stLFRsv: A Germline Structural Variant Analysis Pipeline Using Co-barcoded Reads

AsmMix: an efficient haplotype-resolved hybrid de novo genome assembling pipeline

Accurate haplotyping facilitates distinguishing allele-specific expression, identifying cis-regulatory elements, and characterizing genomic variations, which enables more precise investigations into the relationship between genotype and phenotype. Recent advances in third-generation single-molecule long read and synthetic co-barcoded read sequencing techniques have harnessed long-range information to simplify the assembly graph and improve assembly genomic sequence. However, it remains methodologically challenging to reconstruct the complete haplotypes due to high sequencing error rates of long reads and limited capturing efficiency of co-barcoded reads. We here present a pipeline, AsmMix, for generating both contiguous and accurate diploid genomes. It first assembles co-barcoded reads to generate accurate haplotype-resolved assemblies that may contain many gaps, while the long-read assembly is contiguous but susceptible to errors. Then two assembly sets are integrated into haplotype-resolved assemblies with reduced misassembles. Through extensive evaluation on multiple synthetic datasets, AsmMix consistently demonstrates high precision and recall rates for haplotyping across diverse sequencing platforms, coverage depths, read lengths, and read accuracies, significantly outperforming other existing tools in the field. Furthermore, we validate the effectiveness of our pipeline using a human whole genome dataset (HG002), and produce highly contiguous, accurate, and haplotype-resolved assemblies. These assemblies are evaluated using the GIAB benchmarks, confirming the accuracy of variant calling. Our results demonstrate that AsmMix offers a straightforward yet highly efficient approach that effectively leverages both long reads and co-barcoded reads for haplotype-resolved assembly.

A Simple Cost-Effective Method for Whole-Genome Sequencing, Haplotyping, and Assembly

In this chapter, we describe single-tube long fragment read (stLFR), a simple preparation method for whole-genome sequencing and physical haplotyping based on the DNA co-barcoding strategy. Similar to LFR, stLFR applies the concept of adding the same barcode to subfragments derived from the same long DNA molecule. However, instead of a 384-well plate, stLFR uses the surface of micron-sized magnetic beads to create millions of virtual compartments in a single reaction tube. This is enabled by a split and pool barcoded bead preparation process capable of generating ~500,000 copies of the same unique barcode, from a library of ~3.6 billion unique barcodes, on each bead. The instruments and devices used in the stLFR process are easily accessible in nearly all standard molecular biology laboratories, and the cost of reagents can be as low as 30 dollars per sample. stLFR libraries can be sequenced by standard second-generation sequencing instruments (e.g., MGI or Illumina devices), and the barcode sharing information enables detection and phasing of all variations, including large structural variations. In addition, stLFR data can be used to scaffold contigs and de novo assemble genomes.

MetaTrass: A high-quality metagenome assembler of the human gut microbiome by cobarcoding sequencing reads

Metagenomic evidence of great genetic diversity within the nonconserved regions of the human gut microbial genomes appeals for new methods to elucidate the species-level variability at high resolution. However, current approaches cannot satisfy this methodologically challenge. In this study, we proposed an efficient binning-first-and-assembly-later strategy, named MetaTrass, to recover high-quality species-resolved genomes based on public reference genomes and the single-tube long fragment read (stLFR) technology, which enables cobarcoding. MetaTrass can generate genomes with longer contiguity, higher completeness, and lower contamination than those produced by conventional assembly-first-and-binning-later strategies. From a simulation study on a mock microbial community, MetaTrass showed the potential to improve the contiguity of assembly from kb to Mb without accuracy loss, as compared to other methods based on the next-generation sequencing technology. From four human fecal samples, MetaTrass successfully retrieved 178 high-quality genomes, whereas only 58 ones were provided by the optimal performance of other conventional strategies. Most importantly, these high-quality genomes confirmed the high level of genetic diversity among different samples and unveiled much more. MetaTrass was designed to work with metagenomic reads sequenced by stLFR technology, but is also applicable to other types of cobarcoding libraries. With the high capability of assembling high-quality genomes of metagenomic data sets, MetaTrass seeks to facilitate the study of spatial characters and dynamics of complex microbial communities at enhanced resolution. The open-source code of MetaTrass is available at https://github.com/BGI-Qingdao/MetaTrass.