Kaviar: an accessible system for testing SNV novelty

Glusman, Gustavo; Caballero, Juan; Mauldin, Denise E.; Hood, Leroy; Roach, Jared C.

doi:10.1093/bioinformatics/btr540

Cited by 192 publications

(157 citation statements)

References 22 publications

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“…We annotated variants to RefSeq gene models with Ingenuity Variant Analysis (Qiagen). We used additional annotations from the Family Genomics Workflow (42), including allele frequency estimates from Kaviar (43). Linear mixed modeling of single variant associations was implemented with EMMAX (13).…”

Section: Methodsmentioning

confidence: 99%

Rare variants in neuronal excitability genes influence risk for bipolar disorder

Ament

Szelinger

Glusman

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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We sequenced the genomes of 200 individuals from 41 families multiply affected with bipolar disorder (BD) to identify contributions of rare variants to genetic risk. We initially focused on 3,087 candidate genes with known synaptic functions or prior evidence from genomewide association studies. BD pedigrees had an increased burden of rare variants in genes encoding neuronal ion channels, including subunits of GABA A receptors and voltage-gated calcium channels. Four uncommon coding and regulatory variants also showed significant association, including a missense variant in GABRA6. Targeted sequencing of 26 of these candidate genes in an additional 3,014 cases and 1,717 controls confirmed rare variant associations in ANK3, CACNA1B, CACNA1C, CACNA1D, CACNG2, CAMK2A, and NGF. Variants in promoters and 5′ and 3′ UTRs contributed more strongly than coding variants to risk for BD, both in pedigrees and in the case-control cohort. The genes and pathways identified in this study regulate diverse aspects of neuronal excitability. We conclude that rare variants in neuronal excitability genes contribute to risk for BD. by episodes of mania and depression (1). Episodes of mania are marked by elevated or alternatively irritable mood, grandiosity, racing thoughts, rapid speech, diminished need for sleep, and risk-taking behavior. Depression includes sadness, low energy and motivation, decreased ability to experience pleasure, insomnia, and appetite changes. Psychosis with hallucinations and delusions can occur in either state. BD affects 1-2% of the US population, and if untreated, up to 15% of patients die from suicide. Twin and family studies suggest that heritable causes explain 60-80% of lifetime risk for BD (2), with an approximate eightfold relative risk in the siblings of BD probands (3). Several common genetic markers have shown significant and replicable associations in genome-wide association studies (GWASs), including a region near a voltage-gated calcium channel, CACNA1C, and another near a synaptic scaffolding gene, ANK3 (4). Additive effects of common loci detectable on commercially available genomic arrays may be used to predict about 25% of the risk for BD (5), but typically the function and exact location of the causative variants linked to these loci is unknown.Rare variants may explain additional risk for BD. It is possible that one or a few rare variants of large effect dramatically increase disease risk, resulting in an inheritance model resembling monogenic inheritance in a given family. However, four exomesequencing and whole-genome sequencing (WGS) studies of BD pedigrees have detected few, if any, plausible variants of large effect (6-9). An alternative oligogenic model posits that different combinations of several uncommon or rare variants of moderate effect cluster in affected individuals and collectively cause disease.To test the hypothesis that rare variants contribute to risk for BD, we sequenced the genomes of 200 individuals from 41 multiply affected BD pedigrees of European ancestry. We seque...

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Section: Methodsmentioning

confidence: 99%

Rare variants in neuronal excitability genes influence risk for bipolar disorder

Ament

Szelinger

Glusman

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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159

135

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“…26 Mutations were analyzed for effects on protein function using a 571-residue ferroportin protein (UniProtKB/Swiss-Prot Q9NP59) and the predictive analysis tools: SIFT (Sorting Intolerant From Tolerant; http://blocks.fhcrc.org/sift/SIFT.html) 27 and PolyPhen2 (Polymorphism Phenotyping version 2; using HumDiv model; http://genetics.bwh.harvard.edu/pph2/index.shtml).…”

Section: Predictive Analysis and Worldwide Allele Frequenciesmentioning

confidence: 99%

Reduced sensitivity of the ferroportin Q248H mutant to physiological concentrations of hepcidin

Nekhai

Foster

et al. 2012

Haematologica

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ciency or ferroportin Q248H had lower circulating tumor necrosis factor-α concentrations than iron-replete children with WT ferroportin, 25 led us to hypothesize that ferroportin Q248H has reduced sensitivity to hepcidin but that this property would be observed at lower concentrations of hepcidin than those used in previous studies. 23 Here, we analyzed the sensitivity of ferroportin Q248H to hepcidin at various concentrations by determining the levels of ferroportin transiently expressed in cultured cells and in human primary monocytes derived from humans with different ferroportin genotypes. We also measured ferritin concentrations in these cells, levels that are indicative of cellular iron status. Finally, we examined the effect of Q248H on serum iron measures in patients with sickle cell anemia who have markedly increased macrophage iron export because of chronic hemolysis. Design and Methods Predictive analysis and worldwide allele frequenciesMinor allele frequencies for missense mutations in the single nucleotide polymorphism database (dbSNP) were determined using Kaviar and sequence data (http://db.systemsbiology.net/kaviar). 26Mutations were analyzed for effects on protein function using a 571-residue ferroportin protein (UniProtKB/Swiss-Prot Q9NP59) and the predictive analysis tools: SIFT (Sorting Intolerant From Tolerant; http://blocks.fhcrc.org/sift/SIFT.html) 27 and PolyPhen2 (Polymorphism Phenotyping version 2; using HumDiv model; http://genetics.bwh.harvard.edu/pph2/index.shtml). 28 Cells and media293T cells were purchased from ATCC (Manassas, VA, USA) and cultured in Dulbecco's modified Eagles medium (DMEM) containing 10% fetal bovine serum (FBS) (Life Technologies) and 1% glutamine (Invitrogen, Carlsbad, CA, USA) at 37°C in the presence of 5% CO 2 . Ferroportin expression constructsHuman WT ferroportin, ferroportin Q248H and ferroportin C326Y mutants cloned with c-Myc and histidine tags in a pcDNA3.1 expression vector were kindly provided by Dr. Hal Drakesmith. 23 To generate enhanced green fluorescent protein (EGFP)-tagged human ferroportin, the ferroportin coding sequences from WT ferroportin, ferroportin Q248H and ferroportin C326Y mutants were amplified by polymerase chain reaction (PCR) with the following primers that included XhoI and Kpn1 restriction sites (shown in italics): forward primer, GCCTC-GAGATGACCAGGGCGGGAGATCAC and reverse primer, GCGGTACCGTAACAACAGATGTATTTGCTTGATTTTC. The PCR products were purified on agarose gel, digested with XhoI and Kpn1 (BioLabs, Ipswich, MA) and ligated into the pEGFP-N1 vector (Clontech, Mountain View, CA, USA) which was also digested with XhoI and Kpn1 and ligated. The ligation products were transformed into E. coli DH5α cells (Invitrogen) and kanamycin-resistant colonies were selected. WT ferroportin-EGFP, C326Y and Q248H ferroportin -GFP-expressing plasmids were purified using a Qiagen (Valencia, CA, USA) purification kit and sequenced using the Macrogen service (Rockville, MD, USA). Transfection and treatment293T cells were seeded in 6-well ...

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“…Founder populations (eg, Amish or Iceland) where some non-causal variants are pulled to high frequency may be powerful in eliminating non-causal variants if the disease is rare or not present in the founder population. 54,55 Tools such as Kaviar 56 will allow researchers to quickly search these emerging sources of population frequency data. Finally, a Bayesian approach to integrate cross-population prevalence, allele frequencies, annotation and functional data in a filter-free probabilistic manner is possible but left to explore in future work.…”

Section: Discussionmentioning

confidence: 99%

Leveraging ancestry to improve causal variant identification in exome sequencing for monogenic disorders

et al. 2015

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Recent breakthroughs in exome-sequencing technology have made possible the identification of many causal variants of monogenic disorders. Although extremely powerful when closely related individuals (eg, child and parents) are simultaneously sequenced, sequencing of a single case is often unsuccessful due to the large number of variants that need to be followed up for functional validation. Many approaches filter out common variants above a given frequency threshold (eg, 1%), and then prioritize the remaining variants according to their functional, structural and conservation properties. Here we present methods that leverage the genetic structure across different populations to improve filtering performance while accounting for the finite sample size of the reference panels. We show that leveraging genetic structure reduces the number of variants that need to be followed up by 16% in simulations and by up to 38% in empirical data of 20 exomes from individuals with monogenic disorders for which the causal variants are known.

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Kaviar: an accessible system for testing SNV novelty

Cited by 192 publications

References 22 publications

Rare variants in neuronal excitability genes influence risk for bipolar disorder

Rare variants in neuronal excitability genes influence risk for bipolar disorder

Reduced sensitivity of the ferroportin Q248H mutant to physiological concentrations of hepcidin

Leveraging ancestry to improve causal variant identification in exome sequencing for monogenic disorders

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