OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps

Detection of cryptic balanced chromosomal rearrangements using high-resolution optical genome mapping

BACKGROUND

Chromosomal rearrangements have profound consequences in diverse human genetic diseases. Currently, the detection of balanced chromosomal rearrangements (BCRs) mainly relies on routine cytogenetic G-banded karyotyping. However, cryptic BCRs are hard to detect by karyotyping, and the risk of miscarriage or delivering abnormal offspring with congenital malformations in carrier couples is significantly increased. In the present study, we aimed to investigate the potential of single-molecule optical genome mapping (OGM) in unravelling cryptic chromosomal rearrangements.

METHODS

Eleven couples with normal karyotypes that had abortions/affected offspring with unbalanced rearrangements were enrolled. Ultra-high-molecular-weight DNA was isolated from peripheral blood cells and processed via OGM. The genome assembly was performed followed by variant calling and annotation. Meanwhile, multiple detection strategies, including FISH, long-range-PCR amplicon-based next-generation sequencing and Sanger sequencing were implemented to confirm the results obtained from OGM.

RESULTS

High-resolution OGM successfully detected cryptic reciprocal translocation in all recruited couples, which was consistent with the results of FISH and sequencing. All high-confidence cryptic chromosomal translocations detected by OGM were confirmed by sequencing analysis of rearrangement breakpoints. Moreover, OGM revealed additional complex rearrangement events such as inverted aberrations, further refining potential genetic interpretation.

CONCLUSION

To the best of our knowledge, this is the first study wherein OGM facilitate the rapid and robust detection of cryptic chromosomal reciprocal translocations in clinical practice. With the excellent performance, our findings suggest that OGM is well qualified as an accurate, comprehensive and first-line method for detecting cryptic BCRs in routine clinical testing.

Oxford Nanopore and Bionano Genomics technologies evaluation for plant structural variation detection

Background

Structural Variations (SVs) are genomic rearrangements derived from duplication, deletion, insertion, inversion, and translocation events. In the past, SVs detection was limited to cytological approaches, then to Next-Generation Sequencing (NGS) short reads and partitioned assemblies. Nowadays, technologies such as DNA long read sequencing and optical mapping have revolutionized the understanding of SVs in genomes, due to the enhancement of the power of SVs detection.

This study aims to investigate performance of two techniques, 1) long-read sequencing obtained with the MinION device (Oxford Nanopore Technologies) and 2) optical mapping obtained with Saphyr device (Bionano Genomics) to detect and characterize SVs in the genomes of the two ecotypes of Arabidopsis thaliana, Columbia-0 (Col-0) and Landsberg erecta 1 (Ler-1).

Results

We described the SVs detected from the alignment of the best ONT assembly and DLE-1 optical maps of A. thaliana Ler-1 against the public reference genome Col-0 TAIR10.1. After filtering (SV > 1 kb), 1184 and 591 Ler-1 SVs were retained from ONT and Bionano technologies respectively. A total of 948 Ler-1 ONT SVs (80.1%) corresponded to 563 Bionano SVs (95.3%) leading to 563 common locations. The specific locations were scrutinized to assess improvement in SV detection by either technology. The ONT SVs were mostly detected near TE and gene features, and resistance genes seemed particularly impacted.

Conclusions

Structural variations linked to ONT sequencing error were removed and false positives limited, with high quality Bionano SVs being conserved. When compared with the Col-0 TAIR10.1 reference genome, most of the detected SVs discovered by both technologies were found in the same locations. ONT assembly sequence leads to more specific SVs than Bionano one, the latter being more efficient to characterize large SVs. Even if both technologies are complementary approaches, ONT data appears to be more adapted to large scale populations studies, while Bionano performs better in improving assembly and describing specificity of a genome compared to a reference.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08499-4.

Advances in optical mapping for genomic research

Recent advances in optical mapping have allowed the construction of improved genome assemblies with greater contiguity. Optical mapping also enables genome comparison and identification of large-scale structural variations. Association of these large-scale genomic features with biological functions is an important goal in plant and animal breeding and in medical research. Optical mapping has also been used in microbiology and still plays an important role in strain typing and epidemiological studies. Here, we review the development of optical mapping in recent decades to illustrate its importance in genomic research. We detail its applications and algorithms to show its specific advantages. Finally, we discuss the challenges required to facilitate the optimization of optical mapping and improve its future development and application.

OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps

BACKGROUND

Optical mapping is an emerging technology that complements sequencing-based methods in genome analysis. It is widely used in improving genome assemblies and detecting structural variations by providing information over much longer (up to 1 Mb) reads. Current standards in optical mapping analysis involve assembling optical maps into contigs and aligning them to a reference, which is limited to pairwise comparison and becomes bias-prone when analyzing multiple samples.

FINDINGS

We present a new method, OMMA, that extends optical mapping to the study of complex genomic features by simultaneously interrogating optical maps across many samples in a reference-independent manner. OMMA captures and characterizes complex genomic features, e.g., multiple haplotypes, copy number variations, and subtelomeric structures when applied to 154 human samples across the 26 populations sequenced in the 1000 Genomes Project. For small genomes such as pathogenic bacteria, OMMA accurately reconstructs the phylogenomic relationships and identifies functional elements across 21 Acinetobacter baumannii strains.

CONCLUSIONS

With the increasing data throughput of optical mapping system, the use of this technology in comparative genome analysis across many samples will become feasible. OMMA is a timely solution that can address such computational need. The OMMA software is available at https://github.com/TF-Chan-Lab/OMTools.