Arginine vasopressin influences male reproductive and social behaviours in several vertebrate taxa through its actions at the V1a receptor in the brain. The neuroanatomical distribution of vasopressin V1a receptors varies greatly between species with different forms of social organization. Here we show that centrally administered arginine vasopressin increases affiliative behaviour in the highly social, monogamous prairie vole, but not in the relatively asocial, promiscuous montane vole. Molecular analyses indicate that gene duplication and/or changes in promoter structure of the prairie vole receptor gene may contribute to the species differences in vasopressin-receptor expression. We further show that mice that are transgenic for the prairie vole receptor gene have a neuroanatomical pattern of receptor binding that is similar to that of the prairie vole, and exhibit increased affiliative behaviour after injection with arginine vasopressin. These data indicate that the pattern of V1a-receptor gene expression in the brain may be functionally associated with species-typical social behaviours in male vertebrates.
Massively parallel DNA sequencing offers many benefits, but major inhibitory cost factors include: (1) start-up (i.e., purchasing initial reagents and equipment); (2) buy-in (i.e., getting the smallest possible amount of data from a run); and (3) sample preparation. Reducing sample preparation costs is commonly addressed, but start-up and buy-in costs are rarely addressed. We present dual-indexing systems to address all three of these issues. By breaking the library construction process into universal, re-usable, combinatorial components, we reduce all costs, while increasing the number of samples and the variety of library types that can be combined within runs. We accomplish this by extending the Illumina TruSeq dual-indexing approach to 768 (384 + 384) indexed primers that produce 384 unique dual-indexes or 147,456 (384 × 384) unique combinations. We maintain eight nucleotide indexes, with many that are compatible with Illumina index sequences. We synthesized these indexing primers, purifying them with only standard desalting and placing small aliquots in replicate plates. In qPCR validation tests, 206 of 208 primers tested passed (99% success). We then created hundreds of libraries in various scenarios. Our approach reduces start-up and per-sample costs by requiring only one universal adapter that works with indexed PCR primers to uniquely identify samples. Our approach reduces buy-in costs because: (1) relatively few oligonucleotides are needed to produce a large number of indexed libraries; and (2) the large number of possible primers allows researchers to use unique primer sets for different projects, which facilitates pooling of samples during sequencing. Our libraries make use of standard Illumina sequencing primers and index sequence length and are demultiplexed with standard Illumina software, thereby minimizing customization headaches. In subsequent Adapterama papers, we use these same primers with different adapter stubs to construct amplicon and restriction-site associated DNA libraries, but their use can be expanded to any type of library sequenced on Illumina platforms.
A model-driven discovery process, Computing Life, is used to identify an ensemble of genetic networks that describe the biological clock. A clock mechanism involving the genes white-collar-1 and white-collar-2 (wc-1 and wc-2) that encode a transcriptional activator (as well as a blue-light receptor) and an oscillator frequency (frq) that encodes a cyclin that deactivates the activator is used to guide this discovery process through three cycles of microarray experiments. Central to this discovery process is a new methodology for the rational design of a Maximally Informative Next Experiment (MINE), based on the genetic network ensemble. In each experimentation cycle, the MINE approach is used to select the most informative new experiment in order to mine for clock-controlled genes, the outputs of the clock. As much as 25% of the N. crassa transcriptome appears to be under clock-control. Clock outputs include genes with products in DNA metabolism, ribosome biogenesis in RNA metabolism, cell cycle, protein metabolism, transport, carbon metabolism, isoprenoid (including carotenoid) biosynthesis, development, and varied signaling processes. Genes under the transcription factor complex WCC ( = WC-1/WC-2) control were resolved into four classes, circadian only (612 genes), light-responsive only (396), both circadian and light-responsive (328), and neither circadian nor light-responsive (987). In each of three cycles of microarray experiments data support that wc-1 and wc-2 are auto-regulated by WCC. Among 11,000 N. crassa genes a total of 295 genes, including a large fraction of phosphatases/kinases, appear to be under the immediate control of the FRQ oscillator as validated by 4 independent microarray experiments. Ribosomal RNA processing and assembly rather than its transcription appears to be under clock control, suggesting a new mechanism for the post-transcriptional control of clock-controlled genes.
Arginine vasopressin modulates a number of species-typical social behaviors, including social memory in rats, scent marking and aggressive behavior in hamsters, and partner preference formation and paternal behavior in monogamous rodents. The distribution of V1a receptor binding sites in the brain varies greatly among species. Using in situ hybridization in 2 species of voles with strikingly different patterns of V1a binding sites and social behaviors, the authors demonstrate that differences in V1a receptor binding sites are due to species differences in regional V1a receptor gene expression. It is then demonstrated that the differences in receptor gene expression are associated with species differences in behavioral response to centrally administered vasopressin. Together, these data suggest that the phylogenetic plasticity of central neurohypophyseal peptide receptor expression may contribute to the evolution of species-typical social behaviors.
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