Evidence-based green algal genomics reveals marine diversity and ancestral characteristics of land plants

Background: Prasinophytes are widespread marine green algae that are related to plants. Cellular abundance of the prasinophyte Micromonas has reportedly increased in the Arctic due to climate-induced changes. Thus, studies of these unicellular eukaryotes are important for marine ecology and for understanding Viridiplantae evolution and diversification. Results: We generated evidence-based Micromonas gene models using proteomics and RNA-Seq to improve prasinophyte genomic resources. First, sequences of four chromosomes in the 22 Mb Micromonas pusilla (CCMP1545) genome were finished. Comparison with the finished 21 Mb genome of Micromonas commoda (RCC299; named herein) shows they share ≤8,141 of ~10,000 protein-encoding genes, depending on the analysis method. Unlike RCC299 and other sequenced eukaryotes, CCMP1545 has two abundant repetitive intron types and a high percent (26 %) GC splice donors. Micromonas has more genus-specific protein families (19 %) than other genome sequenced prasinophytes (11 %). Comparative analyses using predicted proteomes from other prasinophytes reveal proteins likely related to scale formation and ancestral photosynthesis. Our studies also indicate that peptidoglycan (PG) biosynthesis enzymes have been lost in multiple independent events in select prasinophytes and plants. However, CCMP1545, polar Micromonas CCMP2099 and prasinophytes from other classes retain the entire PG pathway, like moss and glaucophyte algae. Surprisingly, multiple vascular plants also have the PG pathway, except the Penicillin-Binding Protein, and share a unique bi-domain protein potentially associated with the pathway. Alongside Micromonas experiments using antibiotics that halt bacterial PG biosynthesis, the findings highlight unrecognized phylogenetic complexity in PG-pathway retention and implicate a role in chloroplast structure or division in several extant Viridiplantae lineages. Conclusions: Extensive differences in gene loss and architecture between related prasinophytes underscore their divergence. PG biosynthesis genes from the cyanobacterial endosymbiont that became the plastid, have been selectively retained in multiple plants and algae, implying a biological function. Our studies provide robust genomic resources for emerging model algae, advancing knowledge of marine phytoplankton and plant evolution

Identifying Aspects of the Post-Transcriptional Program Governing the Proteome of the Green Alga Micromonas pusilla.

Micromonas is a unicellular motile alga within the Prasinophyceae, a green algal group that is related to land plants. This picoeukaryote (<2 μm diameter) is widespread in the marine environment but is not well understood at the cellular level. Here, we examine shifts in mRNA and protein expression over the course of the day-night cycle using triplicated mid-exponential, nutrient replete cultures of Micromonas pusilla CCMP1545. Samples were collected at key transition points during the diel cycle for evaluation using high-throughput LC-MS proteomics. In conjunction, matched mRNA samples from the same time points were sequenced using pair-ended directional Illumina RNA-Seq to investigate the dynamics and relationship between the mRNA and protein expression programs of M. pusilla. Similar to a prior study of the marine cyanobacterium Prochlorococcus, we found significant divergence in the mRNA and proteomics expression dynamics in response to the light:dark cycle. Additionally, expressional responses of genes and the proteins they encoded could also be variable within the same metabolic pathway, such as we observed in the oxygenic photosynthesis pathway. A regression framework was used to predict protein levels from both mRNA expression and gene-specific sequence-based features. Several features in the genome sequence were found to influence protein abundance including codon usage as well as 3' UTR length and structure. Collectively, our studies provide insights into the regulation of the proteome over a diel cycle as well as the relationships between transcriptional and translational programs in the widespread marine green alga Micromonas

Identifying Aspects of the Post-Transcriptional Program Governing the Proteome of the Green Alga <i>Micromonas pusilla</i>

<div><p><i>Micromonas</i> is a unicellular motile alga within the Prasinophyceae, a green algal group that is related to land plants. This picoeukaryote (<2 μm diameter) is widespread in the marine environment but is not well understood at the cellular level. Here, we examine shifts in mRNA and protein expression over the course of the day-night cycle using triplicated mid-exponential, nutrient replete cultures of <i>Micromonas pusilla</i> CCMP1545. Samples were collected at key transition points during the diel cycle for evaluation using high-throughput LC-MS proteomics. In conjunction, matched mRNA samples from the same time points were sequenced using pair-ended directional Illumina RNA-Seq to investigate the dynamics and relationship between the mRNA and protein expression programs of <i>M</i>. <i>pusilla</i>. Similar to a prior study of the marine cyanobacterium <i>Prochlorococcus</i>, we found significant divergence in the mRNA and proteomics expression dynamics in response to the light:dark cycle. Additionally, expressional responses of genes and the proteins they encoded could also be variable within the same metabolic pathway, such as we observed in the oxygenic photosynthesis pathway. A regression framework was used to predict protein levels from both mRNA expression and gene-specific sequence-based features. Several features in the genome sequence were found to influence protein abundance including codon usage as well as 3’ UTR length and structure. Collectively, our studies provide insights into the regulation of the proteome over a diel cycle as well as the relationships between transcriptional and translational programs in the widespread marine green alga <i>Micromonas</i>.</p></div

Comparison of protein and mRNA expression patterns across the time course.

<p><b>(A)</b> Comparison of the degree of the correlation (Pearson, R_P) between the mRNA and protein expression profiles, per gene (Z-transformed). Less than 10% of the genes considered were correlated over the course of the experiment (using a threshold of 0.75); while 26% were delayed by 1 time point (1 TPT) and 9% by 2 time points (2 TPTs). <b>(B)</b> Concordance of Gene Set Enrichment Analysis (GSEA) of pairwise correlation (as measured by <i>CS</i>_<i>p</i>; see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#sec002" target="_blank">Methods</a>) indicates there is considerable concordance between the expression programs of several key metabolic pathways, such as the Oxygenic Photosynthesis and TCA pathways. Note this is limited to those pathways that are concordant. Concordant pathways from a similar analysis of log-ratios include many of the same critical pathways (Fig M in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#pone.0155839.s001" target="_blank">S1 File</a>). Complete representations of all pathways from the analysis of abundances and log-ratios are also provided (Figs N and O in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#pone.0155839.s001" target="_blank">S1 File</a>). <b>(C)</b> A global comparison of the expression dynamics observed in the mRNA and protein expression programs.</p

Coverage of the Oxygenic Photosynthesis (OP) Pathway by the joint expression clusters.

<p><b>(A)</b> Cartoon of the OP pathway, with selected interactions color-coded to indicate cluster membership. Light-dependent reactions are indicated by yellow background. Of the 17 interactions in the pathway, 15 were mediated by genes in the high confidence data set (Tables E-G in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#pone.0155839.s001" target="_blank">S1 File</a>). Note that within the light-independent reactions of the Calvin-Bensen-Bassham Cycle we identified two fructose-bisphosphate aldolase (FBA) proteins, wlab.223910 (Class I, Cluster 6) and wlab.149815 (Class II, Cluster 3), both with predicted chloroplast transit peptides. The Class II FBA of the cyanobacterium <i>Synechococcus</i> shows higher reactivity for sedoheptulose-1,7-bisphosphate than for fructose-1,6-bisphosphate than its Class I FBA [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#pone.0155839.ref094" target="_blank">94</a>] and thus, although they have not been experimentally characterized, the <i>M</i>. <i>pusilla</i> FBAs depicted here may also partition within the pathway. <b>(B)</b> Joint mRNA and protein expression profiles of the clusters enriched with OP pathway genes (Clusters 6, 7, & 15). Cluster 6 displays considerable correlation (R² = 0.643) between the mRNA and protein expression patterns, while Cluster 7 and 15 display either marginal (R = 0.161) or inverse (-0.446) correlation. Profiles for Clusters 2 and 3 are show in Figure P in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155839#pone.0155839.s001" target="_blank">S1 File</a>.</p

Sample collection time points, RNA-Seq reads and proteomic spectra measured.

<p>Note that 14 hours after the initial lights on (8:00 a.m.) the lights turned off (i.e. turned off at 10 p.m.) for a 10 hour dark period that ended exactly at 24 hours past the initial lights on (i.e., T4).</p

Temporal dynamics observed in mRNA and protein expression using the high-confidence set.

<p><b>(A)</b> Comparison of absolute abundance values for the mRNA and protein expression data (all time points combined) indicates a moderate correlation between the data types (Spearman’s correlation coefficient, R_S = 0.428, <i>p</i><0.0001). <b>(B)</b> Comparison of the log-ratios relative to T3 indicates a slightly negative correlation (R_S = -0.168, <i>p</i><0.0001). These contrasting results suggest that while a relationship exists between mRNA and protein expression, there are considerable temporal differences between the respective expression programs.</p