Alexandra P
@alexanrna.bsky.social
🇸🇰 PhD student @ KU Leuven and VIB 🇧🇪
Genetics, Bioinformatics, and everything in between (she/her)
Genetics, Bioinformatics, and everything in between (she/her)
12/ Additionally thanks to: @vschpc.bsky.social , @fwovlaanderen.bsky.social , @vib-ccb.bsky.social , @singlecellcore.bsky.social , Genomics Core Leuven, and KU Leuven.
September 10, 2025 at 3:48 PM
12/ Additionally thanks to: @vschpc.bsky.social , @fwovlaanderen.bsky.social , @vib-ccb.bsky.social , @singlecellcore.bsky.social , Genomics Core Leuven, and KU Leuven.
11/ This was a huge collaborative effort, so shoutout to Ruben, Marios, Luuk, Joris in the lab, and our collaborators @jancools.bsky.social , Margo Aertgeerts, Heidi Segers.
September 10, 2025 at 3:48 PM
11/ This was a huge collaborative effort, so shoutout to Ruben, Marios, Luuk, Joris in the lab, and our collaborators @jancools.bsky.social , Margo Aertgeerts, Heidi Segers.
10/ We anticipate SPLONGGET to work on any standard 10X Multiome-compatible sample.
If you want to learn more, read the full pre-print here: www.biorxiv.org/content/10.1....
If you want to learn more, read the full pre-print here: www.biorxiv.org/content/10.1....
Long-read single-cell genome, transcriptome and open chromatin profiling links genotype to phenotypes.
Current single-cell multiomics methods typically provide limited genomic information, constraining genotype-phenotype studies. To address this gap, we developed SPLONGGET (Single-cell Profiling of LON...
www.biorxiv.org
September 10, 2025 at 3:48 PM
10/ We anticipate SPLONGGET to work on any standard 10X Multiome-compatible sample.
If you want to learn more, read the full pre-print here: www.biorxiv.org/content/10.1....
If you want to learn more, read the full pre-print here: www.biorxiv.org/content/10.1....
9/ Taken together, SPLONGGET keeps the quality and ease of use of 10X Multiome and additionally unlocks the whole-genome and full-length transcriptome, allowing us to study the genotype-to-phenotype effects of somatic variation.
September 10, 2025 at 3:48 PM
9/ Taken together, SPLONGGET keeps the quality and ease of use of 10X Multiome and additionally unlocks the whole-genome and full-length transcriptome, allowing us to study the genotype-to-phenotype effects of somatic variation.
8/ With SPLONGGET we were able to figure out the exact molecular mechanisms underpinning CAR T-cell therapy resistance. At relapse, we identify an ~8 MB deletion encompassing CD19 as well as 4 unique SNVs in conserved splice site motives that lead to intron retention and non-functional transcripts.
September 10, 2025 at 3:48 PM
8/ With SPLONGGET we were able to figure out the exact molecular mechanisms underpinning CAR T-cell therapy resistance. At relapse, we identify an ~8 MB deletion encompassing CD19 as well as 4 unique SNVs in conserved splice site motives that lead to intron retention and non-functional transcripts.
7/ We further explore the effect of CNAs on gene expression and chromatin accessibility. For example, we can observe changes between D0 and Q1, when isochromosome 7 is formed (p-arm lost and q-arm gained).
September 10, 2025 at 3:48 PM
7/ We further explore the effect of CNAs on gene expression and chromatin accessibility. For example, we can observe changes between D0 and Q1, when isochromosome 7 is formed (p-arm lost and q-arm gained).
6/ SPLONGGET also allowed us to comprehensively detect different types of variation including SNP and SVs across time points. Importantly, we identify various CNVs from this data, including the ones which are only present at later time points. We can also look at CN profiles of individual cells.
September 10, 2025 at 3:48 PM
6/ SPLONGGET also allowed us to comprehensively detect different types of variation including SNP and SVs across time points. Importantly, we identify various CNVs from this data, including the ones which are only present at later time points. We can also look at CN profiles of individual cells.
5/ With the SPLONGGET transcriptome and accessibility data we identified different tumour subclones and immune populations. To gain more insight into gene regulatory changes over time, we ran SCENIC+ from our collaborators at @steinaerts.bsky.social lab and identified key regulators, including ERG.
September 10, 2025 at 3:48 PM
5/ With the SPLONGGET transcriptome and accessibility data we identified different tumour subclones and immune populations. To gain more insight into gene regulatory changes over time, we ran SCENIC+ from our collaborators at @steinaerts.bsky.social lab and identified key regulators, including ERG.
4/ With our collaborators, @jancools.bsky.social, Margo Aertgeerts, and Heidi Segers we applied SPLONGGET to longitudinal samples from a case of B-ALL to follow its evolution from diagnosis through therapy and ultimately resistance to anti-CD19 CAR T-cell therapy.
September 10, 2025 at 3:48 PM
4/ With our collaborators, @jancools.bsky.social, Margo Aertgeerts, and Heidi Segers we applied SPLONGGET to longitudinal samples from a case of B-ALL to follow its evolution from diagnosis through therapy and ultimately resistance to anti-CD19 CAR T-cell therapy.
3/ Libraries can also be used for target enrichment and are backwards compatible with short reads.
September 10, 2025 at 3:48 PM
3/ Libraries can also be used for target enrichment and are backwards compatible with short reads.
2/ We adapted @10xgenomics.bsky.social Multiome to retain all tagmentation fragments (not just short ATAC ones) and intact cDNA. Sequencing these libraries on @nanoporetech.com simultaneous full-length transcriptome, open chromatin and whole-genome data from 1000’s of cells.
September 10, 2025 at 3:48 PM
2/ We adapted @10xgenomics.bsky.social Multiome to retain all tagmentation fragments (not just short ATAC ones) and intact cDNA. Sequencing these libraries on @nanoporetech.com simultaneous full-length transcriptome, open chromatin and whole-genome data from 1000’s of cells.