Plant pathogens cause severe losses to crop plants and threaten global food production. One striking example is the wheat stem rust fungus, Puccinia graminis f. sp. tritici, which can rapidly evolve new virulent pathotypes in response to resistant host lines. Like several other filamentous fungal and oomycete plant pathogens, its genome features expanded gene families that have been implicated in host-pathogen interactions, possibly encoding effector proteins that interact directly with target host defense proteins. Previous efforts to understand virulence largely relied on the prediction of secreted, small and cysteine-rich proteins as candidate effectors and thus delivered an overwhelming number of candidates. Here, we implement an alternative analysis strategy that uses the signal of adaptive evolution as a line of evidence for effector function, combined with comparative information and expression data. We demonstrate that in planta up-regulated genes that are rapidly evolving are found almost exclusively in pathogen-associated gene families, affirming the impact of host-pathogen co-evolution on genome structure and the adaptive diversification of specialized gene families. In particular, we predict 42 effector candidates that are conserved only across pathogens, induced during infection and rapidly evolving. One of our top candidates has recently been shown to induce genotype-specific hypersensitive cell death in wheat. This shows that comparative genomics incorporating the evolutionary signal of adaptation is powerful for predicting effector candidates for laboratory verification. Our system can be applied to a wide range of pathogens and will give insight into host-pathogen dynamics, ultimately leading to progress in strategies for disease control.

Retinoic acid-related orphan receptor alpha gene (RORa) and the microRNA MIR137 have both recently been identified as novel candidate genes for neuropsychiatric disorders. RORa encodes a ligand-dependent orphan nuclear receptor that acts as a transcriptional regulator and miR-137 is a brain enriched small non-coding RNA that interacts with gene transcripts to control protein levels. Given the mounting evidence for RORa in autism spectrum disorders (ASD) and MIR137 in schizophrenia and ASD, we investigated if there was a functional biological relationship between these two genes. Herein, we demonstrate that miR-137 targets the 3'UTR of RORa in a site specific manner. We also provide further support for MIR137 as an autism candidate by showing that a large number of previously implicated autism genes are also putatively targeted by miR-137. This work supports the role of MIR137 as an ASD candidate and demonstrates a direct biological link between these previously unrelated autism candidate genes.

Heterozygous mutations in CNTNAP2 have been identified in patients with a range of complex phenotypes including intellectual disability, autism and schizophrenia. However heterozygous CNTNAP2 mutations are also found in the normal population. Conversely, homozygous mutations are rare in patient populations and have not been found in any unaffected individuals.

Array-based technologies have been used to detect chromosomal copy number changes (aneuploidies) in the human genome. Recent studies identified numerous copy number variants (CNV) and some are common polymorphisms that may contribute to disease susceptibility. We developed, and experimentally validated, a novel computational framework (QuantiSNP) for detecting regions of copy number variation from BeadArray SNP genotyping data using an Objective Bayes Hidden-Markov Model (OB-HMM). Objective Bayes measures are used to set certain hyperparameters in the priors using a novel re-sampling framework to calibrate the model to a fixed Type I (false positive) error rate. Other parameters are set via maximum marginal likelihood to prior training data of known structure. QuantiSNP provides probabilistic quantification of state classifications and significantly improves the accuracy of segmental aneuploidy identification and mapping, relative to existing analytical tools (Beadstudio, Illumina), as demonstrated by validation of breakpoint boundaries. QuantiSNP identified both novel and validated CNVs. QuantiSNP was developed using BeadArray SNP data but it can be adapted to other platforms and we believe that the OB-HMM framework has widespread applicability in genomic research. In conclusion, QuantiSNP is a novel algorithm for high-resolution CNV/aneuploidy detection with application to clinical genetics, cancer and disease association studies.

We previously discovered that mutations of the human FOXP2 gene cause a monogenic communication disorder, primarily characterized by difficulties in learning to make coordinated sequences of articulatory gestures that underlie speech. Affected people have deficits in expressive and receptive linguistic processing and display structural and/or functional abnormalities in cortical and subcortical brain regions. FOXP2 provides a unique window into neural processes involved in speech and language. In particular, its role as a transcription factor gene offers powerful functional genomic routes for dissecting critical neurogenetic mechanisms. Here, we employ chromatin immunoprecipitation coupled with promoter microarrays (ChIP-chip) to successfully identify genomic sites that are directly bound by FOXP2 protein in native chromatin of human neuron-like cells. We focus on a subset of downstream targets identified by this approach, showing that altered FOXP2 levels yield significant changes in expression in our cell-based models and that FOXP2 binds in a specific manner to consensus sites within the relevant promoters. Moreover, we demonstrate significant quantitative differences in target expression in embryonic brains of mutant mice, mediated by specific in vivo Foxp2-chromatin interactions. This work represents the first identification and in vivo verification of neural targets regulated by FOXP2. Our data indicate that FOXP2 has dual functionality, acting to either repress or activate gene expression at occupied promoters. The identified targets suggest roles in modulating synaptic plasticity, neurodevelopment, neurotransmission, and axon guidance and represent novel entry points into in vivo pathways that may be disturbed in speech and language disorders.

Pathogens secrete effector proteins and many operate inside plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. Although many computational methods exist to predict plant protein subcellular localization, they perform poorly for effectors. We introduce LOCALIZER for predicting plant and effector protein localization to chloroplasts, mitochondria, and nuclei. LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial targeting compared to other methods for 652 plant proteins. For 107 eukaryotic effectors, LOCALIZER outperforms other methods and predicts a previously unrecognized chloroplast transit peptide for the ToxA effector, which we show translocates into tobacco chloroplasts. Secretome-wide predictions and confocal microscopy reveal that rust fungi might have evolved multiple effectors that target chloroplasts or nuclei. LOCALIZER is the first method for predicting effector localisation in plants and is a valuable tool for prioritizing effector candidates for functional investigations. LOCALIZER is available at http://localizer.csiro.au/.

The steadily increasing number of sequenced fungal and oomycete genomes has enabled detailed studies of how these eukaryotic microbes infect plants and cause devastating losses in food crops. During infection, fungal and oomycete pathogens secrete effector molecules which manipulate host plant cell processes to the pathogen's advantage. Proteinaceous effectors are synthesized intracellularly and must be externalized to interact with host cells. Computational prediction of secreted proteins from genomic sequences is an important technique to narrow down the candidate effector repertoire for subsequent experimental validation. In this study, we benchmark secretion prediction tools on experimentally validated fungal and oomycete effectors. We observe that for a set of fungal SwissProt protein sequences, SignalP 4 and the neural network predictors of SignalP 3 (D-score) and SignalP 2 perform best. For effector prediction in particular, the use of a sensitive method can be desirable to obtain the most complete candidate effector set. We show that the neural network predictors of SignalP 2 and 3, as well as TargetP were the most sensitive tools for fungal effector secretion prediction, whereas the hidden Markov model predictors of SignalP 2 and 3 were the most sensitive tools for oomycete effectors. Thus, previous versions of SignalP retain value for oomycete effector prediction, as the current version, SignalP 4, was unable to reliably predict the signal peptide of the oomycete Crinkler effectors in the test set. Our assessment of subcellular localization predictors shows that cytoplasmic effectors are often predicted as not extracellular. This limits the reliability of secretion predictions that depend on these tools. We present our assessment with a view to informing future pathogenomics studies and suggest revised pipelines for secretion prediction to obtain optimal effector predictions in fungi and oomycetes.

DNA demethylases regulate DNA methylation levels in eukaryotes. Arabidopsis encodes four DNA demethylases, DEMETER (DME), REPRESSOR OF SILENCING 1 (ROS1), DEMETER-LIKE 2 (DML2), and DML3. While DME is involved in maternal specific gene expression during seed development, the biological function of the remaining DNA demethylases remains unclear.

Oat crown rust, caused by the fungus Pucinnia coronata f. sp. avenae, is a devastating disease that impacts worldwide oat production. For much of its life cycle, P. coronata f. sp. avenae is dikaryotic, with two separate haploid nuclei that may vary in virulence genotype, highlighting the importance of understanding haplotype diversity in this species. We generated highly contiguous de novo genome assemblies of two P. coronata f. sp. avenae isolates, 12SD80 and 12NC29, from long-read sequences. In total, we assembled 603 primary contigs for 12SD80, for a total assembly length of 99.16 Mbp, and 777 primary contigs for 12NC29, for a total length of 105.25 Mbp; approximately 52% of each genome was assembled into alternate haplotypes. This revealed structural variation between haplotypes in each isolate equivalent to more than 2% of the genome size, in addition to about 260,000 and 380,000 heterozygous single-nucleotide polymorphisms in 12SD80 and 12NC29, respectively. Transcript-based annotation identified 26,796 and 28,801 coding sequences for isolates 12SD80 and 12NC29, respectively, including about 7,000 allele pairs in haplotype-phased regions. Furthermore, expression profiling revealed clusters of coexpressed secreted effector candidates, and the majority of orthologous effectors between isolates showed conservation of expression patterns. However, a small subset of orthologs showed divergence in expression, which may contribute to differences in virulence between 12SD80 and 12NC29. This study provides the first haplotype-phased reference genome for a dikaryotic rust fungus as a foundation for future studies into virulence mechanisms in P. coronata f. sp. avenaeIMPORTANCE Disease management strategies for oat crown rust are challenged by the rapid evolution of Puccinia coronata f. sp. avenae, which renders resistance genes in oat varieties ineffective. Despite the economic importance of understanding P. coronata f. sp. avenae, resources to study the molecular mechanisms underpinning pathogenicity and the emergence of new virulence traits are lacking. Such limitations are partly due to the obligate biotrophic lifestyle of P. coronata f. sp. avenae as well as the dikaryotic nature of the genome, features that are also shared with other important rust pathogens. This study reports the first release of a haplotype-phased genome assembly for a dikaryotic fungal species and demonstrates the amenability of using emerging technologies to investigate genetic diversity in populations of P. coronata f. sp. avenae.

GIPC1 is a cytoplasmic scaffold protein that interacts with numerous receptor signaling complexes, and emerging evidence suggests that it plays a role in tumorigenesis. GIPC1 is highly expressed in a number of human malignancies, including breast, ovarian, gastric, and pancreatic cancers. Suppression of GIPC1 in human pancreatic cancer cells inhibits in vivo tumor growth in immunodeficient mice. To better understand GIPC1 function, we suppressed its expression in human breast and colorectal cancer cell lines and human mammary epithelial cells (HMECs) and assayed both gene expression and cellular phenotype. Suppression of GIPC1 promotes apoptosis in MCF-7, MDA-MD231, SKBR-3, SW480, and SW620 cells and impairs anchorage-independent colony formation of HMECs. These observations indicate GIPC1 plays an essential role in oncogenic transformation, and its expression is necessary for the survival of human breast and colorectal cancer cells. Additionally, a GIPC1 knock-down gene signature was used to interrogate publically available breast and ovarian cancer microarray datasets. This GIPC1 signature statistically correlates with a number of breast and ovarian cancer phenotypes and clinical outcomes, including patient survival. Taken together, these data indicate that GIPC1 inhibition may represent a new target for therapeutic development for the treatment of human cancers.

Readily accessible samples such as peripheral blood or cell lines are increasingly being used in large cohorts to characterise gene expression differences between a patient group and healthy controls. However, cell and RNA isolation procedures and the variety of cell types that make up whole blood can affect gene expression measurements. We therefore systematically investigated global gene expression profiles in peripheral blood from six individuals collected during two visits by comparing five of the following cell and RNA isolation methods: whole blood (PAXgene), peripheral blood mononuclear cells (PBMCs), lymphoblastoid cell lines (LCLs), CD19 and CD20 specific B-cell subsets.

Bats possess extraordinary adaptations, including flight, echolocation, extreme longevity and unique immunity. High-quality genomes are crucial for understanding the molecular basis and evolution of these traits. Here we incorporated long-read sequencing and state-of-the-art scaffolding protocols1 to generate, to our knowledge, the first reference-quality genomes of six bat species (Rhinolophus ferrumequinum, Rousettus aegyptiacus, Phyllostomus discolor, Myotis myotis, Pipistrellus kuhlii and Molossus molossus). We integrated gene projections from our 'Tool to infer Orthologs from Genome Alignments' (TOGA) software with de novo and homology gene predictions as well as short- and long-read transcriptomics to generate highly complete gene annotations. To resolve the phylogenetic position of bats within Laurasiatheria, we applied several phylogenetic methods to comprehensive sets of orthologous protein-coding and noncoding regions of the genome, and identified a basal origin for bats within Scrotifera. Our genome-wide screens revealed positive selection on hearing-related genes in the ancestral branch of bats, which is indicative of laryngeal echolocation being an ancestral trait in this clade. We found selection and loss of immunity-related genes (including pro-inflammatory NF-κB regulators) and expansions of anti-viral APOBEC3 genes, which highlights molecular mechanisms that may contribute to the exceptional immunity of bats. Genomic integrations of diverse viruses provide a genomic record of historical tolerance to viral infection in bats. Finally, we found and experimentally validated bat-specific variation in microRNAs, which may regulate bat-specific gene-expression programs. Our reference-quality bat genomes provide the resources required to uncover and validate the genomic basis of adaptations of bats, and stimulate new avenues of research that are directly relevant to human health and disease1.

We present a genome assembly from an individual male Molossus nigricans (Chordata; Mammalia; Chiroptera; Molossidae). The genome sequence is 2.41 gigabases in span. The majority of the assembly is scaffolded into 24 chromosomal pseudomolecules, with the X sex chromosome assembled.

Bats are able to employ an astonishingly complex vocal repertoire for navigating their environment and conveying social information. A handful of species also show evidence for vocal learning, an extremely rare ability shared only with humans and few other animals. However, despite their potential for the study of vocal communication, bats remain severely understudied at a molecular level. To address this fundamental gap we performed the first transcriptome profiling and genetic interrogation of molecular networks in the brain of a highly vocal bat species, Phyllostomus discolor.

Forkhead box P2 (FOXP2) is a highly conserved transcription factor that has been implicated in human speech and language disorders and plays important roles in the plasticity of the developing brain. The pattern of nucleotide polymorphisms in FOXP2 in modern populations suggests that it has been the target of positive (Darwinian) selection during recent human evolution. In our study, we searched for evidence of selection that might have followed FOXP2 adaptations in modern humans. We examined whether or not putative FOXP2 targets identified by chromatin-immunoprecipitation genomic screening show evidence of positive selection. We developed an algorithm that, for any given gene list, systematically generates matched lists of control genes from the Ensembl database, collates summary statistics for three frequency-spectrum-based neutrality tests from the low-coverage resequencing data of the 1000 Genomes Project, and determines whether these statistics are significantly different between the given gene targets and the set of controls. Overall, there was strong evidence of selection of FOXP2 targets in Europeans, but not in the Han Chinese, Japanese, or Yoruba populations. Significant outliers included several genes linked to cellular movement, reproduction, development, and immune cell trafficking, and 13 of these constituted a significant network associated with cardiac arteriopathy. Strong signals of selection were observed for CNTNAP2 and RBFOX1, key neurally expressed genes that have been consistently identified as direct FOXP2 targets in multiple studies and that have themselves been associated with neurodevelopmental disorders involving language dysfunction.

The integrated analysis of genotypic and expression data for association with complex traits could identify novel genetic pathways involved in complex traits. We profiled 19,573 expression probes in Epstein-Barr virus-transformed lymphoblastoid cell lines (LCLs) from 299 twins and correlated these with 44 quantitative traits (QTs). For 939 expressed probes correlating with more than one QT, we investigated the presence of eQTL associations in three datasets of 57 CEU HapMap founders and 86 unrelated twins. Genome-wide association analysis of these probes with 2.2 m SNPs revealed 131 potential eQTLs (1,989 eQTL SNPs) overlapping between the HapMap datasets, five of which were in cis (58 eQTL SNPs). We then tested 535 SNPs tagging the eQTL SNPs, for association with the relevant QT in 2,905 twins. We identified nine potential SNP-QT associations (P<0.01) but none significantly replicated in five large consortia of 1,097-16,129 subjects. We also failed to replicate previous reported eQTL associations with body mass index, plasma low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides levels derived from lymphocytes, adipose and liver tissue. Our results and additional power calculations suggest that proponents may have been overoptimistic in the power of LCLs in eQTL approaches to elucidate regulatory genetic effects on complex traits using the small datasets generated to date. Nevertheless, larger tissue-specific expression data sets relevant to specific traits are becoming available, and should enable the adoption of similar integrated analyses in the near future.

Forkhead-box protein P2 is a transcription factor that has been associated with intriguing aspects of cognitive function in humans, non-human mammals, and song-learning birds. Heterozygous mutations of the human FOXP2 gene cause a monogenic speech and language disorder. Reduced functional dosage of the mouse version (Foxp2) causes deficient cortico-striatal synaptic plasticity and impairs motor-skill learning. Moreover, the songbird orthologue appears critically important for vocal learning. Across diverse vertebrate species, this well-conserved transcription factor is highly expressed in the developing and adult central nervous system. Very little is known about the mechanisms regulated by Foxp2 during brain development. We used an integrated functional genomics strategy to robustly define Foxp2-dependent pathways, both direct and indirect targets, in the embryonic brain. Specifically, we performed genome-wide in vivo ChIP-chip screens for Foxp2-binding and thereby identified a set of 264 high-confidence neural targets under strict, empirically derived significance thresholds. The findings, coupled to expression profiling and in situ hybridization of brain tissue from wild-type and mutant mouse embryos, strongly highlighted gene networks linked to neurite development. We followed up our genomics data with functional experiments, showing that Foxp2 impacts on neurite outgrowth in primary neurons and in neuronal cell models. Our data indicate that Foxp2 modulates neuronal network formation, by directly and indirectly regulating mRNAs involved in the development and plasticity of neuronal connections.

FOXP2, the first gene to have been implicated in a developmental communication disorder, offers a unique entry point into neuromolecular mechanisms influencing human speech and language acquisition. In multiple members of the well-studied KE family, a heterozygous missense mutation in FOXP2 causes problems in sequencing muscle movements required for articulating speech (developmental verbal dyspraxia), accompanied by wider deficits in linguistic and grammatical processing. Chromosomal rearrangements involving this locus have also been identified. Analyses of FOXP2 coding sequence in typical forms of specific language impairment (SLI), autism, and dyslexia have not uncovered any etiological variants. However, no previous study has performed mutation screening of children with a primary diagnosis of verbal dyspraxia, the most overt feature of the disorder in affected members of the KE family. Here, we report investigations of the entire coding region of FOXP2, including alternatively spliced exons, in 49 probands affected with verbal dyspraxia. We detected variants that alter FOXP2 protein sequence in three probands. One such variant is a heterozygous nonsense mutation that yields a dramatically truncated protein product and cosegregates with speech and language difficulties in the proband, his affected sibling, and their mother. Our discovery of the first nonsense mutation in FOXP2 now opens the door for detailed investigations of neurodevelopment in people carrying different etiological variants of the gene. This endeavor will be crucial for gaining insight into the role of FOXP2 in human cognition.

Application of apomixis, or asexual seed formation, in crop breeding would allow rapid fixation of complex traits, economizing improved crop delivery. Identification of apomixis genes is confounded by the polyploid nature, high genome complexity and lack of genomic sequence integration with reproductive tissue transcriptomes in most apomicts.

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.