Mingfu Zhu

The Characterization of Twenty Sequenced Human Genomes

We present the analysis of twenty human genomes to evaluate the prospects for identifying rare functional variants that contribute to a phenotype of interest. We sequenced at high coverage ten “case” genomes from individuals with severe hemophilia A and ten “control” genomes. We summarize the number of genetic variants emerging from a study of this magnitude, and provide a proof of concept for the identification of rare and highly-penetrant functional variants by confirming that the cause of hemophilia A is easily recognizable in this data set. We also show that the number of novel single nucleotide variants (SNVs) discovered per genome seems to stabilize at about 144,000 new variants per genome, after the first 15 individuals have been sequenced. Finally, we find that, on average, each genome carries 165 homozygous protein-truncating or stop loss variants in genes representing a diverse set of pathways.

An Evaluation of Copy Number Variation Detection Tools from Whole-Exome Sequencing Data

Copy number variation (CNV) has been found to play an important role in human disease. Next‐generation sequencing technology, including whole‐genome sequencing (WGS) and whole‐exome sequencing (WES), has become a primary strategy for studying the genetic basis of human disease. Several CNV calling tools have recently been developed on the basis of WES data. However, the comparative performance of these tools using real data remains unclear. An objective evaluation study of these tools in practical research situations would be beneficial. Here, we evaluated four well‐known WES‐based CNV detection tools (XHMM, CoNIFER, ExomeDepth, and CONTRA) using real data generated in house. After evaluation using six metrics, we found that the sensitive and accurate detection of CNVs in WES data remains challenging despite the many algorithms available. Each algorithm has its own strengths and weaknesses. None of the exome‐based CNV calling methods performed well in all situations; in particular, compared with CNVs identified from high coverage WGS data from the same samples, all tools suffered from limited power. Our evaluation provides a comprehensive and objective comparison of several well‐known detection tools designed for WES data, which will assist researchers in choosing the most suitable tools for their research needs.

A Genome-wide Comparison of the Functional Properties of Rare and Common Genetic Variants in Humans

One of the longest running debates in evolutionary biology concerns the kind of genetic variation that is primarily responsible for phenotypic variation in species. Here, we address this question for humans specifically from the perspective of population allele frequency of variants across the complete genome, including both coding and noncoding regions. We establish simple criteria to assess the likelihood that variants are functional based on their genomic locations and then use whole-genome sequence data from 29 subjects of European origin to assess the relationship between the functional properties of variants and their population allele frequencies. We find that for all criteria used to assess the likelihood that a variant is functional, the rarer variants are significantly more likely to be functional than the more common variants. Strikingly, these patterns disappear when we focus on only those variants in which the major alleles are derived. These analyses indicate that the majority of the genetic variation in terms of phenotypic consequence may result from a mutation-selection balance, as opposed to balancing selection, and have direct relevance to the study of human disease.

SVA: software for annotating and visualizing sequenced human genomes

Summary: Here we present Sequence Variant Analyzer (SVA), a software tool that assigns a predicted biological function to variants identified in next-generation sequencing studies and provides a browser to visualize the variants in their genomic contexts. SVA also provides for flexible interaction with software implementing variant association tests allowing users to consider both the bioinformatic annotation of identified variants and the strength of their associations with studied traits. We illustrate the annotation features of SVA using two simple examples of sequenced genomes that harbor Mendelian mutations. Availability and implementation: Freely available on the web at http://www.svaproject.org. Contact: d.ge@duke.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Using ERDS to infer copy-number variants in high-coverage genomes.

Although there are many methods available for inferring copy-number variants (CNVs) from next-generation sequence data, there remains a need for a system that is computationally efficient but that retains good sensitivity and specificity across all types of CNVs. Here, we introduce a new method, estimation by read depth with single-nucleotide variants (ERDS), and use various approaches to compare its performance to other methods. We found that for common CNVs and high-coverage genomes, ERDS performs as well as the best method currently available (Genome STRiP), whereas for rare CNVs and high-coverage genomes, ERDS performs better than any available method. Importantly, ERDS accommodates both unique and highly amplified regions of the genome and does so without requiring separate alignments for calling CNVs and other variants. These comparisons show that for genomes sequenced at high coverage, ERDS provides a computationally convenient method that calls CNVs as well as or better than any currently available method.

Genome-wide association study of interferon-related cytopenia in chronic hepatitis C patients

BACKGROUND & AIMS Interferon-alfa (IFN)-related cytopenias are common and may be dose-limiting. We performed a genome wide association study on a well-characterized genotype 1 HCV cohort to identify genetic determinants of peginterferon-α (pegIFN)-related thrombocytopenia, neutropenia, and leukopenia. METHODS 1604/3070 patients in the IDEAL study consented to genetic testing. Trial inclusion criteria included a platelet (Pl) count ≥80×10(9)/L and an absolute neutrophil count (ANC) ≥1500/mm(3). Samples were genotyped using the Illumina Human610-quad BeadChip. The primary analyses focused on the genetic determinants of quantitative change in cell counts (Pl, ANC, lymphocytes, monocytes, eosinophils, and basophils) at week 4 in patients >80% adherent to therapy (n=1294). RESULTS 6 SNPs on chromosome 20 were positively associated with Pl reduction (top SNP rs965469, p=10(-10)). These tag SNPs are in high linkage disequilibrium with 2 functional variants in the ITPA gene, rs1127354 and rs7270101, that cause ITPase deficiency and protect against ribavirin (RBV)-induced hemolytic anemia (HA). rs1127354 and rs7270101 showed strong independent associations with Pl reduction (p=10(-12), p=10(-7)) and entirely explained the genome-wide significant associations. We believe this is an example of an indirect genetic association due to a reactive thrombocytosis to RBV-induced anemia: Hb decline was inversely correlated with Pl reduction (r=-0.28, p=10(-17)) and Hb change largely attenuated the association between the ITPA variants and Pl reduction in regression models. No common genetic variants were associated with pegIFN-induced neutropenia or leucopenia. CONCLUSIONS Two ITPA variants were associated with thrombocytopenia; this was largely explained by a thrombocytotic response to RBV-induced HA attenuating IFN-related thrombocytopenia. No genetic determinants of pegIFN-induced neutropenia were identified.

Interleukin 28B polymorphisms are the only common genetic variants associated with low-density lipoprotein cholesterol (LDL-C) in genotype-1 chronic hepatitis C and determine the association between LDL-C and treatment response

Summary.  Low‐density lipoprotein cholesterol (LDL‐C) levels and interleukin 28B (IL28B) polymorphism are associated with sustained viral response (SVR) to peginterferon/ribavirin (pegIFN/RBV) for chronic hepatitis C (CHC) infection. IL28B has been linked with LDL‐C levels using a candidate gene approach, but it is not known whether other genetic variants are associated with LDL‐C, nor how these factors definitively affect SVR. We assessed genetic predictors of serum lipid and triglyceride levels in 1604 patients with genotype 1 (G1) chronic hepatitis C virus (HCV) infection by genome‐wide association study and developed multivariable predictive models of SVR. IL28B polymorphisms were the only common genetic variants associated with pretreatment LDL‐C level in Caucasians (rs12980275, P = 4.7 × 10−17, poor response IL28B variants associated with lower LDL‐C). The association was dependent on HCV infection, IL28B genotype was no longer associated with LDL‐C in SVR patients after treatment, while the association remained significant in non‐SVR patients (P < 0.001). LDL‐C was significantly associated with SVR for heterozygous IL28B genotype patients (P < 0.001) but not for homozygous genotypes. SVR modelling suggested that IL28B heterozygotes with LDL‐C > 130 mg/dL and HCV RNA ≤600 000 IU/mL may anticipate cure rates >80%, while the absence of these two criteria was associated with an SVR rate of <35%. IL28B polymorphisms are the only common genetic variants associated with pretreatment LDL‐C in G1‐HCV. LDL‐C remains significantly associated with SVR for heterozygous IL28B genotype patients, where LDL‐C and HCV RNA burden may identify those patients with high or low likelihood of cure with pegIFN/RBV therapy.

Evaluating whole genome sequence data from the Genetic Absence Epilepsy Rat from Strasbourg and its related non-epileptic strain

Objective The Genetic Absence Epilepsy Rats from Strasbourg (GAERS) are an inbreed Wistar rat strain widely used as a model of genetic generalised epilepsy with absence seizures. As in humans, the genetic architecture that results in genetic generalized epilepsy in GAERS is poorly understood. Here we present the strain-specific variants found among the epileptic GAERS and their related Non-Epileptic Control (NEC) strain. The GAERS and NEC represent a powerful opportunity to identify neurobiological factors that are associated with the genetic generalised epilepsy phenotype. Methods We performed whole genome sequencing on adult epileptic GAERS and adult NEC rats, a strain derived from the same original Wistar colony. We also generated whole genome sequencing on four double-crossed (GAERS with NEC) F2 selected for high-seizing (n = 2) and non-seizing (n = 2) phenotypes. Results Specific to the GAERS genome, we identified 1.12 million single nucleotide variants, 296.5K short insertion-deletions, and 354 putative copy number variants that result in complete or partial loss/duplication of 41 genes. Of the GAERS-specific variants that met high quality criteria, 25 are annotated as stop codon gain/loss, 56 as putative essential splice sites, and 56 indels are predicted to result in a frameshift. Subsequent screening against the two F2 progeny sequenced for having the highest and two F2 progeny for having the lowest seizure burden identified only the selected Cacna1h GAERS-private protein-coding variant as exclusively co-segregating with the two high-seizing F2 rats. Significance This study highlights an approach for using whole genome sequencing to narrow down to a manageable candidate list of genetic variants in a complex genetic epilepsy animal model, and suggests utility of this sequencing design to investigate other spontaneously occurring animal models of human disease.