Where are the cores in this thing? …and what are they computing?

Evolution conserves components below, and goals above, the levels for circuits and computations. This work presents evidence consistent with similar evolutionary conservation of a small, possibly canonical number of circuits and computations, and cites some historical interest in this idea. Electronic circuits are examples of what we would like to know. There are several strikingly common features of nervous systems that may be both conserved and computational essential. There is always a null hypothesis, and the work acknowledges the possibility that computation itself is ad-hoc in multiple areas and nervous systems, and not itself a conserved property. But we don’t know, and we should.

Highly Conserved Evolution of Aquaporin PIPs and TIPs Confers Their Crucial Contribution to Flowering Process in Plants

Flowering is the key process for the sexual reproduction in seed plants. In gramineous crops, the process of flowering, which includes the actions of both glume opening and glume closing, is directly driven by the swelling and withering of lodicules due to the water flow into and out of lodicule cells. All these processes are considered to be controlled by aquaporins, which are the essential transmembrane proteins that facilitate the transport of water and other small molecules across the biological membranes. In the present study, the evolution of aquaporins and their contribution to flowering process in plants were investigated via an integration of genome-wide analysis and gene expression profiling. Across the barley genome, we found that HvTIP1;1, HvTIP1;2, HvTIP2;3, and HvPIP2;1 were the predominant aquaporin genes in lodicules and significantly upregulated in responding to glume opening and closing, suggesting the importance of them in the flowering process of barley. Likewise, the putative homologs of the above four aquaporin genes were also abundantly expressed in lodicules of the other monocots like rice and maize and in petals of eudicots like cotton, tobacco, and tomato. Furthermore, all of them were mostly upregulated in responding to the process of floret opening, indicating a conserved function of these aquaporin proteins in plant flowering. The phylogenetic analysis based on the OneKP database revealed that the homologs of TIP1;1, TIP1;2, TIP2;3, and PIP2;1 were highly conserved during the evolution, especially in the angiosperm species, in line with their conserved function in controlling the flowering process. Taken together, it could be concluded that the highly evolutionary conservation of TIP1;1, TIP1;2, TIP2;3 and PIP2;1 plays important roles in the flowering process for both monocots and eudicots.

Molecular Evolution of Lysine Biosynthesis in Agaricomycetes

As an indispensable essential amino acid in the human body, lysine is extremely rich in edible mushrooms. The α-aminoadipic acid (AAA) pathway is regarded as the biosynthetic pathway of lysine in higher fungal species in Agaricomycetes. However, there is no deep understanding about the molecular evolutionary relationship between lysine biosynthesis and species in Agaricomycetes. Herein, we analyzed the molecular evolution of lysine biosynthesis in Agaricomycetes. The phylogenetic relationships of 93 species in 34 families and nine orders in Agaricomycetes were constructed with six sequences of LSU, SSU, ITS (5.8 S), RPB1, RPB2, and EF1-α datasets, and then the phylogeny of enzymes involved in the AAA pathway were analyzed, especially homocitrate synthase (HCS), α-aminoadipate reductase (AAR), and saccharopine dehydrogenase (SDH). We found that the evolution of the AAA pathway of lysine biosynthesis is consistent with the evolution of species at the order level in Agaricomycetes. The conservation of primary, secondary, predicted tertiary structures, and substrate-binding sites of the enzymes of HCS, AAR, and SDH further exhibited the evolutionary conservation of lysine biosynthesis in Agaricomycetes. Our results provide a better understanding of the evolutionary conservation of the AAA pathway of lysine biosynthesis in Agaricomycetes.

Long-range promoter-enhancer contacts are conserved during evolution and contribute to gene expression robustness

Gene expression is regulated through complex molecular interactions, involving cis-acting elements that can be situated far away from their target genes. Data on long-range contacts between promoters and regulatory elements is rapidly accumulating. However, it remains unclear how these regulatory relationships evolve and how they contribute to the establishment of robust gene expression profiles. Here, we address these questions by comparing genome-wide maps of promoter-centered chromatin contacts in mouse and human. We show that there is significant evolutionary conservation of cis-regulatory landscapes, indicating that selective pressures act to preserve not only regulatory element sequences but also their chromatin contacts with target genes. The extent of evolutionary conservation is remarkable for long-range promoter-enhancer contacts, illustrating how the structure of regulatory landscapes constrains large-scale genome evolution. We show that the evolution of cis-regulatory landscapes, measured in terms of distal element sequences, synteny or contacts with target genes, is significantly associated with gene expression evolution.

ENNGene: an Easy Neural Network model building tool for Genomics

Background: The recent big data revolution in Genomics, coupled with the emergence of Deep Learning as a set of powerful machine learning methods, has shifted the standard practices of machine learning for Genomics. Even though Deep Learning methods such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are becoming widespread in Genomics, developing and training such models is outside the ability of most researchers in the field. Results: Here we present ENNGene - Easy Neural Network model building tool for Genomics. This tool simplifies training of custom CNN or hybrid CNN-RNN models on genomic data via an easy-to-use Graphical User Interface. ENNGene allows multiple input branches, including sequence, evolutionary conservation, and secondary structure, and performs all the necessary preprocessing steps, allowing simple input such as genomic coordinates. The network architecture is selected and fully customized by the user, from the number and types of the layers to each layer's precise set-up. ENNGene then deals with all steps of training and evaluation of the model, exporting valuable metrics such as multi-class ROC and precision-recall curve plots or TensorBoard log files. To facilitate interpretation of the predicted results, we deploy Integrated Gradients, providing the user with a graphical representation of an attribution level of each input position. To showcase the usage of ENNGene, we train multiple models on the RBP24 dataset, quickly reaching the state of the art while improving the performance on more than half of the proteins by including the evolutionary conservation score and tuning the network per protein. Conclusions: As the role of DL in big data analysis in the near future is indisputable, it is important to make it available for a broader range of researchers. We believe that an easy-to-use tool such as ENNGene can allow Genomics researchers without a background in Computational Sciences to harness the power of DL to gain better insights into and extract important information from the large amounts of data available in the field.

Pre-metazoan origin of neuropeptide signalling

Neuropeptides are a diverse class of signalling molecules in metazoans. They occur in all animals with a nervous system and also in neuron-less placozoans. However, their origin has remained unclear because no neuropeptide shows deep homology across lineages and none have been found in sponges. Here, we identify two neuropeptide precursors, phoenixin and nesfatin, with broad evolutionary conservation. By database searches, sequence alignments and gene-structure comparisons we show that both precursors are present in bilaterians, cnidarians, ctenophores and sponges. We also found phoenixin and a secreted nesfatin precursor homolog in the choanoflagellate Salpingoeca rosetta. Phoenixin in particular, is highly conserved, including its cleavage sites, suggesting that prohormone processing occurs also in choanoflagellates. In addition, based on phyletic patterns and negative pharmacological assays we question the originally proposed GPR-173 (SREB3) as a phoenixin receptor. Our findings indicate that signalling by secreted neuropeptide homologs has pre-metazoan origins and thus evolved before neurons.

First person – Emma Lacroix

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Emma Lacroix is first author on ‘Evolutionary conservation of systemic and reversible amyloid aggregation’, published in JCS. Emma is a PhD student in the lab of Dr Tim Audas at Simon Fraser University, Burnaby, Canada, investigating stress-induced physiological amyloid aggregation.