Manoj P. Samanta

The Ectocarpus genome and the independent evolution of multicellularity in brown algae

Brown algae (Phaeophyceae) are complex photosynthetic organisms with a very different evolutionary history to green plants, to which they are only distantly related. These seaweeds are the dominant species in rocky coastal ecosystems and they exhibit many interesting adaptations to these, often harsh, environments. Brown algae are also one of only a small number of eukaryotic lineages that have evolved complex multicellularity (Fig. 1). We report the 214 million base pair (Mbp) genome sequence of the filamentous seaweed Ectocarpus siliculosus (Dillwyn) Lyngbye, a model organism for brown algae, closely related to the kelps (Fig. 1). Genome features such as the presence of an extended set of light-harvesting and pigment biosynthesis genes and new metabolic processes such as halide metabolism help explain the ability of this organism to cope with the highly variable tidal environment. The evolution of multicellularity in this lineage is correlated with the presence of a rich array of signal transduction genes. Of particular interest is the presence of a family of receptor kinases, as the independent evolution of related molecules has been linked with the emergence of multicellularity in both the animal and green plant lineages. The Ectocarpus genome sequence represents an important step towards developing this organism as a model species, providing the possibility to combine genomic and genetic approaches to explore these and other aspects of brown algal biology further.

Predicting protein functions from redundancies in large-scale protein interaction networks

Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (≈89%) of the original associations.

Whole-genome expression profiling of the marine diatom Thalassiosira pseudonana identifies genes involved in silicon bioprocesses

Formation of complex inorganic structures is widespread in nature. Diatoms create intricately patterned cell walls of inorganic silicon that are a biomimetic model for design and generation of three-dimensional silica nanostructures. To date, only relatively simple silica structures can be generated in vitro through manipulation of known diatom phosphoproteins (silaffins) and long-chain polyamines. Here, we report the use of genome-wide transcriptome analyses of the marine diatom Thalassiosira pseudonana to identify additional candidate gene products involved in the biological manipulation of silicon. Whole-genome oligonucleotide tiling arrays and tandem mass spectrometry identified transcripts for >8,000 genes, ≈3,000 of which were not previously described and included noncoding and antisense RNAs. Gene-specific expression profiles detected a set of 75 genes induced only under low concentrations of silicon but not under low concentrations of nitrogen or iron, alkaline pH, or low temperatures. Most of these induced gene products were predicted to contain secretory signals and/or transmembrane domains but displayed no homology to known proteins. Over half of these genes were newly discovered, identified only through the use of tiling arrays. Unexpectedly, a common set of 84 genes were induced by both silicon and iron limitations, suggesting that biological manipulation of silicon may share pathways in common with iron or, alternatively, that iron may serve as a required cofactor for silicon processes. These results provide insights into the transcriptional and translational basis for the biological generation of elaborate silicon nanostructures by these ecologically important microbes.

SpBase: the sea urchin genome database and web site

SpBase is a system of databases focused on the genomic information from sea urchins and related echinoderms. It is exposed to the public through a web site served with open source software (http://spbase.org/). The enterprise was undertaken to provide an easily used collection of information to directly support experimental work on these useful research models in cell and developmental biology. The information served from the databases emerges from the draft genomic sequence of the purple sea urchin, Strongylocentrotus purpuratus and includes sequence data and genomic resource descriptions for other members of the echinoderm clade which in total span 540 million years of evolutionary time. This version of the system contains two assemblies of the purple sea urchin genome, associated expressed sequences, gene annotations and accessory resources. Search mechanisms for the sequences and the gene annotations are provided. Because the system is maintained along with the Sea Urchin Genome resource, a database of sequenced clones is also provided.

Genomic basis for the convergent evolution of electric organs

Only one way to make an electric organ? Electric fish have independently evolved electric organs that help them to communicate, navigate, hunt, and defend themselves. Gallant et al. analyzed the genome of the electric eel and the genes expressed in two other distantly related electric fish. The same genes were recruited within the different species to make evolutionarily new structures that function similarly. Science, this issue p. 1522 Multiple divergent fish lineages have used the same evolutionary toolkit to produce electric organs. Little is known about the genetic basis of convergent traits that originate repeatedly over broad taxonomic scales. The myogenic electric organ has evolved six times in fishes to produce electric fields used in communication, navigation, predation, or defense. We have examined the genomic basis of the convergent anatomical and physiological origins of these organs by assembling the genome of the electric eel (Electrophorus electricus) and sequencing electric organ and skeletal muscle transcriptomes from three lineages that have independently evolved electric organs. Our results indicate that, despite millions of years of evolution and large differences in the morphology of electric organ cells, independent lineages have leveraged similar transcription factors and developmental and cellular pathways in the evolution of electric organs.

A critical reanalysis of the relationship between genomics and well-being

Significance This article critically reanalyzes the work of Fredrickson et al. [Fredrickson BL, et al. (2013) Proc Natl Acad Sci USA 110(33):13684–13689], which claimed to show that distinct dimensions of psychological well-being are differentially correlated with levels of expression of a selection of genes associated with distinct forms of immune response. We show that not only is Fredrickson et al.’s article conceptually deficient, but more crucially, that their statistical analyses are fatally flawed, to the point that their claimed results are in fact essentially meaningless. We believe that our findings may have implications for the reevaluation of other published genomics research based on comparable statistical analyses and that a variant of our methodology might be useful for such a reevaluation. Fredrickson et al. [Fredrickson BL, et al. (2013) Proc Natl Acad Sci USA 110(33):13684–13689] claimed to have observed significant differences in gene expression related to hedonic and eudaimonic dimensions of well-being. Having closely examined both their claims and their data, we draw substantially different conclusions. After identifying some important conceptual and methodological flaws in their argument, we report the results of a series of reanalyses of their dataset. We first applied a variety of exploratory and confirmatory factor analysis techniques to their self-reported well-being data. A number of plausible factor solutions emerged, but none of these corresponded to Fredrickson et al.’s claimed hedonic and eudaimonic dimensions. We next examined the regression analyses that purportedly yielded distinct differential profiles of gene expression associated with the two well-being dimensions. Using the best-fitting two-factor solution that we identified, we obtained effects almost twice as large as those found by Fredrickson et al. using their questionable hedonic and eudaimonic factors. Next, we conducted regression analyses for all possible two-factor solutions of the psychometric data; we found that 69.2% of these gave statistically significant results for both factors, whereas only 0.25% would be expected to do so if the regression process was really able to identify independent differential gene expression effects. Finally, we replaced Fredrickson et al.’s psychometric data with random numbers and continued to find very large numbers of apparently statistically significant effects. We conclude that Fredrickson et al.’s widely publicized claims about the effects of different dimensions of well-being on health-related gene expression are merely artifacts of dubious analyses and erroneous methodology.

cWINNOWER algorithm for finding fuzzy dna motifs.

The cWINNOWER algorithm detects fuzzy motifs in DNA sequences rich in protein-binding signals. A signal is defined as any short nucleotide pattern having up to d mutations differing from a motif of length l. The algorithm finds such motifs if a clique consisting of a sufficiently large number of mutated copies of the motif (i.e., the signals) is present in the DNA sequence. The cWINNOWER algorithm substantially improves the sensitivity of the winnower method of Pevzner and Sze by imposing a consensus constraint, enabling it to detect much weaker signals. We studied the minimum detectable clique size qc as a function of sequence length N for random sequences. We found that qc increases linearly with N for a fast version of the algorithm based on counting three-member sub-cliques. Imposing consensus constraints reduces qc by a factor of three in this case, which makes the algorithm dramatically more sensitive. Our most sensitive algorithm, which counts four-member sub-cliques, needs a minimum of only 13 signals to detect motifs in a sequence of length N = 12,000 for (l, d) = (15, 4).

The Ectocarpus Genome and Brown Algal Genomics

Brown algae are important organisms both because of their key ecological roles in coastal ecosystems and because of the remarkable biological features that they have acquired during their unusual evolutionary history. The recent sequencing of the complete genome of the filamentous brown alga Ectocarpus has provided unprecedented access to the molecular processes that underlie brown algal biology. Analysis of the genome sequence, which exhibits several unusual structural features, identified genes that are predicted to play key roles in several aspects of brown algal metabolism, in the construction of the multicellular bodyplan and in resistance to biotic and abiotic stresses. Information from the genome sequence is currently being used in combination with other genomic, genetic and biochemical tools to further investigate these and other aspects of brown algal biology at the molecular level. Here, we review some of the major discoveries that emerged from the analysis of the Ectocarpus genome sequence, with a particular focus on the unusual genome structure, inferences about brown algal evolution and novel aspects of brown algal metabolism.

In-Depth Query of Large Genomes Using Tiling Arrays

Identification of the transcribed regions in the newly sequenced genomes is one of the major challenges of postgenomic biology. Among different alternatives for empirical transcriptome mapping, whole-genome tiling array experiment emerged as the most comprehensive and unbiased approach. This relatively new method uses high-density oligonucleotide arrays with probes chosen uniformly from both strands of the entire genomes including all genic and intergenic regions. By hybridizing the arrays with tissue specific or pooled RNA samples, a genome-wide picture of transcription can be derived. This chapter discusses computational tools and techniques necessary to successfully conduct genome tiling array experiments.

Unique patterns of transcript and miRNA expression in the South American strong voltage electric eel (Electrophorus electricus)

BackgroundWith its unique ability to produce high-voltage electric discharges in excess of 600 volts, the South American strong voltage electric eel (Electrophorus electricus) has played an important role in the history of science. Remarkably little is understood about the molecular nature of its electric organs.ResultsWe present an in-depth analysis of the genome of E. electricus, including the transcriptomes of eight mature tissues: brain, spinal cord, kidney, heart, skeletal muscle, Sachs’ electric organ, main electric organ, and Hunter’s electric organ. A gene set enrichment analysis based on gene ontology reveals enriched functions in all three electric organs related to transmembrane transport, androgen binding, and signaling. This study also represents the first analysis of miRNA in electric fish. It identified a number of miRNAs displaying electric organ-specific expression patterns, including one novel miRNA highly over-expressed in all three electric organs of E. electricus. All three electric organ tissues also express three conserved miRNAs that have been reported to inhibit muscle development in mammals, suggesting that miRNA-dependent regulation of gene expression might play an important role in specifying an electric organ identity from its muscle precursor. These miRNA data were supported using another complete miRNA profile from muscle and electric organ tissues of a second gymnotiform species.ConclusionsOur work on the E. electricus genome and eight tissue-specific gene expression profiles will greatly facilitate future research on determining the coding and regulatory sequences that specify the function, development, and evolution of electric organs. Moreover, these data and future studies will be informed by the first comprehensive analysis of miRNA expression in an electric fish presented here.