Highly contiguous assemblies of 101 drosophilid genomes
Abstract
Over 100 years of studies in Drosophila melanogaster and related species in the genus Drosophila have facilitated key discoveries in genetics, genomics, and evolution. While high-quality genome assemblies exist for several species in this group, they only encompass a small fraction of the genus. Recent advances in long-read sequencing allow high-quality genome assemblies for tens or even hundreds of species to be efficiently generated. Here, we utilize Oxford Nanopore sequencing to build an open community resource of genome assemblies for 101 lines of 93 drosophilid species encompassing 14 species groups and 35 sub-groups. The genomes are highly contiguous and complete, with an average contig N50 of 10.5 Mb and greater than 97% BUSCO completeness in 97/101 assemblies. We show that Nanopore-based assemblies are highly accurate in coding regions, particularly with respect to coding insertions and deletions. These assemblies, along with a detailed laboratory protocol and assembly pipelines, are released as a public resource and will serve as a starting point for addressing broad questions of genetics, ecology, and evolution at the scale of hundreds of species.
Data availability
All sequencing data and assemblies generated by this study are deposited at NCBI SRA and GenBank under NCBI BioProject PRJNA675888. Accession numbers for all data used but not generated by this study are provided in the supporting files. Dockerfiles and scripts for reproducing pipelines and analyses are provided on GitHub (https://github.com/flyseq/drosophila_assembly_pipelines). A detailed wet lab protocol is provided at Protocols.io (https://dx.doi.org/10.17504/protocols.io.bdfqi3mw).
-
Nanopore-based assembly of many drosophilid genomesNCBI BioProject, PRJNA675888.
-
Sequencing and assembly of 14 Drosophila speciesNCBI BioProject, ID: 427774.
-
modENCODE Drosophila reference genome sequencing (fruit flies)NCBI BioProject, ID: 62477.
-
Drosophila montium Species Group Genomes ProjectNCBI BioProject, ID: 554346.
-
Invertebrate sample from Drosophila repletaNCBI BioProject, ID: 476692.
-
Genome sequences of 10 Drosophila speciesNCBI BioProject, ID: 322011.
-
Raw genomic sequencing data from 16 Drosophila speciesNCBI BioProject, ID: 550077.
Article and author information
Author details
Funding
National Institute of General Medical Sciences (F32GM135998)
- Bernard Y Kim
National Institute of General Medical Sciences (R35GM119816)
- Noah K Whiteman
Uehara Memorial Foundation (201931028)
- Teruyuki Matsunaga
Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178)
- Marina Stamenković-Radak
- Mihailo Jelić
- Marija Savić Veselinović
Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007)
- Marija Tanasković
- Pavle Erić
National Natural Science Foundation of China (32060112)
- Jian-Jun Gao
Japan Society for the Promotion of Science (JP18K06383)
- Masayoshi Watada
European Union Horizon 2020 Research and Innovation Program (765937-CINCHRON)
- Giulia Manoli
- Enrico Bertolini
Czech Science Foundation (19-13381S)
- Vladimír Košťál
Japan Society for the Promotion of Science (JP19H03276)
- Aya Takahashi
National Science Foundation (1345247)
- Donald K Price
National Institute of General Medical Sciences (R35GM118165)
- Dmitri A Petrov
National Institute of Diabetes and Digestive and Kidney Diseases (K01DK119582)
- Jeremy Wang
National Science Foundation (DEB-1457707)
- Corbin D Jones
National Institute of General Medical Sciences (R01GM121750)
- Daniel R Matute
National Institute of General Medical Sciences (R01GM125715)
- Daniel R Matute
Google Cloud Platform Research Credits
- Bernard Y Kim
Google Cloud Platform Research Credits
- Jeremy Wang
National Institute of General Medical Sciences (R35GM122592)
- Artyom Kopp
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Kim et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 9,046
- views
-
- 1,062
- downloads
-
- 132
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Cancer Biology
- Evolutionary Biology
In growing cell populations such as tumours, mutations can serve as markers that allow tracking the past evolution from current samples. The genomic analyses of bulk samples and samples from multiple regions have shed light on the evolutionary forces acting on tumours. However, little is known empirically on the spatio-temporal dynamics of tumour evolution. Here, we leverage published data from resected hepatocellular carcinomas, each with several hundred samples taken in two and three dimensions. Using spatial metrics of evolution, we find that tumour cells grow predominantly uniformly within the tumour volume instead of at the surface. We determine how mutations and cells are dispersed throughout the tumour and how cell death contributes to the overall tumour growth. Our methods shed light on the early evolution of tumours in vivo and can be applied to high-resolution data in the emerging field of spatial biology.