Wenli Gu

Bio: Wenli Gu is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Copy-number variation & Gene duplication. The author has an hindex of 10, co-authored 11 publications receiving 1934 citations. Previous affiliations of Wenli Gu include Ludwig Maximilian University of Munich.

Copy number variation in human health, disease, and evolution.

Abstract: Copy number variation (CNV) is a source of genetic diversity in humans. Numerous CNVs are being identified with various genome analysis platforms, including array comparative genomic hybridization (aCGH), single nucleotide polymorphism (SNP) genotyping platforms, and next-generation sequencing. CNV formation occurs by both recombination-based and replication-based mechanisms and de novo locus-specific mutation rates appear much higher for CNVs than for SNPs. By various molecular mechanisms, including gene dosage, gene disruption, gene fusion, position effects, etc., CNVs can cause Mendelian or sporadic traits, or be associated with complex diseases. However, CNV can also represent benign polymorphic variants. CNVs, especially gene duplication and exon shuffling, can be a predominant mechanism driving gene and genome evolution.

Mechanisms for human genomic rearrangements

Abstract: Genomic rearrangements describe gross DNA changes of the size ranging from a couple of hundred base pairs, the size of an average exon, to megabases (Mb). When greater than 3 to 5 Mb, such changes are usually visible microscopically by chromosome studies. Human diseases that result from genomic rearrangements have been called genomic disorders. Three major mechanisms have been proposed for genomic rearrangements in the human genome. Non-allelic homologous recombination (NAHR) is mostly mediated by low-copy repeats (LCRs) with recombination hotspots, gene conversion and apparent minimal efficient processing segments. NAHR accounts for most of the recurrent rearrangements: those that share a common size, show clustering of breakpoints, and recur in multiple individuals. Non-recurrent rearrangements are of different sizes in each patient, but may share a smallest region of overlap whose change in copy number may result in shared clinical features among different patients. LCRs do not mediate, but may stimulate non-recurrent events. Some rare NAHRs can also be mediated by highly homologous repetitive sequences (for example, Alu, LINE); these NAHRs account for some of the non-recurrent rearrangements. Other non-recurrent rearrangements can be explained by non-homologous end-joining (NHEJ) and the Fork Stalling and Template Switching (FoSTeS) models. These mechanisms occur both in germ cells, where the rearrangements can be associated with genomic disorders, and in somatic cells in which such genomic rearrangements can cause disorders such as cancer. NAHR, NHEJ and FoSTeS probably account for the majority of genomic rearrangements in our genome and the frequency distribution of the three at a given locus may partially reflect the genomic architecture in proximity to that locus. We provide a review of the current understanding of these three models.

Phenotypic consequences of copy number variation: insights from Smith-Magenis and Potocki-Lupski syndrome mouse models.

Abstract: A large fraction of genome variation between individuals is comprised of submicroscopic copy number variation of genomic DNA segments. We assessed the relative contribution of structural changes and gene dosage alterations on phenotypic outcomes with mouse models of Smith-Magenis and Potocki-Lupski syndromes. We phenotyped mice with 1n (Deletion/+), 2n (+/+), 3n (Duplication/+), and balanced 2n compound heterozygous (Deletion/Duplication) copies of the same region. Parallel to the observations made in humans, such variation in gene copy number was sufficient to generate phenotypic consequences: in a number of cases diametrically opposing phenotypes were associated with gain versus loss of gene content. Surprisingly, some neurobehavioral traits were not rescued by restoration of the normal gene copy number. Transcriptome profiling showed that a highly significant propensity of transcriptional changes map to the engineered interval in the five assessed tissues. A statistically significant overrepresentation of the genes mapping to the entire length of the engineered chromosome was also found in the top-ranked differentially expressed genes in the mice containing rearranged chromosomes, regardless of the nature of the rearrangement, an observation robust across different cell lineages of the central nervous system. Our data indicate that a structural change at a given position of the human genome may affect not only locus and adjacent gene expression but also “genome regulation.” Furthermore, structural change can cause the same perturbation in particular pathways regardless of gene dosage. Thus, the presence of a genomic structural change, as well as gene dosage imbalance, contributes to the ultimate phenotype.

High‐resolution molecular genomic autopsy reveals complex sudden unexpected death in epilepsy risk profile

Abstract: Summary Advanced variant detection in genes underlying risk of sudden unexpected death in epilepsy (SUDEP) can uncover extensive epistatic complexity and improve diagnostic accuracy of epilepsy-related mortality. However, the sensitivity and clinical utility of diagnostic panels based solely on established cardiac arrhythmia genes in the molecular autopsy of SUDEP is unknown. We applied the established clinical diagnostic panels, followed by sequencing and a high density copy number variant (CNV) detection array of an additional 253 related ion channel subunit genes to analyze the overall genomic variation in a SUDEP of the 3-year-old proband with severe myoclonic epilepsy of infancy (SMEI). We uncovered complex combinations of single nucleotide polymorphisms and CNVs in genes expressed in both neurocardiac and respiratory control pathways, including SCN1A, KCNA1, RYR3, and HTR2C. Our findings demonstrate the importance of comprehensive high-resolution variant analysis in the assessment of personally relevant SUDEP risk. In this case, the combination of de novo single nucleotide polymorphisms (SNPs) and CNVs in the SCN1A and KCNA1 genes, respectively, is suspected to be the principal risk factor for both epilepsy and premature death. However, consideration of the overall biologically relevant variant complexity with its extensive functional epistatic interactions reveals potential personal risk more accurately.

Enriched rearing improves behavioral responses of an animal model for CNV-based autistic-like traits

Abstract: Potocki-Lupski syndrome (PTLS; MIM #610883), characterized by neurobehavioral abnormalities, intellectual disability and congenital anomalies, is caused by a 3.7-Mb duplication in 17p11.2. Neurobehavioral studies determined that ∼70-90% of PTLS subjects tested positive for autism or autism spectrum disorder (ASD). We previously chromosomally engineered a mouse model for PTLS (Dp(11)17/+) with a duplication of a 2-Mb genomic interval syntenic to the PTLS region and identified consistent behavioral abnormalities in this mouse model. We now report extensive phenotyping with behavioral assays established to evaluate core and associated autistic-like traits, including tests for social abnormalities, ultrasonic vocalizations, perseverative and stereotypic behaviors, anxiety, learning and memory deficits and motor defects. Alterations were identified in both core and associated ASD-like traits. Rearing this animal model in an enriched environment mitigated some, and even rescued selected, neurobehavioral abnormalities, suggesting a role for gene-environment interactions in the determination of copy number variation-mediated autism severity.

10 Years of GWAS Discovery: Biology, Function, and Translation

Abstract: Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.

The contribution of de novo coding mutations to autism spectrum disorder

Abstract: Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.

Origins and functional impact of copy number variation in the human genome

Abstract: Structural variations of DNA greater than 1 kilobase in size account for most bases that vary among human genomes, but are still relatively under-ascertained. Here we use tiling oligonucleotide microarrays, comprising 42 million probes, to generate a comprehensive map of 11,700 copy number variations (CNVs) greater than 443 base pairs, of which most (8,599) have been validated independently. For 4,978 of these CNVs, we generated reference genotypes from 450 individuals of European, African or East Asian ancestry. The predominant mutational mechanisms differ among CNV size classes. Retrotransposition has duplicated and inserted some coding and non-coding DNA segments randomly around the genome. Furthermore, by correlation with known trait-associated single nucleotide polymorphisms (SNPs), we identified 30 loci with CNVs that are candidates for influencing disease susceptibility. Despite this, having assessed the completeness of our map and the patterns of linkage disequilibrium between CNVs and SNPs, we conclude that, for complex traits, the heritability void left by genome-wide association studies will not be accounted for by common CNVs.

DELLY: structural variant discovery by integrated paired-end and split-read analysis

Abstract: Motivation: The discovery of genomic structural variants (SVs) at high sensitivity and specificity is an essential requirement for characterizing naturally occurring variation and for understanding pathological somatic rearrangements in personal genome sequencing data. Of particular interest are integrated methods that accurately identify simple and complex rearrangements in heterogeneous sequencing datasets at single-nucleotide resolution, as an optimal basis for investigating the formation mechanisms and functional consequences of SVs. Results: We have developed an SV discovery method, called DELLY, that integrates short insert paired-ends, long-range mate-pairs and split-read alignments to accurately delineate genomic rearrangements at single-nucleotide resolution. DELLY is suitable for detecting copy-number variable deletion and tandem duplication events as well as balanced rearrangements such as inversions or reciprocal translocations. DELLY, thus, enables to ascertain the full spectrum of genomic rearrangements, including complex events. On simulated data, DELLY compares favorably to other SV prediction methods across a wide range of sequencing parameters. On real data, DELLY reliably uncovers SVs from the 1000 Genomes Project and cancer genomes, and validation experiments of randomly selected deletion loci show a high specificity. Availability: DELLY is available at www.korbel.embl.de/software.html Contact: ed.lbme@hcsuar.saibot

A copy number variation morbidity map of developmental delay

Abstract: To understand the genetic heterogeneity underlying developmental delay, we compared copy number variants (CNVs) in 15,767 children with intellectual disability and various congenital defects (cases) to CNVs in 8,329 unaffected adult controls. We estimate that ∼14.2% of disease in these children is caused by CNVs >400 kb. We observed a greater enrichment of CNVs in individuals with craniofacial anomalies and cardiovascular defects compared to those with epilepsy or autism. We identified 59 pathogenic CNVs, including 14 new or previously weakly supported candidates, refined the critical interval for several genomic disorders, such as the 17q21.31 microdeletion syndrome, and identified 940 candidate dosage-sensitive genes. We also developed methods to opportunistically discover small, disruptive CNVs within the large and growing diagnostic array datasets. This evolving CNV morbidity map, combined with exome and genome sequencing, will be critical for deciphering the genetic basis of developmental delay, intellectual disability and autism spectrum disorders.