Chromosome-level phasing to resolve haplotypes using multiomic data in multiple myeloma reveals complex distal interactions between chromosomes that impacts epigenetic states and gene expression
编号 5940展板 28🕑 4/21 02:00–05:00📍 Section 21主讲 Nathan Becker, MS
Nathan J. Becker1, Enze Liu1, J. Zachary Sanborn2, Attaya Suvannasankha3, Kelvin Lee3, Dickran Kazandjian1, Benjamin Diamond1, Abhishek Pandey1, Rafat Abonour1, Ola Landgren1, Elizabeth M. Munding2, Aneta Mikulasova4, Brian A. Walker1
1University of Miami, Miami, FL,2Dovetail Genomics, Scotts Valley, CA,3Indiana University, Indianapolis, IN,4University of Edinburgh, Edinburgh, United Kingdom
摘要 Abstract
Introduction: Linking markers together into large phase-blocks, and examining the interaction of different sequencing modalities, allows complex genomic and epigenomic states to be integrated to generate true multiomic haplotypes at the chromosomal level.
Methods: Fourteen multiple myeloma patient-derived xenografts were used to generate multiomic data including short- (Illumina) and long-read (PacBio) whole genome sequencing (WGS) to identify single nucleotide variations (SNVs), copy number (CN) abnormalities, structural variation (SV), and DNA methylation, as well as expression, chromatin states (Cut&Tag-IT), and Micro-C/LinkPrep (Dovetail Genomics) to identify 3D chromatin architecture. Chromosome-scale haplotypes of SNVs, SVs, CNVs, DNA methylation, expression, and chromatin marks were generated.
Results: For the first time, complete haplotype-resolved assemblies at the chromosomal level have been generated in multiple myeloma. A 100x coverage genome Micro-C/LinkPrep libraries we were able to phase the long and short arms of each chromosome, resulting in an average 94.3% haplotype phasing per autosome - thereby generating chromosome length haplotypes up to 241.9 Mb. Haplotype-specific heatmaps were generated allowing us to examine the interaction of complex SVs across chromosomes. In one sample, we identified a primary t(11;14) and additional SV events linked to the t(11;14) including a t(3;14), t(11;17), and t(3;17) which created a cyclical pattern. We found that 70-83.5% of reads support specific combinations of haplotype interactions, and that all four SV events were linked and involved the same haplotypes on each chromosome. The pattern of interactions combined with breakpoint analysis in this case indicated a four-way complex reciprocal translocation between chromosomes 3,11,14 and 17. Integration of epigenetic data in this complex SV showed DNA hyper-methylation 17 kb upstream of CCND1 next to the t(11;14) breakpoint as well as increased H3K27ac marks on the same haplotype, indicating spreading of the activating broad domain from the IGH super-enhancer on chromosome 14. Equally, the hypomethylated DNA marks at the IGH promoter are spread to chromosome 3, via the t(3;14), resulting in over-expression of the proto-oncogene SKIL . The same is true for the t(3;17), which shows hypomethylation on both sides of the breakpoint, compared to the non-translocated allele.
Conclusion: We have generated the first chromosome scale haplotype-resolved genomes in multiple myeloma and integrated them with epigenetic states to identify interactions across chromosomes and resolve complex SVs as well as their epigenomic consequences to understand the intricate nature of how the genome is organized.
利益披露 Disclosure
N. J. Becker, None..
E. Liu, None.
J. Sanborn,
Cantata Bio Employment.
A. Suvannasankha, None..
K. Lee, None..
D. Kazandjian, None..
B. Diamond, None..
A. Pandey, None..
R. Abonour, None..
O. Landgren, None.
E. M. Munding,
Cantata Bio Employment.
A. Mikulasova, None..
B. A. Walker, None.