HTSQualC is a flexible and one-step quality control software for high-throughput sequencing data analysis

Long intergenic non-coding RNAs modulate proximal protein-coding gene expression and tolerance to Candidatus Liberibacter spp. in potatoes

Long intergenic non-coding RNAs (lincRNAs) are emerging as regulators of protein-coding genes (PCGs) in many plant and animal developmental processes and stress responses. In this study, we characterize the genome-wide lincRNAs in potatoes responsive to a vascular bacterial disease presumably caused by Candidatus Liberibacter solanacearum (CLso). Approximately 4397 lincRNAs were detected in healthy and infected potato plants at various stages of zebra chip (ZC) disease progression. Of them, ~65% (2844) were novel lincRNAs, and less than 1% (9) were orthologs of Arabidopsis and rice based on reciprocal BLAST analysis, suggesting species-specific expansion. Among the proximal lincRNAs within 50 kbp from a PCG, ~49% were transcribed from the same strand, while ~39% and ~15% followed convergent (head-to-head) and divergent (tail-to-tail) orientations, respectively. Approximately 30% (1308) were differentially expressed following CLso infection, with substantial changes occurring 21 days after infection (DAI). Weighted Gene Co-expression Network Analysis (WGCNA) of lincRNAs and PCGs identified 46 highly correlated lincRNA-PCG pairs exhibiting co-up or co-downregulation. Furthermore, overexpression of selected lincRNAs in transgenic potato hairy roots resulted in perturbation of neighboring PCG expression and conferred tolerance to CLso infection. Our results provide novel insights into potato lincRNAs' identity, expression dynamics, and functional relevance to CLso infection.

An overlooked phenomenon: complex interactions of potential error sources on the quality of bacterial de novo genome assemblies

BACKGROUND

Parameters adversely affecting the contiguity and accuracy of the assemblies from Illumina next-generation sequencing (NGS) are well described. However, past studies generally focused on their additive effects, overlooking their potential interactions possibly exacerbating one another's effects in a multiplicative manner. To investigate whether or not they act interactively on de novo genome assembly quality, we simulated sequencing data for 13 bacterial reference genomes, with varying levels of error rate, sequencing depth, PCR and optical duplicate ratios.

RESULTS

We assessed the quality of assemblies from the simulated sequencing data with a number of contiguity and accuracy metrics, which we used to quantify both additive and multiplicative effects of the four parameters. We found that the tested parameters are engaged in complex interactions, exerting multiplicative, rather than additive, effects on assembly quality. Also, the ratio of non-repeated regions and GC% of the original genomes can shape how the four parameters affect assembly quality.

CONCLUSIONS

We provide a framework for consideration in future studies using de novo genome assembly of bacterial genomes, e.g. in choosing the optimal sequencing depth, balancing between its positive effect on contiguity and negative effect on accuracy due to its interaction with error rate. Furthermore, the properties of the genomes to be sequenced also should be taken into account, as they might influence the effects of error sources themselves.