Transcription factor binding site(s) (TFBS) gain and loss (i.e., turnover) is a well-documented feature of cis-regulatory module (CRM) evolution, yet little attention has been paid to the evolutionary force(s) driving this turnover process. The predominant view, motivated by its widespread occurrence, emphasizes the importance of compensatory mutation and genetic drift. Positive selection, in contrast, although it has been invoked in specific instances of adaptive gene expression evolution, has not been considered as a general alternative to neutral compensatory evolution. In this study we evaluate the two hypotheses by analyzing patterns of single nucleotide polymorphism in the TFBS of well-characterized CRM in two closely related Drosophila species, Drosophila melanogaster and Drosophila simulans. An important feature of the analysis is classification of TFBS mutations according to the direction of their predicted effect on binding affinity, which allows gains and losses to be evaluated independently along the two phylogenetic lineages. The observed patterns of polymorphism and divergence are not compatible with neutral evolution for either class of mutations. Instead, multiple lines of evidence are consistent with contributions of positive selection to TFBS gain and loss as well as purifying selection in its maintenance. In discussion, we propose a model to reconcile the finding of selection driving TFBS turnover with constrained CRM function over long evolutionary time.

Adaptive protein evolution is pervasive in Drosophila. Genomic studies, thus far, have analyzed each protein as a single entity. However, the targets of adaptive events may be localized to particular parts of proteins, such as protein domains or regions involved in protein folding. We compared the population genetic mechanisms driving sequence polymorphism and divergence in defined protein domains and non-domain regions. Interestingly, we find that non-domain regions of proteins are more frequent targets of directional selection. Protein domains are also evolving under directional selection, but appear to be under stronger purifying selection than non-domain regions. Non-domain regions of proteins clearly play a major role in adaptive protein evolution on a genomic scale and merit future investigations of their functional properties.

The population genetic perspective is that the processes shaping genomic variation can be revealed only through simultaneous investigation of sequence polymorphism and divergence within and between closely related species. Here we present a population genetic analysis of Drosophila simulans based on whole-genome shotgun sequencing of multiple inbred lines and comparison of the resulting data to genome assemblies of the closely related species, D. melanogaster and D. yakuba. We discovered previously unknown, large-scale fluctuations of polymorphism and divergence along chromosome arms, and significantly less polymorphism and faster divergence on the X chromosome. We generated a comprehensive list of functional elements in the D. simulans genome influenced by adaptive evolution. Finally, we characterized genomic patterns of base composition for coding and noncoding sequence. These results suggest several new hypotheses regarding the genetic and biological mechanisms controlling polymorphism and divergence across the Drosophila genome, and provide a rich resource for the investigation of adaptive evolution and functional variation in D. simulans.

Monitor lizards are unique among ectothermic reptiles in that they have high aerobic capacity and distinctive cardiovascular physiology resembling that of endothermic mammals. Here, we sequence the genome of the Komodo dragon Varanus komodoensis, the largest extant monitor lizard, and generate a high-resolution de novo chromosome-assigned genome assembly for V. komodoensis using a hybrid approach of long-range sequencing and single-molecule optical mapping. Comparing the genome of V. komodoensis with those of related species, we find evidence of positive selection in pathways related to energy metabolism, cardiovascular homoeostasis, and haemostasis. We also show species-specific expansions of a chemoreceptor gene family related to pheromone and kairomone sensing in V. komodoensis and other lizard lineages. Together, these evolutionary signatures of adaptation reveal the genetic underpinnings of the unique Komodo dragon sensory and cardiovascular systems, and suggest that selective pressure altered haemostasis genes to help Komodo dragons evade the anticoagulant effects of their own saliva. The Komodo dragon genome is an important resource for understanding the biology of monitor lizards and reptiles worldwide.

The chicken has long served as an important model organism in many fields, and continues to aid our understanding of animal development. Functional genomics studies aimed at probing the mechanisms that regulate development require high-quality genomes and transcript annotations. The quality of these resources has improved dramatically over the last several years, but many isoforms and genes have yet to be identified. We hope to contribute to the process of improving these resources with the data presented here: a set of long cDNA sequencing reads, and a curated set of new genes and transcript isoforms not currently represented in the most up-to-date genome annotation currently available to the community of researchers who rely on the chicken genome.

We describe the genome of the western painted turtle, Chrysemys picta bellii, one of the most widespread, abundant, and well-studied turtles. We place the genome into a comparative evolutionary context, and focus on genomic features associated with tooth loss, immune function, longevity, sex differentiation and determination, and the species' physiological capacities to withstand extreme anoxia and tissue freezing.

Understanding how DNA sequence polymorphism relates to variation in gene expression is essential to connecting genotypic differences with phenotypic differences among individuals. Addressing this question requires linking population genomic data with gene expression variation.

Some of the fastest evolving regions of the human genome are conserved noncoding elements with many human-specific DNA substitutions. These human accelerated regions (HARs) are enriched nearby regulatory genes, and several HARs function as developmental enhancers. To investigate if this evolutionary signature is unique to humans, we quantified evidence of accelerated substitutions in conserved genomic elements across multiple lineages and applied this approach simultaneously to the genomes of five apes: human, chimpanzee, gorilla, orangutan, and gibbon. We find roughly similar numbers and genomic distributions of lineage-specific accelerated regions (linARs) in all five apes. In particular, apes share an enrichment of linARs in regulatory DNA nearby genes involved in development, especially transcription factors and other regulators. Many developmental loci harbor clusters of nonoverlapping linARs from multiple apes, suggesting that accelerated evolution in each species affected distinct regulatory elements that control a shared set of developmental pathways. Our statistical tests distinguish between GC-biased and unbiased accelerated substitution rates, allowing us to quantify the roles of different evolutionary forces in creating linARs. We find evidence of GC-biased gene conversion in each ape, but unbiased acceleration consistent with positive selection or loss of constraint is more common in all five lineages. It therefore appears that similar evolutionary processes created independent accelerated regions in the genomes of different apes, and that these lineage-specific changes to conserved noncoding sequences may have differentially altered expression of a core set of developmental genes across ape evolution.

Detailed studies of individual genes have shown that gene expression divergence often results from adaptive evolution of regulatory sequence. Genome-wide analyses, however, have yet to unite patterns of gene expression with polymorphism and divergence to infer population genetic mechanisms underlying expression evolution. Here, we combined genomic expression data--analyzed in a phylogenetic context--with whole genome light-shotgun sequence data from six Drosophila simulans lines and reference sequences from D. melanogaster and D. yakuba. These data allowed us to use molecular population genetics to test for neutral versus adaptive gene expression divergence on a genomic scale. We identified recent and recurrent adaptive evolution along the D. simulans lineage by contrasting sequence polymorphism within D. simulans to divergence from D. melanogaster and D. yakuba. Genes that evolved higher levels of expression in D. simulans have experienced adaptive evolution of the associated 3' flanking and amino acid sequence. Concomitantly, these genes are also decelerating in their rates of protein evolution, which is in agreement with the finding that highly expressed genes evolve slowly. Interestingly, adaptive evolution in 5' cis-regulatory regions did not correspond strongly with expression evolution. Our results provide a genomic view of the intimate link between selection acting on a phenotype and associated genic evolution.

The molecular basis and characteristics of familial non-medullary thyroid cancer are poorly understood. In this study, we performed microRNA (miRNA) profiling of familial and sporadic papillary thyroid cancer tumor samples.

Heart development is exquisitely sensitive to the precise temporal regulation of thousands of genes that govern developmental decisions during differentiation. However, we currently lack a detailed understanding of how chromatin and gene expression patterns are coordinated during developmental transitions in the cardiac lineage. Here, we interrogated the transcriptome and several histone modifications across the genome during defined stages of cardiac differentiation. We find distinct chromatin patterns that are coordinated with stage-specific expression of functionally related genes, including many human disease-associated genes. Moreover, we discover a novel preactivation chromatin pattern at the promoters of genes associated with heart development and cardiac function. We further identify stage-specific distal enhancer elements and find enriched DNA binding motifs within these regions that predict sets of transcription factors that orchestrate cardiac differentiation. Together, these findings form a basis for understanding developmentally regulated chromatin transitions during lineage commitment and the molecular etiology of congenital heart disease.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is an important tool for studying gene regulatory proteins, such as transcription factors and histones. Peak calling is one of the first steps in the analysis of these data. Peak calling consists of two sub-problems: identifying candidate peaks and testing candidate peaks for statistical significance. We surveyed 30 methods and identified 12 features of the two sub-problems that distinguish methods from each other. We picked six methods GEM, MACS2, MUSIC, BCP, Threshold-based method (TM) and ZINBA] that span this feature space and used a combination of 300 simulated ChIP-seq data sets, 3 real data sets and mathematical analyses to identify features of methods that allow some to perform better than the others. We prove that methods that explicitly combine the signals from ChIP and input samples are less powerful than methods that do not. Methods that use windows of different sizes are more powerful than the ones that do not. For statistical testing of candidate peaks, methods that use a Poisson test to rank their candidate peaks are more powerful than those that use a Binomial test. BCP and MACS2 have the best operating characteristics on simulated transcription factor binding data. GEM has the highest fraction of the top 500 peaks containing the binding motif of the immunoprecipitated factor, with 50% of its peaks within 10 base pairs of a motif. BCP and MUSIC perform best on histone data. These findings provide guidance and rationale for selecting the best peak caller for a given application.

We propose that data mining and network analysis utilizing public databases can identify and quantify relationships between scientific discoveries and major advances in medicine (cures). Further development of such approaches could help to increase public understanding and governmental support for life science research and could enhance decision making in the quest for cures.

Dominant mutations in cardiac transcription factor genes cause human inherited congenital heart defects (CHDs); however, their molecular basis is not understood. Interactions between transcription factors and the Brg1/Brm-associated factor (BAF) chromatin remodelling complex suggest potential mechanisms; however, the role of BAF complexes in cardiogenesis is not known. In this study, we show that dosage of Brg1 is critical for mouse and zebrafish cardiogenesis. Disrupting the balance between Brg1 and disease-causing cardiac transcription factors, including Tbx5, Tbx20 and Nkx2-5, causes severe cardiac anomalies, revealing an essential allelic balance between Brg1 and these cardiac transcription factor genes. This suggests that the relative levels of transcription factors and BAF complexes are important for heart development, which is supported by reduced occupancy of Brg1 at cardiac gene promoters in Tbx5 haploinsufficient hearts. Our results reveal complex dosage-sensitive interdependence between transcription factors and BAF complexes, providing a potential mechanism underlying transcription factor haploinsufficiency, with implications for multigenic inheritance of CHDs.

Assignment of alleles to haplotypes for nearly all the variants on all chromosomes can be performed by genetic analysis of a nuclear family with three or more children. Whole-genome sequence data enable deterministic phasing of nearly all sequenced alleles by permitting assignment of recombinations to precise chromosomal positions and specific meioses. We demonstrate this process of genetic phasing on two families each with four children. We generate haplotypes for all of the children and their parents; these haplotypes span all genotyped positions, including rare variants. Misassignments of phase between variants (switch errors) are nearly absent. Our algorithm can also produce multimegabase haplotypes for nuclear families with just two children and can handle families with missing individuals. We implement our algorithm in a suite of software scripts (Haploscribe). Haplotypes and family genome sequences will become increasingly important for personalized medicine and for fundamental biology.

The developmental mechanisms through which the cerebral cortex increased in size and complexity during primate evolution are essentially unknown. To uncover genetic networks active in the developing cerebral cortex, we combined three-dimensional reconstruction of human fetal brains at midgestation and whole genome expression profiling. This novel approach enabled transcriptional characterization of neurons from accurately defined cortical regions containing presumptive Broca and Wernicke language areas, as well as surrounding associative areas. We identified hundreds of genes displaying differential expression between the two regions, but no significant difference in gene expression between left and right hemispheres. Validation by qRTPCR and in situ hybridization confirmed the robustness of our approach and revealed novel patterns of area- and layer-specific expression throughout the developing cortex. Genes differentially expressed between cortical areas were significantly associated with fast-evolving non-coding sequences harboring human-specific substitutions that could lead to divergence in their repertoires of transcription factor binding sites. Strikingly, while some of these sequences were accelerated in the human lineage only, many others were accelerated in chimpanzee and/or mouse lineages, indicating that genes important for cortical development may be particularly prone to changes in transcriptional regulation across mammals. Genes differentially expressed between cortical regions were also enriched for transcriptional targets of FoxP2, a key gene for the acquisition of language abilities in humans. Our findings point to a subset of genes with a unique combination of cortical areal expression and evolutionary patterns, suggesting that they play important roles in the transcriptional network underlying human-specific neural traits.