Related Experiment Video
Updated: May 29, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Accessing medically relevant complex regions with a pangenome graph of 20 near-complete Japanese haplotypes
Yoshihiko Suzuki1,2, Chie Owa3, Haruka Kobayashi3
1Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan. yszkshk@gmail.com.
Abstract:
Pangenome projects have enhanced our understanding of human genomic and genetic diversity, but repetitive regions are still challenging to assemble and yet medically important. Here we generate 20 near-complete haplotypes from 10 Japanese male individuals using three complementary long-read and long-range datasets and construct a pangenome graph from these haplotype-resolved assemblies. All haplotypes achieve an N50 value exceeding 100 Mbp for gapless contigs. We substantially improve the average reconstruction rate of complete haplotypes from 46.8% and 52.8% in two previous pangenome graphs to 91.2% within 30 segmentally duplicated complex regions. Furthermore, we identify complete minor haplotypes in the KIR and SMN regions that are absent in those previous pangenome graphs. We find putatively biased gene conversion events occurring in only one direction around the SMN and beta-defensin (DEFB) genes, implying non-random evolution in these regions. Our study contributes to the growing body of pangenomic data, offering a more refined view of human genomic diversity involving complex segmental duplications.
Related Concept Videos
Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...
Genomics
Evolutionary Relationships through Genome Comparisons
Human Genetics
The complex relationship between genetics and psychology is observable through common biological components such...
Karyotyping
Next-generation Sequencing
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
