Cichlid fishes are famous for large, diverse and replicated adaptive radiations in the Great Lakes of East Africa. To understand the molecular mechanisms underlying cichlid phenotypic diversity, we sequenced the genomes and transcriptomes of five lineages of African cichlids: the Nile tilapia (Oreochromis niloticus), an ancestral lineage with low diversity; and four members of the East African lineage: Neolamprologus brichardi/pulcher (older radiation, Lake Tanganyika), Metriaclima zebra (recent radiation, Lake Malawi), Pundamilia nyererei (very recent radiation, Lake Victoria), and Astatotilapia burtoni (riverine species around Lake Tanganyika). We found an excess of gene duplications in the East African lineage compared to tilapia and other teleosts, an abundance of non-coding element divergence, accelerated coding sequence evolution, expression divergence associated with transposable element insertions, and regulation by novel microRNAs. In addition, we analysed sequence data from sixty individuals representing six closely related species from Lake Victoria, and show genome-wide diversifying selection on coding and regulatory variants, some of which were recruited from ancient polymorphisms. We conclude that a number of molecular mechanisms shaped East African cichlid genomes, and that amassing of standing variation during periods of relaxed purifying selection may have been important in facilitating subsequent evolutionary diversification.

Quantitative real-time polymerase chain reactions (qRT-PCR) have become the method of choice for rapid, sensitive, quantitative comparison of RNA transcript abundance. Useful data from this method depend on fitting data to theoretical curves that allow computation of mRNA levels. Calculating accurate mRNA levels requires important parameters such as reaction efficiency and the fractional cycle number at threshold (CT) to be used; however, many algorithms currently in use estimate these important parameters. Here we describe an objective method for quantifying qRT-PCR results using calculations based on the kinetics of individual PCR reactions without the need of the standard curve, independent of any assumptions or subjective judgments which allow direct calculation of efficiency and CT. We use a four-parameter logistic model to fit the raw fluorescence data as a function of PCR cycles to identify the exponential phase of the reaction. Next, we use a three-parameter simple exponent model to fit the exponential phase using an iterative nonlinear regression algorithm. Within the exponential portion of the curve, our technique automatically identifies candidate regression values using the P-value of regression and then uses a weighted average to compute a final efficiency for quantification. For CT determination, we chose the first positive second derivative maximum from the logistic model. This algorithm provides an objective and noise-resistant method for quantification of qRT-PCR results that is independent of the specific equipment used to perform PCR reactions. Keywordsquantitative polymerase chain reaction; four-parameter logistic model; three-parameter simple exponent model; noise-resistant algorithm

What specific genes and regulatory sequences contribute to the organization and functioning of brain circuits that support social behavior? How does social experience interact with information in the genome to modulate these brain circuits? Here we address these questions by highlighting progress that has been made in identifying and understanding two key "vectors of influence" that link genes, brain, and social behavior: 1) social information alters gene readout in the brain to influence behavior; and 2) genetic variation influences brain function and social behavior. We also briefly discuss how evolutionary changes in genomic elements influence social behavior and outline prospects for a systems biology of social behavior.Genes and social behavior have long had a tempestuous relationship in both science and society, and the "nature-nurture" debate is alive and well (1). This controversy persists because the relationships between genes, brain and social behavior have complex entanglements across many different timeframes, ranging from organismal development and physiology all the way to evolutionary time (Fig. 1). Genes do not specify behavior directly, but rather encode molecular products that build and govern the functioning of the brain through which behavior is expressed. Brain development, brain activity and behavior depend on both inherited and environmental influences, and there is increasing appreciation that social information can in turn impact brain gene expression and behavior. Furthermore, variation in behavior shapes the evolution of genomic elements that influence social behavior through the feedback of natural selection.

Transitive inference (TI) involves using known relationships to deduce unknown ones (for example, using A > B and B > C to infer A > C), and is thus essential to logical reasoning. First described as a developmental milestone in children, TI has since been reported in nonhuman primates, rats and birds. Still, how animals acquire and represent transitive relationships and why such abilities might have evolved remain open problems. Here we show that male fish (Astatotilapia burtoni) can successfully make inferences on a hierarchy implied by pairwise fights between rival males. These fish learned the implied hierarchy vicariously (as 'bystanders'), by watching fights between rivals arranged around them in separate tank units. Our findings show that fish use TI when trained on socially relevant stimuli, and that they can make such inferences by using indirect information alone. Further, these bystanders seem to have both spatial and featural representations related to rival abilities, which they can use to make correct inferences depending on what kind of information is available to them. Beyond extending TI to fish and experimentally demonstrating indirect TI learning in animals, these results indicate that a universal mechanism underlying TI is unlikely. Rather, animals probably use multiple domain-specific representations adapted to different social and ecological pressures that they encounter during the course of their natural lives.

Because information about gender, kin, and social status are essential for reproduction and survival, it seems likely that specialized neural mechanisms have evolved to process social information. This review describes recent studies of four aspects of social information processing: (a) perception of social signals via the vomeronasal system, (b) formation of social memory via long-term filial imprinting and short-term recognition, (c) motivation for parental behavior and pair bonding, and (d) the neural consequences of social experience. Results from these studies and some recent functional imaging studies in human subjects begin to define the circuitry of a "social brain." Such neurodevelopmental disorders as autism and schizophrenia are characterized by abnormal social cognition and corresponding deficits in social behavior; thus social neuroscience offers an important opportunity for translational research with an impact on public health.

Gonadotropin-releasing hormone (GnRH) is a decapeptide widely known for its role in regulating reproduction by serving as a signal from the hypothalamus to pituitary gonadotropes. In addition to hypothalamic GnRH (GnRH-I), a second GnRH form (pGln-His-Trp-Ser-His-GlyTrp-Tyr-Pro-Gly; GnRH-II) with unknown function has been localized to the midbrain of many vertebrates. We show here that a gene encoding GnRH-II is expressed in humans and is located on chromosome 20p13, distinct from the GnRH-I gene that is on 8p21-p11.2. The GnRH-II genomic and mRNA structures parallel those of GnRH-I. However, in contrast to GnRH-I, GnRH-II is expressed at significantly higher levels outside the brain (up to 30؋), particularly in the kidney, bone marrow, and prostate. The widespread expression of GnRH-II suggests it may have multiple functions. Molecular phylogenetic analysis shows that this second gene is likely the result of a duplication before the appearance of vertebrates, and predicts the existence of a third GnRH form in humans and other vertebrates.Gonadotropin-releasing hormone (GnRH) is a decapeptide widely known for its role in regulating reproduction. Release of GnRH from the hypothalamus controls the production of pituitary gonadotropins responsible for gonadal development and growth in all vertebrates. This function for GnRH has been highly conserved during 500 million years of vertebrate evolution despite the fact that its amino acid sequence varies by 50% (1).In addition to the hypothalamic GnRH of variable sequence, many vertebrate species have been shown to express a second, invariant GnRH form (pGln-His-Trp-Ser-His-Gly-Trp-TyrPro-Gly; GnRH-II) (2). By using antibody staining, this form of GnRH has been found in the midbrain in all species where its location has been described (reviewed in ref. 1). Furthermore, nucleic acid probes have been used to identify GnRH-II expression in the midbrain of several fish species and one mammal (1).Recently, a cDNA encoding this second form of GnRH was found in a placental mammal, the tree shrew Tupaia glis (1), thus leading us to search for it in humans. Here we describe the cloning of a cDNA encoding a second form of GnRH in humans and the subsequent isolation and sequencing of the complete human GnRH-II gene, the first description of a nonhypothalamic GnRH gene form in any species. In addition, the structure and chromosomal location of the new GnRH-II gene is compared with that of the previously described form in humans. Finally, we have constructed a molecular phylogeny of GnRH evolution, incorporating new sequence data for GnRH-II cDNAs from three placental mammals: human (this paper), tree shrew (1), and musk shrew (Suncus murinus; R.B.W., T.L.K., S. White, and R.D.F., unpublished data). MATERIALS AND METHODSLibrary Screen. A 270-nt partial cDNA for the putative human GnRH-II was cloned from human thalamus poly(A) RNA (CLONTECH) by using reverse transcription-PCR (RT-PCR) and 3Ј-RACE (rapid amplification of cDNA ends) as described (1). Oligomers flanking putative...

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Corticosteroid hormones, including the mineralocorticoids and the glucocorticoids, regulate diverse physiological functions in vertebrates. These hormones act through two classes of corticosteroid receptors (CR) that are ligand-dependent transcription factors: type I or mineralocorticoid receptor (MR) and type II or glucocorticoid receptor (GR). There is substantial overlap in the binding of these two receptor types to hormones and to DNA. In fish, the overlap in processes controlled by CRs may be different from that in other vertebrates, as fish are thought to synthesize only glucocorticoids, whereas they express both GR and MR. Here we describe the characterization of four CRs in a cichlid fish, Haplochromis burtoni: a previously undescribed GR (HbGR1), another GR expressed in two splice isoforms (HbGR2a and HbGR2b), and an MR (HbMR). Sequence comparison and phylogenetic analysis showed that these CRs sort naturally into GR and MR groups, and that the GR duplication we describe will probably be common to all teleosts. Quantitative PCR revealed differential patterns of CR tissue expression in organs dependent on corticosteroid action. Trans-activation assays demonstrated that the CRs were selective for corticosteroid hormones and showed that the HbMR was similar to mammalian MRs in being more sensitive to both cortisol and aldosterone than the GRs. Additionally, the two HbGR2 isoforms were expressed uniquely in different tissues and were functionally distinct in their actions on classical GR-sensitive promoters. The identification of four CR subtypes in teleosts suggests a more complicated corticosteroid signaling in fish than previously recognized.