Back

AVITI library prep miniaturization and combining with Illumina data for phylogenomic and population genomic analyses

Landis, J. B.; Hufnagel, E.; Felton, J. M.; Harden, J. J.; Almeida, D.; Specht, C. D.

2025-07-31 evolutionary biology
10.1101/2025.07.30.667782 bioRxiv
Show abstract

Recent advancements in next generation sequencing approaches allow for expansion of evolutionary research into the discovery of genetic patterns and processes underlying diversification across scales. The increased popularity of the Element Bioscience AVITI platform, partially due to the high sequencing accuracy and low cost of reagents, is becoming a viable alternative approach for generating massive amounts of comparative sequencing data across diverse organismal lineages. Using a data set of five accessions from the monocot genus Costus, we tested miniaturization conditions for generating robust, cost-effective libraries and made comparisons of data generated by AVITI and Illumina sequencing platforms to investigate the potential for combining data for population genomic and phylogenomic analyses. Our results show that the AVITI and Illumina data sets are highly congruent in terms of inferring overlapping SNPs, with only a small fraction picked up by only one of the two platforms. The rates of duplication in miniaturized libraries were much higher than in full volume libraries and in the Illumina libraries, resulting in missing SNPs and less sequence coverage when volumes are reduced. For all generated libraries, most downstream evolutionary analyses, including clustering algorithms (such as PCA) and phylogenetic inference, yielded similar results. However, Structure analyses were less consistent across datasets, with data from the most miniaturized libraries being assigned to the wrong clusters. The AVITI platform should be seen as a cost-effective approach for generating genomic data for comparison across taxonomic lineages, even for ongoing projects where Illumina data already exists.

Matching journals

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

1
Molecular Ecology Resources
161 papers in training set
Top 0.1%
39.0%
2
BMC Genomics
328 papers in training set
Top 0.2%
8.3%
3
Molecular Phylogenetics and Evolution
61 papers in training set
Top 0.1%
4.8%
50% of probability mass above
4
Methods in Ecology and Evolution
160 papers in training set
Top 0.7%
4.3%
5
Genome Biology and Evolution
280 papers in training set
Top 0.5%
3.6%
6
Ecology and Evolution
232 papers in training set
Top 2%
2.4%
7
Molecular Biology and Evolution
488 papers in training set
Top 2%
2.1%
8
PLOS ONE
4510 papers in training set
Top 51%
1.9%
9
PeerJ
261 papers in training set
Top 6%
1.8%
10
Systematic Biology
121 papers in training set
Top 0.3%
1.7%
11
Molecular Ecology
304 papers in training set
Top 3%
1.7%
12
Scientific Reports
3102 papers in training set
Top 59%
1.7%
13
Applications in Plant Sciences
21 papers in training set
Top 0.2%
1.7%
14
G3 Genes|Genomes|Genetics
351 papers in training set
Top 1%
1.6%
15
NAR Genomics and Bioinformatics
214 papers in training set
Top 2%
1.5%
16
BMC Ecology and Evolution
49 papers in training set
Top 1%
1.5%
17
G3: Genes, Genomes, Genetics
222 papers in training set
Top 0.6%
1.2%
18
Bioinformatics
1061 papers in training set
Top 8%
1.1%
19
Gigabyte
60 papers in training set
Top 1%
0.8%
20
Nature Communications
4913 papers in training set
Top 63%
0.7%
21
New Phytologist
309 papers in training set
Top 5%
0.7%
22
Peer Community Journal
254 papers in training set
Top 4%
0.7%
23
Communications Biology
886 papers in training set
Top 27%
0.7%
24
Microbial Genomics
204 papers in training set
Top 2%
0.7%
25
The Plant Journal
197 papers in training set
Top 4%
0.6%
26
DNA Research
23 papers in training set
Top 0.6%
0.6%