Autism is a pervasive developmental disorder characterized by a triad of deficits: qualitative impairments in social interactions, communication deficits, and repetitive and stereotyped patterns of behavior. Although autism is etiologically heterogeneous, family and twin studies have established a definite genetic basis. The inheritance of idiopathic autism is presumed to be complex, with many genes involved; environmental factors are also possibly contributory. The analysis of chromosome abnormalities associated with autism contributes greatly to the identification of autism candidate genes.

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.

Open reading frames (ORFs) with fewer than 100 codons are generally not annotated in genomes, although bona fide genes of that size are known. Newer biochemical studies have suggested that thousands of small protein-coding ORFs (smORFs) may exist in the human genome, but the true number and the biological significance of the micropeptides they encode remain uncertain. Here, we used a comparative genomics approach to identify high-confidence smORFs that are likely protein-coding. We identified 3,326 high-confidence smORFs using constraint within human populations and evolutionary conservation as additional lines of evidence. Next, we validated that, as a group, our high-confidence smORFs are conserved at the amino-acid level rather than merely residing in highly conserved non-coding regions. Finally, we found that high-confidence smORFs are enriched among disease-associated variants from GWAS. Overall, our results highlight that smORF-encoded peptides likely have important functional roles in human disease.

Homology-driven proteomics is a major tool to characterize proteomes of organisms with unsequenced genomes. This paper addresses practical aspects of automated homology-driven protein identifications by LC-MS/MS on a hybrid LTQ Orbitrap mass spectrometer. All essential software elements supporting the presented pipeline are either hosted at the publicly accessible web server, or are available for free download.

Non-African populations have experienced size reductions in the time since their split from West Africans, leading to the hypothesis that natural selection to remove weakly deleterious mutations has been less effective in the history of non-Africans. To test this hypothesis, we measured the per-genome accumulation of nonsynonymous substitutions across diverse pairs of populations. We find no evidence for a higher load of deleterious mutations in non-Africans. However, we detect significant differences among more divergent populations, as archaic Denisovans have accumulated nonsynonymous mutations faster than either modern humans or Neanderthals. To reconcile these findings with patterns that have been interpreted as evidence of the less effective removal of deleterious mutations in non-Africans than in West Africans, we use simulations to show that the observed patterns are not likely to reflect changes in the effectiveness of selection after the populations split but are instead likely to be driven by other population genetic factors.

Open angle glaucoma (OAG) is a complex disorder with varying etiologies due to multiple genes and environmental effects. This genetic heterogeneity can confound efforts to map loci. Increased homogeneity in a sample can be achieved using either ordered subset analysis (OSA) which groups families, or individual OSA (IOSA), which groups individuals based on disease related covariates. Recently, GLC1I was mapped to 15q11-13 in families with early adult onset of OAG. We tested for linkage to GLC1I in an independent sample of 167 individuals in 25 multiplex OAG families of European descent. We carried out nonparametric linkage analysis on the complete set of 25 families and obtained a maximum LOD score of 1.00 at 9.0 cM. Using mean age at diagnosis (AAD) across the affected individuals within each family to order the families as a proxy for age at onset, we found a maximum OSA LOD score of 2.09 (p=0.021) at 26.1 cM. The mean (+/-s.d.) AAD across the 14 earlier AAD families that contributed to the OSA LOD score was 50.6 years (+/-5.38); the mean AAD for the other 1210 later AAD families that did not contribute to the OSA LOD score (the high-AAD) was 61.7 years (+/-3.50). We also ran IOSA on our families using AAD as our covariate on which to subset affected individuals. The maximum LOD score was 1.01 at 14.3 cM when ordering subjects from early to late AAD. Ordered subset analysis of this sample has provided evidence of linkage close to the previously identified GLC1I glaucoma locus on 15q11-13 in families with middle-aged mean age at diagnosis.

NOGO Receptor 1 (RTN4R) regulates axonal growth, as well as axon regeneration after injury. The gene maps to the 22q11.2 schizophrenia susceptibility locus and is thus a strong functional and positional candidate gene.

Genetic mapping of mutations in model systems has facilitated the identification of genes contributing to fundamental biological processes including human diseases. However, this approach has historically required the prior characterization of informative markers. Here we report a fast and cost-effective method for genetic mapping using next-generation sequencing that combines single nucleotide polymorphism discovery, mutation localization, and potential identification of causal sequence variants. In contrast to prior approaches, we have developed a hidden Markov model to narrowly define the mutation area by inferring recombination breakpoints of chromosomes in the mutant pool. In addition, we created an interactive online software resource to facilitate automated analysis of sequencing data and demonstrate its utility in the zebrafish and mouse models. Our novel methodology and online tools will make next-generation sequencing an easily applicable resource for mutation mapping in all model systems.

We characterize the genetic diversity of Xenopus laevis strains using RNA-seq data and allele-specific analysis. This data provides a catalogue of coding variation, which can be used for improving the genomic sequence, as well as for better sequence alignment, probe design, and proteomic analysis. In addition, we paint a broad picture of the genetic landscape of the species by functionally annotating different classes of mutations with a well-established prediction tool (PolyPhen-2). Further, we specifically compare the variation in the progeny of four crosses: inbred genomic (J)-strain, outbred albino (B)-strain, and two hybrid crosses of J and B strains. We identify a subset of mutations specific to the B strain, which allows us to investigate the selection pressures affecting duplicated genes in this allotetraploid. From these crosses we find the ratio of non-synonymous to synonymous mutations is lower in duplicated genes, which suggests that they are under greater purifying selection. Surprisingly, we also find that function-altering ("damaging") mutations constitute a greater fraction of the non-synonymous variants in this group, which suggests a role for subfunctionalization in coding variation affecting duplicated genes.