Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors.

The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors

Exploring evidence of positive selection reveals genetic basis of meat quality traits in Berkshire pigs through whole genome sequencing

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Abstract Background Natural and artificial selection following domestication has led to the existence of more than a hundred pig breeds, as well as incredible variation in phenotypic traits. Berkshire pigs are regarded as having superior meat quality compared to other breeds. As the meat production industry seeks selective breeding approaches to improve profitable traits such as meat quality, information about genetic determinants of these traits is in high demand. However, most of the studies have been performed using trained sensory panel analysis without investigating the underlying genetic factors. Here we investigate the relationship between genomic composition and this phenotypic trait by scanning for signatures of positive selection in whole-genome sequencing data. Results We generated genomes of 10 Berkshire pigs at a total of 100.6 coverage depth, using the Illumina Hiseq2000 platform. Along with the genomes of 11 Landrace and 13 Yorkshire pigs, we identified genomic variants of 18.9 million SNVs and 3.4 million Indels in the mapped regions. We identified several associated genes related to lipid metabolism, intramuscular fatty acid deposition, and muscle fiber type which attribute to pork quality (TG, FABP1, AKIRIN2, GLP2R, TGFBR3, JPH3, ICAM2, and ERN1) by applying between population statistical tests (XP-EHH and XP-CLR). A statistical enrichment test was also conducted to detect breed specific genetic variation. In addition, de novo short sequence read assembly strategy identified several candidate genes (SLC25A14, IGF1, PI4KA, CACNA1A) as also contributing to lipid metabolism. Conclusions Results revealed several candidate genes involved in Berkshire meat quality; most of these genes are involved in lipid metabolism and intramuscular fat deposition. These results can provide a basis for future research on the genomic characteristics of Berkshire pigs

Structural Phylogenomics Reveals Gradual Evolutionary Replacement of Abiotic Chemistries by Protein Enzymes in Purine Metabolism

<div><p>The origin of metabolism has been linked to abiotic chemistries that existed in our planet at the beginning of life. While plausible chemical pathways have been proposed, including the synthesis of nucleobases, ribose and ribonucleotides, the cooption of these reactions by modern enzymes remains shrouded in mystery. Here we study the emergence of purine metabolism. The ages of protein domains derived from a census of fold family structure in hundreds of genomes were mapped onto enzymes in metabolic diagrams. We find that the origin of the nucleotide interconversion pathway benefited most parsimoniously from the prebiotic formation of adenine nucleosides. In turn, pathways of nucleotide biosynthesis, catabolism and salvage originated ∼300 million years later by concerted enzymatic recruitments and gradual replacement of abiotic chemistries. Remarkably, this process led to the emergence of the fully enzymatic biosynthetic pathway ∼3 billion years ago, concurrently with the appearance of a functional ribosome. The simultaneous appearance of purine biosynthesis and the ribosome probably fulfilled the expanding matter-energy and processing needs of genomic information.</p> </div

Timeline describing the evolution of FF domain structures and the evolution of main pathways of purine metabolism.

<p>The timeline was derived directly from the tree of FFs reconstructed from free-living organisms. Ages are given as node distances (<i>nd_FF</i>) and geological time (Gy). Time flows from top to bottom. The three evolutionary epochs of the protein world defined by Wang et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059300#pone.0059300-Wang2" target="_blank">[8]</a>, “architectural diversification” (epoch 1), “superkingdom specification” (epoch 2), and “organismal diversification” (epoch 3) are overlapped to the timeline (colored with different shades). Landmark discoveries <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059300#pone.0059300-CaetanoAnolls5" target="_blank">[18]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059300#pone.0059300-CaetanoAnolls6" target="_blank">[19]</a> are identified with circles along the timeline. The inset below describes the evolution of the 54 most ancient FFs. Stars represent the fulfillment of a full repertoire of enzymes in a central pathway.</p

Evolutionary accumulation of protein domains at FF level of structural abstraction in the central pathways of purine metabolism.

<p>Evolutionary accumulation of protein domains at FF level of structural abstraction in the central pathways of purine metabolism.</p

The purine metabolic subnetwork (NUC 00230) of MANET 2.0.

<p>Domain structures associated with individual enzymatic activities (described in EC nomenclature) are painted according to their age, in a scale of node distance (<i>nd_F</i>) that ranges from 0 (the oldest enzymes) to 1 (the most recent).</p

Early evolution of the purine metabolic network.

<p>A. Origin of nucleotide metabolism ∼3.8 Gy ago; <i>nd_FF</i>  = 0). B. Emergence of the nucleotide interconversion (INT), catabolism and salvage (CAT) and biosynthetic (BIO) pathways ∼3.5 Gy ago (<i>nd_FF</i>  = 0.061–0.073). C. Fully connected INT, BIO and CAT pathways ∼3 Gy ago (<i>nd_FF</i>  = 0.187). Pathways mediated by prebiotic chemistries that are plausible and most parsimonious are depicted in red and enable the growth of the emergent protein enzyme-mediated pathways of purine metabolism by structural and functional innovation and piecemeal recruitment (recruited FFs are indicated with numbers). Unknown candidate or withering prebiotic pathways are indicated with dashed lines. We note that primordial reactions of the BIO pathway (top of metabolic diagram) in B could have been non-operational in the absence of suitable prebiotic chemistries until later in evolution. FF structures associated with individual enzymatic activities (described in EC nomenclature) are painted according to their age, in a scale of node distance (<i>nd_FF</i>) that ranges from 0 (the oldest enzymes; ∼3.8 Gy ago) to 0.2 (∼3.0 Gy ago).</p

Synergistic and Antagonistic Interplay between Myostatin Gene Expression and Physical Activity Levels on Gene Expression Patterns in Triceps Brachii Muscles of C57/BL6 Mice

<div><p>Levels of myostatin expression and physical activity have both been associated with transcriptome dysregulation and skeletal muscle hypertrophy. The transcriptome of triceps brachii muscles from male C57/BL6 mice corresponding to two genotypes (wild-type and myostatin-reduced) under two conditions (high and low physical activity) was characterized using RNA-Seq. Synergistic and antagonistic interaction and ortholog modes of action of myostatin genotype and activity level on genes and gene pathways in this skeletal muscle were uncovered; 1,836, 238, and 399 genes exhibited significant (FDR-adjusted P-value < 0.005) activity-by-genotype interaction, genotype and activity effects, respectively. The most common differentially expressed profiles were (i) inactive myostatin-reduced relative to active and inactive wild-type, (ii) inactive myostatin-reduced and active wild-type, and (iii) inactive myostatin-reduced and inactive wild-type. Several remarkable genes and gene pathways were identified. The expression profile of nascent polypeptide-associated complex alpha subunit (Naca) supports a synergistic interaction between activity level and myostatin genotype, while Gremlin 2 (Grem2) displayed an antagonistic interaction. Comparison between activity levels revealed expression changes in genes encoding for structural proteins important for muscle function (including troponin, tropomyosin and myoglobin) and for fatty acid metabolism (some linked to diabetes and obesity, DNA-repair, stem cell renewal, and various forms of cancer). Conversely, comparison between genotype groups revealed changes in genes associated with G1-to-S-phase transition of the cell cycle of myoblasts and the expression of Grem2 proteins that modulate the cleavage of the myostatin propeptide. A number of myostatin-feedback regulated gene products that are primarily regulatory were uncovered, including microRNA impacting central functions and Piezo proteins that make cationic current-controlling mechanosensitive ion channels. These important findings extend hypotheses of myostatin and physical activity master regulation of genes and gene pathways, impacting medical practices and therapies associated with muscle atrophy in humans and companion animal species and genome-enabled selection practices applied to food-production animal species.</p></div