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1. Genome analysis of Plectus murrayi , a nematode from continental Antarctica

   https://doi.org/10.1093/g3journal/jkaa045  

   Xue, Xia; Suvorov, Anton; Fujimoto, Stanley; Dilman, Adler R; Adams, Byron J (January 2021, G3 Genes|Genomes|Genetics)

   Félix, M -A (Ed.)

   Abstract Plectus murrayi is one of the most common and locally abundant invertebrates of continental Antarctic ecosystems. Because it is readily cultured on artificial medium in the laboratory and highly tolerant to an extremely harsh environment, P. murrayi is emerging as a model organism for understanding the evolutionary origin and maintenance of adaptive responses to multiple environmental stressors, including freezing and desiccation. The de novo assembled genome of P. murrayi contains 225.741 million base pairs and a total of 14,689 predicted genes. Compared to Caenorhabditis elegans, the architectural components of P. murrayi are characterized by a lower number of protein-coding genes, fewer transposable elements, but more exons, than closely related taxa from less harsh environments. We compared the transcriptomes of lab-reared P. murrayi with wild-caught P. murrayi and found genes involved in growth and cellular processing were up-regulated in lab-cultured P. murrayi, while a few genes associated with cellular metabolism and freeze tolerance were expressed at relatively lower levels. Preliminary comparative genomic and transcriptomic analyses suggest that the observed constraints on P. murrayi genome architecture and functional gene expression, including genome decay and intron retention, may be an adaptive response to persisting in a biotically simplified, yet consistently physically harsh environment. 

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2. Detecting spatially co-expressed gene clusters with functional coherence by graph-regularized convolutional neural network

   https://doi.org/10.1093/bioinformatics/btab812  

   Song, Tianci; Markham, Kathleen K; Li, Zhuliu; Muller, Kristen E; Greenham, Kathleen; Kuang, Rui (December 2021, Bioinformatics)

   Martelli, Pier Luigi (Ed.)

   Abstract Motivation Clustering spatial-resolved gene expression is an essential analysis to reveal gene activities in the underlying morphological context by their functional roles. However, conventional clustering analysis does not consider gene expression co-localizations in tissue for detecting spatial expression patterns or functional relationships among the genes for biological interpretation in the spatial context. In this article, we present a convolutional neural network (CNN) regularized by the graph of protein–protein interaction (PPI) network to cluster spatially resolved gene expression. This method improves the coherence of spatial patterns and provides biological interpretation of the gene clusters in the spatial context by exploiting the spatial localization by convolution and gene functional relationships by graph-Laplacian regularization. Results In this study, we tested clustering the spatially variable genes or all expressed genes in the transcriptome in 22 Visium spatial transcriptomics datasets of different tissue sections publicly available from 10× Genomics and spatialLIBD. The results demonstrate that the PPI-regularized CNN constantly detects gene clusters with coherent spatial patterns and significantly enriched by gene functions with the state-of-the-art performance. Additional case studies on mouse kidney tissue and human breast cancer tissue suggest that the PPI-regularized CNN also detects spatially co-expressed genes to define the corresponding morphological context in the tissue with valuable insights. Availability and implementation Source code is available at https://github.com/kuanglab/CNN-PReg. Supplementary information Supplementary data are available at Bioinformatics online. 

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3. Gene communities in co-expression networks across different tissues

   https://doi.org/10.1371/journal.pcbi.1011616  

   Russell, Madison; Aqil, Alber; Saitou, Marie; Gokcumen, Omer; Masuda, Naoki (November 2023, PLOS Computational Biology)

   Fu, Feng (Ed.)

   With the recent availability of tissue-specific gene expression data, e.g., provided by the GTEx Consortium, there is interest in comparing gene co-expression patterns across tissues. One promising approach to this problem is to use a multilayer network analysis framework and perform multilayer community detection. Communities in gene co-expression networks reveal groups of genes similarly expressed across individuals, potentially involved in related biological processes responding to specific environmental stimuli or sharing common regulatory variations. We construct a multilayer network in which each of the four layers is an exocrine gland tissue-specific gene co-expression network. We develop methods for multilayer community detection with correlation matrix input and an appropriate null model. Our correlation matrix input method identifies five groups of genes that are similarly co-expressed in multiple tissues (a community that spans multiple layers, which we call a generalist community) and two groups of genes that are co-expressed in just one tissue (a community that lies primarily within just one layer, which we call a specialist community). We further found gene co-expression communities where the genes physically cluster across the genome significantly more than expected by chance (on chromosomes 1 and 11). This clustering hints at underlying regulatory elements determining similar expression patterns across individuals and cell types. We suggest thatKRTAP3-1,KRTAP3-3, andKRTAP3-5share regulatory elements in skin and pancreas. Furthermore, we find thatCELA3AandCELA3Bshare associated expression quantitative trait loci in the pancreas. The results indicate that our multilayer community detection method for correlation matrix input extracts biologically interesting communities of genes. 

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4. Insight into the bZIP Gene Family in Solanum tuberosum: Genome and Transcriptome Analysis to Understand the Roles of Gene Diversification in Spatiotemporal Gene Expression and Function

   https://doi.org/10.3390/ijms22010253  

   Herath, Venura; Verchot, Jeanmarie (January 2021, International Journal of Molecular Sciences)

   null (Ed.)

   The basic region-leucine zipper (bZIP) transcription factors (TFs) form homodimers and heterodimers via the coil–coil region. The bZIP dimerization network influences gene expression across plant development and in response to a range of environmental stresses. The recent release of the most comprehensive potato reference genome was used to identify 80 StbZIP genes and to characterize their gene structure, phylogenetic relationships, and gene expression profiles. The StbZIP genes have undergone 22 segmental and one tandem duplication events. Ka/Ks analysis suggested that most duplications experienced purifying selection. Amino acid sequence alignments and phylogenetic comparisons made with the Arabidopsis bZIP family were used to assign the StbZIP genes to functional groups based on the Arabidopsis orthologs. The patterns of introns and exons were conserved within the assigned functional groups which are supportive of the phylogeny and evidence of a common progenitor. Inspection of the leucine repeat heptads within the bZIP domains identified a pattern of attractive pairs favoring homodimerization, and repulsive pairs favoring heterodimerization. These patterns of attractive and repulsive heptads were similar within each functional group for Arabidopsis and S. tuberosum orthologs. High-throughput RNA-seq data indicated the most highly expressed and repressed genes that might play significant roles in tissue growth and development, abiotic stress response, and response to pathogens including Potato virus X. These data provide useful information for further functional analysis of the StbZIP gene family and their potential applications in crop improvement. 

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5. Evolution of Distinct Responses to Low NAD+ Stress by Rewiring the Sir2 Deacetylase Network in Yeasts

   https://doi.org/10.1534/genetics.120.303087  

   Humphrey, Kristen M; Zhu, Lisha; Hickman, Meleah A; Hasan, Shirin; Maria, Haniam; Liu, Tao; Rusche, Laura N (April 2020, Genetics)

   Abstract Evolutionary adaptation increases the fitness of a species in its environment. It can occur through rewiring of gene regulatory networks, such that an organism responds appropriately to environmental changes. We investigated whether sirtuin deacetylases, which repress transcription and require NAD+ for activity, serve as transcriptional rewiring points that facilitate the evolution of potentially adaptive traits. If so, bringing genes under the control of sirtuins could enable organisms to mount appropriate responses to stresses that decrease NAD+ levels. To explore how the genomic targets of sirtuins shift over evolutionary time, we compared two yeast species, Saccharomyces cerevisiae and Kluyveromyces lactis, that display differences in cellular metabolism and life cycle timing in response to nutrient availability. We identified sirtuin-regulated genes through a combination of chromatin immunoprecipitation and RNA expression. In both species, regulated genes were associated with NAD+ homeostasis, mating, and sporulation, but the specific genes differed. In addition, regulated genes in K. lactis were associated with other processes, including utilization of nonglucose carbon sources, detoxification of arsenic, and production of the siderophore pulcherrimin. Consistent with the species-restricted regulation of these genes, sirtuin deletion affected relevant phenotypes in K. lactis but not S. cerevisiae. Finally, sirtuin-regulated gene sets were depleted for broadly conserved genes, consistent with sirtuins regulating processes restricted to a few species. Taken together, these results are consistent with the notion that sirtuins serve as rewiring points that allow species to evolve distinct responses to low NAD+ stress. 

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