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Abstract Background Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. Description The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps and batch gene identifier conversion. Conclusions The Algal Functional Annotation Tool aims to provide an integrated data-mining environment for algal genomics by combining data from multiple annotation databases into a centralized tool. This site is designed to expedite the process of functional annotation and the interpretation of gene lists, such as those derived from high-throughput RNA-seq experiments. The tool is publicly available at http://pathways.mcdb.ucla.edu.

Abstract Background Bisulfite sequencing using next generation sequencers yields genome-wide measurements of DNA methylation at single nucleotide resolution. Traditional aligners are not designed for mapping bisulfite-treated reads, where the unmethylated Cs are converted to Ts. We have developed BS Seeker, an approach that converts the genome to a three-letter alphabet and uses Bowtie to align bisulfite-treated reads to a reference genome. It uses sequence tags to reduce mapping ambiguity. Post-processing of the alignments removes non-unique and low-quality mappings. Results We tested our aligner on synthetic data, a bisulfite-converted Arabidopsis library, and human libraries generated from two different experimental protocols. We evaluated the performance of our approach and compared it to other bisulfite aligners. The results demonstrate that among the aligners tested, BS Seeker is more versatile and faster. When mapping to the human genome, BS Seeker generates alignments significantly faster than RMAP and BSMAP. Furthermore, BS Seeker is the only alignment tool that can explicitly account for tags which are generated by certain library construction protocols. Conclusions BS Seeker provides fast and accurate mapping of bisulfite-converted reads. It can work with BS reads generated from the two different experimental protocols, and is able to efficiently map reads to large mammalian genomes. The Python program is freely available at http://pellegrini.mcdb.ucla.edu/BS_Seeker/BS_Seeker.html.

Abstract Background Reverse-engineering regulatory networks is one of the central challenges for computational biology. Many techniques have been developed to accomplish this by utilizing transcription factor binding data in conjunction with expression data. Of these approaches, several have focused on the reconstruction of the cell cycle regulatory network of Saccharomyces cerevisiae. The emphasis of these studies has been to model the relationships between transcription factors and their target genes. In contrast, here we focus on reverse-engineering the network of relationships among transcription factors that regulate the cell cycle in S. cerevisiae. Results We have developed a technique to reverse-engineer networks of the time-dependent activities of transcription factors that regulate the cell cycle in S. cerevisiae. The model utilizes linear regression to first estimate the activities of transcription factors from expression time series and genome-wide transcription factor binding data. We then use least squares to construct a model of the time evolution of the activities. We validate our approach in two ways: by demonstrating that it accurately models expression data and by demonstrating that our reconstructed model is similar to previously-published models of transcriptional regulation of the cell cycle. Conclusion Our regression-based approach allows us to build a general model of transcriptional regulation of the yeast cell cycle that includes additional factors and couplings not reported in previously-published models. Our model could serve as a starting point for targeted experiments that test the predicted interactions. In the future, we plan to apply our technique to reverse-engineer other systems where both genome-wide time series expression data and transcription factor binding data are available.

An important question is what genes govern the differentiation of plant embryos into suspensor and embryo proper regions following fertilization and division of the zygote. We compared embryo proper and suspensor transcriptomes of four plants that vary in embryo morphology within the suspensor region. We determined that genes encoding enzymes in several metabolic pathways leading to the formation of hormones, such as gibberellic acid, and other metabolites are up-regulated in giant scarlet runner bean and common bean suspensors. Genes involved in transport and Golgi body organization are up-regulated within the suspensors of these plants as well, strengthening the view that giant specialized suspensors serve as a hormone factory and a conduit for transferring substances to the developing embryo proper. By contrast, genes controlling transcriptional regulation, development, and cell division are up-regulated primarily within the embryo proper. Transcriptomes from less specialized soybean and Arabidopsis suspensors demonstrated that fewer genes encoding metabolic enzymes and hormones are up-regulated. Genes active in the embryo proper, however, are functionally similar to those active in scarlet runner bean and common bean embryo proper regions. We uncovered a set of suspensor- and embryo proper-specific transcription factors (TFs) that are shared by all embryos irrespective of morphology, suggesting that they are involved in early differentiation processes common to all plants. Chromatin immunoprecipitation sequencing (ChIP-Seq) experiments with scarlet runner bean and soybean WOX9, an up-regulated suspensor TF, gained entry into a regulatory network important for suspensor development irrespective of morphology., Competing Interests: Competing interest statement: R.B.G. and B.L. are coauthors on a 2019 editorial article., (Copyright © 2021 the Author(s). Published by PNAS.)

MicroRNAs (miRNAs) are important regulatory molecules in eukaryotic organisms. Existing methods for the identification of mature miRNA sequences in plants rely extensively on the search for stem-loop structures, leading to high false negative rates. Here, we describe a probabilistic method for ranking putative plant miRNAs using a naïve Bayes classifier and its publicly available implementation. We use a number of properties to construct the classifier, including sequence length, number of observations, existence of detectable predicted miRNA* sequences, the distribution of nearby reads and mapping multiplicity. We apply the method to small RNA sequence data from soybean, peach, Arabidopsis and rice and provide experimental validation of several predictions in soybean. The approach performs well overall and strongly enriches for known miRNAs over other types of sequences. By utilizing a Bayesian approach to rank putative miRNAs, our method is able to score miRNAs that would be eliminated by other methods, such as those that have low counts or lack detectable miRNA* sequences. As a result, we are able to detect several soybean miRNA candidates, including some that are 24 nucleotides long, a class that is almost universally eliminated by other methods., (© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.)

Background: DNA methylation is an important epigenetic modification involved in many biological processes. Bisulfite treatment coupled with high-throughput sequencing provides an effective approach for studying genome-wide DNA methylation at base resolution. Libraries such as whole genome bisulfite sequencing (WGBS) and reduced represented bisulfite sequencing (RRBS) are widely used for generating DNA methylomes, demanding efficient and versatile tools for aligning bisulfite sequencing data., Results: We have developed BS-Seeker2, an updated version of BS Seeker, as a full pipeline for mapping bisulfite sequencing data and generating DNA methylomes. BS-Seeker2 improves mappability over existing aligners by using local alignment. It can also map reads from RRBS library by building special indexes with improved efficiency and accuracy. Moreover, BS-Seeker2 provides additional function for filtering out reads with incomplete bisulfite conversion, which is useful in minimizing the overestimation of DNA methylation levels. We also defined CGmap and ATCGmap file formats for full representations of DNA methylomes, as part of the outputs of BS-Seeker2 pipeline together with BAM and WIG files., Conclusions: Our evaluations on the performance show that BS-Seeker2 works efficiently and accurately for both WGBS data and RRBS data. BS-Seeker2 is freely available at http://pellegrini.mcdb.ucla.edu/BS_Seeker2/ and the Galaxy server.

Unlabelled: Investigation of the human microbiome has revealed diverse and complex microbial communities at distinct anatomic sites. The microbiome of the human sebaceous follicle provides a tractable model in which to study its dominant bacterial inhabitant, Propionibacterium acnes, which is thought to contribute to the pathogenesis of the human disease acne. To explore the diversity of the bacteriophages that infect P. acnes, 11 P. acnes phages were isolated from the sebaceous follicles of donors with healthy skin or acne and their genomes were sequenced. Comparative genomic analysis of the P. acnes phage population, which spans a 30-year temporal period and a broad geographic range, reveals striking similarity in terms of genome length, percent GC content, nucleotide identity (>85%), and gene content. This was unexpected, given the far-ranging diversity observed in virtually all other phage populations. Although the P. acnes phages display a broad host range against clinical isolates of P. acnes, two bacterial isolates were resistant to many of these phages. Moreover, the patterns of phage resistance correlate closely with the presence of clustered regularly interspaced short palindromic repeat elements in the bacteria that target a specific subset of phages, conferring a system of prokaryotic innate immunity. The limited diversity of the P. acnes bacteriophages, which may relate to the unique evolutionary constraints imposed by the lipid-rich anaerobic environment in which their bacterial hosts reside, points to the potential utility of phage-based antimicrobial therapy for acne., Importance: Propionibacterium acnes is a dominant member of the skin microflora and has also been implicated in the pathogenesis of acne; however, little is known about the bacteriophages that coexist with and infect this bacterium. Here we present the novel genome sequences of 11 P. acnes phages, thereby substantially increasing the amount of available genomic information about this phage population. Surprisingly, we find that, unlike other well-studied bacteriophages, P. acnes phages are highly homogeneous and show a striking lack of genetic diversity, which is perhaps related to their unique and restricted habitat. They also share a broad ability to kill clinical isolates of P. acnes; phage resistance is not prevalent, but when detected, it appears to be conferred by chromosomally encoded immunity elements within the host genome. We believe that these phages display numerous features that would make them ideal candidates for the development of a phage-based therapy for acne.

In this work, we query the Chlamydomonas reinhardtii copper regulon at a whole-genome level. Our RNA-Seq data simulation and analysis pipeline validated a 2-fold cutoff and 10 RPKM (reads per kilobase of mappable length per million mapped reads) (~1 mRNA per cell) to reveal 63 CRR1 targets plus another 86 copper-responsive genes. Proteomic and immunoblot analyses captured 25% of the corresponding proteins, whose abundance was also dependent on copper nutrition, validating transcriptional regulation as a major control mechanism for copper signaling in Chlamydomonas. The impact of copper deficiency on the expression of several O₂-dependent enzymes included steps in lipid modification pathways. Quantitative lipid profiles indicated increased polyunsaturation of fatty acids on thylakoid membrane digalactosyldiglycerides, indicating a global impact of copper deficiency on the photosynthetic apparatus. Discovery of a putative plastid copper chaperone and a membrane protease in the thylakoid suggest a mechanism for blocking copper utilization in the chloroplast. We also found an example of copper sparing in the N assimilation pathway: the replacement of copper amine oxidase by a flavin-dependent backup enzyme. Forty percent of the targets are previously uncharacterized proteins, indicating considerable potential for new discovery in the biology of copper.

The Chlamydomonas reinhardtii transcriptome was characterized from nutrient-replete and sulfur-depleted wild-type and snrk2.1 mutant cells. This mutant is null for the regulatory Ser-Thr kinase SNRK2.1, which is required for acclimation of the alga to sulfur deprivation. The transcriptome analyses used microarray hybridization and RNA-seq technology. Quantitative RT-PCR evaluation of the results obtained by these techniques showed that RNA-seq reports a larger dynamic range of expression levels than do microarray hybridizations. Transcripts responsive to sulfur deprivation included those encoding proteins involved in sulfur acquisition and assimilation, synthesis of sulfur-containing metabolites, Cys degradation, and sulfur recycling. Furthermore, we noted potential modifications of cellular structures during sulfur deprivation, including the cell wall and complexes associated with the photosynthetic apparatus. Moreover, the data suggest that sulfur-deprived cells accumulate proteins with fewer sulfur-containing amino acids. Most of the sulfur deprivation responses are controlled by the SNRK2.1 protein kinase. The snrk2.1 mutant exhibits a set of unique responses during both sulfur-replete and sulfur-depleted conditions that are not observed in wild-type cells; the inability of this mutant to acclimate to S deprivation probably leads to elevated levels of singlet oxygen and severe oxidative stress, which ultimately causes cell death. The transcriptome results for wild-type and mutant cells strongly suggest the occurrence of massive changes in cellular physiology and metabolism as cells become depleted for sulfur and reveal aspects of acclimation that are likely critical for cell survival.

Constitutive heterochromatin in Arabidopsis thaliana is marked by repressive chromatin modifications, including DNA methylation, histone H3 dimethylation at Lys9 (H3K9me2) and monomethylation at Lys27 (H3K27me1). The enzymes catalyzing DNA methylation and H3K9me2 have been identified; alterations in these proteins lead to reactivation of silenced heterochromatic elements. The enzymes responsible for heterochromatic H3K27me1, in contrast, remain unknown. Here we show that the divergent SET-domain proteins ARABIDOPSIS TRITHORAX-RELATED PROTEIN 5 (ATXR5) and ATXR6 have H3K27 monomethyltransferase activity, and atxr5 atxr6 double mutants have reduced H3K27me1 in vivo and show partial heterochromatin decondensation. Mutations in atxr5 and atxr6 also lead to transcriptional activation of repressed heterochromatic elements. Notably, H3K9me2 and DNA methylation are unaffected in double mutants. These results indicate that ATXR5 and ATXR6 form a new class of H3K27 methyltransferases and that H3K27me1 represents a previously uncharacterized pathway required for transcriptional repression in Arabidopsis.

Background: Post-translational modifications of histones play important roles in maintaining normal transcription patterns by directly or indirectly affecting the structural properties of the chromatin. In plants, methylation of histone H3 lysine 4 (H3K4me) is associated with genes and required for normal plant development., Results: We have characterized the genome-wide distribution patterns of mono-, di- and trimethylation of H3K4 (H3K4me1, H3K4me2 and H3K4me3, respectively) in Arabidopsis thaliana seedlings using chromatin immunoprecipitation and high-resolution whole-genome tiling microarrays (ChIP-chip). All three types of H3K4me are found to be almost exclusively genic, and two-thirds of Arabidopsis genes contain at least one type of H3K4me. H3K4me2 and H3K4me3 accumulate predominantly in promoters and 5' genic regions, whereas H3K4me1 is distributed within transcribed regions. In addition, H3K4me3-containing genes are highly expressed with low levels of tissue specificity, but H3K4me1 or H3K4me2 may not be directly involved in transcriptional activation. Furthermore, the preferential co-localization of H3K4me3 and H3K27me3 found in mammals does not appear to occur in plants at a genome-wide level, but H3K4me2 and H3K27me3 co-localize at a higher-than-expected frequency. Finally, we found that H3K4me2/3 and DNA methylation appear to be mutually exclusive, but surprisingly, H3K4me1 is highly correlated with CG DNA methylation in the transcribed regions of genes., Conclusions: H3K4me plays widespread roles in regulating gene expression in plants. Although many aspects of the mechanisms and functions of H3K4me appear to be conserved among all three kingdoms, we observed significant differences in the relationship between H3K4me and transcription or other epigenetic pathways in plants and mammals.

Methylation of histone H3 lysine 9 (H3K9) is a hallmark of transcriptional silencing in many organisms. In Arabidopsis thaliana, dimethylation of H3K9 (H3K9m2) is important in the silencing of transposons and in the control of DNA methylation. We constructed a high-resolution genome-wide map of H3K9m2 methylation by using chromatin immunoprecipitation coupled with whole genome Roche Nimblegen microarrays (ChIP-chip). We observed a very high coincidence between H3K9m2 and CHG methylation (where H is either A,T or C) throughout the genome. The coding regions of genes that are associated exclusively with methylation in a CG context did not contain H3K9m2. In addition, we observed two distinct patterns of H3K9m2. Transposons and other repeat elements present in the euchromatic arms contained small islands of H3K9m2 present at relatively low levels. In contrast, pericentromeric/centromeric regions of Arabidopsis chromosomes contained long, rarely interrupted blocks of H3K9m2 present at much higher average levels than seen in the chromosome arms. These results suggest a complex interplay between H3K9m2 and different types of DNA methylation and suggest that distinct mechanisms control H3K9m2 in different compartments of the genome.

Using a large consortium of undergraduate students in an organized program at the University of California, Los Angeles (UCLA), we have undertaken a functional genomic screen in the Drosophila eye. In addition to the educational value of discovery-based learning, this article presents the first comprehensive genomewide analysis of essential genes involved in eye development. The data reveal the surprising result that the X chromosome has almost twice the frequency of essential genes involved in eye development as that found on the autosomes.

Background: Phylogenetic profiles record the occurrence of homologs of genes across fully sequenced organisms. Proteins with similar profiles are typically components of protein complexes or metabolic pathways. Various existing methods measure similarity between two profiles and, hence, the likelihood that the two proteins co-evolve. Some methods ignore phylogenetic relationships between organisms while others account for such with metrics that explicitly model the likelihood of two proteins co-evolving on a tree. The latter methods more sensitively detect co-evolving proteins, but at a significant computational cost. Here we propose a novel heuristic to improve phylogenetic profile analysis that accounts for phylogenetic relationships between genomes in a computationally efficient fashion. We first order the genomes within profiles and then enumerate runs of consecutive matches and accurately compute the probability of observing these. We hypothesize that profiles with many runs are more likely to involve functionally related proteins than profiles in which all the matches are concentrated in one interval of the tree., Results: We compared our approach to various previously published methods that both ignore and incorporate the underlying phylogeny between organisms. To evaluate performance, we compare the functional similarity of rank-ordered lists of protein pairs that share similar phylogenetic profiles by assessing significance of overlap in their Gene Ontology annotations. Accounting for runs in phylogenetic profile matches improves our ability to identify functionally related pairs of proteins. Furthermore, the networks that result from our approach tend to have smaller clusters of co-evolving proteins than networks computed using previous approaches and are thus more useful for inferring functional relationships. Finally, we report that our approach is orders of magnitude more computationally efficient than full tree-based methods., Conclusion: We have developed an improved method for analyzing phylogenetic profiles. The method allows us to more accurately and efficiently infer functional relationships between proteins based on these profiles than other published approaches. As the number of fully sequenced genomes increases, it becomes more important to account for evolutionary relationships among organisms in comparative analyses. Our approach, therefore, serves as an important example of how these relationships may be accounted for in an efficient manner.

Trimethylation of histone H3 lysine 27 (H3K27me3) plays critical roles in regulating animal development, and in several cases, H3K27me3 is also required for the proper expression of developmentally important genes in plants. However, the extent to which H3K27me3 regulates plant genes on a genome-wide scale remains unknown. In addition, it is not clear whether the establishment and spreading of H3K27me3 occur through the same mechanisms in plants and animals. We identified regions containing H3K27me3 in the genome of the flowering plant Arabidopsis thaliana using a high-density whole-genome tiling microarray. The results suggest that H3K27me3 is a major silencing mechanism in plants that regulates an unexpectedly large number of genes in Arabidopsis (~4,400), and that the maintenance of H3K27me3 is largely independent of other epigenetic pathways, such as DNA methylation or RNA interference. Unlike in animals, where H3K27m3 occupies large genomic regions, in Arabidopsis, we found that H3K27m3 domains were largely restricted to the transcribed regions of single genes. Furthermore, unlike in animals systems, H3K27m3 domains were not preferentially associated with low-nucleosome density regions. The results suggest that different mechanisms may underlie the establishment and spreading of H3K27me3 in plants and animals.

Cytosine methylation is important for transposon silencing and epigenetic regulation of endogenous genes, although the extent to which this DNA modification functions to regulate the genome is still unknown. Here we report the first comprehensive DNA methylation map of an entire genome, at 35 base pair resolution, using the flowering plant Arabidopsis thaliana as a model. We find that pericentromeric heterochromatin, repetitive sequences, and regions producing small interfering RNAs are heavily methylated. Unexpectedly, over one-third of expressed genes contain methylation within transcribed regions, whereas only approximately 5% of genes show methylation within promoter regions. Interestingly, genes methylated in transcribed regions are highly expressed and constitutively active, whereas promoter-methylated genes show a greater degree of tissue-specific expression. Whole-genome tiling-array transcriptional profiling of DNA methyltransferase null mutants identified hundreds of genes and intergenic noncoding RNAs with altered expression levels, many of which may be epigenetically controlled by DNA methylation.

Background: Reverse-engineering regulatory networks is one of the central challenges for computational biology. Many techniques have been developed to accomplish this by utilizing transcription factor binding data in conjunction with expression data. Of these approaches, several have focused on the reconstruction of the cell cycle regulatory network of Saccharomyces cerevisiae. The emphasis of these studies has been to model the relationships between transcription factors and their target genes. In contrast, here we focus on reverse-engineering the network of relationships among transcription factors that regulate the cell cycle in S. cerevisiae., Results: We have developed a technique to reverse-engineer networks of the time-dependent activities of transcription factors that regulate the cell cycle in S. cerevisiae. The model utilizes linear regression to first estimate the activities of transcription factors from expression time series and genome-wide transcription factor binding data. We then use least squares to construct a model of the time evolution of the activities. We validate our approach in two ways: by demonstrating that it accurately models expression data and by demonstrating that our reconstructed model is similar to previously-published models of transcriptional regulation of the cell cycle., Conclusion: Our regression-based approach allows us to build a general model of transcriptional regulation of the yeast cell cycle that includes additional factors and couplings not reported in previously-published models. Our model could serve as a starting point for targeted experiments that test the predicted interactions. In the future, we plan to apply our technique to reverse-engineer other systems where both genome-wide time series expression data and transcription factor binding data are available.

Finding the interacting pairs of proteins between two different protein families whose members are known to interact is an important problem in molecular biology. We developed and tested an algorithm that finds optimal matches between two families of proteins by comparing their distance matrices. A distance matrix provides a measure of the sequence similarity of proteins within a family. Since the protein sets of interest may have dozens of proteins each, the use of an efficient approximate solution is necessary. Therefore the approach we have developed consists of a Metropolis Monte Carlo optimization algorithm which explores the search space of possible matches between two distance matrices. We demonstrate that by using this algorithm we are able to accurately match chemokines and chemokine-receptors as well as the tgfbeta family of ligands and their receptors.