The structure of associations: Method insights from analyzing 28 clinical isolates of Cryptococcus neoformans.

Clinical isolates of a fungal pathogen from a single region or country often exhibit structural clonality or phylogenetic clustering at the sequence or MLST level; such population structure can persist also in larger samples. In efforts to improve causal understanding of pathogenesis at the molecular level, genome-wide association screening methods initially designed for other kingdoms have been applied to fungi. The example of a Colombian dataset of 28 clinical Cryptococcus neoformans VNI isolates indicates where the output from standard pipelines may need to be analyzed in new ways in order to efficiently extract hypotheses for experiments from fungal genotype-phenotype data.

Collections of clinical isolates of a human fungal pathogen can consist of clusters of genetically similar isolates. Such clustering complicates the screening for genetic associations with clinically relevant traits. We propose new methods, illustrating them for the fungus causing cryptococcosis.

From NGS assembly challenges to instability of fungal mitochondrial genomes: A case study in genome complexity.

The presence of repetitive or non-unique DNA persisting over sizable regions of a eukaryotic genome can hinder the genome's successful de novo assembly from short reads: ambiguities in assigning genome locations to the non-unique subsequences can result in premature termination of contigs and thus overfragmented assemblies. Fungal mitochondrial (mtDNA) genomes are compact (typically less than 100 kb), yet often contain short non-unique sequences that can be shown to impede their successful de novo assembly in silico. Such repeats can also confuse processes in the cell in vivo. A well-studied example is ectopic (out-of-register, illegitimate) recombination associated with repeat pairs, which can lead to deletion of functionally important genes that are located between the repeats. Repeats that remain conserved over micro- or macroevolutionary timescales despite such risks may indicate functionally or structurally (e.g., for replication) important regions. This principle could form the basis of a mining strategy for accelerating discovery of function in genome sequences. We present here our screening of a sample of 11 fully sequenced fungal mitochondrial genomes by observing where exact k-mer repeats occurred several times; initial analyses motivated us to focus on 17-mers occurring more than three times. Based on the diverse repeats we observe, we propose that such screening may serve as an efficient expedient for gaining a rapid but representative first insight into the repeat landscapes of sparsely characterized mitochondrial chromosomes. Our matching of the flagged repeats to previously reported regions of interest supports the idea that systems of persisting, non-trivial repeats in genomes can often highlight features meriting further attention.

The complex task of choosing a de novo assembly: lessons from fungal genomes.

Selecting the values of parameters used by de novo genomic assembly programs, or choosing an optimal de novo assembly from several runs obtained with different parameters or programs, are tasks that can require complex decision-making. A key parameter that must be supplied to typical next generation sequencing (NGS) assemblers is the k-mer length, i.e., the word size that determines which de Bruijn graph the program should map out and use. The topic of assembly selection criteria was recently revisited in the Assemblathon 2 study (Bradnam et al., 2013). Although no clear message was delivered with regard to optimal k-mer lengths, it was shown with examples that it is sometimes important to decide if one is most interested in optimizing the sequences of protein-coding genes (the gene space) or in optimizing the whole genome sequence including the intergenic DNA, as what is best for one criterion may not be best for the other. In the present study, our aim was to better understand how the assembly of unicellular fungi (which are typically intermediate in size and complexity between prokaryotes and metazoan eukaryotes) can change as one varies the k-mer values over a wide range. We used two different de novo assembly programs (SOAPdenovo2 and ABySS), and simple assembly metrics that also focused on success in assembling the gene space and repetitive elements. A recent increase in Illumina read length to around 150 bp allowed us to attempt de novo assemblies with a larger range of k-mers, up to 127 bp. We applied these methods to Illumina paired-end sequencing read sets of fungal strains of Paracoccidioides brasiliensis and other species. By visualizing the results in simple plots, we were able to track the effect of changing k-mer size and assembly program, and to demonstrate how such plots can readily reveal discontinuities or other unexpected characteristics that assembly programs can present in practice, especially when they are used in a traditional molecular microbiology laboratory with a 'genomics corner'. Here we propose and apply a component of a first pass validation methodology for benchmarking and understanding fungal genome de novo assembly processes.

The eukaryotic genome, its reads, and the unfinished assembly.

In recent years, readily affordable short read sequences provided by next-generation sequencing (NGS) have become longer and more accurate. This has led to a jump in interest in the utility of NGS-only approaches for exploring eukaryotic genomes. The concept of a static, 'finished' genome assembly, which still appears to be a faraway goal for many eukaryotes, is yielding to new paradigms. We here motivate an object-view concept where the raw reads are the main, fixed object, and assemblies with their annotations take a role of dynamically changing and modifiable views of that object.