Posters - Schedules

The development of next-generation sequencing (NGS) technologies has accelerated the analysis of human genomes and the characterization of human variation at scale. However, some complex variation in the genome has remained elusive to NGS technologies due to the limitations of short reads, some of which may be involved in disease. The improvement of third generation single molecule long-read sequencing technologies is enabling the sequencing and analyses of more complete human genomes. One such technology is PacBio HiFi sequencing that can currently achieve long-read lengths between 10-30 kb with accuracy greater than 99.9%. Furthermore, the recent publication of an alternative human genome assembly by the Telomere-to-Telomere (T2T) consortium provides the first gapless assembly of the human genome opening the possibility of detecting variation in previously unexplored regions of the human genome.
We performed long-read whole genome sequencing (WGS) using PacBio HiFi technology in a patient with a suspected genetic disorder for which NGS exome analysis was inconclusive with the objective of identifying all genomic variation possibly associated with disease. Given the availability of WGS data, we explored different approaches to data analysis leveraging the long-read high quality HiFi data and newly available resources. We mapped and aligned reads to the latest human genome reference assembly GRCh38.p14 and the newly published T2T-CHM3 assembly using pbmm2 to compare the advantages and feasibility of mapping to these two human genome assemblies. Additionally, we performed a de novo assembly using the haplotype resolving assembler Hifiasm. We compared the three assemblies and called simple and structural variants. Finally, we performed analyses to identify variants associated with the phenotype of interest in the patient. In summary, we evaluate the quality, feasibility, and variant overlap for three different assembly and analysis approaches of human WGS PacBio long-read sequence data.

Thanks to the development and improvements provided by next-generation sequencing (NGS) technologies, genomic databases have been growing exponentially. The need for tools that allow the analysis of these generated genomes data has grown consequently. Although there is currently a wide variety of tools for this purpose, it can be cumbersome when choosing an analysis pipeline.

Some studies have provided insight into this subject. In specific, benchmarking studies in the field of metagenomics have looked at microbial genomic assemblies and its polishing. In the specific case of fungi there are a reduced number of studies that tackle this issue. Thus, the main objective of this study was to answer the question of what assembler, Canu or Flye, is better for de novo fungal genome assembly?

For this study, we selected the fungus Setophoma sp. LCM1079, a strain of Phaeosphaeriaceae, a dominant family of the mycobiome of coffee plant Coffea arabica, in Panama. Genomic DNA was extracted from seven days old culture of the fungus in potato dextrose agar using Gentra Puregene Tissue Kit (QIAGEN). Genomic libraries were prepared using the SQK-LSK109 kit of Oxford Nanopore Technologies (ONT) and the TruSeq Nano DNA Kit of Illumina®. The ONT library was loaded into an R9.4.1 flow cell and sequenced in the ONT MinION system with the MinKNOW interface (version 4.2.4); the illumina library was sequenced in the NovaSeq 6000 platform to generate 150 pair-end reads.

Basecalling of ONT data was done with Guppy v.3.4.3. ONT long reads were adapter-trimmed with porechop, then genome assembly was performed with Canu v.2.2 and with Flye v. 2.9.1. After the assembly step, three rounds of polishing were done with Racon v.1.4.22, one round with Medakav.1.7.1 and, one round with Pilon v.1.24, using quality filtered Illumina reads. The polished assemblies were evaluated with Quast v5.0.2, Bandage v.0.8.1, and BUSCO v5.4.3.

A comparison of assemblers, reporting tabulated number of contigs, and quality controls plots were carried out and will be presented. Also, completion and genome coverage will be compared using a reference genome from the Phaeosphaeriaceae. Finally, the most suitable assembler will be reported.

Systemic Lupus Erythematosus (SLE) is an autoimmune disease, for which contribution of tissue-specific factors has been characterized and associated with T and B lymphocytes, as well as innate immune cell subsets. Nowadays a large amount of transcriptomic expression data is now publicly available for analysis. Meta-analysis allow for the integration of datasets from different sources in order to obtain robust gene expression profiles. We performed a meta-analysis using four peripheral blood mononuclear cells (PBMC) datasets with a total amount of 141 SLE patient samples and 38 healthy controls. RNA-seq data was either obtained through the Recount3 database or uniformly processed with the same Recount3-like pipeline monorail-external. Differential expression analysis was performed and combined expression data was meta-analyzed using a random effects model with two different tools, for which we show that only few genes appear to be affected by the disease status of the sample and show they are more heterogeneous between studies. The meta-analysis was also performed using a combined approach analysis that summarizes differentially expressed genes using Fisher’s method p-values and mean of fold change with the MetaVolcanoR tool. For the latter, Gene Ontology term analysis showed association for respiratory chain related pathways in downregulated genes and terms related to initiation and regulation of translation activity in upregulated genes. Additionally, we found genes of interest that were differentially expressed in several datasets and were highlighted by these meta-analysis approaches like DOHH, RIPK3, ACTR6 and ALDH9A1, related to metabolism and translation activity. These results reveal possible research insights for non-immunogenic related SLE research and also highlight the need for further regulatory related research involving distinct cellular pathways and their effect on this disease.