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High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species1-4. To address this issue, the international Genome 10K (G10K) consortium5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences.

Our understanding of bird song, a model system for animal communication and the neurobiology of learning, depends critically on making reliable, validated comparisons between the complex multidimensional syllables that are used in songs. However, most assessments of song similarity are based on human inspection of spectrograms, or computational methods developed from human intuitions. Using a novel automated operant conditioning system, we collected a large corpus of zebra finches' (Taeniopygia guttata) decisions about song syllable similarity. We use this dataset to compare and externally validate similarity algorithms in widely-used publicly available software (Raven, Sound Analysis Pro, Luscinia). Although these methods all perform better than chance, they do not closely emulate the avian assessments. We then introduce a novel deep learning method that can produce perceptual similarity judgements trained on such avian decisions. We find that this new method outperforms the established methods in accuracy and more closely approaches the avian assessments. Inconsistent (hence ambiguous) decisions are a common occurrence in animal behavioural data; we show that a modification of the deep learning training that accommodates these leads to the strongest performance. We argue this approach is the best way to validate methods to compare song similarity, that our dataset can be used to validate novel methods, and that the general approach can easily be extended to other species. Author summary: How do birds hear the differences between their songs? This fascinating question carries implications, since the study of bird song, a model system for the neurobiology of learning and animal communication, depends critically on our ability to assess the similarity of songs. Traditionally, researchers compare sounds by human assessment, or use computational methods based on human intuitions about similarity. However, neither approach is connected to birds' own perception of sound similarity. Here, using a novel automated operant conditioning system, we recorded many thousands of acoustic judgments of similarity from zebra finches, and used this perceptual decision data for the first time to train a deep learning system. The trained system outperforms other computational methods for the task of making the same judgments as birds. This algorithm to compare song similarity, together with the potential of extending the general approach to other species, places the study of bird song on a firmer footing. [ABSTRACT FROM AUTHOR]

Emberizid sparrows (emberizidae) have played a prominent role in the study of avian vocal communication and social behavior. We present here brain transcriptomes for three emberizid model systems, song sparrow Melospiza melodia, white-throated sparrow Zonotrichia albicollis, and Gambel's white-crowned sparrow Zonotrichia leucophrys gambelii. Each of the assemblies covered fully or in part, over 89% of the previously annotated protein coding genes in the zebra finch Taeniopygia guttata, with 16,846, 15,805, and 16,646 unique BLAST hits in song, white-throated and white-crowned sparrows, respectively. As in previous studies, we find tissue of origin (auditory forebrain versus hypothalamus and whole brain) as an important determinant of overall expression profile. We also demonstrate the successful isolation of RNA and RNA-sequencing from post-mortem samples from building strikes and suggest that such an approach could be useful when traditional sampling opportunities are limited. These transcriptomes will be an important resource for the study of social behavior in birds and for data driven annotation of forthcoming whole genome sequences for these and other bird species.

BackgroundSongbirds hold great promise for biomedical, environmental and evolutionary research. A complete draft sequence of the zebra finch genome is imminent, yet a need remains for application of genomic resources within a research community traditionally focused on ethology and neurobiological methods. In response, we developed a core set of genomic tools and a novel collaborative strategy to probe gene expression in diverse songbird species and natural contexts.ResultsWe end-sequenced cDNAs from zebra finch brain and incorporated additional sequences from community sources into a database of 86,784 high quality reads. These assembled into 31,658 non-redundant contigs and singletons, which we annotated via BLAST search of chicken and human databases. The results are publicly available in the ESTIMA:Songbird database. We produced a spotted cDNA microarray with 20,160 addresses representing 17,214 non-redundant products of an estimated 11,500-15,000 genes, validating it by analysis of immediate-early gene (zenk) gene activation following song exposure and by demonstrating effective cross hybridization to genomic DNAs of other songbird species in the Passerida Parvorder. Our assembly was also used in the design of the "Lund-zfa" Affymetrix array representing approximately 22,000 non-redundant sequences. When the two arrays were hybridized to cDNAs from the same set of male and female zebra finch brain samples, both arrays detected a common set of regulated transcripts with a Pearson correlation coefficient of 0.895. To stimulate use of these resources by the songbird research community and to maintain consistent technical standards, we devised a "Community Collaboration" mechanism whereby individual birdsong researchers develop experiments and provide tissues, but a single individual in the community is responsible for all RNA extractions, labelling and microarray hybridizations.ConclusionImmediately, these results set the foundation for a coordinated set of 25 planned experiments by 16 research groups probing fundamental links between genome, brain, evolution and behavior in songbirds. Energetic application of genomic resources to research using songbirds should help illuminate how complex neural and behavioral traits emerge and evolve.

BackgroundIn animals with heteromorphic sex chromosomes, dosage compensation of sex-chromosome genes is thought to be critical for species survival. Diverse molecular mechanisms have evolved to effectively balance the expressed dose of X-linked genes between XX and XY animals, and to balance expression of X and autosomal genes. Dosage compensation is not understood in birds, in which females (ZW) and males (ZZ) differ in the number of Z chromosomes.ResultsUsing microarray analysis, we compared the male:female ratio of expression of sets of Z-linked and autosomal genes in two bird species, zebra finch and chicken, and in two mammalian species, mouse and human. Male:female ratios of expression were significantly higher for Z genes than for autosomal genes in several finch and chicken tissues. In contrast, in mouse and human the male:female ratio of expression of X-linked genes is quite similar to that of autosomal genes, indicating effective dosage compensation even in humans, in which a significant percentage of genes escape X-inactivation.ConclusionBirds represent an unprecedented case in which genes on one sex chromosome are expressed on average at constitutively higher levels in one sex compared with the other. Sex-chromosome dosage compensation is surprisingly ineffective in birds, suggesting that some genomes can do without effective sex-specific sex-chromosome dosage compensation mechanisms.

Synuclein proteins are produced, in vertebrates, by three genes. They share structural resemblance to apolipoproteins, but are abundant in the neuronal cytosol and present in enriched amounts at presynaptic terminals. Synucleins have been specifically implicated in three diseases: Alzheimer's (AD), Parkinson's (PD) and breast cancer. In AD, a peptide derived from [Alpha]-synuclein forms an intrinsic component of plaque amyloid. In PD, an [Alpha]-synuclein allele is genetically linked to several independent familial cases, and the protein appears to accumulate in Lewy bodies. In breast cancer, increased expression of [Gamma]-synuclein correlates with disease progression. In songbirds, [Alpha]-synuclein expression is correlated with plasticity in the developing song control system. Although the normal function of synucleins is unknown, a role in membrane plasticity seems likely.

Abstract Background Production of contextually appropriate social behaviors involves integrated activity across many brain regions. Many songbird species produce complex vocalizations called ‘songs’ that serve to attract potential mates, defend territories, and/or maintain flock cohesion. There are a series of discrete interconnect brain regions that are essential for the successful production of song. The probability and intensity of singing behavior is influenced by the reproductive state. The objectives of this study were to examine the broad changes in gene expression in brain regions that control song production with a brain region that governs the reproductive state. Results We show using microarray cDNA analysis that two discrete brain systems that are both involved in governing singing behavior show markedly different gene expression profiles. We found that cortical and basal ganglia-like brain regions that control the socio-motor production of song in birds exhibit a categorical switch in gene expression that was dependent on their reproductive state. This pattern is in stark contrast to the pattern of expression observed in a hypothalamic brain region that governs the neuroendocrine control of reproduction. Subsequent gene ontology analysis revealed marked variation in the functional categories of active genes dependent on reproductive state and anatomical localization. HVC, one cortical-like structure, displayed significant gene expression changes associated with microtubule and neurofilament cytoskeleton organization, MAP kinase activity, and steroid hormone receptor complex activity. The transitions observed in the preoptic area, a nucleus that governs the motivation to engage in singing, exhibited variation in functional categories that included thyroid hormone receptor activity, epigenetic and angiogenetic processes. Conclusions These findings highlight the importance of considering the temporal patterns of gene expression across several brain regions when engaging in social behaviors.

Abstract Background In an important model for neuroscience, songbirds learn to discriminate songs they hear during tape-recorded playbacks, as demonstrated by song-specific habituation of both behavioral and neurogenomic responses in the auditory forebrain. We hypothesized that microRNAs (miRNAs or miRs) may participate in the changing pattern of gene expression induced by song exposure. To test this, we used massively parallel Illumina sequencing to analyse small RNAs from auditory forebrain of adult zebra finches exposed to tape-recorded birdsong or silence. Results In the auditory forebrain, we identified 121 known miRNAs conserved in other vertebrates. We also identified 34 novel miRNAs that do not align to human or chicken genomes. Five conserved miRNAs showed significant and consistent changes in copy number after song exposure across three biological replications of the song-silence comparison, with two increasing (tgu-miR-25, tgu-miR-192) and three decreasing (tgu-miR-92, tgu-miR-124, tgu-miR-129-5p). We also detected a locus on the Z sex chromosome that produces three different novel miRNAs, with supporting evidence from Northern blot and TaqMan qPCR assays for differential expression in males and females and in response to song playbacks. One of these, tgu-miR-2954-3p, is predicted (by TargetScan) to regulate eight song-responsive mRNAs that all have functions in cellular proliferation and neuronal differentiation. Conclusions The experience of hearing another bird singing alters the profile of miRNAs in the auditory forebrain of zebra finches. The response involves both known conserved miRNAs and novel miRNAs described so far only in the zebra finch, including a novel sex-linked, song-responsive miRNA. These results indicate that miRNAs are likely to contribute to the unique behavioural biology of learned song communication in songbirds.