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Results for “molecular biology”

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bioRxiv2025

RamanMAE: Masked Autoencoders Enable Efficient Molecular Imaging by Learning Biologically Meaningful Spectral Representations

Traditional histopathological analysis of cells and tissue relies on morphological features from stained biopsy samples, which fail to leverage the wealth of chemical information about the underlying pathological states. Raman spectroscopy, a form of vibrational spectroscopy, uses light scattering to capture chemical information about the biological specimen. However, advancements in Raman spectroscopy are hindered by the methods intrinsic low throughput and the difficulty in deriving meaningful insights from the high-dimensional noisy datasets. In this paper, we propose RamanMAE, a spectral language model using masked autoencoders on large Raman spectral datasets from biological applications that can be used for spectral processing in applications with limited data. We achieved excellent reconstruction of masked patches of the spectra. We learned meaningful latent representations of the spectra that capture biological compositional information and serve as a low-dimensional feature space for building downstream machine learning methods. We showed that the decoder serves as an effective smoothing technique to reduce noise in the spectra and allow better localization and visualization of biological features in the spectral maps. We also demonstrated the transferability of the representations learned on one dataset to a different biological application.

biochemistry↗

bioRxiv2023

Three-dimensional dipole orientation mapping with high temporal-spatial resolution using polarization modulation

Fluorescence polarization microscopy is widely used in biology for molecular orientation properties. However, due to the limited temporal resolution of single-molecule orientation localization microscopy and the limited orientation dimension of polarization modulation techniques, achieving simultaneous high temporal-spatial resolution mapping of the three-dimensional (3D) orientation of fluorescent dipoles remains an outstanding problem. Here, we present a super-resolution 3D orientation mapping (3DOM) microscope that resolves 3D orientation by extracting phase information of the six polarization modulation components in reciprocal space. 3DOM achieves an azimuthal precision of 2{degrees} and a polar precision of 3{degrees} with spatial resolution of 128 nm in the experiments. We validate that 3DOM not only reveals the heterogeneity of the milk fat globule membrane, but also elucidates the 3D structure of biological filaments, including the 3D spatial conformation of {lambda}-DNA and the structural disorder of actin filaments. Furthermore, 3DOM images the dipole dynamics of microtubules labeled with green fluorescent protein in live U2OS cells, reporting dynamic 3D orientation variations. Given its easy integration into existing wide-field microscopes, we expect the 3DOM microscope to provide a multi-view versatile strategy for investigating molecular structure and dynamics in biological macromolecules across multiple spatial and temporal scales.

molecular biology↗

bioRxiv2026

Unifying physical and molecular coordinate systems across modalities in spatial biology

Establishing a unified physical and molecular coordinate system from fragmented multi-modal data is a longstanding challenge in biology. Here, we present MAPS, a modality-agnostic platform for spatial biology comprising (1) MAPS-alignment for ultrafast alignment of any modality, (2) MAPS-integration for both anchored and unanchored integration across orthogonal modalities for 3D multi-modal reconstruction, and (3) MAPS-Explorer for large-scale interactive 3D analysis. MAPS outperformed existing methods across extensive benchmarks on 34 datasets spanning 16 technology platforms and 6 modalities, while delineating fine-grained multi-modal tissue architectures across diverse biological systems in mouse and human. At cross-consortium scale, MAPS integrated 434 slices comprising 21 million cells from 18 atlases and 5 modalities to construct the most comprehensive 3D multi-modal mouse brain atlas. At individual laboratory scale, MAPS empowered routine 2D spatial assays to reconstruct continuous 3D multi-modal landscapes of human hepatocellular carcinoma, revealing the limitations of 2D spatial relationships and uncovering depth-dependent immune-state transitions.

bioinformatics↗

bioRxiv2023

Human DCP1 promotes mRNA decapping by enhancing the RNA binding affinity of DCP2

The mRNA 5-cap structure removal by the decapping enzyme DCP2 is a critical step in gene regulation. While DCP2 is the catalytic subunit in the decapping complex, its activity is strongly enhanced by multiple factors, particularly DCP1, which is the major activator in yeast. However, the precise role of DCP1 in metazoans has yet to be fully elucidated. Moreover, in humans, the specific biological functions of the two DCP1 paralogs, DCP1a and DCP1b, remain largely unknown. To investigate the role of human DCP1, we generated cell-lines that were deficient in DCP1a, DCP1b or both to evaluate the importance of DCP1 in the decapping machinery. Our results highlight the importance of human DCP1 in decapping process and show that the EVH1 domain of DCP1 enhances the mRNA-binding affinity of DCP2. Transcriptome and metabolome analyses outline the distinct functions of DCP1a and DCP1b in human cells, regulating specific endogenous mRNA targets and biological processes. Overall, our findings provide insights into the molecular mechanism of human DCP1 in mRNA decapping and shed light on the distinct functions of its paralogs.

molecular biology↗

bioRxiv2024

Unravelling the Molecular Footprints of Diabetic Foot Ulcers: In Silico Discovery of Key Protein and MicroRNA Signatures

Diabetic foot ulcers (DFUs) present a significant clinical challenge, characterized by chronic inflammation and impaired wound healing. This study employs Gene Ontology (GO) analysis to identify critical biological processes, molecular functions, cellular components, and pathways associated with DFUs, aiming to uncover novel therapeutic targets. The analysis reveals significant enrichment in biological processes such as Positive Regulation of miRNA Transcription and Regulation of miRNA Transcription, highlighting the crucial role of microRNAs, including hsa-miR-34a-5p, hsa-miR-155-5p, hsa-miR-17-5p, hsa-miR-29b-3p, hsa-miR-7-5p, hsa-miR-1-3p, and hsa-miR-23b-3p, in regulating wound healing and inflammation. Enriched molecular functions, such as DNA-binding Transcription Activator Activity and Protein Phosphatase Binding, suggest that targeting genes like TP53, GAPDH, AKT1, MYC, TNF, EGFR, STAT3, FN1, VEGFA, and JUN could modulate critical cellular processes and improve DFU management. The analysis also identifies key cellular components, including Vesicle and Platelet Alpha Granule Lumen, as crucial for cellular transport and signaling, suggesting that interventions targeting these components could enhance wound repair. Furthermore, enriched pathways such as Proteoglycans in Cancer and Human Cytomegalovirus Infection indicate potential mechanisms and viral influences relevant to DFUs. These findings provide a comprehensive framework for developing targeted therapies that address the multifaceted pathology of DFUs, offering promising avenues for improving patient outcomes and advancing wound healing strategies.

molecular biology↗

bioRxiv2020

Internetwork connectivity of molecular networks across species of life

BackgroundMolecular interactions have been studied as independent complex networks in systems biology. However, molecular networks dont exist independently of each other. In a network of networks approach (called multiplex), we uncover the design principles for the joint organization of transcriptional regulatory network (TRN) and protein-protein interaction (PPI) network. ResultsWe find that TRN and PPI networks are non-randomly coupled in the TRN-PPI multiplex across five different eukaryotic species. Gene degrees in TRN (number of downstream genes) are positively correlated with protein degrees in PPI (number of interacting protein partners). Gene-gene interactions in TRN and protein-protein interactions in PPI also non-randomly overlap in the multiplex. These design principles are conserved across the five eukaryotic species. We show that the robustness of the TRN-PPI multiplex is dependent on these design principles. Further, functionally important genes and proteins, such as essential, disease-related and those involved in host-pathogen PPI networks, are preferentially situated in essential parts of the human multiplex with highly overlapping interactions. ConclusionWe unveil the multiplex architecture of TRN and PPI networks across different species. Multiplex architecture may thus define a general framework for studying molecular networks across the different species of life. This approach may uncover the building blocks of the hierarchical organization of molecular interactions.

systems biology↗

bioRxiv2026

In silico transcriptomic analysis reveals shared molecular signatures and immune-associated pathways between Hashimotos thyroiditis and type 2 diabetes with exploratory drug repurposing

The management of Hashimotos thyroiditis (HT), one of the most prevalent autoimmune disorders worldwide, becomes more complex when it coexists with type 2 diabetes (T2D) compared with the management of either disease alone. This complexity may arise from overlapping genetic, metabolic, and immune dysregulation, as well as potential therapeutic conflicts. Although HT and T2D are known to co-occur and share immune and metabolic features, the molecular characteristics underlying these overlaps have not been systematically explored. This study aimed to identify shared gene expression signatures and associated biological pathways between HT and T2D using an in silico, hypothesis-generating approach, and to explore candidate compounds that may be relevant to both conditions. Independent transcriptomic datasets (GSE138198 for control/HT and GSE29231 for control/T2D) were analyzed, leading to the identification of 59 genes that were differentially expressed in both HT and T2D compared with control samples. Protein-protein interaction (PPI) network analysis prioritized five shared key genes (sKGs): CDC42, CD74, FOS, RAC2, and YWHAB. Functional enrichment analysis of these sKGs revealed overlapping biological processes, molecular functions, cellular components, and immune-related signaling pathways, as well as shared regulatory networks involving transcription factors (FOXC1 and HNF4A) and microRNAs (hsa-miR-221-3p and hsa-miR-29a-3p). Immune infiltration analysis demonstrated broadly similar patterns of immune dysregulation in both diseases, providing additional biological context for the observed shared molecular signatures. Finally, an exploratory in silico drug repurposing pipeline incorporating molecular docking, ADMET profiling, drug-likeness assessment, and molecular dynamics simulations prioritized three candidate compounds: gliquidone, oleanolic acid, and glipizide for further investigation. Overall, this study provides a hypothesis-generating framework highlighting shared molecular features between HT and T2D, which may inform future experimental validation and clinical research. Author SummaryIn this work, we wanted to better understand why Hashimotos thyroiditis, an autoimmune condition that affects the thyroid gland, is often seen in people who also have type 2 diabetes. Treating patients who live with both conditions can be difficult, and we were interested in finding out whether they share common biological causes. To do this, we examined genetic data from individuals with each disease and looked for patterns that appeared in both groups. We discovered several genes that seem to act in similar ways in the two conditions, particularly genes linked to immune system activity and associated pathways. This finding suggests that shared molecular signatures and immune-associated pathways may play a role in the development of both diseases. We also explored how these shared genetic features influence larger biological processes and immune responses. The similarities we found support the idea that the two diseases may be connected through related biological pathways. In addition, we used computer-based screening methods to identify existing drugs that might influence these shared pathways. While these results need further testing, we hope our findings help open new directions for research and eventually contribute to better care for patients affected by both conditions.

bioinformatics↗

bioRxiv2020

Non-epigenetic mechanisms enable short memories of the environment for cell cycle commitment

Cells continuously survey their environment in order to make fundamental decisions, including whether to divide, migrate, or differentiate. However, a fascinating phenomenon in biology is that cells often possess memory--they temporally integrate both past and present signals to make a reliable decision. Cellular memory manifests across different biological systems over different timescales, and a variety of underlying molecular mechanisms have been proposed. Here we investigate a non-epigenetic molecular mechanism underpinning how a single yeast cell can remember its recent environmental history to decide whether to enter the cell cycle. This "memories" is encoded by the phosphorylation level of the cell cycle inhibitor Whi5. G1 cyclin Cln3 senses environmental nutrient levels and promotes cell-cycle entry by phosphorylating and thus inactivating Whi5. We developed an optogenetic system whereby the nuclear localization of Cln3 can be rapidly and reversibly controlled by light. By monitoring cellular response to different temporal profiles of Cln3, we found that cell cycle entry requires the time duration of nuclear Cln3, supporting the model of "cellular memories". Moreover, instead of the memory could last for the entire G1 phase as previously observed in glucose, we found Whi5 re-activates rapidly, with a similar half-time [~] 12 min, in a variety of nutrient and stress conditions. Our results suggest yeast cell can shortly remember its recent environmental cues to decide whether to enter the cell cycle.

molecular biology↗

bioRxiv2021

Molecular diet analysis in zebra and quagga mussels (Dreissena spp.) and an assessment of the utility of aquatic filter feeders as biological eDNA filters

Molecular gut content analysis is a popular tool to study food web interactions and was recently also suggested as an alternative source for DNA based biomonitoring. However, the overabundant consumers DNA often outcompetes that of its diet during PCR. Blocking approaches are an efficient means to reduce consumer amplification while retaining broad specificity for dietary taxa. We here designed an assay to monitor the eukaryotic diet of mussels and test their utility as biological eDNA filters to monitor planktonic communities. We designed several rDNA primer sets with a broad taxonomic suitability for eukaryotes, which suppress the amplification of mussels. The primers were tested using mussel DNA extracts and the results were compared to eDNA water samples collected next to the mussel colonies. Taxonomic recovery, as well as patterns of alpha and beta diversity, were compared between mussels and water samples. In addition, we analyzed time series samples of mussel samples from different German rivers. Our primer sets efficiently block the amplification of various mussel genera. The recovered DNA reflects a broad dietary preference across the eukaryotic tree of life and considerable taxonomic overlap with filtered water samples. We also recover various taxa of possible commensals and parasites, associated with the mussels. Our protocol will enable large scale dietary analysis in mussels, facilitate aquatic food web analysis, elucidate the ecological impact of invasive bivalves and the rapid survey of mussel aquacultures for pathogens. Moreover, we show that mussels could serve as an interesting complementary DNA source for biomonitoring.

ecology↗

bioRxiv2024

Einstein from Noise: Statistical Analysis

"Einstein from noise" (EfN) is a prominent example of the model bias phenomenon, where systematic errors in the statistical model lead to spurious but consistent estimates. In the EfN experiment, one falsely believes that a set of observations contains noisy, shifted copies of a template signal (e.g., an Einstein image), whereas in reality, it contains only pure noise observations. To estimate the signal, the observations are first aligned with the template using cross-correlation and then averaged. Although the observations contain nothing but noise, it was recognized early on that this process produces a signal that resembles the template signal! This model bias pitfall was at the heart of a central scientific controversy about validation techniques in structural biology. This paper provides a comprehensive statistical analysis of the EfN phenomenon above. We show that the Fourier phases of the EfN estimator (namely, the average of the aligned noise observations) converge to the Fourier phases of the template signal, thereby explaining the observed structural similarity. Additionally, we prove that the convergence rate of Fourier phases is inversely proportional to the number of noise observations and, in the high-dimensional regime, to the Fourier magnitudes of the template signal. Moreover, in the high-dimensional regime, the EfN estimator converges to a scaled version of the template signal. This work not only deepens the theoretical understanding of the EfN phenomenon but also highlights potential pitfalls in template matching techniques and emphasizes the need for careful interpretation of noisy observations across disciplines in engineering, statistics, physics, and biology.

molecular biology↗

bioRxiv2025

Differential quantitative requirements for pre-mRNA splicing-regulated shelterin protein levels in distinct telomere functions

Telomeres perform multiple functions to maintain genome stability, including telomere length regulation, chromosome end protection, and meiotic chromosome dynamics. These functions are governed by shelterin, a telomere-binding protein complex. Here, we show that efficient pre-mRNA splicing of the Schizosaccharomyces pombe shelterin components Rap1 and Poz1 ensures sufficient protein levels, which are critical for telomere maintenance. Our analyses revealed that Tls1 and Cay1 act at distinct steps in splicing, specifically affecting rap1 and poz1 transcripts: Tls1 strongly interacts with Brr2 (a splicing factor), whereas Cay1 preferentially associates with introns. Accordingly, deletion of tls1 and cay1 synergistically impaired splicing of rap1 and poz1 transcripts and reduced their protein levels, leading to abnormal telomere elongation. Removal of introns from the rap1 and poz1 genes restored normal protein levels and telomere length, confirming that defective splicing underlies these defects. Analyses of the phenotypes of single and double tls1{Delta} and cay1{Delta} mutants revealed that different telomere functions vary in their dependence on Rap1 levels: telomere length regulation and, to a lesser extent, meiosis require higher protein abundance, whereas chromosome end protection can be sustained with minimal amounts. These findings reveal a hierarchical requirement for Rap1 across telomere functions and establish a framework for understanding how splicing-dependent regulation of shelterin components coordinates multiple aspects of telomere biology.

molecular biology↗

bioRxiv2026

Transcription terminators can be strong promoters

A dogma of RNA synthesis is that promoter activity and termination are unrelated processes governed by completely different DNA sequences. Serendipitously, we find that two class II terminators for bacteriophage T7 RNA polymerase (RNAP), the natural T7 concatemer junction (CJ) and the artificial vesicular stomatitis virus (VSV) terminator, are context-dependent strong promoters for E. coli RNAP. However, the third class II member, the artificial human preproparathyroid hormone (PTH) terminator, is not a promoter. Transcription start sites and mutagenesis for CJ and VSV reveal a {sigma}70 extended TGn promoter motif that is lacking in PTH. Furthermore, results resolve the prior paradox of class II termination apparently occurring only in vitro, not in vivo, enabling demonstration of class II termination in vivo by both T7 and E. coli RNAPs. In addition, engineering of T7 RNAP increases its efficiency of class II termination in vivo. Given that prokaryotic synthetic biology is reliant on class I (hairpin) terminators, with T{Phi} used almost exclusively in constructs for T7 RNAP, recombination is an issue in large constructs. Thus, small class II terminators, now better understood with respect to terminator and promoter activities in the context of various sequences and RNAPs, extends the synthetic biology toolkit.

molecular biology↗

bioRxiv2025

Selection of nanobodies against liponanoparticle-embedded membrane proteins by yeast surface display

Single-domain antibodies, known as nanobodies (Nbs), are widely used in structural biology, therapeutics, and as molecular probes in biology and biotechnology. Nbs towards soluble proteins are routinely developed via alpaca immunization or directed evolution in yeast cell-surface display. However, for membrane proteins, the targets are generally detergent-solubilized, and there remains a need for Nb development methods against membrane proteins in a native-like membrane environment. To address this need, we present a protocol for Nb selection via extraction of membrane proteins into amphiphilic polymers such as styrene-maleic acid to produce purified membrane proteins in stable liponanoparticles. Proof of generality is demonstrated by applying the pipeline to four membrane-resident enzymes of differing fold, oligomerization state, and membrane topology (reentrant membrane helix, transmembrane, membrane-associated). Following screening for optimal stabilization into liponanoparticles, Nbs were selected against four target proteins from glycoconjugate biosynthesis pathways. The selected Nbs showed high affinity and selectivity towards their target proteins with KD apparent values ranging from 15 nM to 200 nM, depending on the Nb-protein conjugate. In accordance with their tight binding, various Nb-protein complexes were found to be stable to size-exclusion chromatography purification. The Nbs were also amenable to sortase-mediated ligation, enabling their conversion into molecular probes for the target membrane protein. The ability to select for such high-affinity Nb against membrane proteins in SMALP will facilitate their widespread application in cell biology and biomedical applications.

biochemistry↗

bioRxiv2026

The novel viper FETUA-3 protein evolved a unique mode of inhibiting snake venom metalloproteinases

Molecular innovation and coevolution play major roles in the evolution of biological diversity, yet we have relatively few instances in which we understand the biological and molecular bases of coevolution. Rattlesnakes and other vipers have evolved resistance to their own novel venom metalloproteinase (MP) toxins through the invention and coevolution of serum-borne inhibitors (FETUAs) derived from the ancestral, non-inhibitory, serum glycoprotein Fetuin-A. However, how FETUAs acquired their function and their mechanism of action are unknown. Here, we use a combination of structure prediction, site-directed mutagenesis, functional analyses, and molecular dynamics to elucidate how the rattlesnake FETUA-3 protein evolved to inhibit three classes of venom MP toxins. We show that FETUA-3 uses a combination of structural motifs to bind multiple MPs with high-affinity and acts as a potent noncompetitive inhibitor by inserting its N-terminus into MP active sites and directly disrupting substrate cleavage. We also find strong selective constraints on key N-terminal residues that maintain FETUA-3 specificity for multiple MP targets. These results reveal that FETUA-3 evolved a unique mechanism of action distinct from other vertebrate metalloproteinase inhibitors and how a small number of FETUA proteins controls the activities of a large family of venom toxins.

evolutionary biology↗

bioRxiv2023

Unravelling the regulatory function of a short 3'UTR sequence in zebrafish and in human cells

The mechanisms of gene expression regulation are essential for cell identity and function, and their disruption usually leads to human disease. The 3 untranslated region (UTR) of mRNA contains important regulatory elements of gene expression, including upstream sequence elements (USEs) that are cis-regulatory sequences localized upstream of polyA signals (PAS). One of the best functionally characterised USEs is located in the 3UTR of the Drosophilas polo gene, which disruption leads to critical phenotypes in adult flies. In this work we found that the USE of the Drosophilas polo gene (DplUSE) is also found in in the 3UTR of vertebrate genes, including zebrafish, mouse and human genes, showing higher levels of conservation than the whole 3UTR sequence. Using reporter assays, we show that DplUSE is able to increase gene expression in vitro in human cell lines and in vivo in zebrafish embryos. Importantly, in humans, the DplUSE containing genes are enriched for genes associated to serious diseases such as Congenital abnormalities and Malignant neoplasms, illustrating the potential of this sequence to modulate genes with relevant biological functions and related with human health. Concomitantly, when sequestering the molecular machinery that operates at the DplUSE using a dominant negative strategy, we show that this is enough to dysregulate DplUSE containing genes in human cells and disrupt proper embryo development in zebrafish. Aiming to understand the molecular mechanism operating at the DplUSE, we identified three RNA binding proteins (RBP) that specifically bind to the DplUSE in vertebrates. Importantly, one of such RBPs is PTBP1, the vertebrate orthologue of the fruit flys RBP Heph, that was demonstrated to be required for the DplUSE function in Drosophila. To test if PTBP1is essential for the DplUSE function, as observed in Drosophila, we depleted PTBP1 from human cells and observed a downregulation of the expression of DplUSE containing genes, demonstrating that the molecular mechanisms that operate at DplUSE are ultra-conserved. Finally, we explored if variants in DplUSE consensus could be associated to human disease. We found a reported single nucleotide polymorphism (SNP; rs3087967) that is associated with malignant tumor of colon and generates an ectopic consensus of DplUSE in the 3 UTR of the tumorigenic POU2AF2/C11orf53 gene. We further show that this ectopic DplUSE motif causes a gain-of-function in vivo in zebrafish gut cells, suggesting its involvement in colon cancer development. These results show that a short motif present in the 3UTR of genes from phylogenetically distant bilaterians, from fruit flies to humans, control genes expression through an ultra-conserved mechanism involving RBPs binding and its dysregulation might impact in human disease.

molecular biology↗

bioRxiv2024

Ordering molecular diversity in untargeted metabolomics via molecular community networking

Natures molecular diversity is not random but displays intricate organization stemming from biological necessity. Molecular networking connects metabolites with structural similarity, enabling molecular discoveries from mass spectrometry data using arbitrary similarity thresholds that can fracture natural metabolite families. We present molecular community networking (MCN), that optimizes connectivity for each metabolite, rescuing lost relationships and capturing otherwise "hidden" metabolite connections. Using MCN, we demonstrate the discovery of novel dipeptide-conjugated bile acids.

biochemistry↗

bioRxiv2024

Scalable emulation of protein equilibrium ensembles with generative deep learning

Following the sequence and structure revolutions, predicting the dynamical mechanisms of proteins that implement biological function remains an outstanding scientific challenge. Several experimental techniques and molecular dynamics (MD) simulations can, in principle, determine conformational states, binding configurations and their probabilities, but suffer from low throughput. Here we develop a Biomolecular Emulator (BioEmu), a generative deep learning system that can generate thousands of statistically independent samples from the protein structure ensemble per hour on a single graphical processing unit. By leveraging novel training methods and vast data of protein structures, over 200 milliseconds of MD simulation, and experimental protein stabilities, BioEmus protein ensembles represent equilibrium in a range of challenging and practically relevant metrics. Qualitatively, BioEmu samples many functionally relevant conformational changes, ranging from formation of cryptic pockets, over unfolding of specific protein regions, to large-scale domain rearrangements. Quantitatively, BioEmu samples protein conformations with relative free energy errors around 1 kcal/mol, as validated against millisecond-timescale MD simulation and experimentally-measured protein stabilities. By simultaneously emulating structural ensembles and thermodynamic properties, BioEmu reveals mechanistic insights, such as the causes for fold destabilization of mutants, and can efficiently provide experimentally-testable hypotheses.

molecular biology↗

bioRxiv2018

Gene expression across tissues, sex, and life stages in the sea urchin Tripneustes gratilla

The pan-tropical sea urchin Tripneustes gratilla is an ecologically and economically important shallow water algal grazer. The aquaculture of T. gratilla has spurred growing interest in the population biology of the species, and by extension the generation of more molecular resources. To this purpose, de novo transcriptomes of T. gratilla were generated for two adults, a male and a female, as well as for a cohort of approximately 1,000 plutei larvae. Gene expression profiles of three adult tissue samples were quantified and compared. These samples were of gonadal tissue, the neural ring, and pooled tube feet and pedicellariae. Levels of shared and different gene expression between sexes, as well as across functional categories of interest, including the immune system, toxins, genes involved in fertilization, and sensory genes are highlighted. Differences in expression of Sex determining Region Y-related High Mobility Group box groups and general isoform expression between the sexes is observed. Additionally an expansion of the tumor suppressor DMBT1 was observed in T. gratilla when compared to the annotated genome of the sea urchin Strongylocentrotus purpuratus. The draft transcriptome of T. gratilla is presented here in order to facilitate more genomic level analysis of de-novo sea urchin systems.

molecular biology↗