We used RNA sequencing to query the Chlamydomonas reinhardtii transcriptome for regulation by CO 2 and by the transcription regulator CIA5 (CCM1). Both CO 2 and CIA5 are known to play roles in acclimation to low CO 2 and in induction of an essential CO 2 -concentrating mechanism (CCM), but less is known about their interaction and impact on the whole transcriptome. Our comparison of the transcriptome of a wild type versus a cia5 mutant strain under three different CO 2 conditions, high CO 2 (5%), low CO 2 (0.03 to 0.05%), and very low CO 2 (<0.02%), provided an entry into global changes in the gene expression patterns occurring in response to the interaction between CO 2 and CIA5. We observed a massive impact of CIA5 and CO 2 on the transcriptome, affecting almost 25% of all Chlamydomonas genes, and we discovered an array of gene clusters with distinctive expression patterns that provide insight into the regulatory interaction between CIA5 and CO 2 . Several individual clusters respond primarily to either CIA5 or CO 2 , providing access to genes regulated by one factor but decoupled from the other. Three distinct clusters clearly associated with CCM-related genes may represent a rich source of candidates for new CCM components, including a small cluster of genes encoding putative inorganic carbon transporters.

Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as evidenced by the Encyclopedia of DNA Elements (ENCODE) Project. To this end, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the standard methodology. Mapping such protein-DNA interactions in vivo using ChIP-seq presents multiple challenges not only in sample preparation and sequencing but also for computational analysis. Here, we present step-by-step guidelines for the computational analysis of ChIP-seq data. We address all the major steps in the analysis of ChIP-seq data: sequencing depth selection, quality checking, mapping, data normalization, assessment of reproducibility, peak calling, differential binding analysis, controlling the false discovery rate, peak annotation, visualization, and motif analysis. At each step in our guidelines we discuss some of the software tools most frequently used. We also highlight the challenges and problems associated with each step in ChIP-seq data analysis. We present a concise workflow for the analysis of ChIP-seq data in Figure 1 that complements and expands on the recommendations of the ENCODE and modENCODE projects. Each step in the workflow is described in detail in the following sections.

BackgroundLittle is known about the mechanisms of adaptation of life to the extreme environmental conditions encountered in polar regions. Here we present the genome sequence of a unicellular green alga from the division chlorophyta, Coccomyxa subellipsoidea C-169, which we will hereafter refer to as C-169. This is the first eukaryotic microorganism from a polar environment to have its genome sequenced.ResultsThe 48.8 Mb genome contained in 20 chromosomes exhibits significant synteny conservation with the chromosomes of its relatives Chlorella variabilis and Chlamydomonas reinhardtii. The order of the genes is highly reshuffled within synteny blocks, suggesting that intra-chromosomal rearrangements were more prevalent than inter-chromosomal rearrangements. Remarkably, Zepp retrotransposons occur in clusters of nested elements with strictly one cluster per chromosome probably residing at the centromere. Several protein families overrepresented in C. subellipsoidae include proteins involved in lipid metabolism, transporters, cellulose synthases and short alcohol dehydrogenases. Conversely, C-169 lacks proteins that exist in all other sequenced chlorophytes, including components of the glycosyl phosphatidyl inositol anchoring system, pyruvate phosphate dikinase and the photosystem 1 reaction center subunit N (PsaN).ConclusionsWe suggest that some of these gene losses and gains could have contributed to adaptation to low temperatures. Comparison of these genomic features with the adaptive strategies of psychrophilic microbes suggests that prokaryotes and eukaryotes followed comparable evolutionary routes to adapt to cold environments.

Gene duplication followed by functional specialization is a potent force in the evolution of biological diversity. A comparative study of two highly conserved duplicated genes, ARABIDOPSIS TRITHORAX-LIKE PROTEIN1 (ATX1) and ATX2, revealed features of both partial redundancy and of functional divergence. Although structurally similar, their regulatory sequences have diverged, resulting in distinct temporal and spatial patterns of expression of the ATX1 and ATX2 genes. We found that ATX2 methylates only a limited fraction of nucleosomes and that ATX1 and ATX2 influence the expression of largely nonoverlapping gene sets. Even when coregulating shared targets, ATX1 and ATX2 may employ different mechanisms. Most remarkable is the divergence of their biochemical activities: both proteins methylate K4 of histone H3, but while ATX1 trimethylates it, ATX2 dimethylates it. ATX2 and ATX1 provide an example of separated K4 di from K4 trimethyltransferase activity.

BackgroundThe molecular mechanisms of genome reprogramming during transcriptional responses to stress are associated with specific chromatin modifications. Available data, however, describe histone modifications only at individual plant genes induced by stress. We have no knowledge of chromatin modifications taking place at genes whose transcription has been down-regulated or on the genome-wide chromatin modification patterns that occur during the plant's response to dehydration stress.ResultsUsing chromatin immunoprecipitation and deep sequencing (ChIP-Seq) we established the whole-genome distribution patterns of histone H3 lysine 4 mono-, di-, and tri-methylation (H3K4me1, H3K4me2, and H3K4me3, respectively) in Arabidopsis thaliana during watered and dehydration stress conditions. In contrast to the relatively even distribution of H3 throughout the genome, the H3K4me1, H3K4me2, and H3K4me3 marks are predominantly located on genes. About 90% of annotated genes carry one or more of the H3K4 methylation marks. The H3K4me1 and H3K4me2 marks are more widely distributed (80% and 84%, respectively) than the H3K4me3 marks (62%), but the H3K4me2 and H3K4me1 levels changed only modestly during dehydration stress. By contrast, the H3K4me3 abundance changed robustly when transcripts levels from responding genes increased or decreased. In contrast to the prominent H3K4me3 peaks present at the 5'-ends of most transcribed genes, genes inducible by dehydration and ABA displayed atypically broader H3K4me3 distribution profiles that were present before and after the stress.ConclusionsA higher number (90%) of annotated Arabidopsis genes carry one or more types of H3K4me marks than previously reported. During the response to dehydration stress the changes in H3K4me1, H3K4me2, and H3K4me3 patterns show different dynamics and specific patterns at up-regulated, down-regulated, and unaffected genes. The different behavior of each methylation mark during the response process illustrates that they have distinct roles in the transcriptional response of implicated genes. The broad H3K4me3 distribution profiles on nucleosomes of stress-induced genes uncovered a specific chromatin pattern associated with many of the genes involved in the dehydration stress response.