Long noncoding RNAs with enhancer-like function in human cells.

While the long noncoding RNAs (ncRNAs) constitute a large portion of the mammalian transcriptome, their biological functions has remained elusive. A few long ncRNAs that have been studied in any detail silence gene expression in processes such as X-inactivation and imprinting. We used a GENCODE annotation of the human genome to characterize over a thousand long ncRNAs that are expressed in multiple cell lines. Unexpectedly, we found an enhancer-like function for a set of these long ncRNAs in human cell lines. Depletion of a number of ncRNAs led to decreased expression of their neighboring protein-coding genes, including the master regulator of hematopoiesis, SCL (also called TAL1), Snai1 and Snai2. Using heterologous transcription assays we demonstrated a requirement for the ncRNAs in activation of gene expression. These results reveal an unanticipated role for a class of long ncRNAs in activation of critical regulators of development and differentiation.

Four layer multi-omics reveals molecular responses to aneuploidy in Leishmania.

Aneuploidy causes system-wide disruptions in the stochiometric balances of transcripts, proteins, and metabolites, often resulting in detrimental effects for the organism. The protozoan parasite Leishmania has an unusually high tolerance for aneuploidy, but the molecular and functional consequences for the pathogen remain poorly understood. Here, we addressed this question in vitro and present the first integrated analysis of the genome, transcriptome, proteome, and metabolome of highly aneuploid Leishmania donovani strains. Our analyses unambiguously establish that aneuploidy in Leishmania proportionally impacts the average transcript- and protein abundance levels of affected chromosomes, ultimately correlating with the degree of metabolic differences between closely related aneuploid strains. This proportionality was present in both proliferative and non-proliferative in vitro promastigotes. However, as in other Eukaryotes, we observed attenuation of dosage effects for protein complex subunits and in addition, non-cytoplasmic proteins. Differentially expressed transcripts and proteins between aneuploid Leishmania strains also originated from non-aneuploid chromosomes. At protein level, these were enriched for proteins involved in protein metabolism, such as chaperones and chaperonins, peptidases, and heat-shock proteins. In conclusion, our results further support the view that aneuploidy in Leishmania can be adaptive. Additionally, we believe that the high karyotype diversity in vitro and absence of classical transcriptional regulation make Leishmania an attractive model to study processes of protein homeostasis in the context of aneuploidy and beyond.

Highly significant improvement of protein sequence alignments with AlphaFold2.

MOTIVATION: Protein sequence alignments are essential to structural, evolutionary and functional analysis, but their accuracy is often limited by sequence similarity unless molecular structures are available. Protein structures predicted at experimental grade accuracy, as achieved by AlphaFold2, could therefore have a major impact on sequence analysis. RESULTS: Here, we find that multiple sequence alignments estimated on AlphaFold2 predictions are almost as accurate as alignments estimated on experimental structures and significantly closer to the structural reference than sequence-based alignments. We also show that AlphaFold2 structural models of relatively low quality can be used to obtain highly accurate alignments. These results suggest that, besides structure modeling, AlphaFold2 encodes higher-order dependencies that can be exploited for sequence analysis. AVAILABILITY AND IMPLEMENTATION: All data, analyses and results are available on Zenodo (https://doi.org/10.5281/zenodo.7031286). The code and scripts have been deposited in GitHub (https://github.com/cbcrg/msa-af2-nf) and the various containers in (https://cloud.sylabs.io/library/athbaltzis/af2/alphafold, https://hub.docker.com/r/athbaltzis/pred). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Incorporating alignment uncertainty into Felsenstein's phylogenetic bootstrap to improve its reliability.

MOTIVATION: Most evolutionary analyses are based on pre-estimated multiple sequence alignment. Wong et al. established the existence of an uncertainty induced by multiple sequence alignment when reconstructing phylogenies. They were able to show that in many cases different aligners produce different phylogenies, with no simple objective criterion sufficient to distinguish among these alternatives. RESULTS: We demonstrate that incorporating MSA induced uncertainty into bootstrap sampling can significantly increase correlation between clade correctness and its corresponding bootstrap value. Our procedure involves concatenating several alternative multiple sequence alignments of the same sequences, produced using different commonly used aligners. We then draw bootstrap replicates while favoring columns of the more unique aligner among the concatenated aligners. We named this concatenation and bootstrapping method, Weighted Partial Super Bootstrap (wpSBOOT). We show on three simulated datasets of 16, 32 and 64 tips that our method improves the predictive power of bootstrap values. We also used as a benchmark an empirical collection of 853 one to one orthologous genes from seven yeast species and found wpSBOOT to significantly improve discrimination capacity between topologically correct and incorrect trees. Bootstrap values of wpSBOOT are comparable to similar readouts estimated using a single method. However, for reduced trees by 50 and 95% bootstrap thresholds, wpSBOOT comes out the lowest Type I error (less FP). AVAILABILITY AND IMPLEMENTATION: The automated generation of replicates has been implemented in the T-Coffee package, which is available as open source freeware available from www.tcoffee.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pergola-web: a web server for the visualization and analysis of longitudinal behavioral data using repurposed genomics tools and standards.

We present a new web application to query and visualize time-series behavioral data: the Pergola web-server. This server provides a user-friendly interface for exploring longitudinal behavioral data taking advantage of the Pergola Python library. Using the server, users can process the data applying some basic operations, such as binning or grouping, while formatting the data into existing genomic formats. Thanks to this repurposing of genomics standards, the application automatically renders an interactive data visualization based on sophisticated genome visualization tools. Our tool allows behavioral scientists to share, display and navigate complex behavioral data comprising multiple individuals and multiple data types, in a scalable and flexible manner. A download option allows for further analysis using genomic tools. The server can be a great resource for the field in a time where behavioral science is entering a data-intensive cycle thanks to high-throughput behavioral phenotyping platforms. Pergola is publicly available at http://pergola.crg.eu/.

Evolutionary Footprints Reveal Insights into Plant MicroRNA Biogenesis.

MicroRNAs (miRNAs) are endogenous small RNAs that recognize target sequences by base complementarity and play a role in the regulation of target gene expression. They are processed from longer precursor molecules that harbor a fold-back structure. Plant miRNA precursors are quite variable in size and shape, and are recognized by the processing machinery in different ways. However, ancient miRNAs and their binding sites in target genes are conserved during evolution. Here, we designed a strategy to systematically analyze MIRNAs from different species generating a graphical representation of the conservation of the primary sequence and secondary structure. We found that plant MIRNAs have evolutionary footprints that go beyond the small RNA sequence itself, yet their location along the precursor depends on the specific MIRNA We show that these conserved regions correspond to structural determinants recognized during the biogenesis of plant miRNAs. Furthermore, we found that the members of the miR166 family have unusual conservation patterns and demonstrated that the recognition of these precursors in vivo differs from other known miRNAs. Our results describe a link between the evolutionary conservation of plant MIRNAs and the mechanisms underlying the biogenesis of these small RNAs and show that the MIRNA pattern of conservation can be used to infer the mode of miRNA biogenesis.

Improved definition of the mouse transcriptome via targeted RNA sequencing.

Targeted RNA sequencing (CaptureSeq) uses oligonucleotide probes to capture RNAs for sequencing, providing enriched read coverage, accurate measurement of gene expression, and quantitative expression data. We applied CaptureSeq to refine transcript annotations in the current murine GRCm38 assembly. More than 23,000 regions corresponding to putative or annotated long noncoding RNAs (lncRNAs) and 154,281 known splicing junction sites were selected for targeted sequencing across five mouse tissues and three brain subregions. The results illustrate that the mouse transcriptome is considerably more complex than previously thought. We assemble more complete transcript isoforms than GENCODE, expand transcript boundaries, and connect interspersed islands of mapped reads. We describe a novel filtering pipeline that identifies previously unannotated but high-quality transcript isoforms. In this set, 911 GENCODE neighboring genes are condensed into 400 expanded gene models. Additionally, 594 GENCODE lncRNAs acquire an open reading frame (ORF) when their structure is extended with CaptureSeq. Finally, we validate our observations using current FANTOM and Mouse ENCODE resources.

Generalized Bootstrap Supports for Phylogenetic Analyses of Protein Sequences Incorporating Alignment Uncertainty.

Phylogenetic reconstructions are essential in genomics data analyses and depend on accurate multiple sequence alignment (MSA) models. We show that all currently available large-scale progressive multiple alignment methods are numerically unstable when dealing with amino-acid sequences. They produce significantly different output when changing sequence input order. We used the HOMFAM protein sequences dataset to show that on datasets larger than 100 sequences, this instability affects on average 21.5% of the aligned residues. The resulting Maximum Likelihood (ML) trees estimated from these MSAs are equally unstable with over 38% of the branches being sensitive to the sequence input order. We established that about two-thirds of this uncertainty stems from the unordered nature of children nodes within the guide trees used to estimate MSAs. To quantify this uncertainty we developed unistrap, a novel approach that estimates the combined effect of alignment uncertainty and site sampling on phylogenetic tree branch supports. Compared with the regular bootstrap procedure, unistrap provides branch support estimates that take into account a larger fraction of the parameters impacting tree instability when processing datasets containing a large number of sequences.

Multiple sequence alignment modeling: methods and applications.

This review provides an overview on the development of Multiple sequence alignment (MSA) methods and their main applications. It is focused on progress made over the past decade. The three first sections review recent algorithmic developments for protein, RNA/DNA and genomic alignments. The fourth section deals with benchmarks and explores the relationship between empirical and simulated data, along with the impact on method developments. The last part of the review gives an overview on available MSA local reliability estimators and their dependence on various algorithmic properties of available methods.

Epistasis as the primary factor in molecular evolution.

The main forces directing long-term molecular evolution remain obscure. A sizable fraction of amino-acid substitutions seem to be fixed by positive selection, but it is unclear to what degree long-term protein evolution is constrained by epistasis, that is, instances when substitutions that are accepted in one genotype are deleterious in another. Here we obtain a quantitative estimate of the prevalence of epistasis in long-term protein evolution by relating data on amino-acid usage in 14 organelle proteins and 2 nuclear-encoded proteins to their rates of short-term evolution. We studied multiple alignments of at least 1,000 orthologues for each of these 16 proteins from species from a diverse phylogenetic background and found that an average site contained approximately eight different amino acids. Thus, without epistasis an average site should accept two-fifths of all possible amino acids, and the average rate of amino-acid substitutions should therefore be about three-fifths lower than the rate of neutral evolution. However, we found that the measured rate of amino-acid substitution in recent evolution is 20 times lower than the rate of neutral evolution and an order of magnitude lower than that expected in the absence of epistasis. These data indicate that epistasis is pervasive throughout protein evolution: about 90 per cent of all amino-acid substitutions have a neutral or beneficial impact only in the genetic backgrounds in which they occur, and must therefore be deleterious in a different background of other species. Our findings show that most amino-acid substitutions have different fitness effects in different species and that epistasis provides the primary conceptual framework to describe the tempo and mode of long-term protein evolution.

Extinction and reinstatement of an operant responding maintained by food in different models of obesity.

A major problem in treating obesity is the high rate of relapse to abnormal food-taking habits after maintaining an energy balanced diet. Alterations of eating behavior such as compulsive-like behavior and lack of self-control over food intake play a critical role in relapse. In this study, we used an operant paradigm of food-seeking behavior on two different diet-induced obesity models, a free-choice chocolate-mixture diet and a high-fat diet with face validity for a rapid development of obesity or for unhealthy food regularly consumed in our societies. A reduced operant performance and motivation for the hedonic value of palatable chocolate pellets was revealed in both obesity mouse models. However, only mice exposed to high-fat diet showed an increased compulsive-like behavior in the absence of the reinforcer further characterized by impaired operant learning, enhanced impulsivity and intensified inflexibility. We used principal component analysis to globally identify the specific behaviors responsible for the differences among diet groups. Learning impairment and inflexible behaviors contributed to a first principal component, explaining the largest proportion of the variance in the high-fat diet mice phenotype. Reinforcement, impulsion and compulsion were the main contributors to the second principal component explaining the differences in the chocolate-mixture mice behavioral phenotype. These behaviors were not exclusive of chocolate group because some high-fat individuals showed similar values on this component. These data indicate that extended access to hypercaloric diets differentially modifies operant behavior learning, behavioral flexibility, impulsive-like and compulsive-like behavior, and these effects were dependent on the exposure to each specific diet.

Time-course and dynamics of obesity-related behavioral changes induced by energy-dense foods in mice.

Obesity represents an important risk factor contributing to the global burden of disease. The current obesogenic environment with easy access to calorie-dense foods is fueling this obesity epidemic. However, how these foods contribute to the progression of feeding behavior changes that lead to overeating is not well understood and needs systematic assessment. Using novel automated methods for the high-throughput screening of behavior, we here examine mice meal pattern upon long-term exposure to a free-choice chocolate-mixture diet and a high-fat diet with face validity for a rapid development of obesity induced by unhealthy food regularly consumed in our societies. We identified rapid diet-specific behavioral changes after exposure to those high-caloric diets. Mice fed with high-fat chow, showed long-lasting meal pattern disturbances, which initiate with a stable loss of circadian feeding rhythmicity. Mice receiving a chocolate-mixture showed qualitatively similar changes, though less marked, consisting in a transient disruption of the feeding behavior and the circadian feeding rhytmicity. Strikingly, compulsive-like eating behavior is triggered immediately after exposure to both high-fat food and chocolate-mixture diet, well before any changes in body weight could be observed. We propose these changes as behavioral biomarkers of prodromal states of obesity that could allow early intervention.

PSI/TM-Coffee: a web server for fast and accurate multiple sequence alignments of regular and transmembrane proteins using homology extension on reduced databases.

The PSI/TM-Coffee web server performs multiple sequence alignment (MSA) of proteins by combining homology extension with a consistency based alignment approach. Homology extension is performed with Position Specific Iterative (PSI) BLAST searches against a choice of redundant and non-redundant databases. The main novelty of this server is to allow databases of reduced complexity to rapidly perform homology extension. This server also gives the possibility to use transmembrane proteins (TMPs) reference databases to allow even faster homology extension on this important category of proteins. Aside from an MSA, the server also outputs topological prediction of TMPs using the HMMTOP algorithm. Previous benchmarking of the method has shown this approach outperforms the most accurate alignment methods such as MSAProbs, Kalign, PROMALS, MAFFT, ProbCons and PRALINE™. The web server is available at http://tcoffee.crg.cat/tmcoffee.

A novel, noncanonical mechanism of cytoplasmic polyadenylation operates in Drosophila embryogenesis.

Cytoplasmic polyadenylation is a widespread mechanism to regulate mRNA translation that requires two sequences in the 3' untranslated region (UTR) of vertebrate substrates: the polyadenylation hexanucleotide, and the cytoplasmic polyadenylation element (CPE). Using a cell-free Drosophila system, we show that these signals are not relevant for Toll polyadenylation but, instead, a "polyadenylation region" (PR) is necessary. Competition experiments indicate that PR-mediated polyadenylation is required for viability and is mechanistically distinct from the CPE/hexanucleotide-mediated process. These data indicate that Toll mRNA is polyadenylated by a noncanonical mechanism, and suggest that a novel machinery functions for cytoplasmic polyadenylation during Drosophila embryogenesis.

Alignathon: a competitive assessment of whole-genome alignment methods.

Multiple sequence alignments (MSAs) are a prerequisite for a wide variety of evolutionary analyses. Published assessments and benchmark data sets for protein and, to a lesser extent, global nucleotide MSAs are available, but less effort has been made to establish benchmarks in the more general problem of whole-genome alignment (WGA). Using the same model as the successful Assemblathon competitions, we organized a competitive evaluation in which teams submitted their alignments and then assessments were performed collectively after all the submissions were received. Three data sets were used: Two were simulated and based on primate and mammalian phylogenies, and one was comprised of 20 real fly genomes. In total, 35 submissions were assessed, submitted by 10 teams using 12 different alignment pipelines. We found agreement between independent simulation-based and statistical assessments, indicating that there are substantial accuracy differences between contemporary alignment tools. We saw considerable differences in the alignment quality of differently annotated regions and found that few tools aligned the duplications analyzed. We found that many tools worked well at shorter evolutionary distances, but fewer performed competitively at longer distances. We provide all data sets, submissions, and assessment programs for further study and provide, as a resource for future benchmarking, a convenient repository of code and data for reproducing the simulation assessments.

TCS: a web server for multiple sequence alignment evaluation and phylogenetic reconstruction.

This article introduces the Transitive Consistency Score (TCS) web server; a service making it possible to estimate the local reliability of protein multiple sequence alignments (MSAs) using the TCS index. The evaluation can be used to identify the aligned positions most likely to contain structurally analogous residues and also most likely to support an accurate phylogenetic reconstruction. The TCS scoring scheme has been shown to be accurate predictor of structural alignment correctness among commonly used methods. It has also been shown to outperform common filtering schemes like Gblocks or trimAl when doing MSA post-processing prior to phylogenetic tree reconstruction. The web server is available from http://tcoffee.crg.cat/tcs.

An improved understanding of TNFL/TNFR interactions using structure-based classifications.

Tumor Necrosis Factor Ligand (TNFL)-Tumor Necrosis Factor Receptor (TNFR) interactions control key cellular processes; however, the molecular basis of the specificity of these interactions remains poorly understood. Using the T-RMSD (tree based on root mean square deviation), a newly developed structure-based sequence clustering method, we have re-analyzed the available structural data to re-interpret the interactions between TNFLs and TNFRs. This improves the classification of both TNFLs and TNFRs, such that the new groups defined here are in much stronger agreement with structural and functional features than existing schemes. Our clustering approach also identifies traces of a convergent evolutionary process for TNFLs and TNFRs, leading us to propose the co-evolution of TNFLs and the third cysteine rich domain (CRD) of large TNFRs.

Transcript profiling of jasmonate-elicited Taxus cells reveals a ß-phenylalanine-CoA ligase.

Plant cell cultures constitute eco-friendly biotechnological platforms for the production of plant secondary metabolites with pharmacological activities, as well as a suitable system for extending our knowledge of secondary metabolism. Despite the high added value of taxol and the importance of taxanes as anticancer compounds, several aspects of their biosynthesis remain unknown. In this work, a genomewide expression analysis of jasmonate-elicited Taxus baccata cell cultures by complementary DNA-amplified fragment length polymorphism (cDNA-AFLP) indicated a correlation between an extensive elicitor-induced genetic reprogramming and increased taxane production in the targeted cultures. Subsequent in silico analysis allowed us to identify 15 genes with a jasmonate-induced differential expression as putative candidates for genes encoding enzymes involved in five unknown steps of taxane biosynthesis. Among them, the TB768 gene showed a strong homology, including a very similar predicted 3D structure, with other genes previously reported to encode acyl-CoA ligases, thus suggesting a role in the formation of the taxol lateral chain. Functional analysis confirmed that the TB768 gene encodes an acyl-CoA ligase that localizes to the cytoplasm and is able to convert ß-phenylalanine, as well as coumaric acid, into their respective derivative CoA esters. ß-phenylalanyl-CoA is attached to baccatin III in one of the last steps of the taxol biosynthetic pathway. The identification of this gene will contribute to the establishment of sustainable taxol production systems through metabolic engineering or synthetic biology approaches.

SARA-Coffee web server, a tool for the computation of RNA sequence and structure multiple alignments.

This article introduces the SARA-Coffee web server; a service allowing the online computation of 3D structure based multiple RNA sequence alignments. The server makes it possible to combine sequences with and without known 3D structures. Given a set of sequences SARA-Coffee outputs a multiple sequence alignment along with a reliability index for every sequence, column and aligned residue. SARA-Coffee combines SARA, a pairwise structural RNA aligner with the R-Coffee multiple RNA aligner in a way that has been shown to improve alignment accuracy over most sequence aligners when enough structural data is available. The server can be accessed from http://tcoffee.crg.cat/apps/tcoffee/do:saracoffee.

CARMEN, a human super enhancer-associated long noncoding RNA controlling cardiac specification, differentiation and homeostasis.

Long noncoding RNAs (lncRNAs) are emerging as important regulators of developmental pathways. However, their roles in human cardiac precursor cell (CPC) remain unexplored. To characterize the long noncoding transcriptome during human CPC cardiac differentiation, we profiled the lncRNA transcriptome in CPCs isolated from the human fetal heart and identified 570 lncRNAs that were modulated during cardiac differentiation. Many of these were associated with active cardiac enhancer and super enhancers (SE) with their expression being correlated with proximal cardiac genes. One of the most upregulated lncRNAs was a SE-associated lncRNA that was named CARMEN, (CAR)diac (M)esoderm (E)nhancer-associated (N)oncoding RNA. CARMEN exhibits RNA-dependent enhancing activity and is upstream of the cardiac mesoderm-specifying gene regulatory network. Interestingly, CARMEN interacts with SUZ12 and EZH2, two components of the polycomb repressive complex 2 (PRC2). We demonstrate that CARMEN knockdown inhibits cardiac specification and differentiation in cardiac precursor cells independently of MIR-143 and -145 expression, two microRNAs located proximal to the enhancer sequences. Importantly, CARMEN expression was activated during pathological remodeling in the mouse and human hearts, and was necessary for maintaining cardiac identity in differentiated cardiomyocytes. This study demonstrates therefore that CARMEN is a crucial regulator of cardiac cell differentiation and homeostasis.