Assessing sequence heterogeneity in Chlorellaceae DNA barcode markers for phylogenetic inference

Nurhaida Kamaruddin

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Type :	article
Subject :	Q Science (General)
ISSN :	1687-157X
Main Author :	Nurhaida Kamaruddin
Additional Authors :	Marina Mokhtar Norjan Yusof Raja Farhana Raja Khairuddin
Title :	Assessing sequence heterogeneity in Chlorellaceae DNA barcode markers for phylogenetic inference

Place of Production :	Tanjung Malim
Publisher :	Fakulti Sains dan Matematik
Year of Publication :	2023
Notes :	Journal of Genetic Engineering and Biotechnology
Corporate Name :	Universiti Pendidikan Sultan Idris
HTTP Link :	Click to view web link

Abstract : Universiti Pendidikan Sultan Idris

Phylogenetic inference is an important approach that allows the recovery of the evolutionary history and the origin of the Chlorellaceae species. Despite the species potential for biofuel feedstock production, their high phenotypic plasticity and similar morphological structures among the species have muddled the taxonomy and identification of the Chlorellaceae species. This study aimed to decipher Chlorellaceae DNA barcode marker heterogeneity by examining the sequence divergence and genomic properties of 18S rRNA, ITS (ITS1-5.8S rRNA-ITS2-28S rRNA), and rbcL from 655 orthologous sequences of 64 species across 31 genera in the Chlorellaceae family. The study assessed the distinct evolutionary properties of the DNA markers that may have caused the discordance between individual trees in the phylogenetic inference using the Robinson-Foulds distance and the Shimodaira-Hasegawa test. Our findings suggest that using the supermatrix approach improves the congruency between trees by reducing stochastic error and increasing the confidence of the inferred Chlorellaceae phylogenetic tree. This study also found that the phylogenies inferred through the supermatrix approach might not always be well supported by all markers. The study highlights that assessing sequence heterogeneity prior to the phylogenetic inference could allow the approach to accommodate sequence evolutionary properties and support species identification from the most congruent phylogeny, which can better represent the evolution of Chlorellaceae species. 2023, Academy of Scientific Research and Technology.

References

Francis WR, Canfeld DE (2020) Very few sites can reshape the inferred phylogenetic tree. PeerJ 8:e8865. https://doi.org/10.7717/peerj.8865

Shen XX, Hittinger CT, Rokas A (2017) Contentious relationships in phylogenomic studies can be driven by a handful of genes. Nat Ecol Evol 1:0126. https://doi.org/10.1038/s41559-017-0126

Horreo JL (2012) “Representative Genes”, is it OK to use a small amount of data to obtain a phylogeny that is at least close to the true tree? J Evol Biol 25(12):2661–2664. https://doi.org/10.1111/j.1420-9101.2012.02622.x

Jefroy O, Brinkmann H, Delsuc F, Philippe H (2006) Phylogenomics: the beginning of incongruence? Trends Genet 22(4):225–231. https://doi.org/10.1016/j.tig.2006.02.003

Salichos L, Rokas A (2013) Inferring ancient divergences requires genes with strong phylogenetic signals. Nature 497:327–331. https://doi.org/10.1038/nature12130

Dequeiroz A, Gatesy J (2007) The supermatrix approach to systematics. In Trends Ecol Evol 22(1):34–41. https://doi.org/10.1016/j.tree.2006.10.0027. One Thousand Plant Transcriptomes Initiative (2019) One thousand plant transcriptomes and the phylogenomics of green plants. Nature 574:679–685. https://doi.org/10.1038/s41586-019-1693-2

McCraney WT, Thacker CE, Alfaro ME (2020) Supermatrix phylogeny resolves goby lineages and reveals unstable root of Gobiaria. Mol Phylogenet Evol 151:106862

Philippe H, de Vienne DM, Ranwez V, Roure B, Baurain D, Delsuc F (2017) Pitfalls in supermatrix phylogenomics. Eur J Taxon 283:1–25

Gatesy J, Matthee C, DeSalle R, Hayashi C (2002) Resolution of a supertree/supermatrix paradox. Syst Biol 51(4):652–664 11. Golobof PA, Szumik CA (2016) Problems with supertrees based on the subtree prune-and-regraft distance, with comments on majority rule supertrees. Cladistics 32(1):82–89. https://doi.org/10.1111/cla.12111

Pace NR (2009) Mapping the tree of life: progress and prospects. Microbiol Mol Biol Rev 73(4):565–576. https://doi.org/10.1128/mmbr.00033-09

Som A (2014) Causes, consequences and solutions of phylogenetic incongruence. Brief Bioinform 16(3):536–548. https://doi.org/10.1093/bib/bbu015

Guccione A, Biondi N, Sampietro G, Rodolf L, Bassi N, Tredici MR (2014) Chlorella for protein and biofuels: from strain selection to outdoor cultivation in a Green Wall Panel photobioreactor. Biotechnol Biofuels 7(1):1–12. https://doi.org/10.1186/1754-6834-7-84

Milano J, Chyuan H, Masjuki HH, Chong WT, Kee M (2016) Microalgae biofuels as an alternative to fossil fuel for power generation. Renew Sustain Energy Rev 58:180–197. https://doi.org/10.1016/j.rser.2015.12.150

Nordin N, Yusof N, Maeda T, Mustapha NA, Mohd-Yusof MZ, Raja-Khairuddin RF (2020) Mechanism of carbon partitioning towards starch and

triacylglycerol in Chlorella vulgaris under nitrogen stress through wholetranscriptome analysis. Biomass Bioenerg 138:105600. https://doi.org/10.1016/j.biombioe.2020.105600

Singh P, Kumari S, Guldhe A, Misra R, Rawat I, Bux F (2016) Trends and novel strategies for enhancing lipid accumulation and quality in microalgae. Renew Sustain Energy Rev 55:1–16. https://doi.org/10.1016/j.rser.2015.11.001

Darienko T, Rad-Menéndez C, Campbell C, Pröschold T (2019) Are there any true marine Chlorella species? Molecular phylogenetic assessment and ecology of marine Chlorella-like organisms, including a description of Droopiella gen. nov. Syst Biodivers 17(8):811–829. https://doi.org/10.1080/14772000.2019.1690597

Krienitz L, Hegewald EH, Hepperle D, Huss VAR, Rohr T, Wolf M (2004) Phylogenetic relationship of Chlorella and Parachlorella gen. nov. (Chlorophyta, Trebouxiophyceae). Phycologia 43(5):529–542. https://doi.org/10.2216/i0031-8884-43-5-529.1

Čertnerová D (2021) Nuclei isolation protocols for fow cytometry allowing nuclear DNA content estimation in problematic microalgal groups. J Appl Phycol 33:2057–2067. https://doi.org/10.1007/s10811-021-02433-z

Tear CJY, Lim C, Wu J, Zhao H (2013) Accumulated lipids rather than the rigid cell walls impede the extraction of genetic materials for efective colony PCRs in Chlorella vulgaris. Microb Cell Fact 12:106. https://doi.org/10.1186/1475-2859-12-106

Das B, Deka S (2019) A cost-efective and environmentally sustainable process for phycoremediation of oil feld formation water for its safe disposal and reuse. Sci Rep 9(1):1–15. https://doi.org/10.1038/s41598-019-51806-5

Kunrunmi O, Adesalu T, Kumar S (2017) Genetic identifcation of new microalgal species from Epe Lagoon of West Africa accumulating high lipids. Algal Res 22:68–78. https://doi.org/10.1016/j.algal.2016.12.009

Lemieux C, Otis C, Turmel M (2014) Chloroplast phylogenomic analysis resolves deep-level relationships within the green algal class Trebouxiophyceae. BMC Evol Biol 14(1):1–15. https://doi.org/10.1186/s12862-014-0211-2

Khaw YS, Khong NMH, Shaharuddin NA, Yusof FM (2020) A simple 18S rDNA approach for the identifcation of cultured eukaryotic microalgae with an emphasis on primers. J Microbiol Methods 172:105890. https://doi.org/10.1016/j.mimet.2020.105890

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