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. 2014 Jan;10(1):e1004094.
doi: 10.1371/journal.pgen.1004094. Epub 2014 Jan 9.

Nannochloropsis genomes reveal evolution of microalgal oleaginous traits

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Nannochloropsis genomes reveal evolution of microalgal oleaginous traits

Dongmei Wang et al. PLoS Genet. 2014 Jan.

Abstract

Oleaginous microalgae are promising feedstock for biofuels, yet the genetic diversity, origin and evolution of oleaginous traits remain largely unknown. Here we present a detailed phylogenomic analysis of five oleaginous Nannochloropsis species (a total of six strains) and one time-series transcriptome dataset for triacylglycerol (TAG) synthesis on one representative strain. Despite small genome sizes, high coding potential and relative paucity of mobile elements, the genomes feature small cores of ca. 2,700 protein-coding genes and a large pan-genome of >38,000 genes. The six genomes share key oleaginous traits, such as the enrichment of selected lipid biosynthesis genes and certain glycoside hydrolase genes that potentially shift carbon flux from chrysolaminaran to TAG synthesis. The eleven type II diacylglycerol acyltransferase genes (DGAT-2) in every strain, each expressed during TAG synthesis, likely originated from three ancient genomes, including the secondary endosymbiosis host and the engulfed green and red algae. Horizontal gene transfers were inferred in most lipid synthesis nodes with expanded gene doses and many glycoside hydrolase genes. Thus multiple genome pooling and horizontal genetic exchange, together with selective inheritance of lipid synthesis genes and species-specific gene loss, have led to the enormous genetic apparatus for oleaginousness and the wide genomic divergence among present-day Nannochloropsis. These findings have important implications in the screening and genetic engineering of microalgae for biofuels.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Structural features of the six Nannochloropsis genomes.
(A) Whole-genome based phylogeny of Nannochloropsis. A maximum likelihood (consensus) tree was generated using the PhyML program (JTT model) with 1,000 replicates based on the 1,085 six-way single-copy orthologous gene sets identified from the six Nannochloropsis genomes (Text S1). Percentages of replicate trees in the bootstrap test are shown next to the branches. (B) Genome divergence in Nannochloropsis. For each pair of genomes that consists of IMET1 and another Nannochloropsis strain, the percentages of strain-specific proteins versus their discrepancies in the full-length 18S rDNA sequence were plotted. Ten S. cerevisiae strains, eight E. coli strains, nine Synechococcus strains and two each of Ostreococcus and Micromonas were also included. For prokaryotic organisms including E. coli and Synechococcus, the percentages of strain-specific proteins were plotted against the discrepancies in 16S rDNA sequences. (C) The number of genes from the Nannochloropsis genomes and the Nannochloropsis core, with successive inclusion of each additional strain. (D) Functional categorization of Nannochloropsis core proteins. GO Slim terms corresponding to each GO term are presented.
Figure 2
Figure 2. Structure of paralogous groups in each Nannochloropsis strain.
Each circle represents a paralogous group. The area of the circle is proportional to the size of the paralogous group. The top 15 largest paralogous groups in each of the six Nannochloropsis genomes and the other three model microalgae (including T. pseudonana, C. merolae and C. reinhardtii) are shown. The largest paralogous groups in the six Nannochloropsis genomes and the other three model microalgae, including T. pseudonana, C. merolae and C. reinhardtii. The color of the circle represents the functions (as defined by the associated GO Slim terms in biological process) encoded by the paralogous group. The paralogous groups in each Nannochloropsis strain are relatively small in size.
Figure 3
Figure 3. Functional conservation and variation of the Nannochloropsis genomes.
For each genome, the numbers of genes assigned to each GO term and its subcategory terms are shown. The color scheme, defined by the scale bar on the top, represents the degree of relative enrichment or depletion for each functional category as compared to C. reinhardtii. The p values of enrichment or depletion were calculated using a binomial test corrected by FDR for multiple comparisons. IMET1, N. oceanica IMET1; 531, N. oceanica CCMP531; 529, N. granulata CCMP529; 525, N. oculata CCMP525; 526, N. gaditana CCMP526; 537, N. salina CCMP537; cre, C. reinhardtii.
Figure 4
Figure 4. Enrichment of lipid biosynthesis genes in each of the six Nannochloropsis strains.
(A) The gene dose expansion in N. oceanica IMET1 as compared to C. reinhardtii. In the schema, enzymes in each reaction node in the Nannochloropsis and C. reinhardtii lipid biosynthesis pathways are represented as yellow and blue circles, respectively. Length of radius stands for gene dose. Putative HGT genes in each node in IMET1 are shown in purple. Chlamydomonas genes were not investigated for HGT events here. (B) The expansion in gene dose was conserved among the Nannochloropsis genomes. Each colored cell in the heatmap represents the gene copy numbers in each of the Nannochloropsis strains and in C. reinhardtii. The scale of the color bar ranges from 1 (the lowest copy number among the genomes) to 13 (the highest copy number).
Figure 5
Figure 5. Divergent phylogenetic origins of Nannochloropsis DGAT-2 genes.
(A) Gene doses of DGAT-1 and DGAT-2 in Nannochloropsis and several model organisms. The numbers of DGAT-1 and DGAT-2 genes in each genome are indicated by different colors. N. oceanica IMET1 is marked by red star. (B) Schema illustrating the divergent phylogenetic origins of Nannochloropsis DGAT-2 from the red/green algae-related endosymbionts and potential secondary host. The protein names listed in each individual schematic cell indicate the DGAT-2 genes that were likely to be encoded in the genome. Abbreviations: N, nucleus; C, chloroplast; M, mitochondria.

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Grants and funding

This work was supported by Ministry of Science and Technology of China (2012CB721101; 2012AA02A707; 2011CB200902), National Natural Science Foundation of China (31010103907, 91231205, 61103167) and International Innovation Partnership Program from Chinese Academy of Sciences. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.