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Little is known about the prevalence, functionality and ecological roles of temperate phages for members of the mycolic acid producing bacteria, the Mycolata. While many lytic phages infective for these organisms have been isolated, and assessed for their suitability for use as biological control agents of activated sludge foaming, no studies have investigated how temperate phages might be induced for this purpose. Bioinformatic analysis using the PHAge Search Tool (PHAST) on Mycolata whole genome sequence data in GenBank for members of the genera Gordonia, Mycobacterium, Nocardia, Rhodococcus, and Tsukamurella revealed 83% contained putative prophage DNA sequences. Subsequent prophage inductions using mitomycin C were conducted on 17 Mycolata strains. This led to the isolation and genome characterization of three novel Caudovirales temperate phages, namely GAL1, GMA1, and TPA4, induced from Gordonia alkanivorans, Gordonia malaquae, and Tsukamurella paurometabola, respectively. All possessed highly distinctive dsDNA genome sequences.

Cutibacterium acnes (C. acnes) is a gram-positive bacterium and a member of the human skin microbiome. Despite being the most abundant skin commensal, certain members have been associated with common inflammatory disorders such as acne vulgaris. The availability of the complete genome sequences from various C. acnes clades have enabled the identification of putative methyltransferases, some of them potentially belonging to restriction-modification (R-M) systems which protect the host of invading DNA. However, little is known on whether these systems are functional in the different C. acnes strains. To investigate the activity of these putative R-M and their relevance in host protective mechanisms, we analyzed the methylome of six representative C. acnes strains by Oxford Nanopore Technologies (ONT) sequencing. We detected the presence of a 6-methyladenine modification at a defined DNA consensus sequence in strain KPA171202 and recombinant expression of this R-M system confirmed its methylation activity. Additionally, a R-M knockout mutant verified the loss of methylation properties of the strain. We studied the potential of one C. acnes bacteriophage (PAD20) in killing various C. acnes strains and linked an increase in its specificity to phage DNA methylation acquired upon infection of a methylation competent strain. We demonstrate a therapeutic application of this mechanism where phages propagated in R-M deficient strains selectively kill R-M deficient acne-prone clades while probiotic ones remain resistant to phage infection.

The NRC immune receptor network has evolved in asterid plants from a pair of linked genes into a genetically dispersed and phylogenetically structured network of sensor and helper NLR (nucleotide-binding domain and leucine-rich repeat-containing) proteins. In some species, such as the model plant Nicotiana benthamiana and other Solanaceae, the NRC (NLR-REQUIRED FOR CELL DEATH) network forms up to half of the NLRome, and NRCs are scattered throughout the genome in gene clusters of varying complexities. Here, we describe NRCX, an atypical member of the NRC family that lacks canonical features of these NLR helper proteins, such as a functional N-terminal MADA motif and the capacity to trigger autoimmunity. In contrast to other NRCs, systemic gene silencing of NRCX in N. benthamiana markedly impairs plant growth resulting in a dwarf phenotype. Remarkably, dwarfism of NRCX silenced plants is partially dependent on NRCX paralogs NRC2 and NRC3, but not NRC4. Despite its negative impact on plant growth when silenced systemically, spot gene silencing of NRCX in mature N. benthamiana leaves doesn’t result in visible cell death phenotypes. However, alteration of NRCX expression modulates the hypersensitive response mediated by NRC2 and NRC3 in a manner consistent with a negative role for NRCX in the NRC network. We conclude that NRCX is an atypical member of the NRC network that has evolved to contribute to the homeostasis of this genetically unlinked NLR network.

The cytoplasmic polyadenylation element-binding protein Orb2 is a key regulator of long-term memory (LTM) in Drosophila. The N-terminus of the Orb2 isoform A is required for LTM and forms cross-β fibrils on its own. However, this N-terminus is not part of the core found in ex vivo fibrils. We previously showed that besides forming cross-β fibrils, the N-terminus of Orb2A binds anionic lipid membranes as an amphipathic helix. Here, we show that the Orb2A N-terminus can similarly interact with calcium activated calmodulin (CaM) and that this interaction prevents fibril formation. Because CaM is a known regulator of LTM, this interaction could potentially explain the regulatory role of Orb2A in LTM.

Transcription factors are regulatory proteins known to modulate gene expression. These are the critical component of signaling pathways and help in mitigating various developmental and stress responses. Among them, bZIP, BBR, and BZR transcription factor families are well known to play a crucial role in regulating growth, development, and defense responses. However, limited data is available on these transcription factors in Triticum aestivum. In this study, bZIP, BBR, and BZR sequences from Brachypodium distachyon, Oryza sativa, Oryza barthii, Oryza brachyantha, T. aestivum, Triticum urartu, Sorghum bicolor, Zea mays were retrieved, and dendrograms were constructed to analyze the evolutionary relatedness among them. The sequences clustered into one group indicated a degree of evolutionary correlation highlighting the common lineage of cereal grains. This analysis also exhibited that these genes were highly conserved among studied monocots emphasizing their common ancestry. Furthermore, these transcription factor genes were evaluated for envisaging conserved motifs, gene structure, and subcellular localization in T. aestivum. This comprehensive computational analysis has provided an insight into transcription factor evolution that can also be useful in developing approaches for future functional characterization of these genes in T. aestivum. Furthermore, the data generated can be beneficial in future for genetic manipulation of economically important plants.

© 2021 Ellis et al., Aberrant repair of DNA double-strand breaks can recombine distant chromosomal breakpoints. Chromosomal rearrangements compromise genome function and are a hallmark of ageing. Rearrangements are challenging to detect in non-dividing cell populations, because they reflect individually rare, heterogeneous events. The genomic distribution of de novo rearrangements in non-dividing cells, and their dynamics during ageing, remain therefore poorly characterized. Studies of genomic instability during ageing have focussed on mitochondrial DNA, small genetic variants, or proliferating cells. To characterize genome rearrangements during cellular ageing in non-dividing cells, we interrogated a single diagnostic measure, DNA breakpoint junctions, using Schizosaccharomyces pombe as a model system. Aberrant DNA junctions that accumulated with age were associated with microhomology sequences and R-loops. Global hotspots for age-associated breakpoint formation were evident near telomeric genes and linked to remote breakpoints elsewhere in the genome, including the mitochondrial chromosome. Formation of breakpoint junctions at global hotspots was inhibited by the Sir2 histone deacetylase and might be triggered by an age-dependent de-repression of chromatin silencing. An unexpected mechanism of genomic instability may cause more local hotspots: age-associated reduction in an RNA-binding protein triggering R-loops at target loci. This result suggests that biological processes other than transcription or replication can drive genome rearrangements. Notably, we detected similar signatures of genome rearrangements that accumulated in old brain cells of humans. These findings provide insights into the unique patterns and possible mechanisms of genome rearrangements in non-dividing cells, which can be promoted by ageing-related changes in gene-regulatory proteins., This research was funded by a BBSRC-DTP studentship to DAE (London Interdisciplinary Doctoral Programme) [grant number BB/M009513/1] funded by the Biotechnology and Biological Sciences Research Council (https://bbsrc.ukri.org/); a Wellcome Senior Investigator Award to JB [grant number 095598/Z/11/Z] funded by the Wellcome Trust (https://wellcome.org/); and Medical Research Council funding to SM (https://mrc.ukri.org/).

Ginger (Zingiber officinale Rosc.) is an economically important and valuable spice crop around the world. It is used as food, spice, condiment, and medicine. A considerable extent of genetic diversity in ginger occurs in the Western Ghats and North-Eastern India. However, genetic diversity studies at the molecular level in ginger is limited due to limited availability of genetic and genomic information. In the present study, for the first time, we have identified and validated expressed sequence tag (EST)-simple sequence repeat (SSR) markers from ginger. We obtained 16,790 EST-SSR loci from 78987 unigenes, and 4597 SSR loci in the predicted 76929 coding sequences from RNA-Seq assembled contigs of ginger through Illumina paired-end sequencing. Gene ontology results indicate that the unigenes with SSR loci participate in various biological processes such as metabolism, growth, and development in ginger. One hundred and twenty-five primer pairs were designed from unigenes and coding sequences. These primers were tested for PCR optimization, characterization, and amplification and identified 12 novel EST-SSR markers. Twelve flanking polymorphic EST-SSR primers were validated using 48 ginger genotypes representing North-Eastern India and different eco-geographical adaptations by PCR amplification and allele sizing through capillary electrophoresis. Twelve EST-SSR primers generated a total of 111 alleles with an average of 9.25 alleles per locus and allele sizes ranging between 115-189bp. This study implies that the SSR markers designed from transcriptome sequences provides ample EST-SSR resources, which are helpful for genetic diversity analysis of Zingiberaceae species and molecular verification of ginger genotypes.

Reverse vaccinology is an evolving approach for improving vaccine effectiveness and minimizing adverse responses by limiting immunizations to critical epitopes. Towards this goal, we sought to identify immunogenic amino acid motifs and linear epitopes of the SARS-CoV-2 spike protein that elicit IgG in COVID-19 mRNA vaccine recipients. Paired pre/post vaccination samples from N=20 healthy adults, and post-vaccine samples from an additional N=13 individuals were used to immunoprecipitate IgG targets expressed by a bacterial display random peptide library, and preferentially recognized peptides were mapped to the spike primary sequence. The data identify several distinct amino acid motifs recognized by vaccine-induced IgG, a subset of those targeted by IgG from natural infection, which may mimic 3-dimensional conformation (mimotopes). Dominant linear epitopes were identified in the C-terminal domains of the S1 and S2 subunits (aa 558-569, 627-638, and 1148-1159) which have been previously associated with SARS-CoV-2 neutralization in vitro and demonstrate identity to bat coronavirus and SARS-CoV, but limited homology to non-pathogenic human coronavirus. The identified COVID-19 mRNA vaccine epitopes should be considered in the context of variants, immune escape and vaccine and therapy design moving forward.

Fsv1/Stx8 is a Schizosaccharomyces pombe protein similar to mammalian syntaxin 8. stx8Δ cells are sensitive to salts, and the prevacuolar endosome (PVE) is altered in stx8Δ cells. These defects depend on the SNARE domain, data that confirm the conserved function of syntaxin8 and Stx8 in vesicle fusion at the PVE. Stx8 localizes at the trans-Golgi network (TGN) and the prevacuolar endosome (PVE), and its recycling depends on the retromer component Vps35, and on the sorting nexins Vps5, Vps17, and Snx3. Several experimental approaches demonstrate that Stx8 is a cargo of the Snx3-retromer. Using extensive truncation and alanine scanning mutagenesis, we identified the Stx8 sorting signal. This signal is an IEMeaM sequence that is located in an unstructured protein region, must be distant from the transmembrane (TM) helix, and where the 133I, 134E, 135M, and 138M residues are all essential for recycling. This sorting motif is different from those described for most retromer cargoes, which include aromatic residues, and resembles the sorting motif of mammalian polycystin-2 (PC2). Comparison of Stx8 and PC2 motifs leads to an IEMxx(I/M) consensus. Computer-assisted screening for this and for a loose Ψ(E/D)ΨXXΨ motif (where Ψ is a hydrophobic residue with large aliphatic chain) shows that syntaxin 8 and PC2 homologues from other organisms bear variation of this motif. The phylogeny of the Stx8 sorting motifs from the Schizosaccharomyces species shows that their divergence is similar to that of the genus, showing that they have undergone evolutionary divergence. A preliminary analysis of the motifs in syntaxin 8 and PC2 sequences from various organisms suggests that they might have also undergone evolutionary divergence, what suggests that the presence of almost-identical motifs in Stx8 and PC2 might be a case of convergent evolution., Author summary Eukaryotes possess membranous intracellular compartments, whose communication is essential for cellular homeostasis. Protein complexes that facilitate the generation, transport, and fusion of coated vesicles mediate this communication. Since alterations in these processes lead to human disease, their characterization is of biological and medical interest. Retromer is a protein complex that facilitates retrograde trafficking from the prevacuolar endosome to the Golgi, being essential for the functionality of the endolysosomal system. SNAREs are required for vesicle fusion and, after facilitating membrane merging, are supposed to return to their donor organelle for new rounds of fusion. However, little is known about this recycling. We have found that Stx8, a fungal SNARE similar to human syntaxin 8, is a retromer cargo, and have identified its retromer binding motif. Sequence screening and comparison has determined that this sorting motif is conserved mainly in fungal Stx8 sequences. Notably, this motif is similar to the retromer sorting motif that is present in a family of vertebrate ion transporters. Our initial phylogenetic analyses suggest that, although retromer and some of its cargoes are conserved, the sorting motif in the cargoes might have undergone evolutionary divergence.

Candida albicans, an opportunistic fungal pathogen, is a significant cause of human infections, particularly in immunocompromised individuals. Phenotypic plasticity between two morphological phenotypes, yeast and hyphae, is a key mechanism by which C. albicans can thrive in many microenvironments and cause disease in the host. Understanding the decision points and key driver genes controlling this important transition and how these genes respond to different environmental signals is critical to understanding how C. albicans causes infections in the host. Here we build and analyze a Boolean dynamical model of the C. albicans yeast to hyphal transition, integrating multiple environmental factors and regulatory mechanisms. We validate the model by a systematic comparison to prior experiments, which led to agreement in 17 out of 22 cases. The discrepancies motivate alternative hypotheses that are testable by follow-up experiments. Analysis of this model revealed two time-constrained windows of opportunity that must be met for the complete transition from the yeast to hyphal phenotype, as well as control strategies that can robustly prevent this transition. We experimentally validate two of these control predictions in C. albicans strains lacking the transcription factor UME6 and the histone deacetylase HDA1, respectively. This model will serve as a strong base from which to develop a systems biology understanding of C. albicans morphogenesis., Author summary Candida albicans is a pathogenic organism that commonly causes infection in humans, particularly in immunocompromised individuals, and patients in hospitals. A key mechanism mediating its infectiousness is a morphological change from single yeast cells into branching cell collectives called hyphae. C. albicans cells undergo this transition in response to multiple environmental signals, including pH, temperature, serum levels, or other molecules. Understanding how the cells process these environmental signals is critical to understanding how C. albicans adapts to thrive in human hosts. Here, we built and analyzed a mathematical model of the C. albicans yeast to hyphal transition, integrating multiple environmental factors and regulatory mechanisms. Analysis of this model revealed two time-constrained windows of opportunity that must be met for the complete transition from the yeast to hyphal phenotype. We probed this model to identify interventional control strategies that can block the transition. We experimentally validate two of these control predictions: deletion of the transcription factor UME6, and deletion of the histone deacetylase HDA1. This model can be used to identify alternative hypotheses, enabling progress toward a systems biology understanding of C. albicans morphological changes.

DNA replication complexes (replisomes) frequently encounter barriers that can eject them prematurely from the genome. To avoid the lethality of incomplete DNA replication that arises from these events, bacteria have evolved “DNA replication restart” mechanisms to reload replisomes onto abandoned replication forks. The Escherichia coli PriA DNA helicase orchestrates this process by recognizing and remodeling replication forks and recruiting additional proteins that help to drive replisome reloading. We have identified a conserved sequence motif within a linker region of PriA that docks into a groove on the exterior of the PriA helicase domain. Alterations to the motif reduce the apparent processivity and attenuate structure-specific helicase activity in PriA, implicating the motif as a potential autoregulatory element in replication fork processing. The study also suggests that multiple PriA molecules may function in tandem to enhance DNA unwinding processivity, highlighting an unexpected similarity between PriA and other DNA helicases.

We report a new subgroup of Type III Restriction-Modification systems that use m4C methylation for host protection. Recognition specificities for six such systems, each recognizing a novel motif, have been determined using single molecule real-time DNA sequencing. In contrast to all previously characterized Type III systems which modify adenine to m6A, protective methylation of the host genome in these new systems is achieved by the N4-methylation of a cytosine base in one strand of an asymmetric 4 to 6 base pair recognition motif. Type III systems are heterotrimeric enzyme complexes containing a single copy of an ATP-dependent restriction endonuclease-helicase (Res) and a dimeric DNA methyltransferase (Mod). The Type III Mods are beta-class amino-methyltransferases, examples of which form either N6-methyl adenine or N4-methyl cytosine in Type II RM systems. The Type III m4C Mod and Res proteins are diverged, suggesting ancient origin or that m4C modification has arisen from m6A MTases multiple times in diverged lineages. Two of the systems, from thermophilic organisms, required expression of both Mod and Res to efficiently methylate an E. coli host, unlike previous findings that Mod alone is proficient at modification, suggesting that the division of labor between protective methylation and restriction activities is atypical in these systems. Two of the characterized systems, and many homologous putative systems, appear to include a third protein; a conserved putative helicase/ATPase subunit of unknown function and located 5’ of the mod gene. The function of this additional ATPase is not yet known, but close homologs co-localize with the typical Mod and Res genes in hundreds of putative Type III systems. Our findings demonstrate a rich diversity within Type III RM systems.

Nidoviruses and arenaviruses are the only known RNA viruses encoding a 3’-5’ exonuclease domain (ExoN). The proofreading activity of the ExoN domain has played a key role in the growth of nidoviral genomes, while in arenaviruses this domain partakes in the suppression of the host innate immune signaling. Sequence and structural homology analyses suggest that these proteins have been hijacked from cellular hosts many times. Analysis of the available nidoviral ExoN sequences reveals a high conservation level comparable to that of the viral RNA-dependent RNA polymerases (RdRp), which are the most conserved viral proteins. Two highly preserved zinc fingers are present in all nidoviral exonucleases, while in the arenaviral protein only one zinc finger can be identified. This is in sharp contrast with the reported lack of zinc fingers in cellular ExoNs, and opens the possibility of therapeutic strategies in the struggle against COVID-19.

ELAV/Hu factors are conserved RNA binding proteins (RBPs) that play diverse roles in mRNA processing and regulation. The founding member, Drosophila Elav, was recognized as a vital neural factor 35 years ago. Nevertheless, little was known about its impacts on the transcriptome, and potential functional overlap with its paralogs. Building on our recent findings that neural-specific lengthened 3’ UTR isoforms are co-determined by ELAV/Hu factors, we address their impacts on splicing. While only a few splicing targets of Drosophila are known, ectopic expression of each of the three family members (Elav, Fne and Rbp9) alters hundreds of cassette exon and alternative last exon (ALE) splicing choices. Reciprocally, double mutants of elav/fne, but not elav alone, exhibit opposite effects on both classes of regulated mRNA processing events in larval CNS. While manipulation of Drosophila ELAV/Hu RBPs induces both exon skipping and inclusion, characteristic ELAV/Hu motifs are enriched only within introns flanking exons that are suppressed by ELAV/Hu factors. Moreover, the roles of ELAV/Hu factors in global promotion of distal ALE splicing are mechanistically linked to terminal 3’ UTR extensions in neurons, since both processes involve bypass of proximal polyadenylation signals linked to ELAV/Hu motifs downstream of cleavage sites. We corroborate the direct action of Elav in diverse modes of mRNA processing using RRM-dependent Elav-CLIP data from S2 cells. Finally, we provide evidence for conservation in mammalian neurons, which undergo broad programs of distal ALE and APA lengthening, linked to ELAV/Hu motifs downstream of regulated polyadenylation sites. Overall, ELAV/Hu RBPs orchestrate multiple broad programs of neuronal mRNA processing and isoform diversification in Drosophila and mammalian neurons., Author summary ELAV/Hu factors comprise a conserved family of RNA binding proteins (RBPs), many of which are enriched or restricted to neurons. This study shows that overlapping activities of Drosophila ELAV/Hu RBPs determine global patterns of neural alternative splicing, including of cassette exons and alternative last exon (ALE) isoforms. This is supported by both genetic necessity in double mutant CNS, as well as their sufficiency to drive these mRNA processing changes in a non-neuronal setting. The ability of ELAV/Hu RBPs to induce the usage of distal ALE isoforms connects to their recently described functions in global extension of 3’UTRs in neural isoforms. Evidence is provided that switching to distal alternative last exons and to terminal 3’ UTR extensions are also coordinated in mammalian neurons, and show signatures of direct regulation by ELAV/Hu RBPs.

With the increasing ability to use high-throughput next-generation sequencing to quantify the diversity of the human T cell receptor (TCR) repertoire, the ability to use TCR sequences to infer antigen-specificity could greatly aid potential diagnostics and therapeutics. Here, we use a machine-learning approach known as Restricted Boltzmann Machine to develop a sequence-based inference approach to identify antigen-specific TCRs. Our approach combines probabilistic models of TCR sequences with clone abundance information to extract TCR sequence motifs central to an antigen-specific response. We use this model to identify patient personalized TCR motifs that respond to individual tumor and infectious disease antigens, and to accurately discriminate specific from non-specific responses. Furthermore, the hidden structure of the model results in an interpretable representation space where TCRs responding to the same antigen cluster, correctly discriminating the response of TCR to different viral epitopes. The model can be used to identify condition specific responding TCRs. We focus on the examples of TCRs reactive to candidate neoantigens and selected epitopes in experiments of stimulated TCR clone expansion., Author summary Large repertoires of immune cells, such as T cells, are increasingly made available by high-throughput sequencing. Exploiting such datasets to infer how T cells respond to antigens could help design vaccines and adoptive T-cell therapies. We here propose an approach based on probabilistic machine learning to identify and characterize responding T cells. After learning, this approach is able to distinguish clones that specifically respond to different antigen stimulations. The model parameters and the low-dimensional representations of the T-cell sequences identify sequence motifs underlying T-cell recognition at the molecular level. The approach is illustrated on repertoire data describing in vitro stimulation of T cells by cancer-related neoantigens, as well as on data for common infectious diseases.

23 p.-5 fig.-2 tab., Antibiotic resistance is a serious global problem. Antibiotic resistance genes (ARG), which are widespread in environmental bacteria, can be transferred to pathogenic bacteria via horizontal gene transfer (HGT). Gut microbiomes are especially apt for the emergence and dissemination of ARG. Conjugation is the HGT route that is predominantly responsible for the spread of ARG. Little is known about conjugative elements of Gram-positive bacteria, including those of the phylum Firmicutes, which are abundantly present in gut microbiomes. A critical step in the conjugation process is the relaxase-mediated site-and strand-specific nick in the oriT region of the conjugative element. This generates a single-stranded DNA molecule that is transferred from the donor to the recipient cell via a connecting channel. Here we identified and characterized the relaxosome components oriT and the relaxase of the conjugative plasmid pLS20 of the Firmicute Bacillus subtilis. We show that the relaxase gene, named rel(LS20), is essential for conjugation, that it can function in trans and provide evidence that Tyr26 constitutes the active site residue. In vivo and in vitro analyses revealed that the oriT is located far upstream of the relaxase gene and that the nick site within oriT is located on the template strand of the conjugation genes. Surprisingly, the Rel(LS20) shows very limited similarity to known relaxases. However, more than 800 genes to which no function had been attributed so far are predicted to encode proteins showing significant similarity to RelLS20. Interestingly, these putative relaxases are encoded almost exclusively in Firmicutes bacteria. Thus, RelLS20 constitutes the prototype of a new family of relaxases. The identification of this novel relaxase family will have an important impact in different aspects of future research in the field of HGT in Gram-positive bacteria in general, and specifically in the phylum of Firmicutes, and in gut microbiome research., Work in the Meijer lab was funded by the Spanish government through grant Bio2013- 41489-P of the Ministry of Economy and Competitiveness, and through grant Bio2016- 77883-C2-1-P of the Ministry of Economy, Industry and Competitiveness; the former grant also funded AMA and CGC. The Spanish government also supported DRB, JRLO, and CA.DRB was funded by grant Bio2016-77883-C2-2-P of the Ministry of Economy, Industry and Competitiveness, and JRLO and CA were supported by grant BFU2014-52070-C2-2-P of the Ministry of Economy and Competitiveness to CA.LJW's work was supported by Wellcome Trust grant WT098374AIA to Jeff Errington.

Potato (Solanum tuberosum L.) is an important food crop that is grown and consumed worldwide. The growth and productivity of this crop are severely affected by various abiotic stresses. Basic leucine zipper (bZIP) transcription factors (TFs) in plants are well known for their function during growth and development. However, systematic and in-depth identification and functional characterization of the bZIP gene family of potato is lacking. In the current study, we identified a total of 90 bZIPs (StbZIP) distributed on 12 linkage groups of potato. Based on the previous functional annotation and classification of bZIPs in Arabidopsis, wheat, and rice, a phylogenetic tree of potato bZIPs was constructed and genes were categorized into various functional groups (A to I, S, and U) as previously annotated in Arabidopsis thaliana. Analyses of the transcript sequence (RNA-seq) data led to identifying a total of 18 candidate StbZIPs [four in roots, eight in the tuber, six in mesocarp and endocarp] that were expressed in a tissue-specific manner. Differential expression analysis under the various abiotic conditions (salt, mannitol, water, and heat stress) and treatment with phytohormones (ABA, GA, IAA, and BAP) led to the identification of forty-two [thirteen under salt stress, two under mannitol stress, ten under water stress, and eighteen under heat stress], and eleven [eight and three StbZIPs upon treatment with ABA, and IAA, respectively] candidate StbZIPs, respectively. Using sequence information of candidate StbZIPs, a total of 22 SSR markers were also identified in this study. In conclusion, the genome-wide identification analysis coupled with RNA-Seq expression data led to identifying candidate StbZIPs, which are dysregulated, and may play a pivotal role under various abiotic stress conditions. This study will pave the way for future functional studies using forward and reverse genetics to improve abiotic stress tolerance in potato.

Dirigent-jacalin (D-J) genes belong to the plant chimeric lectin family, and play vital roles in plant growth and resistance to abiotic and biotic stresses. To explore the functions of the D-J family in the growth and development of Moso bamboo (Phyllostachys edulis), their physicochemical properties, phylogenetic relationships, gene and protein structures, and expression patterns were analyzed in detail. Four putative PeD-J genes were identified in the Moso bamboo genome, and microsynteny and phylogenetic analyses indicated that they represent a new branch in the evolution of plant lectins. PeD-J proteins were found to be composed of a dirigent domain and a jacalin-related lectin domain, each of which contained two different motifs. Multiple sequence alignment and homologous modeling analysis indicated that the three-dimensional structure of the PeD-J proteins was significantly different compared to other plant lectins, primarily due to the tandem dirigent and jacalin domains. We surveyed the upstream putative promoter regions of the PeD-Js and found that they mainly contained cis-acting elements related to hormone and abiotic stress response. An analysis of the expression patterns of root, leaf, rhizome and panicle revealed that four PeD-J genes were highly expressed in the panicle, indicating that they may be required during the formation and development of several different tissue types in Moso bamboo. Moreover, PeD-J genes were shown to be involved in the rapid growth and development of bamboo shoots. Quantitative Real-time PCR (qRT PCR) assays further verified that D-J family genes were responsive to hormones and stresses. The results of this study will help to elucidate the biological functions of PeD-Js during bamboo growth, development and stress response.

Pathogens that infect plants and animals use a diverse arsenal of effector proteins to suppress the host immune system and promote infection. Identification of effectors in pathogen genomes is foundational to understanding mechanisms of pathogenesis, for monitoring field pathogen populations, and for breeding disease resistance. We identified candidate effectors from the lettuce downy mildew pathogen Bremia lactucae by searching the predicted proteome for the WY domain, a structural fold found in effectors that has been implicated in immune suppression as well as effector recognition by host resistance proteins. We predicted 55 WY domain containing proteins in the genome of B. lactucae and found substantial variation in both sequence and domain architecture. These candidate effectors exhibit several characteristics of pathogen effectors, including an N-terminal signal peptide, lineage specificity, and expression during infection. Unexpectedly, only a minority of B. lactucae WY effectors contain the canonical N-terminal RXLR motif, which is a conserved feature in the majority of cytoplasmic effectors reported in Phytophthora spp. Functional analysis of 21 effectors containing WY domains revealed 11 that elicited cell death on wild accessions and domesticated lettuce lines containing resistance genes, indicative of recognition of these effectors by the host immune system. Only two of the 11 recognized effectors contained the canonical RXLR motif, suggesting that there has been an evolutionary divergence in sequence motifs between genera; this has major consequences for robust effector prediction in oomycete pathogens., Author summary There is a molecular battle that takes place during infection of plants and animals by pathogens. Some of the weapons in the pathogen’s arsenal are known as “effectors;” these are secreted proteins that enter host cells to alter their physiology and suppress the immune system. Effectors can also be a liability for pathogens because potential hosts have evolved ways to recognize these effectors, triggering a defense response leading to localized cell death, preventing the spread of the pathogen. Here we computationally predicted effectors encoded in the genome of Bremia lactucae, the pathogen causing the downy mildew disease of lettuce and tested 21 of these proteins in the lab to see what effects they would have on the host plant. Five effectors were demonstrated to suppress the basal immune system of lettuce. Eleven effectors caused programmed cell death when introduced to certain lettuce lines, which indicates recognition of these proteins by the host immune system. In addition to contributing to our understanding of the mechanisms of pathogenesis, this study of effectors facilitates breeding for disease resistant lettuce, which will decrease agricultural reliance on fungicides.

Long regulatory elements (LREs), such as CpG islands, polydA:dT tracts or AU-rich elements, are thought to play key roles in gene regulation but, as opposed to conventional binding sites of transcription factors, few methods have been proposed to formally and automatically characterize them. We present here a computational approach named DExTER (Domain Exploration To Explain gene Regulation) dedicated to the identification of candidate LREs (cLREs) and apply it to the analysis of the genomes of P. falciparum and other eukaryotes. Our analyses show that all tested genomes contain several cLREs that are somewhat conserved along evolution, and that gene expression can be predicted with surprising accuracy on the basis of these long regions only. Regulation by cLREs exhibits very different behaviours depending on species and conditions. In P. falciparum and other Apicomplexan organisms as well as in Dictyostelium discoideum, the process appears highly dynamic, with different cLREs involved at different phases of the life cycle. For multicellular organisms, the same cLREs are involved in all tissues, but a dynamic behavior is observed along embryonic development stages. In P. falciparum, whose genome is known to be strongly depleted of transcription factors, cLREs are predictive of expression with an accuracy above 70%, and our analyses show that they are associated with both transcriptional and post-transcriptional regulation signals. Moreover, we assessed the biological relevance of one LRE discovered by DExTER in P. falciparum using an in vivo reporter assay. The source code (python) of DExTER is available at https://gite.lirmm.fr/menichelli/DExTER., Author summary Gene expression is regulated at different levels and by different mechanisms in Eukaryotes. At the DNA level, transcription factors (TFs) are supposed to play a key role by binding short motifs in promoters or enhancers. In Plasmodium falciparum, the causative agent of severe malaria in humans, different levels of gene regulation are also present, but very few TFs have been identified and validated so far. We propose here a computational method for the identification of a new type of regulatory elements called long regulatory elements (LRE). Contrary to TF motifs, that are usually 6-12bp long, LREs may span dozens or hundreds of base pairs. Moreover, no computational method have been specifically dedicated to their identification until now. We show with our method that, depending on species and conditions, LREs may play important role in gene regulation. For P. falciparum, these elements appear to determine a very large part of gene expression variation in all stages of the parasite life cycle.

In response to stimuli, biological processes are tightly controlled by dynamic cellular signaling mechanisms. Reversible protein phosphorylation occurs on rapid time-scales (milliseconds to seconds), making it an ideal carrier of these signals. Advances in mass spectrometry-based proteomics have led to the identification of many tens of thousands of phosphorylation sites, yet for the majority of these the kinase is unknown and the underlying network topology of signaling networks therefore remains obscured. Identifying kinase substrate relationships (KSRs) is therefore an important goal in cell signaling research. Existing consensus sequence motif based prediction algorithms do not consider the biological context of KSRs, and are therefore insensitive to many other mechanisms guiding kinase-substrate recognition in cellular contexts. Here, we use temporal information to identify biologically relevant KSRs from Large-scale In Vivo Experiments (KSR-LIVE) in a data-dependent and automated fashion. First, we used available phosphorylation databases to construct a repository of existing experimentally-predicted KSRs. For each kinase in this database, we used time-resolved phosphoproteomics data to examine how its substrates changed in phosphorylation over time. Although substrates for a particular kinase clustered together, they often exhibited a different temporal pattern to the phosphorylation of the kinase. Therefore, although phosphorylation regulates kinase activity, our findings imply that substrate phosphorylation likely serve as a better proxy for kinase activity than kinase phosphorylation. KSR-LIVE can thereby infer which kinases are regulated within a biological context. Moreover, KSR-LIVE can also be used to automatically generate positive training sets for the subsequent prediction of novel KSRs using machine learning approaches. We demonstrate that this approach can distinguish between Akt and Rps6kb1, two kinases that share the same linear consensus motif, and provide evidence suggesting IRS-1 S265 as a novel Akt site. KSR-LIVE is an open-access algorithm that allows users to dissect phosphorylation signaling within a specific biological context, with the potential to be included in the standard analysis workflow for studying temporal high-throughput signal transduction data.

Animals display characteristic behavioural patterns when performing a task, such as the spiraling of a soaring bird or the surge-and-cast of a male moth searching for a female. Identifying such recurring sequences occurring rarely in noisy behavioural data is key to understanding the behavioural response to a distributed stimulus in unrestrained animals. Existing models seek to describe the dynamics of behaviour or segment individual locomotor episodes rather than to identify the rare and transient sequences of locomotor episodes that make up the behavioural response. To fill this gap, we develop a lexical, hierarchical model of behaviour. We designed an unsupervised algorithm called “BASS” to efficiently identify and segment recurring behavioural action sequences transiently occurring in long behavioural recordings. When applied to navigating larval zebrafish, BASS extracts a dictionary of remarkably long, non-Markovian sequences consisting of repeats and mixtures of slow forward and turn bouts. Applied to a novel chemotaxis assay, BASS uncovers chemotactic strategies deployed by zebrafish to avoid aversive cues consisting of sequences of fast large-angle turns and burst swims. In a simulated dataset of soaring gliders climbing thermals, BASS finds the spiraling patterns characteristic of soaring behaviour. In both cases, BASS succeeds in identifying rare action sequences in the behaviour deployed by freely moving animals. BASS can be easily incorporated into the pipelines of existing behavioural analyses across diverse species, and even more broadly used as a generic algorithm for pattern recognition in low-dimensional sequential data., Author summary Animals in the wild perform characteristic motor sequences during a task, for example, the surge-and-cast of a male moth while it searches for a female or that of a soaring bird spiraling up a thermal. Such sequences recur yet occur transiently and are not easily inferred from behavioural data. How can we find recurring yet transient action sequences from noisy behavioural data without access to stimulus information? To address this question, we developed an unsupervised algorithm to extract an animal’s action sequence repertoire in a manner analogous to how young children learn language from speech. Applying this approach on larval zebrafish, we uncovered a sequence of fast large-angle turns and burst swims that fish use to escape from an aversive environment. On simulations of a soaring bird, we recovered the characteristic spiraling patterns executed by the bird during thermalling. The algorithm can be more generally used to find rare but stereotypical patterns in low-dimensional sequential data.

Proteases are an important class of enzymes, whose activity is central to many physiologic and pathologic processes. Detailed knowledge of protease specificity is key to understanding their function. Although many methods have been developed to profile specificities of proteases, few have the diversity and quantitative grasp necessary to fully define specificity of a protease, both in terms of substrate numbers and their catalytic efficiencies. We have developed a concept of “selectome”; the set of substrate amino acid sequences that uniquely represent the specificity of a protease. We applied it to two closely related members of the Matrixin family–MMP-2 and MMP-9 by using substrate phage display coupled with Next Generation Sequencing and information theory-based data analysis. We have also derived a quantitative measure of substrate specificity, which accounts for both the number of substrates and their relative catalytic efficiencies. Using these advances greatly facilitates elucidation of substrate selectivity between closely related members of a protease family. The study also provides insight into the degree to which the catalytic cleft defines substrate recognition, thus providing basis for overcoming two of the major challenges in the field of proteolysis: 1) development of highly selective activity probes for studying proteases with overlapping specificities, and 2) distinguishing targeted proteolysis from bystander proteolytic events., Author summary Proteases and proteolysis are intimately involved in virtually all biological processes from embryonic development to programmed cell death and cellular protein recycling. As the only irreversible posttranslational modification, proteolysis represents a committed step in regulation of biological networks and pathways. Imbalance of proteolytic activity has catastrophic implications and is the basis of many genetic disorders as well as a multitude of pathological states of varying etiologies. To understand protease function, one must gain insight into the repertoires of substrates targeted by these enzymes. As many proteases recognize a wide variety of sequences in proteins, it is a challenge to establish if a particular cleavage represents a targeted or a bystander proteolytic event. In addition, since many proteases have overlapping specificities, especially among closely related members of the same gene families, it is a challenge to develop highly selective tools for studying or inhibition of these enzymes. In this work, we used two closely related proteases (MMP-2 and 9) as a model system for development of an information theory-based approach to quantification of substrate specificity and demonstrated its potential for distinguishing between the target and bystander proteolytic events as well as for uncovering selectivity between closely related proteases.

Interactions between disordered proteins involve a wide range of changes in the structure and dynamics of the partners involved. These changes can be classified in terms of binding modes, which include disorder-to-order (DO) transitions, when proteins fold upon binding, as well as disorder-to-disorder (DD) transitions, when the conformational heterogeneity is maintained in the bound states. Furthermore, systematic studies of these interactions are revealing that proteins may exhibit different binding modes with different partners. Proteins that exhibit this context-dependent binding can be referred to as fuzzy proteins. Here we investigate amino acid code for fuzzy binding in terms of the entropy of the probability distribution of transitions towards decreasing order. We implement these entropy calculations into the FuzPred (http://protdyn-fuzpred.org) algorithm to predict the range of context-dependent binding modes of proteins from their amino acid sequences. As we illustrate through a variety of examples, this method identifies those binding sites that are sensitive to the cellular context or post-translational modifications, and may serve as regulatory points of cellular pathways., Author summary Great advances have been made in the last several decades in deciphering how the behavior of proteins is encoded in their amino acid sequences. A variety of sequence-based prediction methods have been developed to estimate a wide range of properties of proteins, including secondary structure propensity, native state structures, preference for being disordered and tendency to aggregate. Much less is known, however, about the rules that regulate the conformational changes of proteins upon binding. In particular, many proteins change their binding modes upon interacting with different partners, or as a consequence of post-translational modifications or changes in the cellular milieu. Here we address the problem of how amino acid sequences can encode different binding modes depending on their binding partners, and describe the FuzPred method of predicting context-dependent binding modes.

Here we provide bioinformatic evidence that the Organo-Arsenical Exporter (ArsP), Endoplasmic Reticulum Retention Receptor (KDELR), Mitochondrial Pyruvate Carrier (MPC), L-Alanine Exporter (AlaE), and the Lipid-linked Sugar Translocase (LST) protein families are members of the Transporter-Opsin-G Protein-coupled Receptor (TOG) Superfamily. These families share domains homologous to well-established TOG superfamily members, and their topologies of transmembranal segments (TMSs) are compatible with the basic 4-TMS repeat unit characteristic of this Superfamily. These repeat units tend to occur twice in proteins as a result of intragenic duplication events, often with subsequent gain/loss of TMSs in many superfamily members. Transporters within the ArsP family allow microbial pathogens to expel toxic arsenic compounds from the cell. Members of the KDELR family are involved in the selective retrieval of proteins that reside in the endoplasmic reticulum. Proteins of the MPC family are involved in the transport of pyruvate into mitochondria, providing the organelle with a major oxidative fuel. Members of family AlaE excrete L-alanine from the cell. Members of the LST family are involved in the translocation of lipid-linked glucose across the membrane. These five families substantially expand the range of substrates of transport carriers in the superfamily, although KDEL receptors have no known transport function. Clustering of protein sequences reveals the relationships among families, and the resulting tree correlates well with the degrees of sequence similarity documented between families. The analyses and programs developed to detect distant relatedness, provide insights into the structural, functional, and evolutionary relationships that exist between families of the TOG superfamily, and should be of value to many other investigators.

Intrinsically disordered regions (IDRs) are prevalent in the eukaryotic proteome. Common functional roles of IDRs include forming flexible linkers or undergoing allosteric folding-upon-binding. Recent studies have suggested an additional functional role for IDRs: generating steric pressure on the plasma membrane during endocytosis, via molecular crowding. However, in order to accomplish useful functions, such crowding needs to be regulated in space (e.g., endocytic hotspots) and time (e.g., during vesicle formation). In this work, we explore binding-induced regulation of IDR steric volume. We simulate the IDRs of two proteins from Clathrin-mediated endocytosis (CME) to see if their conformational spaces are regulated via binding-induced expansion. Using Monte-Carlo computational modeling of excluded volumes, we generate large conformational ensembles (3 million) for the IDRs of Epsin and Eps15 and dock the conformers to the alpha subunit of Adaptor Protein 2 (AP2α), their CME binding partner. Our results show that as more molecules of AP2α are bound, the Epsin-derived ensemble shows a significant increase in global dimensions, measured as the radius of Gyration (RG) and the end-to-end distance (EED). Unlike Epsin, Eps15-derived conformers that permit AP2α binding at one motif were found to be more likely to accommodate binding of AP2α at other motifs, suggesting a tendency toward co-accessibility of binding motifs. Co-accessibility was not observed for any pair of binding motifs in Epsin. Thus, we speculate that the disordered regions of Epsin and Eps15 perform different roles during CME, with accessibility in Eps15 allowing it to act as a recruiter of AP2α molecules, while binding-induced expansion of the Epsin disordered region could impose steric pressure and remodel the plasma membrane during vesicle formation., Author summary Protein functions were originally believed to arise from ordered protein structures. This dogma was later challenged by the identification of intrinsically disordered proteins that lack specific structure. The functional roles of such proteins usually fell in two categories–exploiting the disorder for flexibility (like floppy connector), or imposing order upon binding to an external partner. In this study we explore the possibility of an alternative mechanism that harnesses disorder for function through regulated molecular crowding. Specifically, we use modeling to study two proteins involved in reshaping the cell membrane, Epsin and Eps15. We ask if they undergo binding-induced expansion, where binding of an external partner AP2 causes not a transition toward order, but rather an energetically favorable increase in propensity to occupy larger volumes. Our results show that Epsin tends to occupy a larger volume when bound to AP2, consistent with increased molecular crowding, which could help reshape the cell membrane. Such regulation of disorder via binding (without folding) opens hitherto unexplored avenues that cells might employ to harness disorder.

Efficient nuclear transgene expression in the green microalga Chlamydomonas reinhardtii is generally hindered by low transcription rates. Introns can increase transcript abundance by a process called Intron-Mediated Enhancement (IME) in this alga and has been broadly observed in other eukaryotes. However, the mechanisms of IME in microalgae are poorly understood. Here, we identified 33 native introns from highly expressed genes in C. reinhardtii selected from transcriptome studies as well as 13 non-native introns. We investigated their IME capacities and probed the mechanism of action by modification of splice sites, internal sequence motifs, and position within transgenes. Several introns were found to elicit strong IME and found to be broadly applicable in different expression constructs. We determined that IME in C. reinhardtii exclusively occurs from introns within transcribed ORFs regardless of the promoter and is not induced by traditional enhancers of transcription. Our results elucidate some mechanistic details of IME in C. reinhardtii, which are similar to those observed in higher plants yet underly distinctly different induction processes. Our findings narrow the focus of targets responsible for algal IME and provides evidence that introns are underestimated regulators of C. reinhardtii nuclear gene expression., Author summary Although many genetic tools and basic transformation strategies exist for the model microalga Chlamydomonas reinhardtii, high-level genetic engineering with this organism is hindered by its inherent recalcitrance to foreign gene expression and limited knowledge of responsible expression regulators. In this work, we characterized the dynamics of 33 endogenous and 13 non-native introns and their effect on gene expression as artificial insertions into codon optimized transgenes. We found that introns from different origins have the capacity to increase gene expression rates. Intron-mediated enhancement was observed exclusively when these elements were placed in transcripts but not outside of transcribed mRNA regions. Insertion of different endogenous introns into coding sequences was found to positively affect expression rates through a synergy of additive transcription enhancement and exon length reduction, similar to those natively found in the C. reinhardtii genome. Our results indicate that intensive mRNA processing plays an underestimated role in the regulation of native gene expression in C. reinhardtii. In addition to internal sequence motifs, the location of artificially introduced introns greatly affected transgene expression levels. This work is highly valuable to the greater microalgal and synthetic biology research communities and contributes to broadening our understanding of eukaryotic intron-mediated enhancement.

The bacteriophage population is vast, dynamic, old, and genetically diverse. The genomics of phages that infect bacterial hosts in the phylum Actinobacteria show them to not only be diverse but also pervasively mosaic, and replete with genes of unknown function. To further explore this broad group of bacteriophages, we describe here the isolation and genomic characterization of 116 phages that infect Microbacterium spp. Most of the phages are lytic, and can be grouped into twelve clusters according to their overall relatedness; seven of the phages are singletons with no close relatives. Genome sizes vary from 17.3 kbp to 97.7 kbp, and their G+C% content ranges from 51.4% to 71.4%, compared to ~67% for their Microbacterium hosts. The phages were isolated on five different Microbacterium species, but typically do not efficiently infect strains beyond the one on which they were isolated. These Microbacterium phages contain many novel features, including very large viral genes (13.5 kbp) and unusual fusions of structural proteins, including a fusion of VIP2 toxin and a MuF-like protein into a single gene. These phages and their genetic components such as integration systems, recombineering tools, and phage-mediated delivery systems, will be useful resources for advancing Microbacterium genetics.

The AINTEGUMENTA-like (AIL) proteins, which belong to the AP2 family, play important roles in regulating the growth and development of plant organs. The AIL family has not yet been comprehensively studied in rapeseed (Brassica napus), an allotetraploid and model organism for the study of polyploid evolution. In the present study, 99 AIL family genes were identified and characterized from B. rapa, B. oleracea, B. napus, B. juncea, and B. nigra using a comprehensive genome-wide study, including analyses of phylogeny, gene structure, chromosomal localization, and expression pattern. Using a phylogenetic analysis, the AIL genes were divided into eight groups, which were closely related to the eight AtAIL genes, and which shared highly conserved structural features within the same subfamily. The non-synonymous/synonymous substitution ratios of the paralogs and orthologs were less than 1, suggesting that the AIL genes mainly experienced purifying selection during evolution. In addition, the RNA sequencing data and qRT-PCR analysis revealed that the B. napus AIL genes exhibited organ- and developmental stage-specific expression patterns. Certain genes were highly expressed in the developing seeds (BnaAIL1, BnaAIL2, BnaAIL5, and BnaAIL6), the roots (BnaANT, BnaAIL5, and BnaAIL6), and the stem (BnaAIL7B). Our results provide valuable information for further functional analysis of the AIL family in B. napus and related Brassica species.

Ankyrin containing proteins are one of the most abundant repeat protein families present in all extant organisms. They are made with tandem copies of similar amino acid stretches that fold into elongated architectures. Here, we built and curated a dataset of 200 thousand proteins that contain 1.2 million Ankyrin regions and characterize the abundance, structure and energetics of the repetitive regions in natural proteins. We found that there is a continuous roughly exponential variety of array lengths with an exceptional frequency at 24 repeats. We described that individual repeats are seldom interrupted with long insertions and accept few deletions, in line with the known tertiary structures. We found that longer arrays are made up of repeats that are more similar to each other than shorter arrays, and display more favourable folding energy, hinting at their evolutionary origin. The array distributions show that there is a physical upper limit to the size of an array of repeats of about 120 copies, consistent with the limit found in nature. The identity patterns within the arrays suggest that they may have originated by sequential copies of more than one Ankyrin unit. Fil: Galpern, Ezequiel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina Fil: Freiberger, Maria Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina Fil: Ferreiro, Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina

Mitogen-activated protein kinase (MAPK) is a form of serine/threonine protein kinase that activated by extracellular stimulation acting through the MAPK cascade (MAPKKK-MAPKK-MAPK). The MAPK cascade gene family, an important family of protein kinases, plays a vital role in responding to various stresses and hormone signal transduction processes in plants. In this study, we identified 14 CmMAPKs, 6 CmMAPKKs and 64 CmMAPKKKs in melon genome. Based on structural characteristics and a comparison of phylogenetic relationships of MAPK gene families from Arabidopsis, cucumber and watermelon, CmMAPKs and CmMAPKKs were categorized into 4 groups, and CmMAPKKKs were categorized into 3 groups. Furthermore, chromosome location revealed an unevenly distribution on chromosomes of MAPK cascade genes in melon, respectively. Eventually, qRT-PCR analysis showed that all 14 CmMAPKs had different expression patterns under drought, salt, salicylic acid (SA), methyl jasmonate (MeJA), red light (RL), and Podosphaera xanthii (P. xanthii) treatments. Overall, the expression levels of CmMAPK3 and CmMAPK7 under different treatments were higher than those in control. Our study provides an important basis for future functional verification of MAPK genes in regulating responses to stress and signal substance in melon.

Prenylated Rab Acceptor 1 (PRA1/Rabac1) is a four-pass transmembrane protein that has been found to localize to the Golgi and promiscuously associate with a diverse array of Rab GTPases. We have previously identified PRA1 to be among the earliest significantly down-regulated genes in the rd1 mouse model of retinitis pigmentosa, a retinal degenerative disease. Here, we show that an endogenous subpopulation of PRA1 resides within the endoplasmic reticulum (ER) at ER-mitochondria membrane contact sites in cultured mammalian cells. We also demonstrate that PRA1 contains two previously unidentified ER retention/retrieval amino acid sequences on its cytosolic N-terminal region: a membrane distal di-arginine motif and a novel membrane proximal FFAT-like motif. Using a truncation construct that lacks complete Golgi targeting information, we show that mutation of either motif leads to an increase in cell surface localization, while mutation of both motifs exhibits an additive effect. We also present evidence that illustrates that N- or C- terminal addition of a tag to full-length PRA1 leads to differential localization to either the Golgi or reticular ER, phenotypes that do not completely mirror endogenous protein localization. The presence of multiple ER retention motifs on the PRA1 N-terminal region further suggests that it has a functional role within the ER.

The Lipocalin Apolipoprotein D (ApoD) is one of the few genes consistently overexpressed in the aging brain, and in most neurodegenerative and psychiatric diseases. Its functions include metabolism regulation, myelin management, neuroprotection, and longevity regulation. Knowledge of endogenous regulatory mechanisms controlling brain disease-triggered ApoD expression is relevant if we want to boost pharmacologically its neuroprotecting potential. In addition to classical transcriptional control, Lipocalins have a remarkable variability in mRNA 5’UTR-dependent translation efficiency. Using bioinformatic analyses, we uncover strong selective pressures preserving ApoD 5’UTR properties, indicating unexpected functional conservation. PCR amplifications demonstrate the production of five 5’UTR variants (A-E) in mouse ApoD, with diverse expression levels across tissues and developmental stages. Importantly, Variant E is specifically expressed in the oxidative stress-challenged brain. Predictive analyses of 5’UTR secondary structures and enrichment in elements restraining translation, point to Variant E as a tight regulator of ApoD expression. We find two genomic regions conserved in human and mouse ApoD: a canonical (α) promoter region and a previously unknown region upstream of Variant E that could function as an alternative mouse promoter (β). Luciferase assays demonstrate that both α and β promoter regions can drive expression in cultured mouse astrocytes, and that Promoter β activity responds proportionally to incremental doses of the oxidative stress generator Paraquat. We postulate that Promoter β works in association with Variant E 5’UTR as a regulatory tandem that organizes ApoD gene expression in the nervous system in response to oxidative stress, the most common factor in aging and neurodegeneration.

Regulatory regions, like promoters and enhancers, cover an estimated 5-15% of the human genome. Changes to these sequences are thought to underlie much of human phenotypic variation and a substantial proportion of genetic causes of disease. However, our understanding of their functional encoding in DNA is still very limited. Applying machine or deep learning methods can shed light on this encoding and gapped k-mer support vector machines (gkm-SVMs) or convolutional neural networks (CNNs) are commonly trained on putative regulatory sequences.Here, we investigate the impact of negative sequence selection on model performance. By training gkm-SVM and CNN models on open chromatin data and corresponding negative training dataset, both learners and two approaches for negative training data are compared. Negative sets use either genomic background sequences or sequence shuffles of the positive sequences. Model performance was evaluated on three different tasks: predicting elements active in a cell-type, predicting cell-type specific elements, and predicting elements’ relative activity as measured from independent experimental data.Our results indicate strong effects of the negative training data, with genomic backgrounds showing overall best results. Specifically, models trained on highly shuffled sequences perform worse on the complex tasks of tissue-specific activity and quantitative activity prediction, and seem to learn features of artificial sequences rather than regulatory activity. Further, we observe that insufficient matching of genomic background sequences results in model biases. While CNNs achieved and exceeded the performance of gkm-SVMs for larger training datasets, gkm-SVMs gave robust and best results for typical training dataset sizes without the need of hyperparameter optimization.

Motivation Cellular identity and behavior is controlled by complex gene regulatory networks. Transcription factors (TFs) bind to specific DNA sequences to regulate the transcription of their target genes. On the basis of these TF motifs in cis-regulatory elements we can model the influence of TFs on gene expression. In such models of TF motif activity the data is usually modeled assuming a linear relationship between the motif activity and the gene expression level. A commonly used method to model motif influence is based on Ridge Regression. One important assumption of linear regression is the independence between samples. However, if samples are generated from the same cell line, tissue, or other biological source, this assumption may be invalid. This same assumption of independence is also applied to different yet similar experimental conditions, which may also be inappropriate. In theory, the independence assumption between samples could lead to loss in signal detection. Here we investigate whether a Bayesian model that allows for correlations results in more accurate inference of motif activities. Results We extend the Ridge Regression to a Bayesian Linear Mixed Model, which allows us to model dependence between different samples. In a simulation study, we investigate the differences between the two model assumptions. We show that our Bayesian Linear Mixed Model implementation outperforms Ridge Regression in a simulation scenario where the noise, which is the signal that can not be explained by TF motifs, is uncorrelated. However, we demonstrate that there is no such gain in performance if the noise has a similar covariance structure over samples as the signal that can be explained by motifs. We give a mathematical explanation to why this is the case. Using four representative real datasets we show that at most ∼​40% of the signal is explained by motifs using the linear model. With these data there is no advantage to using the Bayesian Linear Mixed Model, due to the similarity of the covariance structure. Availability & implementation The project implementation is available at https://github.com/Sim19/SimGEXPwMotifs.

The genus Vitivirus in the family Betaflexiviridae includes eleven viruses known to infect grapevine: grapevine vitiviruses A, B, D, E, F, G, H, I, J, L and M (GVA-GVM). Three of these viruses, GVA, GVB and GVD, have been associated with the etiology of rugose wood disease in grapevine and cause agronomically significant losses. The other vitiviruses were more recently discovered and their effects on grapevine are undetermined. To certify grape material for propagation as virus tested, an updated reverse transcription PCR (RT-PCR) assay to detect all known vitiviruses is desirable. To accomplish this, multiple grapevine vitivirus sequences were aligned at the amino acid level to search for conserved motifs. Two highly conserved motifs were found at an ideal distance for RT-PCR detection in the RNA-dependent RNA polymerase region of the replicase protein. The amino acid motifs were back translated to create degenerate primers and used to successfully amplify all eleven grapevine vitiviruses. The RT-PCR primers were used to test a panel of vitivirus-infected vines for inclusivity as well as vines infected with closely related viruses in the Betaflexiviridae family (i.e. grapevine pinot gris virus and grapevine rupestris stem pitting-associated virus) for exclusivity. Broader use of these primers to detect vitiviruses in other plant hosts was investigated. In summary, an end-point RT-PCR assay that detects all the known grapevine vitiviruses and potentially other members of the genus Vitivirus has been developed. The universal assay represents an alternative to individual assays to reduce the work associated with the diagnosis of vitiviruses, including for regulatory purposes.

Acquired resistance to endocrine therapy is responsible for half of the therapeutic failures in the treatment of breast cancer. Recent findings have implicated increased expression of the ETS transcription factor ELF5 as a potential modulator of estrogen action and driver of endocrine resistance, and here we provide the first insight into the mechanisms by which ELF5 modulates estrogen sensitivity. Using chromatin immunoprecipitation sequencing we found that ELF5 binding overlapped with FOXA1 and ER at super enhancers, enhancers and promoters, and when elevated, caused FOXA1 and ER to bind to new regions of the genome, in a pattern that replicated the alterations to the ER/FOXA1 cistrome caused by the acquisition of resistance to endocrine therapy. RNA sequencing demonstrated that these changes altered estrogen-driven patterns of gene expression, the expression of ER transcription-complex members, and 6 genes known to be involved in driving the acquisition of endocrine resistance. Using rapid immunoprecipitation mass spectrometry of endogenous proteins, and proximity ligation assays, we found that ELF5 interacted physically with members of the ER transcription complex, such as DNA-PKcs. We found 2 cases of endocrine-resistant brain metastases where ELF5 levels were greatly increased and ELF5 patterns of gene expression were enriched, compared to the matched primary tumour. Thus ELF5 alters ER-driven gene expression by modulating the ER/FOXA1 cistrome, by interacting with it, and by modulating the expression of members of the ER transcriptional complex, providing multiple mechanisms by which ELF5 can drive endocrine resistance., Author summary Two thirds of breast cancers are initially treated with endocrine therapy because they are likely to rely on estrogen for their proliferation. Understanding why this therapy ultimately fails in 2/3 of cases offers the chance of durable treatment. In 2012 we hypothesised that normal developmental cell fate decisions taken by mammary progenitor cells persist in tumours that are maintained by instances of a cancerous progenitor, and that a change in the relative influence of the two major transcription factors that drive progenitor cell fate, ER to specify the hormone sensing lineage, and ELF5 to specify the ER- alveolar lineage, may allow a cancer to shift control of proliferation from estrogen to ELF5. Here we show that these transcription factors are often co located at super enhancers, enhancers and at the promoters of differentially regulated genes. When the levels of ELF5 were increased this caused ER and its pioneer factor FOXA1 to move to new regions of the genome associated with resistance to hormonal therapy. We also showed that ELF both regulated and bound directly to members of the ER-transcriptional complex. These findings provide the first indication of the mechanisms by which an increase in ELF5 could drive the acquisition of endocrine resistance.

We study the limits imposed by transcription factor specificity on the maximum number of binding motifs that can coexist in a gene regulatory network, using the SwissRegulon Fantom5 collection of 684 human transcription factor binding sites as a model. We describe transcription factor specificity using regular expressions and find that most human transcription factor binding site motifs are separated in sequence space by one to three motif-discriminating positions. We apply theorems based on the pigeonhole principle to calculate the maximum number of transcription factors that can coexist given this degree of specificity, which is in the order of ten thousand and would fully utilize the space of DNA subsequences. Taking into account an expanded DNA alphabet with modified bases can further raise this limit by several orders of magnitude, at a lower level of sequence space usage. Our results may guide the design of transcription factors at both the molecular and system scale.

Pervasive enhancer transcription is at the origin of more than half of all long noncoding RNAs in humans. Transcription of enhancer-associated long noncoding RNAs (elncRNA) contribute to their cognate enhancer activity and gene expression regulation in cis. Recently, splicing of elncRNAs was shown to be associated with elevated enhancer activity. However, whether splicing of elncRNA transcripts is a mere consequence of accessibility at highly active enhancers or if elncRNA splicing directly impacts enhancer function, remains unanswered. We analysed genetically driven changes in elncRNA splicing, in humans, to address this outstanding question. We showed that splicing related motifs within multi-exonic elncRNAs evolved under selective constraints during human evolution, suggesting the processing of these transcripts is unlikely to have resulted from transcription across spurious splice sites. Using a genome-wide and unbiased approach, we used nucleotide variants as independent genetic factors to directly assess the causal relationship that underpin elncRNA splicing and their cognate enhancer activity. We found that the splicing of most elncRNAs is associated with changes in chromatin signatures at cognate enhancers and target mRNA expression. We provide evidence that efficient and conserved processing of enhancer-associated elncRNAs contributes to enhancer activity., Author summary Most, if not all, active enhancers are transcribed, giving rise to a plethora of transcripts, including enhancer-associated long noncoding RNAs (elncRNAs). Changes in elncRNA levels impacts cognate enhancer activity. Recently splicing of elncRNA has also been found to associate with enhancer activity. Whether this associations reflects a contribution of elncRNA splicing to increased enhancer activity or else is simply the consequence of increased chromatin accessibility that promotes transcriptional elongation and allows for spurious splicing events remains unknown. We show that natural selection has acted, at the species and population level, to preserve DNA elements required for frequent and efficient elncRNA splicing Importantly, using a genome-wide and unbiased statistical population genomics approach, we demonstrate that elncRNA splicing is associated with cognate enhancer function, contributing to chromatin status and enhancer activity. Our results provides strong evidence that efficient elncRNA splicing contributes to enhancer activity genome-wide.

Tuber mustard, which is the raw material of Fuling pickle, is a crop with great economic value. However, during growth and development, tuber mustard is frequently attacked by the pathogen Plasmodiophora brassicae and frequently experiences salinity stress. Jasmonic acid (JA) is a hormone related to plant resistance to biotic and abiotic stress. Jasmonate ZIM domain proteins (JAZs) are crucial components of the JA signaling pathway and play important roles in plant responses to biotic and abiotic stress. To date, no information is available about the characteristics of the JAZ family genes in tuber mustard. Here, 38 BjJAZ genes were identified in the whole genome of tuber mustard. The BjJAZ genes are located on 17 of 18 chromosomes in the tuber mustard genome. The gene structures and protein motifs of the BjJAZ genes are conserved between tuber mustard and Arabidopsis. The results of qRT-PCR analysis showed that BjuA030800 was specifically expressed in root, and BjuA007483 was specifically expressed in leaf. In addition, 13 BjJAZ genes were transiently induced by P. brassicae at 12 h, and 7 BjJAZ genes were induced by salt stress from 12 to 24 h. These results provide valuable information for further studies on the role of BjJAZ genes in the regulation of plant growth and development and in the response to biotic and abiotic stress.

Carotenoid cleavage dioxygenase (CCD), a key enzyme in carotenoid metabolism, cleaves carotenoids to form apo-carotenoids, which play a major role in plant growth and stress responses. CCD genes had not previously been systematically characterized in Brassica napus (rapeseed), an important oil crop worldwide. In this study, we identified 30 BnCCD genes and classified them into nine subgroups based on a phylogenetic analysis. We identified the chromosomal locations, gene structures, and cis-promoter elements of each of these genes and performed a selection pressure analysis to identify residues under selection. Furthermore, we determined the subcellular localization, physicochemical properties, and conserved protein motifs of the encoded proteins. All the CCD proteins contained a retinal pigment epithelial membrane protein (RPE65) domain. qRT-PCR analysis of expression of 20 representative BnCCD genes in 16 tissues of the B. napus cultivar Zhong Shuang 11 ('ZS11') revealed that members of the BnCCD gene family possess a broad range of expression patterns. This work lays the foundation for functional studies of the BnCCD gene family.

Hepatocellular carcinoma (HCC), which is associated with an absence of obvious symptoms and poor prognosis, is the second leading cause of cancer death worldwide. Genome-wide molecular biology studies should provide biological insights into HCC development. Based on the importance of phosphorylation for signal transduction, several protein kinase inhibitors have been developed that improve the survival of cancer patients. However, a comprehensive database of HCC-related phosphorylated biomarkers (HCCPMs) and novel HCCPMs prediction platform has been lacking. We have thus constructed the dBMHCC databases to provide expression profiles, phosphorylation and drug information, and evidence type; gathered information on HCC-related pathways and their involved genes as candidate HCC biomarkers; and established a system for evaluating protein phosphorylation and HCC-related biomarkers to improve the reliability of biomarker prediction. The resulting dBMHCC contains 611 notable HCC-related genes, 234 HCC-related pathways, 17 phosphorylation-related motifs and their 255 corresponding protein kinases, 5955 HCC biomarkers, and 1077 predicted HCCPMs. Methionine adenosyltransferase 2B (MAT2B) and acireductone dioxygenase 1 (ADI1), which regulate HCC development and hepatitis C virus infection, respectively, were among the top 10 HCCPMs predicted by dBMHCC. Platelet-derived growth factor receptor alpha (PDGFRA), which had the highest evaluation score, was identified as the target of one HCC drug (Regorafenib), five cancer drugs, and four non-cancer drugs. dBMHCC is an open resource for HCC phosphorylated biomarkers, which supports researchers investigating the development of HCC and designing novel diagnosis methods and drug treatments. Database URL: http://predictor.nchu.edu.tw/dBMHCC.

Eukaryotic cells partition a wide variety of important materials and processes into biomolecular condensates—phase-separated droplets that lack a membrane. In addition to nonspecific electrostatic or hydrophobic interactions, phase separation also depends on specific binding motifs that link together constituent molecules. Nevertheless, few rules have been established for how these ubiquitous specific, saturating, motif-motif interactions drive phase separation. By integrating Monte Carlo simulations of lattice-polymers with mean-field theory, we show that the sequence of heterotypic binding motifs strongly affects a polymer’s ability to phase separate, influencing both phase boundaries and condensate properties (e.g. viscosity and polymer diffusion). We find that sequences with large blocks of single motifs typically form more inter-polymer bonds, which promotes phase separation. Notably, the sequence of binding motifs influences phase separation primarily by determining the conformational entropy of self-bonding by single polymers. This contrasts with systems where the molecular architecture primarily affects the energy of the dense phase, providing a new entropy-based mechanism for the biological control of phase separation., Author summary Cells need to concentrate biomolecules in the right place at the right time in order to function. Many important intracellular compartments are liquid droplets formed by phase separation, the same process that separates oil from vinegar. The properties of such “biomolecular condensates” depend on the component molecules, such as proteins and RNAs. These molecules are polymers made of many interacting monomers, often organized into “motifs,” and the sequence of motifs shapes the properties of the condensates. Recent work has revealed important principles governing phase separation when the motifs are charged and interact across long distances, but many phase-separating molecules form specific interactions that are short-range and one-to-one. How does the sequence of specifically-interacting motifs affect phase separation? Using a combination of simulations and theoretical calculations, we show that the sequence has profound effects on both the formation and properties of condensates. Sequences with large blocks of identical motifs are better at phase separating but more viscous and solid-like. Importantly, we find that sequence controls phase separation via the proclivity to form self-bonds instead of forming bonds with other polymers. Thus the sequence of specifically-interacting motifs provides a control point for the formation and properties of phase-separated intracellular compartments.

Transcription-related proteins are frequently identified as targets of sumoylation, including multiple subunits of the RNA polymerase II (RNAPII) general transcription factors (GTFs). However, it is not known how sumoylation affects GTFs or whether they are sumoylated when they assemble at promoters to facilitate RNAPII recruitment and transcription initiation. To explore how sumoylation can regulate transcription genome-wide, we performed SUMO ChIP-seq in yeast and found, in agreement with others, that most chromatin-associated sumoylated proteins are detected at genes encoding tRNAs and ribosomal proteins (RPGs). However, we also detected 147 robust SUMO peaks at promoters of non-ribosomal protein-coding genes (non-RPGs), indicating that sumoylation also regulates this gene class. Importantly, SUMO peaks at non-RPGs align specifically with binding sites of GTFs, but not other promoter-associated proteins, indicating that it is GTFs specifically that are sumoylated there. Predominantly, non-RPGs with SUMO peaks are among the most highly transcribed, have high levels of TFIIF, and show reduced RNAPII levels when cellular sumoylation is impaired, linking sumoylation with elevated transcription. However, detection of promoter-associated SUMO by ChIP might be limited to sites with high levels of substrate GTFs, and promoter-associated sumoylation at non-RPGs may actually be far more widespread than we detected. Among GTFs, we found that TFIIF is a major target of sumoylation, specifically at lysines 60/61 of its Tfg1 subunit, and elevating Tfg1 sumoylation resulted in decreased interaction of TFIIF with RNAPII. Interestingly, both reducing promoter-associated sumoylation, in a sumoylation-deficient Tfg1-K60/61R mutant strain, and elevating promoter-associated SUMO levels, by constitutively tethering SUMO to Tfg1, resulted in reduced RNAPII occupancy at non-RPGs. This implies that dynamic GTF sumoylation at non-RPG promoters, not simply the presence or absence of SUMO, is important for maintaining elevated transcription. Together, our findings reveal a novel mechanism of regulating the basal transcription machinery through sumoylation of promoter-bound GTFs., Author summary Six general transcription factors (GTFs) assemble at promoters of protein-coding genes to enable recruitment of RNA polymerase II (RNAPII) and facilitate transcription initiation, but little is known about how they are regulated once promoter-bound. Here, we demonstrate that, in budding yeast, some components of GTFs are post-translationally modified by the SUMO peptide specifically when they are assembled at promoters. We determined that the large subunit of TFIIF, Tgf1, is the major target of sumoylation among GTFs and that increasing Tfg1 sumoylation reduces the interaction of TFIIF with RNAPII. Consistent with this, we found that increasing levels of SUMO at promoters of some protein-coding genes, by permanently attaching SUMO to Tfg1, resulted in reduced RNAPII levels associated with those genes. On the other hand, reducing promoter-associated sumoylation, by mutating SUMO-modified residues on Tfg1, also reduced RNAPII occupancy levels. Explaining these apparently contradictory findings, we propose that dynamic sumoylation of promoter-bound GTFs, not merely the presence or absence of SUMO, is important for facilitating rearrangements of promoter-bound GTF components that enhance transcription. Together, our data reveal a novel level of regulating the basal transcription machinery through SUMO modification at promoters of protein-coding genes.

RNA splicing is a key process in eukaryotic gene expression, in which an intron is spliced out of a pre-mRNA molecule to eventually produce a mature mRNA. Most intron-containing genes are constitutively spliced, hence efficient splicing of an intron is crucial for efficient regulation of gene expression. Here we use a large synthetic oligo library of ~20,000 variants to explore how different intronic sequence features affect splicing efficiency and mRNA expression levels in S. cerevisiae. Introns are defined by three functional sites, the 5’ donor site, the branch site, and the 3’ acceptor site. Using a combinatorial design of synthetic introns, we demonstrate how non-consensus splice site sequences in each of these sites affect splicing efficiency. We then show that S. cerevisiae splicing machinery tends to select alternative 3’ splice sites downstream of the original site, and we suggest that this tendency created a selective pressure, leading to the avoidance of cryptic splice site motifs near introns’ 3’ ends. We further use natural intronic sequences from other yeast species, whose splicing machineries have diverged to various extents, to show how intron architectures in the various species have been adapted to the organism’s splicing machinery. We suggest that the observed tendency for cryptic splicing is a result of a loss of a specific splicing factor, U2AF1. Lastly, we show that synthetic sequences containing two introns give rise to alternative RNA isoforms in S. cerevisiae, demonstrating that merely a synthetic fusion of two introns might be suffice to facilitate alternative splicing in yeast. Our study reveals novel mechanisms by which introns are shaped in evolution to allow cells to regulate their transcriptome. In addition, it provides a valuable resource to study the regulation of constitutive and alternative splicing in a model organism., Author summary RNA splicing is a process in which parts of a new pre-mRNA are spliced out of the mRNA molecule to produce eventually a mature mRNA. Those RNA segments that are spliced out are termed introns, and they are found in most genes in eukaryotic organisms. Hence regulation of this process has a major role in the control of gene expression. The budding yeast S. cerevisiae is a popular model organism for eukaryotic cell biology, but in terms of splicing it differs, as it has only few intron-containing genes. Nevertheless, this species has been used to study basic principles of splicing regulation based on its ~300 introns. Here we used the technology of a large synthetic genetic library to introduce many new intron-containing genes to the yeast genome, to explore splicing regulation at a wider scope than was possible so far. Reassuringly, our results confirm known regulatory mechanisms, and further expand our understanding of splicing regulation, specifically how the yeast splicing machinery interacts with the end of introns, and how through evolution introns have evolved to avoid unwanted misidentifications of this end. We further demonstrate the potential of the yeast splicing machinery to alternatively splice a two-intron gene, which is common in other eukaryotes but rare in yeast. Our work presents a first-of-its-kind resource for the systematic study of splicing in live cells.

Discovering sequence features that differentially direct cells to alternate fates is key to understanding both cellular development and the consequences of disease related mutations. We introduce Expected Pattern Effect and Differential Expected Pattern Effect, two black-box methods that can interpret genome regulatory sequences for cell type-specific or condition specific patterns. We show that these methods identify relevant transcription factor motifs and spacings that are predictive of cell state-specific chromatin accessibility. Finally, we integrate these methods into framework that is readily accessible to non-experts and available for download as a binary or installed via PyPI or bioconda at https://cgs.csail.mit.edu/deepaccess-package/., Author summary Within the genome are the instructions to build all the cell types that make up the human body. However, understanding these instructions and how and when these instructions go wrong in cancer or genetically inherited disease is an open problem. Deep neural networks provide powerful models to learn the relationship between DNA sequence and functional consequence across many different cell types, such as whether a particular stretch of DNA is accessible and genes in that region can be expressed or is inaccessible and therefore genes are inactive. Despite these advances, a major setback in deep learning is that it is challenging to understand what patterns of DNA sequence that a deep learning model has learned to associate with a particular genomic function, whether these patterns are significant, and how to determine whether these patterns are specific to a particular cell type or are general “housekeeping” patterns that function across many cell types. We introduce Expected Pattern Effect and Differential Expected Pattern Effect, two methods which allow us to evaluate the significance of particular patterns of DNA sequence features on models trained to predict function across multiple cell types, and apply this to problems of transcription factor binding and DNA accessibility across multiple cell types.

Toxoplasma gondii is an obligate intracellular parasite that can cause serious opportunistic disease in the immunocompromised or through congenital infection. To progress through its life cycle, Toxoplasma relies on multiple layers of gene regulation that includes an array of transcription and epigenetic factors. Over the last decade, the modification of mRNA has emerged as another important layer of gene regulation called epitranscriptomics. Here, we report that epitranscriptomics machinery exists in Toxoplasma, namely the methylation of adenosines (m6A) in mRNA transcripts. We identified novel components of the m6A methyltransferase complex and determined the distribution of m6A marks within the parasite transcriptome. m6A mapping revealed the modification to be preferentially located near the 3’-boundary of mRNAs. Knockdown of the m6A writer components METTL3 and WTAP resulted in diminished m6A marks and a complete arrest of parasite replication. Furthermore, we examined the two proteins in Toxoplasma that possess YTH domains, which bind m6A marks, and showed them to be integral members of the cleavage and polyadenylation machinery that catalyzes the 3’-end processing of pre-mRNAs. Loss of METTL3, WTAP, or YTH1 led to a defect in transcript 3’-end formation. Together, these findings establish that the m6A epitranscriptome is essential for parasite viability by contributing to the processing of mRNA 3’-ends., Author summary Toxoplasma gondii is a parasite of medical importance that causes disease upon immuno-suppression. Uncovering essential pathways that the parasite uses for its basic biological processes may reveal opportunities for new anti-parasitic drug therapies. Here, we describe the machinery that Toxoplasma uses to modify specific adenosine residues within its messenger RNAs (mRNA) by N6-adenosine methylation (m6A). We discovered that m6A mRNA methylation is prevalent in multiple stages of the parasite life cycle and is required for parasite replication. We also establish that m6A plays a major role in the proper maturation of mRNA. Two proteins that bind m6A modifications on mRNA associate with factors responsible for the cleavage and final processing steps of mRNA maturation. Since all of the machinery is conserved from plants to Toxoplasma and other related parasites, we propose that this system operates similarly in these organisms.

Free-living bacteria adapt to environmental change by reprogramming gene expression through precise interactions of hundreds of DNA-binding proteins. A predictive understanding of bacterial physiology requires us to globally monitor all such protein–DNA interactions across a range of environmental and genetic perturbations. Here, we show that such global observations are possible using an optimized version of in vivo protein occupancy display technology (in vivo protein occupancy display—high resolution, IPOD-HR) and present a pilot application to Escherichia coli. We observe that the E. coli protein–DNA interactome organizes into 2 distinct prototypic features: (1) highly dynamic condition-dependent transcription factor (TF) occupancy; and (2) robust kilobase scale occupancy by nucleoid factors, forming silencing domains analogous to eukaryotic heterochromatin. We show that occupancy dynamics across a range of conditions can rapidly reveal the global transcriptional regulatory organization of a bacterium. Beyond discovery of previously hidden regulatory logic, we show that these observations can be utilized to computationally determine sequence specificity models for the majority of active TFs. Our study demonstrates that global observations of protein occupancy combined with statistical inference can rapidly and systematically reveal the transcriptional regulatory and structural features of a bacterial genome. This capacity is particularly crucial for non-model bacteria that are not amenable to routine genetic manipulation., This study uses a novel technology (IPOD-HR) to quantify the protein occupancy of an entire bacterial chromosomes at high-resolution; in addition to enabling the monitoring of global transcriptional regulatory dynamics, IPOD-HR reveals densely occupied silencing domains akin to eukaryotic heterochromatin.

Color vision in Drosophila melanogaster is based on the expression of five different color-sensing Rhodopsin proteins in distinct subtypes of photoreceptor neurons. Promoter regions of less than 300 base pairs are sufficient to reproduce the unique, photoreceptor subtype-specific rhodopsin expression patterns. The underlying cis-regulatory logic remains poorly understood, but it has been proposed that the rhodopsin promoters have a bipartite structure: the distal promoter region directs the highly restricted expression in a specific photoreceptor subtype, while the proximal core promoter region provides general activation in all photoreceptors. Here, we investigate whether the rhodopsin promoters exhibit a strict specialization of their distal (subtype specificity) and proximal (general activation) promoter regions, or if both promoter regions contribute to generating the photoreceptor subtype-specific expression pattern. To distinguish between these two models, we analyze the expression patterns of a set of hybrid promoters that combine the distal promoter region of one rhodopsin with the proximal core promoter region of another rhodopsin. We find that the function of the proximal core promoter regions extends beyond providing general activation: these regions play a previously underappreciated role in generating the non-overlapping expression patterns of the different rhodopsins. Therefore, cis-regulatory motifs in both the distal and the proximal core promoter regions recruit transcription factors that generate the unique rhodopsin patterns in a combinatorial manner. We compare this combinatorial regulatory logic to the regulatory logic of olfactory receptor genes and discuss potential implications for the evolution of rhodopsins., Author summary Each type of sensory receptor neuron in our body expresses a specific sensory receptor protein, which allows us to detect and discriminate a variety of environmental stimuli. The regulatory logic that controls this spatially precise and highly restricted expression of sensory receptor proteins remains poorly understood. As a model system, we study the mechanisms that control the expression of different color-sensing Rhodopsin proteins in distinct subtypes of Drosophila photoreceptors, which is the basis for color vision. Compact promoter regions of less than 300 base pairs are sufficient to reproduce the non-overlapping rhodopsin patterns. However, the regulatory logic that underlies the combination (sometimes called ‘grammar’) of the cis-regulatory motifs (sometimes called ‘vocabulary’) within the rhodopsin promoters remains poorly understood. Here, we find that specific combinations of cis-regulatory motifs in the distal and the proximal core promoter regions of each rhodopsin direct its unique expression pattern.