Characterizing Transcriptional Networks in Male Rainbow Darter (Etheostoma caeruleum) that Regulate Testis Development over a Complete Reproductive Cycle

Dissecting the dynamic cellular transcriptional atlas of adult teleost testis development throughout the annual reproductive cycle

Teleost testis development during the annual cycle involves dramatic changes in cellular compositions and molecular events. In this study, the testicular cells derived from adult black rockfish at distinct stages - regressed, regenerating and differentiating - were meticulously dissected via single-cell transcriptome sequencing. A continuous developmental trajectory of spermatogenic cells, from spermatogonia to spermatids, was delineated, elucidating the molecular events involved in spermatogenesis. Subsequently, the dynamic regulation of gene expression associated with spermatogonia proliferation and differentiation was observed across spermatogonia subgroups and developmental stages. A bioenergetic transition from glycolysis to mitochondrial respiration of spermatogonia during the annual developmental cycle was demonstrated, and a deeper level of heterogeneity and molecular characteristics was revealed by re-clustering analysis. Additionally, the developmental trajectory of Sertoli cells was delineated, alongside the divergence of Leydig cells and macrophages. Moreover, the interaction network between testicular micro-environment somatic cells and spermatogenic cells was established. Overall, our study provides detailed information on both germ and somatic cells within teleost testes during the annual reproductive cycle, which lays the foundation for spermatogenesis regulation and germplasm preservation of endangered species.

Transcriptomes of Testes at Different Developmental Stages in the Opsariichthys bidens Predict Key Genes for Testis Development and Spermatogenesis

Testis development is a complex process involving multiple genes, and the molecular mechanisms underlying testis development in Opsariichthys bidens remain unclear. We performed transcriptome sequencing analysis on a total of 12 samples of testes from stages II, III, IV, and V of O. bidens and obtained a total of 79.52 Gb clean data, as well as 288,573 transcripts and 116,215 unigenes. Differential expression analysis showed that 22,857 differentially expressed genes (DEGs) were screened in six comparison groups (III vs. II, IV vs. II, V vs. II, IV vs. III, V vs. III, and V vs. IV). Kyoto Encyclopedia of Genes and Genomes enrichment analysis of DEGs showed that six comparison groups were significantly enriched for a total of 20 significantly up- or down-regulated pathways, including six pathways related to signal transduction, three pathways related to energy metabolism, five pathways related to disease, and two pathways related to ribosomes. Furthermore, our investigation revealed that DEGs were enriched in several important functional pathways, such as Huntington's disease signaling pathway, TGF-β signaling pathway, and ribosome signaling pathway. Protein-protein interaction network analysis of DEGs identified 63 up-regulated hub genes, including 9 kinesin genes and 2 cytoplasmic dynein genes, and 39 down-regulated hub genes, including 13 ribosomal protein genes. This result contributes to the knowledge of spermatogenesis and testis development in O. bidens.

Biological networks across scales

Many biological systems across scales of size and complexity exhibit a time-varying complex network structure that emerges and self-organizes as a result of interactions with the environment. Network interactions optimize some intrinsic cost functions that are unknown and involve for example energy efficiency, robustness, resilience, and frailty. A wide range of networks exist in biology, from gene regulatory networks important for organismal development, protein interaction networks that govern physiology and metabolism, and neural networks that store and convey information to networks of microbes that form microbiomes within hosts, animal contact networks that underlie social systems, and networks of populations on the landscape connected by migration. Increasing availability of extensive (big) data is amplifying our ability to quantify biological networks. Similarly, theoretical methods that describe network structure and dynamics are being developed. Beyond static networks representing snapshots of biological systems, collections of longitudinal data series can help either at defining and characterizing network dynamics over time or analyzing the dynamics constrained to networked architectures. Moreover, due to interactions with the environment and other biological systems, a biological network may not be fully observable. Also, subnetworks may emerge and disappear as a result of the need for the biological system to cope with for example invaders or new information flows. The confluence of these developments renders tractable the question of how the structure of biological networks predicts and controls network dynamics. In particular, there may be structural features that result in homeostatic networks with specific higher-order statistics (e.g., multifractal spectrum), which maintain stability over time through robustness and/or resilience to perturbation. Alternative, plastic networks may respond to perturbation by (adaptive to catastrophic) shifts in structure. Here, we explore the opportunity for discovering universal laws connecting the structure of biological networks with their function, positioning them on the spectrum of time-evolving network structure, i.e. dynamics of networks, from highly stable to exquisitely sensitive to perturbation. If such general laws exist, they could transform our ability to predict the response of biological systems to perturbations-an increasingly urgent priority in the face of anthropogenic changes to the environment that affect life across the gamut of organizational scales.

Footprints of local adaptation span hundreds of linked genes in the Atlantic silverside genome

The study of local adaptation in the presence of ongoing gene flow is the study of natural selection in action, revealing the functional genetic diversity most relevant to contemporary pressures. In addition to individual genes, genome‐wide architecture can itself evolve to enable adaptation. Distributed across a steep thermal gradient along the east coast of North America, Atlantic silversides (Menidia menidia) exhibit an extraordinary degree of local adaptation in a suite of traits, and the capacity for rapid adaptation from standing genetic variation, but we know little about the patterns of genomic variation across the species range that enable this remarkable adaptability. Here, we use low‐coverage, whole‐transcriptome sequencing of Atlantic silversides sampled along an environmental cline to show marked signatures of divergent selection across a gradient of neutral differentiation. Atlantic silversides sampled across 1371 km of the southern section of its distribution have very low genome‐wide differentiation (median F_ST = 0.006 across 1.9 million variants), consistent with historical connectivity and observations of recent migrants. Yet almost 14,000 single nucleotide polymorphisms (SNPs) are nearly fixed (F_ST > 0.95) for alternate alleles. Highly differentiated SNPs cluster into four tight linkage disequilibrium (LD) blocks that span hundreds of genes and several megabases. Variants in these LD blocks are disproportionately nonsynonymous and concentrated in genes enriched for multiple functions related to known adaptations in silversides, including variation in lipid storage, metabolic rate, and spawning behavior. Elevated levels of absolute divergence and demographic modeling suggest selection maintaining divergence across these blocks under gene flow. These findings represent an extreme case of heterogeneity in levels of differentiation across the genome, and highlight how gene flow shapes genomic architecture in continuous populations. Locally adapted alleles may be common features of populations distributed along environmental gradients, and will likely be key to conserving variation to enable future responses to environmental change.

Characterizing transcriptome in female scallop Chlamys farreri provides new insights into the molecular mechanisms of reproductive regulation during ovarian development and spawn

Bivalve mollusks are descendants of an early-Cambrian lineage and have successfully evolved unique strategies for reproduction. Nonetheless, the molecular mechanisms underlying reproductive regulation in mollusks remain to be elucidated. In this study, transcriptomes of ovary at four reproductive stages in female Chlamys farreri were characterized by RNA-Seq. Regarding signaling pathways, ECM-receptor interaction pathway, mTOR signaling pathway, Fanconi anemia pathway, FoxO signaling pathway, Wnt signaling pathway and Hedgehog signaling pathway were enriched during ovarian development processes. In addition, pathways related to energy metabolism such as Nitrogen metabolism and Arachidonic acid metabolism were enriched at spawn stage. Interestingly, Neuroactive ligand-receptor interaction was significantly enriched involved in ovarian development and spawn, and indicated the potential functions of nervous system on reproductive regulation in C. farreri. What's more, this study identified and characterized fourteen genes involved in "sex hormones synthesis and regulation", "ovarian development and spawn" and "maternal immunity" during the four reproductive stages in C. farreri. We determined that CYP17 uniquely affected gamete release by influencing the physiological balance among the steroid hormones and showed that receptors of the 5-HT and GABA neurotransmitters were tightly associated with ovarian maturation. Furthermore, to the best of our knowledge, this is the first study to report the maternal effect gene Zar1 in bivalve mollusks, likewise the maternal immunity genes displayed coordinated and cooperative expression during reproductive periods, which strengthened the environmental adaptation mechanisms of bivalves. Taken together, this study provides the first dynamic transcriptomic analysis of C. farreri at four key reproductive stages, which will assist in revealing the molecular mechanisms underlying bivalves on reproductive regulation in ovarian development and spawn.

Transcriptome Dynamics During Turbot Spermatogenesis Predicting the Potential Key Genes Regulating Male Germ Cell Proliferation and Maturation

Spermatogenesis is a dynamic developmental process in which spermatogonial stem cells proliferate, differentiate and mature into functional spermatozoa. These processes require an accurate gene regulation network. Here, we investigated the dynamic changes that occur during spermatogenesis through a combination of histological and transcriptome analyses of different developmental stages of the testis. We constructed 18 testis transcriptome libraries, and the average length, N50, and GC content of the unigenes were 1,795 bp; 3,240 bp and 49.25%, respectively. Differentially expressed genes (DEGs) that were related to germ cell proliferation and maturation, such as NANOS3, RARs, KIFs, steroid hormone synthesis-related genes and receptor genes, were identified between pairs of testis at different developmental stages. Gene ontology annotation and pathway analyses were conducted on DEGs with specific expression patterns involved in the regulation of spermatogenesis. Nine important pathways such as steroid hormone biosynthesis related to spermatogenesis were identified. A total of 21 modules that ranged from 49 to 7,448 genes were designed by a weighted gene co-expression network analysis. Furthermore, a total of 83 candidate miRNA were identified by computational methods. Our study provides the first transcriptomic evidence for differences in gene expression between different developmental stages of spermatogenesis in turbot (Scophthalmus maximus).

Are we closer to the vision? A proposed framework for incorporating omics into environmental assessments

Environmental science has benefited a great deal from omics-based technologies. High-throughput toxicology has defined adverse outcome pathways (AOPs), prioritized chemicals of concern, and identified novel actions of environmental chemicals. While many of these approaches are conducted under rigorous laboratory conditions, a significant challenge has been the interpretation of omics data in "real-world" exposure scenarios. Clarity in the interpretation of these data limits their use in environmental monitoring programs. In recent years, one overarching objective of many has been to address fundamental questions concerning experimental design and the robustness of data collected under the broad umbrella of environmental genomics. These questions include: (1) the likelihood that molecular profiles return to a predefined baseline level following remediation efforts, (2) how reference site selection in an urban environment influences interpretation of omics data and (3) what is the most appropriate species to monitor in the environment from an omics point of view. In addition, inter-genomics studies have been conducted to assess transcriptome reproducibility in toxicology studies. One lesson learned from inter-genomics studies is that there are core molecular networks that can be identified by multiple laboratories using the same platform. This supports the idea that "omics-networks" defined a priori may be a viable approach moving forward for evaluating environmental impacts over time. Both spatial and temporal variability in ecosystem structure is expected to influence molecular responses to environmental stressors, and it is important to recognize how these variables, as well as individual factor (i.e. sex, age, maturation), may confound interpretation of network responses to chemicals. This mini-review synthesizes the progress made towards adopting these tools into environmental monitoring and identifies future challenges to be addressed, as we move into the next era of high throughput sequencing. A conceptual framework for validating and incorporating molecular networks into environmental monitoring programs is proposed. As AOPs become more defined and their potential in environmental monitoring assessments becomes more recognized, the AOP framework may prove to be the conduit between omics and penultimate ecological responses for environmental risk assessments.