Prybol, C. J. | bioRxiv Science

bioRxiv2024

A Novel Approach for Accurate Sequence Assembly Using de Bruijn graphs

Sequence assembly methods are valuable for reconstructing genomes from shorter read fragments. Modern nucleic acid sequencing instruments produce quality scores associated with each reported base; however, these quality scores are not generally used as a core part of sequence assembly or alignment algorithms. Here, we leverage weighted de Bruijn graphs as graphical probability models representing the relative abundances and qualities of kmers within FASTQ-encoded observations. We then utilize these weighted de Bruijn graphs to identify alternate, higher-likelihood candidate sequences compared to the original observations, which are known to contain errors. By improving the original observations with these resampled paths, iteratively across increasing k-lengths, we can use this expectation-maximization approach to "polish" read sets from any sequencing technology according to the mutual information shared in the reads. We use this polishing approach to probabilistically correct simulated short- and long-read datasets of lower coverages and higher error rates than some algorithms can produce satisfactory assemblies for. We find that this approach corrects sequencing errors at rates that are able to produce error-free and nearly-error-free de Bruijn assembly graphs for simulated read-set challenges.

bioinformatics↗

bioRxiv2018

Identification of rare-disease genes in diverse undiagnosed cases using whole blood transcriptome sequencing and large control cohorts

RNA sequencing (RNA-seq) is a complementary approach for Mendelian disease diagnosis for patients in whom exome-sequencing is not informative. For both rare neuromuscular and mitochondrial disorders, its application has improved diagnostic rates. However, the generalizability of this approach to diverse Mendelian diseases has yet to be evaluated. We sequenced whole blood RNA from 56 cases with undiagnosed rare diseases spanning 11 diverse disease categories to evaluate the general application of RNA-seq to Mendelian disease diagnosis. We developed a robust approach to compare rare disease cases to existing large sets of RNA-seq controls (N=1,594 external and N=31 family-based controls) and demonstrated the substantial impacts of gene and variant filtering strategies on disease gene identification when combined with RNA-seq. Across our cohort, we observed that RNA-seq yields a 8.5% diagnostic rate. These diagnoses included diseases where blood would not intuitively reflect evidence of disease. We identified RARS2 as an under-expression outlier containing compound heterozygous pathogenic variants for an individual exhibiting profound global developmental delay, seizures, microcephaly, hypotonia, and progressive scoliosis. We also identified a new splicing junction in KCTD7 for an individual with global developmental delay, loss of milestones, tremors and seizures. Our study provides a broad evaluation of blood RNA-seq for the diagnosis of rare disease.

genomics↗