Mining statistically-solid k-mers for accurate NGS error correction

Scalable, ultra-fast, and low-memory construction of compacted de Bruijn graphs with Cuttlefish 2

The de Bruijn graph is a key data structure in modern computational genomics, and construction of its compacted variant resides upstream of many genomic analyses. As the quantity of genomic data grows rapidly, this often forms a computational bottleneck. We present Cuttlefish 2, significantly advancing the state-of-the-art for this problem. On a commodity server, it reduces the graph construction time for 661K bacterial genomes, of size 2.58Tbp, from 4.5 days to 17-23 h; and it constructs the graph for 1.52Tbp white spruce reads in approximately 10 h, while the closest competitor requires 54-58 h, using considerably more memory.

Simultaneous compression of multiple error-corrected short-read sets for faster data transmission and better de novo assemblies

Next-Generation Sequencing has produced incredible amounts of short-reads sequence data for de novo genome assembly over the last decades. For efficient transmission of these huge datasets, high-performance compression algorithms have been intensively studied. As both the de novo assembly and error correction methods utilize the overlaps between reads data, a concern is that the will the sequencing errors bring up negative effects on genome assemblies also affect the compression of the NGS data. This work addresses two problems: how current error correction algorithms can enable the compression algorithms to make the sequence data much more compact, and whether the sequence-modified reads by the error-correction algorithms will lead to quality improvement for de novo contig assembly. As multiple sets of short reads are often produced by a single biomedical project in practice, we propose a graph-based method to reorder the files in the collection of multiple sets and then compress them simultaneously for a further compression improvement after error correction. We use examples to illustrate that accurate error correction algorithms can significantly reduce the number of mismatched nucleotides in the reference-free compression, hence can greatly improve the compression performance. Extensive test on practical collections of multiple short-read sets does confirm that the compression performance on the error-corrected data (with unchanged size) significantly outperforms that on the original data, and that the file reordering idea contributes furthermore. The error correction on the original reads has also resulted in quality improvements of the genome assemblies, sometimes remarkably. However, it is still an open question that how to combine appropriate error correction methods with an assembly algorithm so that the assembly performance can be always significantly improved.

The third international hackathon for applying insights into large-scale genomic composition to use cases in a wide range of organisms

In October 2021, 59 scientists from 14 countries and 13 U.S. states collaborated virtually in the Third Annual Baylor College of Medicine & DNANexus Structural Variation hackathon. The goal of the hackathon was to advance research on structural variants (SVs) by prototyping and iterating on open-source software. This led to nine hackathon projects focused on diverse genomics research interests, including various SV discovery and genotyping methods, SV sequence reconstruction, and clinically relevant structural variation, including SARS-CoV-2 variants. Repositories for the projects that participated in the hackathon are available at https://github.com/collaborativebioinformatics.

Gene Mining and Flavour Metabolism Analyses of Wickerhamomyces anomalus Y-1 Isolated From a Chinese Liquor Fermentation Starter

Luzhou-flavoured liquor is one of Chinese most popular distilled liquors. Hundreds of flavoured components have been detected from this liquor, with esters as its primary flavouring substance. Among these esters, ethyl hexanoate was the main component. As an essential functional microbe that produces ethyl hexanoate, yeast is an important functional microorganism that produces ethyl hexanoate. The synthesis of ethyl hexanoate in yeast mainly involves the lipase/esterase synthesis pathway, alcohol transferase pathway and alcohol dehydrogenase pathway. In this study, whole-genome sequencing of W. anomalus Y-1 isolated from a Chinese liquor fermentation starter, a fermented wheat starter containing brewing microorganisms, was carried out using the Illumina HiSeq X Ten platform. The sequence had a length of 15,127,803 bp with 34.56% GC content, encoding 7,024 CDS sequences, 69 tRNAs and 1 rRNA. Then, genome annotation was performed using three high-quality databases, namely, COG, KEGG and GO databases. The annotation results showed that the ko7019 pathway of gene 6,340 contained the Eht1p enzyme, which was considered a putative acyltransferase similar to Eeb1p and had 51.57% homology with two known medium-chain fatty acid ethyl ester synthases, namely, Eht1 and Eeb1. Ethyl hexanoate in W. anomalus was found to be synthesised through the alcohol acyltransferase pathway, while acyl-coenzyme A and alcohol were synthesised under the catalytic action of Eht1p. The results of this study are beneficial to the exploration of key genes of ester synthesis and provide reference for the improvement of liquor flavoured.

Dual UMIs and Dual Barcodes With Minimal PCR Amplification Removes Artifacts and Acquires Accurate Antibody Repertoire

Antibody repertoire sequencing (Rep-seq) has been widely used to reveal repertoire dynamics and to interrogate antibodies of interest at single nucleotide-level resolution. However, polymerase chain reaction (PCR) amplification introduces extensive artifacts including chimeras and nucleotide errors, leading to false discovery of antibodies and incorrect assessment of somatic hypermutations (SHMs) which subsequently mislead downstream investigations. Here, a novel approach named DUMPArts, which improves the accuracy of antibody repertoires by labeling each sample with dual barcodes and each molecule with dual unique molecular identifiers (UMIs) via minimal PCR amplification to remove artifacts, is developed. Tested by ultra-deep Rep-seq data, DUMPArts removed inter-sample chimeras, which cause artifactual shared clones and constitute approximately 15% of reads in the library, as well as intra-sample chimeras with erroneous SHMs and constituting approximately 20% of the reads, and corrected base errors and amplification biases by consensus building. The removal of these artifacts will provide an accurate assessment of antibody repertoires and benefit related studies, especially mAb discovery and antibody-guided vaccine design.

Comparative analysis of 7 short-read sequencing platforms using the Korean Reference Genome: MGI and Illumina sequencing benchmark for whole-genome sequencing

BACKGROUND

DNBSEQ-T7 is a new whole-genome sequencer developed by Complete Genomics and MGI using DNA nanoball and combinatorial probe anchor synthesis technologies to generate short reads at a very large scale-up to 60 human genomes per day. However, it has not been objectively and systematically compared against Illumina short-read sequencers.

FINDINGS

By using the same KOREF sample, the Korean Reference Genome, we have compared 7 sequencing platforms including BGISEQ-500, DNBSEQ-T7, HiSeq2000, HiSeq2500, HiSeq4000, HiSeqX10, and NovaSeq6000. We measured sequencing quality by comparing sequencing statistics (base quality, duplication rate, and random error rate), mapping statistics (mapping rate, depth distribution, and percent GC coverage), and variant statistics (transition/transversion ratio, dbSNP annotation rate, and concordance rate with single-nucleotide polymorphism [SNP] genotyping chip) across the 7 sequencing platforms. We found that MGI platforms showed a higher concordance rate for SNP genotyping than HiSeq2000 and HiSeq4000. The similarity matrix of variant calls confirmed that the 2 MGI platforms have the most similar characteristics to the HiSeq2500 platform.

CONCLUSIONS

Overall, MGI and Illumina sequencing platforms showed comparable levels of sequencing quality, uniformity of coverage, percent GC coverage, and variant accuracy; thus we conclude that the MGI platforms can be used for a wide range of genomics research fields at a lower cost than the Illumina platforms.

Genetic characterization and population structure of different coat colour variants of Badri cattle

The present study aimed to genetically characterize the Badri cattle and its three colour variants and assess their population structure using 24 microsatellite markers. Out of 96 animals analyzed, 32 each were collected from grey (GVBC), brown (BrVBC) and black (BVBC) colour variants of Badri cattle (BC). The genetic diversity parameters including allele frequencies, observed and effective number of alleles, observed and expected heterozygosity, PIC, Shannon's indices and F-statistics were estimated using POPGENE software. Bottleneck analysis was performed using both qualitative and quantitative approaches. A total of 274 alleles (50 private and 224 shared) were scored for BC, GVBC, BrVBC and BVBC with mean number of 11.417, 9.083, 9.125 and 9.083 alleles, respectively. All populations exhibited average heterozygosity estimate > 0.5 indicating existence of substantial genetic variability, concurrent with revelations from Shannon's indices. Observed mean PIC estimates (> 0.74) were indicative of optimum informativeness of used microsatellite markers. The mean inbreeding estimates (F) in GVBC, BrVBC and BVBC were 0.041, - 0.024 and 0.016, respectively. The pair wise genetic (> 0.91) pointed towards similarity between different colour variant populations. STRUCTURE analysis also revealed clear admixture for the three Badri colour variants indicating absence of genetic differentiation. The present study revealed first-hand information that populations of Badri cattle with different phenotypes with respect to coat colour are genetically related and can be considered as a single breed. The comprehensive knowledge generated for Badri cattle will help in designing breeding plan for its genetic improvement and deciding the conservation priorities.

Efficient Mining of Variants From Trios for Ventricular Septal Defect Association Study

Ventricular septal defect (VSD) is a fatal congenital heart disease showing severe consequence in affected infants. Early diagnosis plays an important role, particularly through genetic variants. Existing panel-based approaches of variants mining suffer from shortage of large panels, costly sequencing, and missing rare variants. Although a trio-based method alleviates these limitations to some extent, it is agnostic to novel mutations and computational intensive. Considering these limitations, we are studying a novel variants mining algorithm from trio-based sequencing data and apply it on a VSD trio to identify associated mutations. Our approach starts with irrelevant k-mer filtering from sequences of a trio via a newly conceived coupled Bloom Filter, then corrects sequencing errors by using a statistical approach and extends kept k-mers into long sequences. These extended sequences are used as input for variants needed. Later, the obtained variants are comprehensively analyzed against existing databases to mine VSD-related mutations. Experiments show that our trio-based algorithm narrows down candidate coding genes and lncRNAs by about 10- and 5-folds comparing with single sequence-based approaches, respectively. Meanwhile, our algorithm is 10 times faster and 2 magnitudes memory-frugal compared with existing state-of-the-art approach. By applying our approach to a VSD trio, we fish out an unreported gene—CD80, a combination of two genes—MYBPC3 and TRDN and a lncRNA—NONHSAT096266.2, which are highly likely to be VSD-related.