[7/8] *Filtering SVs for disease-association*. Using our SV sites resource in addition with the variants detected from the HGSVC3 assemblies, @hugocarmaga.bsky.social was able to filter out 99% SVs for a rare disease sample, leaving only 160 candidate sites.

[6/8] *Evidence for deletion recurrence*. @hufsahashraf.bsky.social developed a detection method by screening the flanks for recurrence-indicating SNPs with phylogenetic validation and found 6 recurrent deletions flanked by Alu/LINEs, implicating transposable element-mediated NAHR in SV recurrence.

[5/8] *Homology Analysis of the SV Landscape*. Carsten Maximilian Hain used the LRS data to contrast SV length vs homology length on the flanking sites, showing that SV formation happens across a wide range of homology lengths.

[4/8] *SV Annotation Method*. @bernardo-rodriguez.bsky.social ‬ developed SVAN (bit.ly/4m6ye27), a novel SV annotation method that classifies sequence-resolved SVs based on sequence features, successfully classifying 108,328 sites.

[3/8] *New Methods Developed.* We developed various new pangenome-based tools to analyze the LRS data. @asoylev.bsky.social developed SVarp (doi.org/10.1101/2024...), an SV discovery tool. I developed Giggles (bit.ly/4lZC6lI), a genome inference tool. Both use LRS data along with a pangenome graph.

[2/8] *Graph-based analysis from intermediate coverage sequencing*. We devised the SV Analysis by Graph Augmentation (SAGA) framework to leverage common variants from @humanpangenome.bsky.social‬ and add rare variants from additional samples with LRS data. We provide genotypes for 167,291 SV sites.

[1/8] *New Open-Access Long Read Resource*. We sequenced 1,019 genomes from the 1000 Genomes Project sample cohort using @nanoporetech.com long-read sequencing (LRS) to median 17x coverage. Publication at go.nature.com/4ffPb8f.

@hhu.de @crg.eu @embl.org @impvienna.bsky.social