Skip to main content
NCBI home page
microPublication Biology logoLink to microPublication Biology
. 2022 Jan 27;2022:10.17912/micropub.biology.000518. doi: 10.17912/micropub.biology.000518

Genetic diversity estimates for the Caenorhabditis Intervention Testing Program screening panel

Anastasia A Teterina 1,2, Anna L Coleman-Hulbert 1, Stephen A Banse 1, John H Willis 1, Viviana I Perez 3, Gordon J Lithgow 4, Monica Driscoll 5, Patrick C Phillips 1,§
Reviewed by: Erik Andersen
PMCID: PMC8796004  PMID: 35098051

Abstract

The Caenorhabditis Intervention Testing Program (CITP) was founded on the principle that compounds with positive effects across a genetically diverse test-set should have an increased probability of engaging conserved biochemical pathways with mammalian translational potential. To fulfill its mandate, the CITP uses a genetic diversity panel of Caenorhabditis strains for assaying longevity effects of candidate compounds. The panel comprises 22 strains from three different species, collected globally, to achieve inter-population genetic diversity. The three represented species, C. elegans, C. briggsae, and C. tropicalis, are all sequential hermaphrodites, which simplifies experimental procedures while maximizing intra-population homogeneity. Here, we present estimates of the genetic diversity encapsulated by the constituent strains in the panel based on their most recently published and publicly available whole-genome sequences, as well as two newly generated genomic data sets. We observed average genome-wide nucleotide diversity (π) within the C. elegans (1.2e-3), C. briggsae (7.5e-3), and C. tropicalis strains (2.6e-3) greater than estimates for human populations, and comparable to that found in mouse populations. Our analysis supports the assumption that the CITP screening panel encompasses broad genetic diversity, suggesting that lifespan-extending chemicals with efficacy across the panel should be enriched for interventions that function on conserved processes that are shared across genetic backgrounds. While the diversity panel was established by the CITP for studying longevity interventions, the panel may prove useful for the broader research community when seeking broadly efficacious interventions for any phenotype with potential genetic background effects.

Figure 1. Geographic and genetic diversity in the CITP strain panel.

Figure 1. Geographic and genetic diversity in the CITP strain panel

Open in a new tab

(A) The CITP diversity panel represents 22 total nematode strains from three species, C. elegans (black circles), C. briggsae (orange triangles), and C. tropicalis (teal squares). (B) Two-dimensional representation of diversity and relatedness of the strains, LD1 and LD2 represent two latent dimensions. Bright colors indicate the core CITP strains (C. elegans:N2-PD1073, JU775, MY16; C. briggsae: AF16, HK104, ED3092; and C. tropicalis:JU1373, JU1630, QG843), while all other strains in the CITP diversity panel are indicated by muted colors. (C) Nucleotide diversity (π) of the strains used in the CITP diversity panel estimated on non-overlapping 100 kb genomic windows, core strains demonstrated by bright colors, all other strains of the panel in muted colors. The grey boxes represent the mean and the standard deviations.

Description

Model organisms have been fruitful tools for elucidating core biological principles. The power of model organism study, in part, is due to the ability to grow large populations with known genetic makeup. One of the most widely adopted genetic models is the hermaphroditic nematode Caenorhabditis elegans. The reproductive style of C. elegans makes it particularly easy to generate and maintain large populations of genetically identical individuals. In fact, the control over genetic variability helped make C. elegans the first multi-cellular organism to have its entire genome sequenced (C. elegans Sequencing Consortium 1998). Despite the success garnered using genetically homogeneous populations, it has become increasingly apparent that many of the phenotypes of interest for study are dependent on genetic background (see Evans et al. 2021 for review). Examples of these background-influenced phenotypes range from α-synuclein toxicity (Wang et al. 2019), to behavioral responses to temperature (Stegeman et al. 2013), dietary influence on lifespan and reproduction (Stastna et al. 2015), and pharmacological efficacy (Lucanic et al. 2017). The dependence on genetic background suggests that attempts to identify core biological systems and functionality could benefit from assaying across genetic diversity to identify genetic background-independent phenotypes. One way to achieve this is to use a panel of populations with intra-population homogeneity and inter-population diversity.

With the importance of genetic background effects in mind, the Caenorhabditis Intervention Testing Program (CITP) was designed to identify anti-aging and longevity-promoting compound interventions effective in a genetically diverse set of Caenorhabditis nematode populations (Lucanic et al. 2017). To date, 55 chemical compounds have been tested for reproducible, genetic background-independent effects on longevity (Lucanic et al. 2017; Banse et al. 2019; Coleman-Hulbert et al. 2019; Coleman-Hulbert et al. 2020; Morshead et al. 2020; Osman et al. 2021; Banse et al. 2021; Onken et al. 2021). The genetic diversity panel used by the CITP is composed of 22 strains from three hermaphroditic species, which facilitates maintenance of intra-population homogeneity. While the full panel is composed of 22 stains, a smaller core sub-panel of nine strains (three from each of three species, C. elegans (N2-PD1073, JU775, MY16), C. briggsae (AF16, HK104, ED3092), and C. tropicalis (JU1373, JU1630, QG843) is used in initial compound effect characterization (Banse et al. 2021). Here, we present estimates of the genetic diversity encapsulated by the constituent strains of the CITP panel, and core sub-panel, based on their most recently published and publicly available whole-genome sequences.

When establishing the genetic diversity panel for compound screening, the CITP sought strains that represented both broad geographic and genetic diversity. The three species represented in the panel are themselves globally distributed, but with ecological restrictions. For example, C. elegans is typically isolated from cooler ecological niches than C. tropicalis (Kiontke et al. 2011; Frézal and Félix 2015; Noble et al. 2021), while C. briggsae is found in niches that range from cool to warm (Frézal and Félix 2015). The wide species distributions enabled the CITP to assemble a panel of strains isolated worldwide, with representatives from most continents (Figure 1A). We next sought to determine the genetic diversity encapsulated by the panel by collecting genomic data for the strains (see Reagents) and analyzing the genomes for variation within each species (see Software). To visualize the population structure within the panel for each species we used a variational autoencoder approach, popVAE (Battey et al. 2021), to project genotypes of the strains on two latent dimensions (Figure 1B). We then determined the nucleotide diversity in the panel. The observed average genome-wide nucleotide diversity (π) among the C. elegans, C. briggsae, and C. tropicalis strains were, respectively, 1.2e-3, 7.5e-3, and 2.6e-3 (3.8e-4, 6.2e-3, and 2.4e-3 for the nine core CITP strains), which is consistent with previous estimates for those species (Graustein et al. 2002; Jovelin et al. 2009; Andersen et al. 2012; Crombie et al. 2019; Noble et al. 2021). Figure 1C shows nucleotide diversity estimated on 100 kb windows along the genomes for both the 20 strains in the full panel with available sequencing data, and for the nine strains in the core sub-panel. The estimated level of genetic diversity within these Caenorhabditis species is higher than that within human populations (Yu et al. 2004; Perry et al. 2013; Prado-Martinez et al. 2013; Arbiza et al. 2014; 1000 Genomes Project Consortium et al. 2015) and comparable to that found in mouse populations (Halligan et al. 2010; Booker and Keightley 2018). Our analysis supports the assumption that the CITP screening panel encompasses broad genetic diversity, suggesting that lifespan-extending chemicals with efficacy across the panel should be enriched for interventions that function on conserved processes that are shared across genetic backgrounds. While the diversity panel was established by the CITP for studying longevity interventions, the panel may prove useful for the broader research community when seeking broadly efficacious interventions for any phenotype with potential genetic background effects.

Methods

To generate estimates of the genetic variability among the strains in the CITP diversity panel we collected publicly available genomic data for 18 of the 22 CITP strains (see Reagents below). Because comparable Illumina-based sequencing was unavailable for N2-PD1073 and ED3092, two strains present in the core-subpanel of nine strains, we generated whole genome data for these two strains using standard protocols. In brief, we used proteinase K to digest whole worms and isolated total genomic DNA using the Genomic DNA Clean & Concentrator kit (Zymo Research). Genomic libraries were then generated using the Nextera XT DNA Library Preparation Kit (Illumina, Inc.). Sequencing was carried out on the Illumina NovaSeq 6000 platform by the Genomics and Cell Characterization Core Facility (GC3F) at the University of Oregon. We then used the two new genomic datasets, along with the 18 available in the NCBI database, to calculate genetic diversity estimates using our software pipeline (described below).

Reagents

While most of the strains in the CITP diversity panel can be obtained from the Caenorhabditis Genetics Center (CGC), the C. elegans wild-isolates should be ordered from the Caenorhabditis elegans Natural Diversity Resource (CeNDR) (Cook et al. 2017). Strains unavailable from those sources (e.g., N2-PD1073) can be obtained directly from the CITP upon request. Relevant to the unavailability of PD1073 at the CGC, PD1073 is a close relative of PD1074 which is distributed by the CGC as a wild type reference strain. PD1073, PD1074, and PD1075 are three subclones of the N2-derivative strain VC2010 that were generated in the process of assembling a new N2 reference (“VC2010-1.0”) genome (Yoshimura et al. 2019). All strains in the genetic diversity panel and the associated SRA read accession IDs used in this study are listed below:

C. elegans: strain CB4856 (with SRA read accession numbers SRR9322768, SRR9322769, SRR9322775, SRR9322863, SRR9322864), ED3040 (SRR9322720, SRR9322724, SRR9322725, SRR9322726, SRR9322818), JU1088 (SRR9322295, SRR9322300, SRR9322301), JU1652 (SRR9322577, SRR9322578, SRR9322579), JU775 (SRR9322349, SRR9322352, SRR9322355, SRR9322364), MY16 (SRR9322907, SRR9322327, SRR9322913, SRR9322161), QX1211 (SRR9324168, SRR9324217, SRR9323954, SRR9323955);

C. briggsae: AF16 (SRR2002620), HK104 (ERR3063412, ERR3063411, SRR8333803), JU1348 (SRR1793004), JU726 (SRR1792964), NIC20 (SRR1793012), QR25 (SRR1793006);

C. tropicalis: JU1373 (SRR12623131, SRR241785), JU1630 (SRR12623130), NIC58 (SRR12623045, SRR12623063), QG131 (SRR12623047), QG834 (SRR12623046).

No genomic data is publicly available for C. briggsae strain JU1264 and C. tropicalis NIC122.

Raw reads for C. elegans N2-PD1073 and C. briggsae ED3092 strains generated in this study were deposited to the SRA database (https://www.ncbi.nlm.nih.gov/sra) under the project accession ID PRJNA773598.

The core CITP strains are C. elegans N2-PD1073, MY16, and JU775; C. briggsae AF16, ED3092, and HK104; C. tropicalis JU1373, JU1630, and QG834.

Software

We estimated genetic diversity of the CITP strains using whole-genomic data for 20 out of 22 CITP strains from the panel. Reads from the SRA database were downloaded with SRA-toolkit (the SRA Toolkit Development Team). We evaluated the read quality with FastQC v.0.11.5 (Andrews 2010) and MultiQC v.1.3 (Ewels et al. 2016), and filtered and trimmed reads with Skewer v.0.2.2 (Jiang et al. 2014). We mapped filtered reads to the C. elegans, C. briggsae,and C. tropicalis genomes obtained from the WormBase database (https://wormbase.org//) version WS280 (with accession ID PRJNA13758, PRJNA10731, PRJNA53597, respectively) by BWA-MEM v.0.7.17 (Li 2013) and SAMtools v.1.5 (Li et al. 2009), and deduplicated with the Picard tools v.2.17.6 (Broad Institute). We called and filtered variants using GATK v.3.7 (McKenna et al. 2010) software and BEDtools v.2.25 (Quinlan and Hall 2010), and estimated the nucleotide diversity using VCFtools v.0.1.15 (Danecek et al. 2011), masking repetitive regions, indels, complex variants, and regions with too low or high coverage. We projected genotypes of the CITP strains on two latent dimensions using popVAE (Battey et al. 2021), and visualized them in R v.3.5 (R Core team 2018) using packages ggplot2 (Wickham 2016) and ggrepel.

All the tools used for the analysis are publicly available and free, the scripts used to get the results and figures are in the GitHub repository (https://github.com/phillips-lab/CITP_diversity/) and are available under the MIT license. The global map was generated in MATLAB R2021b (MathWorks, Inc.) using the MATLAB Mapping Toolbox. The location coordinates used for the strains are included in the GitHub repository. Figure readability was improved by moving panel relative positions, updating color coding, and improving text aesthetics using Adobe Illustrator 2022 in a manner consistent with image integrity standards.

Acknowledgments

Acknowledgments

We acknowledge the members of the Phillips labs for helpful discussions. We thank the CITP Advisory Committee, Max Guo and Ronald Kohanski (National Institute on Aging) for extensive discussion. This work was conducted using the resources of the Research Advanced Computing Services at the University of Oregon.

Funding

This work was supported by funding from National Institutes of Health grants (U01 AG045844, U01 AG045864, U01 AG045829, U24 AG056052, and R35 GM131838)

References

  1. 1000 Genomes Project Consortium. Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA, Abecasis GR. A global reference for human genetic variation. Nature. 2015 Oct 01;526(7571):68–74. doi: 10.1038/nature15393. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Andersen EC, Gerke JP, Shapiro JA, Crissman JR, Ghosh R, Bloom JS, Félix MA, Kruglyak L. Chromosome-scale selective sweeps shape Caenorhabditis elegans genomic diversity. Nat Genet. 2012 Jan 29;44(3):285–290. doi: 10.1038/ng.1050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Andrews S. 2010. FastQC: a quality control tool for high throughput sequence data. [Computer Software]
  4. Arbiza L, Gottipati S, Siepel A, Keinan A. Contrasting X-linked and autosomal diversity across 14 human populations. Am J Hum Genet. 2014 May 15;94(6):827–844. doi: 10.1016/j.ajhg.2014.04.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Banse SA, Lucanic M, Sedore CA, Coleman-Hulbert AL, Plummer WT, Chen E, Kish JL, Hall D, Onken B, Presley MP, Jones EG, Blue BW, Garrett T, Abbott M, Xue J, Guo S, Johnson E, Foulger AC, Chamoli M, Falkowski R, Melentijevic I, Harinath G, Huynh P, Patel S, Edgar D, Jarrett CM, Guo M, Kapahi P, Lithgow GJ, Driscoll M, Phillips PC. Automated lifespan determination across Caenorhabditis strains and species reveals assay-specific effects of chemical interventions. Geroscience. 2019 Dec 10;41(6):945–960. doi: 10.1007/s11357-019-00108-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Banse SA, Sedore CA, Johnson E, Coleman-Hulbert AL, Onken B, Hall D, Jackson EG, Huynh P, Foulger AC, Guo S, Garrett T, Xue J, Inman D, Morshead ML, Plummer WT, Chen E, Bhamik D, Chen MK, Harinath G, Chamoli M, Quinn RP, Falkowski R, Edgar D, Schmidt MO, Lucanic M, Guo M, Driscoll M, Lithgow GJ, Phillips PC. 2021. Antioxidants green tea extract and nordihydroguaiaretic acid confer species and strain specific lifespan and health effects in <i>Caenorhabditis</i> nematodes. bioRxiv preprint.
  7. Battey CJ, Coffing GC, Kern AD. Visualizing population structure with variational autoencoders. G3 (Bethesda) 2021 Jan 18;11(1) doi: 10.1093/g3journal/jkaa036. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Booker TR, Keightley PD. Understanding the Factors That Shape Patterns of Nucleotide Diversity in the House Mouse Genome. Mol Biol Evol. 2018 Dec 01;35(12):2971–2988. doi: 10.1093/molbev/msy188. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. C. elegans Sequencing Consortium. Genome sequence of the nematode C. elegans: a platform for investigating biology. Science. 1998 Dec 11;282(5396):2012–2018. doi: 10.1126/science.282.5396.2012. [DOI] [PubMed] [Google Scholar]
  10. Coleman-Hulbert AL, Johnson E, Sedore CA, Banse SA, Guo M, Driscoll M, Lithgow GJ, Phillips PC. Caenorhabditis Intervention Testing Program: the tyrosine kinase inhibitor imatinib mesylate does not extend lifespan in nematodes. MicroPubl Biol. 2019 Jul 01;2019 doi: 10.17912/micropub.biology.000131. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Coleman-Hulbert AL, Johnson E, Sedore CA, Banse SA, Guo M, Driscoll M, Lithgow GJ, Phillips PC. Caenorhabditis Intervention Testing Program: the creatine analog β-guanidinopropionic acid does not extend lifespan in nematodes. MicroPubl Biol. 2020 Jan 01;2020 doi: 10.17912/micropub.biology.000207. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Cook DE, Zdraljevic S, Roberts JP, Andersen EC. CeNDR, the Caenorhabditis elegans natural diversity resource. Nucleic Acids Res. 2016 Oct 01;45(D1):D650–D657. doi: 10.1093/nar/gkw893. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Crombie TA, Zdraljevic S, Cook DE, Tanny RE, Brady SC, Wang Y, Evans KS, Hahnel S, Lee D, Rodriguez BC, Zhang G, van der Zwagg J, Kiontke K, Andersen EC. Deep sampling of Hawaiian Caenorhabditis elegans reveals high genetic diversity and admixture with global populations. Elife. 2019 Dec 01;8 doi: 10.7554/eLife.50465. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST, McVean G, Durbin R, 1000 Genomes Project Analysis Group. The variant call format and VCFtools. Bioinformatics. 2011 Jun 01;27(15):2156–2158. doi: 10.1093/bioinformatics/btr330. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Evans KS, van Wijk MH, McGrath PT, Andersen EC, Sterken MG. From QTL to gene: C. elegans facilitates discoveries of the genetic mechanisms underlying natural variation. Trends Genet. 2021 Jul 01;37(10):933–947. doi: 10.1016/j.tig.2021.06.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Jun 16;32(19):3047–3048. doi: 10.1093/bioinformatics/btw354. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Frézal L, Félix MA. C. elegans outside the Petri dish. Elife. 2015 Mar 30;4 doi: 10.7554/eLife.05849. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Graustein A, Gaspar JM, Walters JR, Palopoli MF. Levels of DNA polymorphism vary with mating system in the nematode genus caenorhabditis. Genetics. 2002 May 01;161(1):99–9107. doi: 10.1093/genetics/161.1.99. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Halligan DL, Oliver F, Eyre-Walker A, Harr B, Keightley PD. Evidence for pervasive adaptive protein evolution in wild mice. PLoS Genet. 2010 Jan 22;6(1):e1000825–e1000825. doi: 10.1371/journal.pgen.1000825. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Jiang H, Lei R, Ding SW, Zhu S. Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads. BMC Bioinformatics. 2014 Jun 12;15:182–182. doi: 10.1186/1471-2105-15-182. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Jovelin R, Dunham JP, Sung FS, Phillips PC. High nucleotide divergence in developmental regulatory genes contrasts with the structural elements of olfactory pathways in caenorhabditis. Genetics. 2008 Nov 10;181(4):1387–1397. doi: 10.1534/genetics.107.082651. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kiontke KC, Félix MA, Ailion M, Rockman MV, Braendle C, Pénigault JB, Fitch DH. A phylogeny and molecular barcodes for Caenorhabditis, with numerous new species from rotting fruits. BMC Evol Biol. 2011 Nov 21;11:339–339. doi: 10.1186/1471-2148-11-339. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Li H. 2013. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv:1303.3997 [q-bio.GN].
  24. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, 1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009 Jun 01;25(16):2078–2079. doi: 10.1093/bioinformatics/btp352. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Lucanic M, Plummer WT, Chen E, Harke J, Foulger AC, Onken B, Coleman-Hulbert AL, Dumas KJ, Guo S, Johnson E, Bhaumik D, Xue J, Crist AB, Presley MP, Harinath G, Sedore CA, Chamoli M, Kamat S, Chen MK, Angeli S, Chang C, Willis JH, Edgar D, Royal MA, Chao EA, Patel S, Garrett T, Ibanez-Ventoso C, Hope J, Kish JL, Guo M, Lithgow GJ, Driscoll M, Phillips PC. Impact of genetic background and experimental reproducibility on identifying chemical compounds with robust longevity effects. Nat Commun. 2017 Feb 21;8:14256–14256. doi: 10.1038/ncomms14256. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010 Jul 19;20(9):1297–1303. doi: 10.1101/gr.107524.110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Morshead ML, Sedore CA, Jones EG, Hall D, Plummer WT, Garrett T, Lucanic M, Guo M, Driscoll M, Phillips PC, Lithgow G. Caenorhabditis Intervention Testing Program: the farnesoid X receptor agonist obeticholic acid does not robustly extend lifespan in nematodes. MicroPubl Biol. 2020 May 27;2020 doi: 10.17912/micropub.biology.000257. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Noble LM, Yuen J, Stevens L, Moya N, Persaud R, Moscatelli M, Jackson JL, Zhang G, Chitrakar R, Baugh LR, Braendle C, Andersen EC, Seidel HS, Rockman MV. Selfing is the safest sex for Caenorhabditis tropicalis. Elife. 2021 Jan 11;10 doi: 10.7554/eLife.62587. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Onken B, Sedore CA, Coleman-Hulbert AL, Hall D, Johnson E, Jones EG, Banse SA, Huynh P, Guo S, Xue J, Chen E, Harinath G, Foulger AC, Chao EA, Hope J, Bhaumik D, Plummer T, Inman D, Morshead M, Guo M, Lithgow GJ, Phillips PC, Driscoll M. Metformin treatment of diverse Caenorhabditis species reveals the importance of genetic background in longevity and healthspan extension outcomes. Aging Cell. 2021 Nov 27;21(1):e13488–e13488. doi: 10.1111/acel.13488. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Osman HC, Sedore CA, Jackson EG, Battistoni ET, Hall D, Foulger A, Lucanic M, Guo M, Driscoll M, Phillips P, Lithgow GJ. Caenorhabditis Intervention Testing Program: the herbicide diuron does not robustly extend lifespan in nematodes. MicroPubl Biol. 2021 Sep 23;2021 doi: 10.17912/micropub.biology.000448. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Perry GH, Louis EE Jr, Ratan A, Bedoya-Reina OC, Burhans RC, Lei R, Johnson SE, Schuster SC, Miller W. Aye-aye population genomic analyses highlight an important center of endemism in northern Madagascar. Proc Natl Acad Sci U S A. 2013 Mar 25;110(15):5823–5828. doi: 10.1073/pnas.1211990110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Prado-Martinez J, Sudmant PH, Kidd JM, Li H, Kelley JL, Lorente-Galdos B, Veeramah KR, Woerner AE, O'Connor TD, Santpere G, Cagan A, Theunert C, Casals F, Laayouni H, Munch K, Hobolth A, Halager AE, Malig M, Hernandez-Rodriguez J, Hernando-Herraez I, Prüfer K, Pybus M, Johnstone L, Lachmann M, Alkan C, Twigg D, Petit N, Baker C, Hormozdiari F, Fernandez-Callejo M, Dabad M, Wilson ML, Stevison L, Camprubí C, Carvalho T, Ruiz-Herrera A, Vives L, Mele M, Abello T, Kondova I, Bontrop RE, Pusey A, Lankester F, Kiyang JA, Bergl RA, Lonsdorf E, Myers S, Ventura M, Gagneux P, Comas D, Siegismund H, Blanc J, Agueda-Calpena L, Gut M, Fulton L, Tishkoff SA, Mullikin JC, Wilson RK, Gut IG, Gonder MK, Ryder OA, Hahn BH, Navarro A, Akey JM, Bertranpetit J, Reich D, Mailund T, Schierup MH, Hvilsom C, Andrés AM, Wall JD, Bustamante CD, Hammer MF, Eichler EE, Marques-Bonet T. Great ape genetic diversity and population history. Nature. 2013 Jul 01;499(7459):471–475. doi: 10.1038/nature12228. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010 Jan 28;26(6):841–842. doi: 10.1093/bioinformatics/btq033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. R Core Team. 2018. R: A language and environment for statistical computing.
  35. Stastna JJ, Snoek LB, Kammenga JE, Harvey SC. Genotype-dependent lifespan effects in peptone deprived Caenorhabditis elegans. Sci Rep. 2015 Nov 01;5:16259–16259. doi: 10.1038/srep16259. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Stegeman GW, de Mesquita MB, Ryu WS, Cutter AD. Temperature-dependent behaviours are genetically variable in the nematode Caenorhabditis briggsae. J Exp Biol. 2012 Nov 15;216(Pt 5):850–858. doi: 10.1242/jeb.075408. [DOI] [PubMed] [Google Scholar]
  37. Wang YA, Snoek BL, Sterken MG, Riksen JAG, Stastna JJ, Kammenga JE, Harvey SC. Genetic background modifies phenotypic and transcriptional responses in a C. elegans model of α-synuclein toxicity. BMC Genomics. 2019 Mar 20;20(1):232–232. doi: 10.1186/s12864-019-5597-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Wickham H. 2016. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4. DOI: 10.1007/978-3-319-24277-4
  39. Yoshimura J, Ichikawa K, Shoura MJ, Artiles KL, Gabdank I, Wahba L, Smith CL, Edgley ML, Rougvie AE, Fire AZ, Morishita S, Schwarz EM. Recompleting the Caenorhabditis elegans genome. Genome Res. 2019 May 23;29(6):1009–1022. doi: 10.1101/gr.244830.118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Yu N, Jensen-Seaman MI, Chemnick L, Ryder O, Li WH. Nucleotide diversity in gorillas. Genetics. 2004 Mar 01;166(3):1375–1383. doi: 10.1534/genetics.166.3.1375. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from microPublication Biology are provided here courtesy of California Institute of Technology

RESOURCES