experiments. Our team has analyzed data from a wide range of transcriptomic sequencing experiments, organisms and biological and medical applications. Browse our highlights below.

Read more about RNA-seq data analysis

All analyses

References and customer cases

All references

Selected publications from our customers

  • Singh, A. et al. (2022). Urolithin A improves muscle strength, exercise performance, and biomarkers of mitochondrial health in a randomized trial in middle-aged adults. Cell reports. Medicine, 3(5), 100633. https://doi.org/10.1016/j.xcrm.2022.100633
  • Tusup, M. et al. (2022). Epitranscriptomics modifier *** indirectly triggers Toll-like receptor 3 and can enhance immune infiltration in tumors. Molecular therapy : the journal of the American Society of Gene Therapy, 30(3), 1163–1170. https://doi.org/10.1016/j.ymthe.2021.09.022
  • Pommergaard, H. C. et al. (2022). Aldehyde dehydrogenase expression may be a prognostic biomarker and associated with liver cirrhosis in patients resected for hepatocellular carcinoma. Surgical oncology, 40, 101677. https://doi.org/10.1016/j.suronc.2021.101677
  • Martins, R. R. et al. (2022). Trancriptomic signatures of telomerase-dependent and -independent ageing, in the zebrafish gut and brain. bioRxiv 2022.05.24.493215; doi: 101677. https://doi.org/10.1101/2022.05.24.493215
  • Pommergaard, H. C. et al. (2021). Peroxisome proliferator-activated receptor activity correlates with poor survival in patients resected for hepatocellular carcinoma. Journal of hepato-biliary-pancreatic sciences, 28(4), 327–335. https://doi.org/10.1002/jhbp.745
  • Lehto, T. K. et al. (2021). Transcript analysis of commercial prostate cancer risk stratification panels in hard-to-predict grade group 2-4 prostate cancers. The Prostate, 81(7), 368–376. https://doi.org/10.1002/pros.24108
  • Hussey, G. S. et al. (2020). Lipidomics and RNA sequencing reveal a novel subpopulation of nanovesicle within extracellular matrix biomaterials. Science advances, 6(12), eaay4361. https://doi.org/10.1126/sciadv.aay4361
  • Oksanen, M. et al. (2020). NF-E2-related factor 2 activation boosts antioxidant defenses and ameliorates inflammatory and amyloid properties in human Presenilin-1 mutated Alzheimer's disease astrocytes. Glia, 68(3), 589–599. https://doi.org/10.1002/glia.23741
  • Lemke, P. et al. (2020). Transcriptome Analysis of Solanum Tuberosum Genotype RH89-039-16 in Response to Chitosan. Frontiers in plant science, 11, 1193. https://doi.org/10.3389/fpls.2020.01193
  • Tiihonen, J. et al. (2020). Neurobiological roots of psychopathy. Molecular psychiatry, 25(12), 3432–3441. https://doi.org/10.1038/s41380-019-0488-z
  • Gurvich, O. L. et al. (2020). Transcriptomics uncovers substantial variability associated with alterations in manufacturing processes of macrophage cell therapy products. Scientific reports, 10(1), 14049. https://doi.org/10.1038/s41598-020-70967-2
  • Gabriel, M. et al. (2020). A relational database to identify differentially expressed genes in the endometrium and endometriosis lesions. Scientific data, 7(1), 284. https://doi.org/10.1038/s41597-020-00623-x
  • Tiihonen, J. et al. (2019). Sex-specific transcriptional and proteomic signatures in schizophrenia. Nature communications, 10(1), 3933. https://doi.org/10.1038/s41467-019-11797-3
  • Tarkkonen, K et al. (2017). Comparative analysis of osteoblast gene expression profiles and Runx2 genomic occupancy of mouse and human osteoblasts in vitro. Gene, 626, 119–131. https://doi.org/10.1016/j.gene.2017.05.028
  • Sugano, Y. et al. (2017). Comparative transcriptomic analysis identifies evolutionarily conserved gene products in the vertebrate renal distal convoluted tubule. Pflugers Archiv : European journal of physiology, 469(7-8), 859–867. https://doi.org/10.1007/s00424-017-2009-8

Selected publications from our team

  • Rodriguez-Martinez, A. et al. (2022). Novel ZNF414 activity characterized by integrative analysis of ChIP-exo, ATAC-seq and RNA-seq data. Biochimica et biophysica acta. Gene regulatory mechanisms, 1865(3), 194811. Advance online publication. https://doi.org/10.1016/j.bbagrm.2022.194811
  • Taavitsainen, S. et al. (2021). Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse. Nature communications, 12(1), 5307. https://doi.org/10.1038/s41467-021-25624-1
  • Armaka M. et al. (2021). Single-cell chromatin and transcriptome dynamics of Synovial Fibroblasts transitioning from homeostasis to pathology in modelled TNF-driven arthritis. bioRxiv 2021.08.27.457747. doi: https://doi.org/10.1101/2021.08.27.457747
  • Linna-Kuosmanen, S. et al. (2021). NRF2 is a key regulator of endothelial microRNA expression under proatherogenic stimuli. Cardiovascular research, 117(5), 1339–1357. https://doi.org/10.1093/cvr/cvaa219
  • Moreau, P. R. et al. (2021). Profiling of Primary and Mature miRNA Expression in Atherosclerosis-Associated Cell Types. Arteriosclerosis, thrombosis, and vascular biology, 41(7), 2149–2167. https://doi.org/10.1161/ATVBAHA.121.315579
  • Zannikou, M. et al. (2021). MAP3K8 Regulates Cox-2-Mediated Prostaglandin E2 Production in the Lung and Suppresses Pulmonary Inflammation and Fibrosis. Journal of immunology (Baltimore, Md. : 1950), 206(3), 607–620. https://doi.org/10.4049/jimmunol.2000862
  • Filppu, P. et al. (2021). CD109-GP130 interaction drives glioblastoma stem cell plasticity and chemoresistance through STAT3 activity. JCI insight, 6(9), e141486. https://doi.org/10.1172/jci.insight.141486
  • Verta, J. P. et al. (2021). Genetic Drift Dominates Genome-Wide Regulatory Evolution Following an Ancient Whole-Genome Duplication in Atlantic Salmon. Genome biology and evolution, 13(5), evab059. https://doi.org/10.1093/gbe/evab059
  • Liakos, A. et al. (2020). Continuous transcription initiation guarantees robust repair of all transcribed genes and regulatory regions. Nature communications, 11(1), 916. https://doi.org/10.1038/s41467-020-14566-9
  • Harjula, S. E. et al. (2020). Characterization of immune response against Mycobacterium marinum infection in the main hematopoietic organ of adult zebrafish (Danio rerio). Developmental and comparative immunology, 103, 103523. https://doi.org/10.1016/j.dci.2019.103523
  • Morianos, I. et al. (2020). Activin-A limits Th17 pathogenicity and autoimmune neuroinflammation via CD39 and CD73 ectonucleotidases and Hif1-α-dependent pathways. Proceedings of the National Academy of Sciences of the United States of America, 117(22), 12269–12280. https://doi.org/10.1073/pnas.1918196117
  • Mehtonen, J. et al. (2020). Single cell characterization of B-lymphoid differentiation and leukemic cell states during chemotherapy in ETV6-RUNX1-positive pediatric leukemia identifies drug-targetable transcription factor activities. Genome medicine, 12(1), 99. https://doi.org/10.1186/s13073-020-00799-2
  • Viiri, L. E. et al. (2019). Extensive reprogramming of the nascent transcriptome during iPSC to hepatocyte differentiation. Scientific reports, 9(1), 3562. https://doi.org/10.1038/s41598-019-39215-0
  • Pölönen, P. et al. (2019). Hemap: An Interactive Online Resource for Characterizing Molecular Phenotypes across Hematologic Malignancies. Cancer research, 79(10), 2466–2479. https://doi.org/10.1158/0008-5472.CAN-18-2970
  • Moreau, P. R. et al. (2018). Transcriptional Profiling of Hypoxia-Regulated Non-coding RNAs in Human Primary Endothelial Cells. Frontiers in cardiovascular medicine, 5, 159. https://doi.org/10.3389/fcvm.2018.00159
  • Bouvy-Liivrand, M. et al. (2017). Analysis of primary microRNA loci from nascent transcriptomes reveals regulatory domains governed by chromatin architecture. Nucleic acids research, 45(17), 9837–9849. https://doi.org/10.1093/nar/gkx680
  • Lavigne, M. D. et al. (2017). Global unleashing of transcription elongation waves in response to genotoxic stress restricts somatic mutation rate. Nature communications, 8(1), 2076. https://doi.org/10.1038/s41467-017-02145-4

Browse all

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