An atlas of human long non-coding RNAs with accurate 5' ends.

Long non-coding RNAs (lncRNAs) are largely heterogeneous and functionally uncharacterized. Here, using FANTOM5 cap analysis of gene expression (CAGE) data, we integrate multiple transcript collections to generate a comprehensive atlas of 27,919 human lncRNA genes with high-confidence 5' ends and expression profiles across 1,829 samples from the major human primary cell types and tissues. Genomic and epigenomic classification of these lncRNAs reveals that most intergenic lncRNAs originate from enhancers rather than from promoters. Incorporating genetic and expression data, we show that lncRNAs overlapping trait-associated single nucleotide polymorphisms are specifically expressed in cell types relevant to the traits, implicating these lncRNAs in multiple diseases. We further demonstrate that lncRNAs overlapping expression quantitative trait loci (eQTL)-associated single nucleotide polymorphisms of messenger RNAs are co-expressed with the corresponding messenger RNAs, suggesting their potential roles in transcriptional regulation. Combining these findings with conservation data, we identify 19,175 potentially functional lncRNAs in the human genome.

Variable-order sequence modeling improves bacterial strain discrimination for Ion Torrent DNA reads.

BACKGROUND: Genome sequencing provides a powerful tool for pathogen detection and can help resolve outbreaks that pose public safety and health risks. Mapping of DNA reads to genomes plays a fundamental role in this approach, where accurate alignment and classification of sequencing data is crucial. Standard mapping methods crudely treat bases as independent from their neighbors. Accuracy might be improved by using higher order paired hidden Markov models (HMMs), which model neighbor effects, but introduce design and implementation issues that have typically made them impractical for read mapping applications. We present a variable-order paired HMM that we term VarHMM, which addresses central issues involved with higher order modeling for sequence alignment. RESULTS: Compared with existing alignment methods, VarHMM is able to model higher order distributions and quantify alignment probabilities with greater detail and accuracy. In a series of comparison tests, in which Ion Torrent sequenced DNA was mapped to similar bacterial strains, VarHMM consistently provided better strain discrimination than any of the other alignment methods that we compared with. CONCLUSIONS: Our results demonstrate the advantages of higher ordered probability distribution modeling and also suggest that further development of such models would benefit read mapping in a range of other applications as well.

Sexually dimorphic activation of dopaminergic areas depends on affiliation during courtship and pair formation.

For many species, dyadic interaction during courtship and pair bonding engage intense emotional states that control approach or avoidance behavior. Previous studies have shown that one component of a common social brain network (SBN), dopaminergic areas, are highly engaged during male songbird courtship of females. We tested whether the level of activity in dopaminergic systems of both females and males during courtship is related to their level of affiliation. In order to objectively quantify affiliative behaviors, we developed a system for tracking the position of both birds during free interaction sessions. During a third successive daily interaction session, there was a range of levels of affiliation among bird pairs, as quantified by several position and movement parameters. Because both positive and negative social interactions were present, we chose to characterize affiliation strength by pair valence. As a potential neural system involved in regulating pair valence, the level of activity of the dopaminergic group A11 (within the central gray) was selectively reduced in females of positive valence pairs. Further, activation of non-dopaminergic neurons in VTA was negatively related to valence, with this relationship strongest in ventral VTA of females. Together, these results suggest that inhibition of fear or avoidance networks may be associated with development of close affiliation, and highlight the importance of negative as well as positive emotional states in the process of courtship, and in development of long-lasting social bonds.

Singing-related activity in anterior forebrain of male zebra finches reflects courtship motivation for target females.

A critical function of singing by male songbirds is to attract a female mate. Previous studies have suggested that the anterior forebrain system is involved in this courtship behavior. Neural activity in this system, including the striatal Area X, is strikingly dependent on the function of male singing. When males sing to attract a female bird rather than while alone, less variable neural activity results in less variable song spectral features, which may be attractive to the female. These characteristics of neural activity and singing thus may reflect a male's motivation for courtship. Here, we compared the variability of neural activity and song features between courtship singing directed to a female with whom a male had previously formed a pair-bond or to other females. Surprisingly, across all units, there was no clear tendency for a difference in variability of neural activity or song features between courtship of paired females, nonpaired females, or dummy females. However, across the population of recordings, there was a significant relationship between the relative variability of syllable frequency and neural activity: when syllable frequency was less variable to paired than nonpaired females, neural activity was also less variable (and vice-versa). These results show that the lower variability of neural activity and syllable frequency during directed singing is not a binary distinction from undirected singing, but can vary in intensity, possibly related to the relative preference of a male for his singing target.