Food and Fermentation Industries >

2022 , Vol. 48 >Issue 4: 82 - 89

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.028904

Transcriptomic analysis of Dunaliella parva during different growth periods

  • SONG Wei ,
  • TANG Liqun ,
  • GAO Fan
Expand
  • 1(Shanxi Sports Vocational School, Taiyuan 030006, China)
    2(School of Life Science, Shanxi University, Taiyuan 030006, China)

Received date: 2021-08-11

  Revised date: 2021-10-06

  Online published: 2022-03-16

Fold

Abstract

As a class of unique salt-tolerance green alga, Dunaliella parva has industrial production potential due to its rich bioactive substances. With the wide application of transcriptomic sequencing, more and more algae functional genes have been discovered. However, the transcriptomic sequencing of D. parva during different growth phases has not been reported yet, which greatly limits the further research on its growth and development mechanism. In this study, transcriptomic sequencing of the algal samples at the early, mid and late growth stages based on morphological, omics and bioinformatics methods was performed. A total of 90 153 unigenes with 49 643 coding domain sequences from 9 cDNA libraries were obtained in this alga. 66.36% of them could be annotated by the seven major bio-databases. 272 contigs were de novo assembled with a 1 305 bp N50 and a GC percentage of 52.32%. The unigenes could be divided into 4 clusters based on their fragments per kilobase of transcript per million fragments values. Compared with the early-stage group, the number of down-regulated genes (52 891) was larger than that of the up-regulated ones (20 759). Integral component of membrane was the most significant ontology in both the mid and late stage sample via gene ontology enrichment analyzing compared with the early-stage sample. Additionally, splicesome and RNA transport were the most significant pathways in the mid and late stage sample, respectively, via KEGG pathway enrichment analysis. The quality of the transcriptomic sequencing data and de novo assembly was high. The screened differentially expressed genes and their predicted functional information will lay a foundation for the further research on growth and development mechanism analysis, algal strain molecular improvement and industrial application of this alga.

Key words： Dunaliella parva; transcriptomic analysis; differentially expressed genes; growth period

Cite this article

SONG Wei , TANG Liqun , GAO Fan . Transcriptomic analysis of Dunaliella parva during different growth periods[J]. Food and Fermentation Industries, 2022 , 48(4) : 82 -89 . DOI: 10.13995/j.cnki.11-1802/ts.028904

References

[1] 王培磊, 袁子懿.盐度对盐生杜氏藻生长及其色素积累的影响[J].水产科学, 2009, 28(2):71-74.
WANG P L, YUAN Z Y.Effects of salinity on the growth and pigment accumulation of alga Dunaliella salina[J].Fisheries Science, 2009, 28(2):71-74.
[2] 韦芳三, 李纯厚, 戴明, 等.盐度变化对盐藻生物量和总脂含量的影响[J].湖南农业科学, 2011(1):134-136;139.
WEI F S, LI C H, DAI M, et al.Effects of salinity change on the biomass and lipid content of Dunaliella salina[J].Hunan Agricultural Sciences, 2011(1):134-136;139.
[3] 尚常花, 秦磊, 朱顺妮, 等.培养基成分含量对巴夫杜氏藻生长的影响[J].新能源进展, 2013(2):170-173.
SHANG C H, QIN L, ZHU S N, et al.The effect of changed concentration of medium component on growth in Dunaliella parva [J].Advances in New and Renewable Energy, 2013(2):170-173.
[4] 尚常花, 朱顺妮, 袁振宏, 等.巴夫杜氏藻GAPDH基因部分序列的克隆[J].广东农业科学, 2011, 38(13):126-127;134.
SHANG C H, ZHU S N, YUAN Z H, et al.Cloning of partial sequence of a gene encoding GAPDH from Dunaliella parva[J].Guangdong Agricultural Sciences, 2011, 38(13):126-127;134.
[5] BENMOUSSA-DAHMEN I, CHTOUROU H, REZGUI F, et al.Salinity stress increases lipid, secondary metabolites and enzyme activity in Amphora subtropica and Dunaliella sp.for biodiesel production[J].Bioresource Technology, 2016, 218:816-825.
[6] GIERAHN T M, WADSWORTH M H II, HUGHES T K, et al.Seq-Well:Portable, low-cost RNA sequencing of single cells at high throughput[J].Nature Methods, 2017, 14(4):395-398.
[7] HONG L, LIU J L, MIDOUN S Z, et al.Transcriptome sequencing and annotation of the halophytic microalga Dunaliella salina[J].Journal of Zhejiang University Science B, 2017, 18(10):833-844.
[8] YAO L, TAN K W M, TAN T W, et al.Exploring the transcriptome of non-model oleaginous microalga Dunaliella tertiolecta through high-throughput sequencing and high performance computing[J].BMC Bioinformatics, 2017, 18(1):122.
[9] PUENTE-SÁNCHEZ F, OLSSON S, AGUILERA A.Comparative transcriptomic analysis of the response of Dunaliella acidophila (chlorophyta) to short-term cadmium and chronic natural metal-rich water exposures[J].Microbial Ecology, 2016, 72(3):595-607.
[10] HE Q H, LIN Y Q, TAN H, et al.Transcriptomic profiles of Dunaliella salina in response to hypersaline stress[J].BMC Genomics, 2020, 21(1):115.
[11] SHANG C H, BI G C, YUAN Z H, et al.Discovery of genes for production of biofuels through transcriptome sequencing of Dunaliella parva[J].Algal Research, 2016, 13:318-326.
[12] MAK S S T, GOPALAKRISHNAN S, CARØE C, et al.Comparative performance of the BGISEQ-500 vs. Illumina HiSeq2500 sequencing platforms for palaeogenomic sequencing[J].GigaScience, 2017, 6(8):1-13.
[13] 王婷, 冯佳, 谢树莲.培养条件对杜氏藻β-胡萝卜素含量的影响[J].食品工业科技, 2014, 35(24):177-181.
WANG T, FENG J, XIE S L.Effects on culture conditions for β-carotene contents of Dunaliella sp.[J].Science and Technology of Food Industry, 2014, 35(24):177-181.
[14] CHEN Y X, CHEN Y S, SHI C M, et al.SOAPnuke:A MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data[J].GigaScience, 2018, 7(1):1-6.
[15] LANGDON W B.Performance of genetic programming optimised Bowtie2 on genome comparison and analytic testing (GCAT) benchmarks[J].BioData Mining, 2015, 8(1):1.
[16] PERTEA G, HUANG X Q, LIANG F, et al.TIGR Gene Indices clustering tools (TGICL):A softwaresystem for fast clustering of large EST datasets[J].Bioinformatics, 2003, 19(5):651-652.
[17] SEPPEY M, MANNI M, ZDOBNOV E M.BUSCO:Assessing genome assembly and annotation completeness[J].Methods in Molecular Biology, 2019, 1 962:227-245.
[18] JIN J P, TIAN F, YANG D C, et al.PlantTFDB 4.0:Toward a central hub for transcription factors and regulatory interactions in plants[J].Nucleic Acids Research, 2017, 45:1 040-1 045.
[19] TIAN Y Y, BAI S, DANG Z H, et al.Genome-wide identification and characterization of long non-coding RNAs involved in fruit ripening and the climacteric in Cucumis melo[J].BMC Plant Biology, 2019, 19(1):369.
[20] DJEBALI S, WUCHER V, FOISSAC S, et al.Bioinformatics pipeline for transcriptome sequencing analysis[J].Methods in Molecular Biology, 2017, 1 468:201-219.
[21] GÖTZ S, GARCÍA-GÓMEZ J M, TEROL J, et al.High-throughput functional annotation and data mining with the Blast2GO suite[J].Nucleic Acids Research, 2008, 36(10):3 420-3 435.
[22] PANAHI B, FRAHADIAN M, DUMS J T, et al.Integration of cross species RNA-seq meta-analysis and machine-learning models identifies the most important salt stress-responsive pathways in microalga Dunaliella[J].Frontiers in Genetics, 2019, 10:752.
[23] POLLE J E W, BARRY K, CUSHMAN J, et al.Draft nuclear genome sequence of the halophilic and beta-carotene-accumulating green alga Dunaliella salina strain CCAP19/18[J].Genome Announcements, 2017, 5(43):e01105-17.
[24] 尚常花, 王忠铭, 袁振宏, 等.氮限制对产油杜氏藻转录组的影响[J].中国油料作物学报, 2016, 38(4):524-528.
SHANG C H, WANG Z M, YUAN Z H, et al.Effect of nitrogen limitation on transcriptome of oleaginous Dunaliella parva[J].Chinese Journal of Oil Crop Sciences, 2016, 38(4):524-528.
[25] WANG D M, NING K, LI J, et al.Nannochloropsis genomes reveal evolution of microalgal oleaginous traits[J].PLoS Genetics, 2014, 10(1):e1004094.
[26] 张学成, 孟振, 时艳侠, 等.光照、温度和营养盐对三株盐生杜氏藻生长和色素积累的影响[J].中国海洋大学学报, 2006, 36(5):754-762.
ZHANG X C, MENG Z, SHI Y X, et al.The effect of light, temperature and nutrition on growth and pigment accumulation of three strains of Dunaliella salina[J].Periodical of Ocean University of China, 2006, 36(5):754-762.
[27] 柴玉荣, 王天云, 薛乐勋.新型生物反应器—杜氏盐藻研究进展[J].中国生物工程杂志, 2004, 24(2):30-33.
CHAI Y R, WANG T Y, XUE L X.Recent progress in a new bioreactor:Dunaliella salina[J].China Biotechnology, 2004, 24(2):30-33.
Options
Outlines

/

〈 〉

Powered by Beijing Magtech Co. Ltd,.