Back

Optimised DNA isolation from marine sponges for natural sampler DNA (nsDNA) metabarcoding

Harper, L. R.; Neave, E. F.; Sellers, G. S.; Cunnington, A. V.; Arias, M. B.; Craggs, J.; MacDonald, B.; Riesgo, A.; Mariani, S.

2022-07-11 molecular biology
10.1101/2022.07.11.499619 bioRxiv
Show abstract

Marine sponges have recently been recognised as natural samplers of environmental DNA (eDNA) due to their effective water filtration and their ubiquitous, sessile and regenerative nature. However, laboratory workflows for metabarcoding of sponge tissue have not been optimised to ensure that these natural samplers achieve their full potential for community survey. We used a phased approach to investigate the influence of DNA isolation procedures on the biodiversity information recovered from sponges. In Phase 1, we compared three treatments of residual ethanol preservative in sponge tissue alongside five DNA extraction protocols. The results of Phase 1 informed which ethanol treatment and DNA extraction protocol should be used in Phase 2, where we assessed the effect of starting tissue mass on extraction success and whether homogenisation of sponge tissue is required. Phase 1 results indicated that ethanol preservative may contain unique and/or additional biodiversity information to that present in sponge tissue, but blotting tissue dry generally recovered more taxa and generated more sequence reads from the wild sponge species. Tissue extraction protocols performed best in terms of DNA concentration, taxon richness and proportional read counts, but the non-commercial tissue protocol was selected for Phase 2 due to cost-efficiency and greater recovery of target taxa. In Phase 2 overall, we found that homogenisation may not be required for sponge tissue and more starting material does not necessarily improve taxon detection. These results combined provide an optimised DNA isolation procedure for sponges to enhance marine biodiversity assessment using natural sampler DNA metabarcoding.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Molecular Ecology Resources
171 papers in training set
Top 0.1%
23.6%
2
Environmental DNA
56 papers in training set
Top 0.1%
19.6%
3
Metabarcoding and Metagenomics
14 papers in training set
Top 0.1%
13.2%
50% of probability mass above
4
Frontiers in Marine Science
62 papers in training set
Top 0.1%
7.1%
5
PeerJ
308 papers in training set
Top 0.4%
7.1%
6
Coral Reefs
21 papers in training set
Top 0.1%
2.6%
7
Molecular Ecology
336 papers in training set
Top 2%
2.5%
8
PLOS ONE
5266 papers in training set
Top 41%
2.5%
9
Journal of Fish Biology
17 papers in training set
Top 0.1%
2.2%
10
F1000Research
88 papers in training set
Top 2%
1.5%
11
Scientific Reports
3612 papers in training set
Top 60%
1.4%
12
Ecology and Evolution
267 papers in training set
Top 4%
1.4%
13
Biological Invasions
14 papers in training set
Top 0.3%
1.2%
14
Journal of Phycology
14 papers in training set
Top 0.2%
1.1%
15
BMC Genomics
406 papers in training set
Top 8%
0.9%
16
Ecological Indicators
21 papers in training set
Top 0.5%
0.9%
17
Methods in Ecology and Evolution
176 papers in training set
Top 2%
0.6%
18
Biological Conservation
46 papers in training set
Top 0.9%
0.6%
19
Evolutionary Applications
108 papers in training set
Top 2%
0.6%
20
Freshwater Biology
12 papers in training set
Top 0.4%
0.5%
21
Limnology and Oceanography: Methods
11 papers in training set
Top 0.3%
0.5%
22
Biology Methods and Protocols
61 papers in training set
Top 3%
0.5%
23
Ecological Applications
34 papers in training set
Top 1%
0.5%