bioRxiv ScienceSearch

bioRxiv · 10.1101/076208

Using MinION nanopore sequencing to generate a de novo eukaryotic draft genome: preliminary physiological and genomic description of the extremophilic red alga Galdieria sulphuraria strain SAG 107.79

Abstract

We report here the de novo assembly of a eukaryotic genome using only MinION nanopore DNA sequence data by examining a novel Galdieria sulphuraria genome: strain SAG 107.79. This extremophilic red alga was targeted for full genome sequencing as we found that it could grow on a wide variety of carbon sources and could uptake several precious and rare-earth metals, which places it as an interesting biological target for disparate industrial biotechnological uses. Phylogenetic analysis clearly places this as a species of G. sulphuraria. Here we additionally show that the genome assembly generated via nanopore long read data was of a high quality with regards to low total number of contiguous DNA sequences and long length of assemblies. Collectively, the MinION platform looks to rival other competing approaches for de novo genome acquisition with available informatics tools for assembly. The genome assembly is publically released as NCBI BioProject PRJNA330791. Further work is needed to reduce small insertion-deletion errors, relative to short-read assemblies.

Explore related subjects

Keep this discovery

BibTeXRIS

Amanda M. Davis, Manuela Iovinella, Sally James, Thomas Robshaw, Jennifer H. Dodson, Lorenzo Herrero-Davila, James H. Clark, Maria Agapiou, Simon McQueen-Mason, Gabriele Pinto, Claudia Ciniglia, James P. J. Chong, Peter D Ashton, Seth Jon Davis. 2016-09-20. Using MinION nanopore sequencing to generate a de novo eukaryotic draft genome: preliminary physiological and genomic description of the extremophilic red alga Galdieria sulphuraria strain SAG 107.79. https://doi.org/10.1101/076208

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Identification of genetic variants affecting vitamin D receptor binding and associations with autoimmune disease

Large numbers of statistically significant associations between sentinel SNPs and case-control status have been replicated by genome-wide association studies. Nevertheless, few underlying molecular mechanisms of complex disease are currently known. We investigated whether variation in binding of a transcription factor, the vitamin D receptor (VDR) whose activating ligand vitamin D has been proposed as a modifiable factor in multiple disorders, could explain any of these associations. VDR modifies gene expression by binding DNA as a heterodimer with the Retinoid X receptor (RXR).\n\nWe identified 43,332 genetic variants significantly associated with altered VDR binding affinity (VDR-BVs) using a high-resolution (ChIP-exo) genome-wide analysis of 27 HapMap lymphoblastoid cell lines. VDR-BVs are enriched in consensus RXR::VDR binding motifs, yet most fell outside of these motifs, implying that genetic variation often affects binding affinity only indirectly. Finally, we compared 341 VDR-BVs replicating by position in multiple individuals against background sets of variants lying within VDR-binding regions that had been matched in allele frequency and were independent with respect to linkage disequilibrium. In this stringent test, these replicated VDR-BVs were significantly (q < 0.1) and substantially (> 2-fold) enriched in genomic intervals associated with autoimmune and other diseases, including inflammatory bowel disease, Crohns disease and rheumatoid arthritis. The approachs validity is underscored by RXR::VDR motif sequence being predictive of binding strength and being evolutionarily constrained.\n\nOur findings are consistent with altered RXR::VDR binding contributing to immunity-related diseases. Replicated VDR-BVs associated with these disorders could represent causal disease risk alleles whose effect may be modifiable by vitamin D levels.

Genomics

Two novel genes discovered in human mitochondrial DNA using PacBio full-length transcriptome data

In this study, we introduced a general framework to use PacBio full-length transcriptome sequencing for the investigation of the fundamental problems in mitochondrial biology, e.g. genome arrangement, heteroplasmy, RNA processing and the regulation of transcription or replication. As a result, we produced the first full-length human mitochondrial transcriptome from the MCF7 cell line based on the PacBio platform and characterized the human mitochondrial transcriptome with more comprehensive and accurate information. The most important finding was two novel lnRNAs hsa-MDL1 and hsa-MDL1AS, which are encoded by the mitochondrial D-loop regions. We propose hsa-MDL1 and hsa-MDL1AS, as the precursors of transcription initiation RNAs (tiRNAs), belong to a novel class of long non-coding RNAs (lnRNAs), which is named as long tiRNAs (ltiRNAs). Based on the mitochondrial RNA processing model, the primary tiRNAs, precursors and mature tiRNAs could be discovered to completely reveal tiRNAs from their origins to functions. The MDL1 and MDL1AS lnRNAs and their regulation mechanisms exist ubiquitously from insects to human.

Genomics

Omics and bioinformatics approaches to target boar taint

In livestock species, a rapid growth in high-throughput omics data has accelerated the pace of studies that target to dissect economically important traits to provide better quality animal products to consumers. In pig industries, young boars are generally castrated to remove boar taint, a phenotypic and inheritable trait well-known by an abnormally bad smell and taste in pork meat derived from some uncastrated male pigs. Existence of porcine reference genome made possible to catalogue genome-wide QTLs, candidate genes and biomarkers in associations with boar taint and other industrially significant traits in pigs. The aim of this paper to review the contribution of bioinformatics resources and omics technology in boar taint related studies. This paper also provides concise details about state-of-the-art sequencing technology.

Genomics