Long-read sequencing reveals the complex structure of extra dic(21;21) chromosome and its biological effects.

Complex congenital chromosome abnormalities are rare but often cause severe symptoms. However, the structures and biological impacts of such abnormalities have seldomly been analyzed at the molecular level. Previously, we reported a Japanese female patient with severe developmental defects. The patient had an extra dicentric chromosome 21 (chr21) consisting of two partial chr21 copies fused together within their long arms along with two centromeres and many copy number changes. In this study, we performed whole-genome, transcriptional, and DNA methylation analyses, coupled with novel bioinformatic approaches, to reveal the complex structure of the extra chromosome and its transcriptional and epigenetic changes. Long-read sequencing accurately identified the structures of junctions related to the copy number changes in extra chr21 and suggested the mechanism of the structural changes. Our transcriptome analysis showed the overexpression of genes in extra chr21. Additionally, an allele-specific DNA methylation analysis of the long-read sequencing data suggested that the centromeric region of extra chr21 was hypermethylated, a property associated with the inactivation of one centromere in the extra chromosome. Our comprehensive analysis provides insights into the molecular mechanism underlying the generation of the extra chromosome and its pathogenic roles.

Localized assembly for long reads enables genome-wide analysis of repetitive regions at single-base resolution in human genomes.

BACKGROUND: Long-read sequencing technologies have the potential to overcome the limitations of short reads and provide a comprehensive picture of the human genome. However, the characterization of repetitive sequences by reconstructing genomic structures at high resolution solely from long reads remains difficult. Here, we developed a localized assembly method (LoMA) that constructs highly accurate consensus sequences (CSs) from long reads. METHODS: We developed LoMA by combining minimap2, MAFFT, and our algorithm, which classifies diploid haplotypes based on structural variants and CSs. Using this tool, we analyzed two human samples (NA18943 and NA19240) sequenced with the Oxford Nanopore sequencer. We defined target regions in each genome based on mapping patterns and then constructed a high-quality catalog of the human insertion solely from the long-read data. RESULTS: The assessment of LoMA showed a high accuracy of CSs (error rate < 0.3%) compared with raw data (error rate > 8%) and superiority to a previous study. The genome-wide analysis of NA18943 and NA19240 identified 5516 and 6542 insertions (≥ 100 bp), respectively. Most insertions (~ 80%) were derived from tandem repeats and transposable elements. We also detected processed pseudogenes, insertions in transposable elements, and long insertions (> 10 kbp). Finally, our analysis suggested that short tandem duplications are associated with gene expression and transposons. CONCLUSIONS: Our analysis showed that LoMA constructs high-quality sequences from long reads with substantial errors. This study revealed the true structures of the insertions with high accuracy and inferred the mechanisms for the insertions, thus contributing to future human genome studies. LoMA is available at our GitHub page: https://github.com/kolikem/loma .