Dataset Information

Genome sequencing and de novo assembly of the giant unicellular alga Acetabularia acetabulum using droplet MDA.

ABSTRACT: The macroscopic single-celled green alga Acetabularia acetabulum has been a model system in cell biology for more than a century. However, no genomic information is available from this species. Since the alga has a long life cycle, is difficult to grow in dense cultures, and has an estimated diploid genome size of almost 2 Gb, obtaining sufficient genomic material for genome sequencing is challenging. Here, we have attempted to overcome these challenges by amplifying genomic DNA using multiple displacement amplification (MDA) combined with microfluidics technology to distribute the amplification reactions across thousands of microscopic droplets. By amplifying and sequencing DNA from five single cells we were able to recover an estimated ~ 7-11% of the total genome, providing the first draft of the A. acetabulum genome. We highlight challenges associated with genome recovery and assembly of MDA data due to biases arising during genome amplification, and hope that our study can serve as a reference for future attempts on sequencing the genome from non-model eukaryotes.

SUBMITTER: Andresen IJ

PROVIDER: S-EPMC8211769 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Genome sequencing and de novo assembly of the giant unicellular alga Acetabularia acetabulum using droplet MDA.

Andresen Ina J IJ Orr Russell J S RJS Krabberød Anders K AK Shalchian-Tabrizi Kamran K Bråte Jon J

Scientific reports 20210617 1

The macroscopic single-celled green alga Acetabularia acetabulum has been a model system in cell biology for more than a century. However, no genomic information is available from this species. Since the alga has a long life cycle, is difficult to grow in dense cultures, and has an estimated diploid genome size of almost 2 Gb, obtaining sufficient genomic material for genome sequencing is challenging. Here, we have attempted to overcome these challenges by amplifying genomic DNA using multiple d ...[more]

PMID: 34140556

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Project description:There are very few methods for de novo genome assembly based on the overlap graph approach. It is considered as giving more exact results than the so-called de Bruijn graph approach but in much greater time and of much higher memory usage. It is not uncommon that assembly methods involving the overlap graph model are not able to successfully compute greater data sets, mainly due to memory limitation of a computer. This was the reason for developing in last decades mainly de Bruijn-based assembly methods, fast and fairly accurate. However, the latter methods can fail for longer or more repetitive genomes, as they decompose reads to shorter fragments and lose a part of information. An efficient assembler for processing big data sets and using the overlap graph model is still looked out. We propose a new genome-scale de novo assembler based on the overlap graph approach, designed for short-read sequencing data. The method, ALGA, incorporates several new ideas resulting in more exact contigs produced in short time. Among these ideas we have creation of a sparse but quite informative graph, reduction of the graph including a procedure referring to the problem of minimum spanning tree of a local subgraph, and graph traversal connected with simultaneous analysis of contigs stored so far. What is rare in genome assembly, the algorithm is almost parameter-free, with only one optional parameter to be set by a user. ALGA was compared with nine state-of-the-art assemblers in tests on genome-scale sequencing data obtained from real experiments on six organisms, differing in size, coverage, GC content, and repetition rate. ALGA produced best results in the sense of overall quality of genome reconstruction, understood as a good balance between genome coverage, accuracy, and length of resulting sequences. The algorithm is one of tools involved in processing data in currently realized national project Genomic Map of Poland. ALGA is available at http://alga.put.poznan.pl. Supplementary material is available at Bioinformatics online.

Dataset Information

Genome sequencing and de novo assembly of the giant unicellular alga Acetabularia acetabulum using droplet MDA.

Publications

Genome sequencing and de novo assembly of the giant unicellular alga Acetabularia acetabulum using droplet MDA.

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