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Background Structural variations (SVs) account for about 1% of the differences among human genomes and play a significant role in phenotypic variation and disease susceptibility. The emerging nanopore sequencing technology can generate long sequence reads and can potentially provide accurate SV identification. However, the tools for aligning long-read data and detecting SVs have not been thoroughly evaluated. Results Using four nanopore datasets, including both empirical and simulated reads, we evaluate four alignment tools and three SV detection tools. We also evaluate the impact of sequencing depth on SV detection. Finally, we develop a machine learning approach to integrate call sets from multiple pipelines. Overall SV callers’ performance varies depending on the SV types. For an initial data assessment, we recommend using aligner minimap2 in combination with SV caller Sniffles because of their speed and relatively balanced performance. For detailed analysis, we recommend incorporating information from multiple call sets to improve the SV call performance. Conclusions We present a workflow for evaluating aligners and SV callers for nanopore sequencing data and approaches for integrating multiple call sets. Our results indicate that additional optimizations are needed to improve SV detection accuracy and sensitivity, and an integrated call set can provide enhanced performance. The nanopore technology is improving, and the sequencing community is likely to grow accordingly. In turn, better benchmark call sets will be available to more accurately assess the performance of available tools and facilitate further tool development.

Background Genomic safe harbors are regions of the genome that can maintain transgene expression without disrupting the function of host cells. Genomic safe harbors play an increasingly important role in improving the efficiency and safety of genome engineering. However, limited safe harbors have been identified. Results Here, we develop a framework to facilitate searches for genomic safe harbors by integrating information from polymorphic mobile element insertions that naturally occur in human populations, epigenomic signatures, and 3D chromatin organization. By applying our framework to polymorphic mobile element insertions identified in the 1000 Genomes project and the Genotype-Tissue Expression (GTEx) project, we identify 19 candidate safe harbors in blood cells and 5 in brain cells. For three candidate sites in blood, we demonstrate the stable expression of transgene without disrupting nearby genes in host erythroid cells. We also develop a computer program, Genomics and Epigenetic Guided Safe Harbor mapper (GEG-SH mapper), for knowledge-based tissue-specific genomic safe harbor selection. Conclusions Our study provides a new knowledge-based framework to identify tissue-specific genomic safe harbors. In combination with the fast-growing genome engineering technologies, our approach has the potential to improve the overall safety and efficiency of gene and cell-based therapy in the near future.

Tibetans have lived at very high altitudes for thousands of years, and they have a distinctive suite of physiological traits that enable them to tolerate environmental hypoxia. These phenotypes are clearly the result of adaptation to this environment, but their genetic basis remains unknown. We report genome-wide scans that reveal positive selection in several regions that contain genes whose products are likely involved in high-altitude adaptation. Positively selected haplotypes of EGLN1 and PPARA were significantly associated with the decreased hemoglobin phenotype that is unique to this highland population. Identification of these genes provides support for previously hypothesized mechanisms of high-altitude adaptation and illuminates the complexity of hypoxia-response pathways in humans.

Hundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power. A central challenge for joint analysis is that different WGS data processing pipelines cause substantial differences in variant calling in combined datasets, necessitating computationally expensive reprocessing. This approach is no longer tenable given the scale of current studies and data volumes. Here, we define WGS data processing standards that allow different groups to produce functionally equivalent (FE) results, yet still innovate on data processing pipelines. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results and produce significantly less variability than sequencing replicates. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for community-wide human genetics studies. Sharing of whole genome sequencing (WGS) data improves study scale and power, but data from different groups are often incompatible. Here, US genome centers and NIH programs define WGS data processing standards and a flexible validation method, facilitating collaboration in human genetics research.

Autism spectrum disorder (ASD) is defined by common behavioral characteristics, raising the possibility of shared pathogenic mechanisms. Yet, vast clinical and etiological heterogeneity suggests personalized phenotypes. Surprisingly, our iPSC studies find that six individuals from two distinct ASD subtypes, idiopathic and 16p11.2 deletion, have common reductions in neural precursor cell (NPC) neurite outgrowth and migration even though whole genome sequencing demonstrates no genetic overlap between the datasets. To identify signaling differences that may contribute to these developmental defects, an unbiased phospho-(p)-proteome screen was performed. Surprisingly despite the genetic heterogeneity, hundreds of shared p-peptides were identified between autism subtypes including the mTOR pathway. mTOR signaling alterations were confirmed in all NPCs across both ASD subtypes, and mTOR modulation rescued ASD phenotypes and reproduced autism NPC-associated phenotypes in control NPCs. Thus, our studies demonstrate that genetically distinct ASD subtypes have common defects in neurite outgrowth and migration which are driven by the shared pathogenic mechanism of mTOR signaling dysregulation. Although the clinical presentation of individuals with autism spectrum disorder (ASD) can vary widely, the core features are repetitive behaviors and difficulties with social interactions and communication. In most cases, the cause of autism is unknown. However, in some cases, such as a form of ASD known as 16p11.2 deletion syndrome, specific genetic changes are responsible. Despite this variability in possible causes and clinical manifestations, the similarity of the core behavioral symptoms across different forms of the disorder indicates that there could be a shared biological mechanism. Furthermore, genetic studies suggest that abnormalities in early fetal brain development could be a crucial underlying cause of ASD. In order to form the complex structure of the brain, fetal brain cells must migrate and start growing extensions that ultimately become key structures of neurons. To test for shared biological mechanisms, Prem et al. reprogrammed blood cells from people with either 16p11.2 deletion syndrome or ASD with an unknown cause to become fetal-like brain cells. Experiments showed that both migration of the cells and their growth of extensions were similarly disrupted in the cells derived from both groups of individuals with autism. These crucial developmental changes were driven by alterations to an important signaling molecule in a pathway involved in brain function, known as the mTOR pathway. However, in some cells the pathway was overactive, whereas in others it was underactive. To probe the potential of the mTOR pathway as a therapeutic target, Prem et al. tested drugs that manipulate the pathway, finding that they could successfully reverse the defects in cells derived from people with both types of ASD. The discovery that a shared biological process may underpin different forms of ASD is important for understanding the early brain changes that are involved. A common target, like the mTOR pathway, could offer hope for treatments for a wide range of ASDs. However, to translate these benefits to the clinic, further research is needed to understand whether a treatment that is effective in fetal cells would also benefit people with autism.

Early human embryogenesis relies on maternal gene products accumulated during oocyte growth and maturation, until around day-3 post-fertilization when human zygotic genome activation occurs. The maternal-to-zygotic transition (MZT) is a tightly coordinated process of selective maternal transcript clearance and new zygotic transcript production. If MZT is disrupted, it will lead to developmental arrest and pregnancy loss. It is well established that microRNA (miRNA) mutations disrupt regulation of their target transcripts. We hypothesize that some cases of embryonic arrest and pregnancy loss could be explained by the mutations in the maternal genome that affect miRNA-target transcript pairs. To this end, we examined mutations within miRNAs or miRNA binding sites in the 3ʼ untranslated regions (3ʼUTR) of target transcripts. Using whole-exome sequencing data from 178 women undergoing in vitro fertilization (IVF) procedures, we identified 1197 variants in miRNA genes, including 93 single nucleotide variants (SNVs) and 19 small insertions/deletions (INDELs) within the seed region of 100 miRNAs. Eight miRNA seed-region variants were significantly enriched among our patients when compared to a normal population. Within predicted 3ʼUTR miRNA binding sites, we identified 7393 SNVs and 1488 INDELs. Between our patients and a normal population, 52 SNVs and 30 INDELs showed significant association in the single-variant testing, whereas 51 genes showed significant association in the gene-burden analysis for genes that are expressed in preimplantation embryos. Interestingly, we found that many genes with disrupted 3ʼUTR miRNA binding sites follow gene expression patterns resembling MZT. In addition, some of these variants showed dramatic allele frequency difference between the patient and the normal group, offering potential utility as biomarkers for screening patients prior to IVF procedures.

Background Mobile elements are a major source of structural variants in the human genome, and some mobile elements can regulate gene expression and transcript splicing. However, the impact of polymorphic mobile element insertions (pMEIs) on gene expression and splicing in diverse human tissues has not been thoroughly studied. The multi-tissue gene expression and whole genome sequencing data generated by the Genotype-Tissue Expression (GTEx) project provide a great opportunity to systematically evaluate the role of pMEIs in regulating gene expression in human tissues. Results Using the GTEx whole genome sequencing data, we identify 20,545 high-quality pMEIs from 639 individuals. Coupling pMEI genotypes with gene expression profiles, we identify pMEI-associated expression quantitative trait loci (eQTLs) and splicing quantitative trait loci (sQTLs) in 48 tissues. Using joint analyses of pMEIs and other genomic variants, pMEIs are predicted to be the potential causal variant for 3522 eQTLs and 3717 sQTLs. The pMEI-associated eQTLs and sQTLs show a high level of tissue specificity, and these pMEIs are enriched in the proximity of affected genes and in regulatory elements. Using reporter assays, we confirm that several pMEIs associated with eQTLs and sQTLs can alter gene expression levels and isoform proportions, respectively. Conclusion Overall, our study shows that pMEIs are associated with thousands of gene expression and splicing variations, indicating that pMEIs could have a significant role in regulating tissue-specific gene expression and transcript splicing. Detailed mechanisms for the role of pMEIs in gene regulation in different tissues will be an important direction for future studies.

BRAF-driven colorectal cancer is among the poorest prognosis subtypes of colon cancer. Previous studies suggest that BRAF -mutant serrated cancers frequently exhibit Microsatellite Instability (MSI) and elevated levels of WNT signaling. The loss of tumor-suppressor Smad4 in oncogenic BRAF-V600E mouse models promotes rapid serrated tumor development and progression, and SMAD4 mutations co-occur in human patient tumors with BRAF-V600E mutations. This study assesses the role of SMAD4 in early-stage serrated tumorigenesis. SMAD4 loss promotes microsatellite stable (MSS) serrated tumors in an oncogenic BRAF-V600E context, providing a model for MSS serrated cancers. Inactivation of Msh2 in these mice accelerated tumor formation, and whole-exome sequencing of both MSS and MSI serrated tumors derived from these mouse models revealed that all serrated tumors developed oncogenic WNT mutations, predominantly in the WNT-effector gene Ctnnb1 (β-catenin). Mouse models mimicking the oncogenic β-catenin mutation show that the combination of three oncogenic mutations ( Ctnnb1, Braf , and Smad4 ) are critical to drive rapid serrated dysplasia formation. Re-analysis of human tumor data reveals BRAF-V600E mutations co-occur with oncogenic mutations in both WNT and SMAD4/TGFβ pathways. These findings identify SMAD4 as a critical factor in early-stage serrated cancers and helps broaden the knowledge of this rare but aggressive subset of colorectal cancer.

Tourette syndrome (TS) is a childhood-onset neuropsychiatric disorder characterized by repetitive motor movements and vocal tics. The clinical manifestations of TS are complex and often overlap with other neuropsychiatric disorders. TS is highly heritable; however, the underlying genetic basis and molecular and neuronal mechanisms of TS remain largely unknown. We performed whole-exome sequencing of a hundred trios (probands and their parents) with detailed records of their clinical presentations and identified a risk gene, ASH1L, that was both de novo mutated and associated with TS based on a transmission disequilibrium test. As a replication, we performed follow-up targeted sequencing of ASH1L in additional 524 unrelated TS samples and replicated the association (P value = 0.001). The point mutations in ASH1L cause defects in its enzymatic activity. Therefore, we established a transgenic mouse line and performed an array of anatomical, behavioral, and functional assays to investigate ASH1L function. The Ash1l+/− mice manifested tic-like behaviors and compulsive behaviors that could be rescued by the tic-relieving drug haloperidol. We also found that Ash1l disruption leads to hyper-activation and elevated dopamine-releasing events in the dorsal striatum, all of which could explain the neural mechanisms for the behavioral abnormalities in mice. Taken together, our results provide compelling evidence that ASH1L is a TS risk gene.

Reproductive success requires the development of viable oocytes and the accurate segregation of chromosomes during meiosis. Failure to segregate chromosomes properly can lead to infertility, miscarriages, or developmental disorders. A variety of factors contribute to accurate chromosome segregation and oocyte development, such as spindle assembly and sister chromatid cohesion. However, many proteins required for meiosis remain unknown. In this study, we aimed to develop a screening pipeline for identifying novel meiotic and fertility genes using the genome of Drosophila melanogaster . To accomplish this goal, genes upregulated within meiotically active tissues were identified. More than 240 genes with no known function were silenced using RNA interference (RNAi) and the effects on meiosis and fertility were assessed. We identified 94 genes that when silenced caused infertility and/or high levels of chromosomal nondisjunction. The vast majority of these genes have human and mouse homologs that are also poorly studied. Through this screening process, we identified novel genes that are crucial for meiosis and oocyte development but have not been extensively studied in human or model organisms. Understanding the function of these genes will be an important step towards the understanding of their biological significance during reproduction.