Non-reference Allele Research Articles

Evaluation of variants in the ENTPD1 and ENTPD2 genes in athletic horses with exercise-induced pulmonary haemorrhage

BackgroundExercise-induced pulmonary haemorrhage (EIPH) in athletic horses is characterized by the presence of blood from the lungs in the tracheobronchial tree after intense exercise. Despite the high prevalence of EIPH in horses, the primary aetiology remains unknown. Variants in the genes encoding CD39 and CD39L1 (ENTPD1 and ENTPD2, respectively) were previously reported as potential genetic causes involved in EIPH pathogenesis. However, the role of these variants in haemostatic functions is unknown.ResultsTo investigate the association between EIPH and missense variants in the ENTPD1 (rs1152296272, rs68621348, and rs68621347) and ENTPD2 genes (rs782872967), 76 Thoroughbred horses diagnosed with EIPH and 56 without clinical signs of EIPH (control group) by trachea-bronchial endoscopy were genotyped. The rs1152296272 and rs68621347 variants were linked, which explained why the same results were found in all horses. Approximately 96% and 95% of the EIPH and control horses, respectively, carried at least one nonreference allele for these variants. In contrast, 100% of the control horses and 96% of the EIPH horses were homozygous for the reference allele for the rs68621348 variant. In the EIPH group, 1.5% of the horses were homozygotes and 24% were heterozygous for the nonreference allele of the rs782872967 variant. In the control group, the nonreference allele of this variant was observed only in heterozygotes (16%). There were no significant differences between groups for any of the variants.ConclusionsThe variants previously described in the genes encoding the CD39 and CD39L1 enzymes were highly present in the studied population. However, no association was found between the occurrence of EIPH and the presence of these variants in Thoroughbred horses in this study.

Development of polymorphic simple sequences repeats markers from whole gene resequencing data comparison of 68 Oncorhynchus mykiss

Rainbow trout (Oncorhynchus mykiss) is a significant cold-water fish farmed in China. Currently, most molecular marker-assisted breeding applications in rainbow trout rely on SSR markers. Although many rainbow trout SSR markers have been developed, methods for mining many polymorphic SSR markers from the genome and identifying them efficiently and rapidly are still lacking. For this reason, this study used in silico simulation method to rapidly develop a large number of polymorphic SSR markers quickly. A total of 354,613 SSR loci with two to six nucleotide repeat motifs were mined from 32 chromosomes of the rainbow trout reference genome using GMATA. The chromosome sequences of the reference genome were then aligned to the whole genome sequencing data (10×) of 68 rainbow trout samples. In silico genotyping was performed using the HipSTR programme to compare and count the variation in the number of repeats of the motifs of the SSR loci in the samples. The loci with high deletion rates and monomorphism were discarded, while those with more than one non-reference allele were kept. The final set of polymorphic SSR loci screened was 78,828. Finally, 4,821 SSR loci were selected with more than 3 alleles and no deletion in all rainbow trout samples and were physically mapped. The average polymorphic information content of these loci was 0.692, indicating high levels of polymorphism. These SSRs were utilized to analyse the genetic diversity and population structure of the 68 rainbow trout samples. The results showed that these 68 samples were divided into two groups. These newly discovered polymorphic SSR markers will provide valuable information for evaluating the construction of rainbow trout family lines for genetic diversity and improvement.

DMRT3 Allele Frequencies in Batida- and Picada-Gaited Donkeys and Mules in Brazil.

In Brazil, the production of mules with a comfortable gait primarily involves the breeding of marching saddle mules. This is achieved by crossing gaited Pêga donkeys with horses from the Mangalarga Marchador and Campolina breeds. The DMRT3:g.22999655C>A SNP is implicated in regulating gait phenotypes observed in various horse breeds, including the batida (CC) and picada (CA) gaits found in these horse breeds. We aimed to determine if genotypes influenced gait type in 159 mules and 203 donkeys genotyped for the DMRT3 SNP by PCR-RFLP analysis. About 47% of mules had the CC-genotype, while 53% had the CA-genotype. Donkeys predominantly had the CC-genotype (97%), and none had AA. Both CC- and CA-genotypes were evenly distributed among mules with the batida or picada gaits. In donkeys, the CC-genotype frequencies were consistent regardless of gait type. However, the CA-genotype was more common in picada-gaited donkeys than in batida-gaited donkeys. The prevalence of CA mules and the rare presence of the non-reference allele in donkeys align with previous findings in Mangalarga Marchador and Campolina horses. This suggests that the non-reference allele likely originated from the mares involved in donkey crosses. Our results also imply that factors beyond this variant, such as other genes and polymorphisms, influence gait traits in equids.

Insertion of a TRIM-like sequence in MdFLS2-1 promoter is associated with its allele-specific expression in response to Alternaria alternata in apple.

Alternaria blotch disease, caused by Alternaria alternata apple pathotype (AAAP), is one of the major fungal diseases in apple. Early field observations revealed, the anther-derived homozygote Hanfu line (HFTH1) was highly susceptible to AAAP, whereas Hanfu (HF) exhibited resistance to AAAP. To understand the molecular mechanisms underlying the difference in sensitivity of HF and HFTH1 to AAAP, we performed allele-specific expression (ASE) analysis and comparative transcriptomic analysis before and after AAAP inoculation. We reported an important immune gene, namely, MdFLS2, which displayed strong ASE in HF with much lower expression levels of HFTH1-derived alleles. Transient overexpression of the dominant allele of MdFLS2-1 from HF in GL-3 apple leaves could enhance resistance to AAAP and induce expression of genes related to salicylic acid pathway. In addition, MdFLS2-1 was identified with an insertion of an 85-bp terminal-repeat retrotransposon in miniature (TRIM) element-like sequence in the upstream region of the nonreference allele. In contrast, only one terminal direct repeat (TDR) from TRIM-like sequence was present in the upstream region of the HFTH1-derived allele MdFLS2-2. Furthermore, the results of luciferase and β-glucuronidase reporter assays demonstrated that the intact TRIM-like sequence has enhancer activity. This suggested that insertion of the TRIM-like sequence regulates the expression level of the allele of MdFLS2, in turn, affecting the sensitivity of HF and HFTH1 to AAAP.

Long-read mapping to repetitive reference sequences using Winnowmap2.

Approximately 5-10% of the human genome remains inaccessible due to the presence of repetitive sequences such as segmental duplications and tandem repeat arrays. We show that existing long-read mappers often yield incorrect alignments and variant calls within long, near-identical repeats, as they remain vulnerable to allelic bias. In the presence of a nonreference allele within a repeat, a read sampled from that region could be mapped to an incorrect repeat copy. To address this limitation, we developed a new long-read mapping method, Winnowmap2, by using minimal confidently alignable substrings. Winnowmap2 computes each read mapping through a collection of confident subalignments. This approach is more tolerant of structural variation and more sensitive to paralog-specific variants within repeats. Our experiments highlight that Winnowmap2 successfully addresses the issue of allelic bias, enabling more accurate downstream variant calls in repetitive sequences.

Human Genetic Diversity Alters Therapeutic Gene Editing Off-Target Outcomes

CRISPR gene editing holds great promise to modify somatic genomes to ameliorate disease. In silico prediction of homologous sites coupled with biochemical evaluation of possible genomic off-targets may predict genotoxicity risk of individual gene editing reagents. However, standard computational and biochemical methods focus on reference genomes and do not consider the impact of genetic diversity on off-target potential. Here we developed a web application called CRISPRme that explicitly and efficiently integrates human genetic variant datasets with orthogonal genomic annotations to predict and prioritize off-target sites at scale. The method considers both single-nucleotide variants (SNVs) and indels, accounts for bona fide haplotypes, accepts spacer:protospacer mismatches and bulges, and is suitable for personal genome analyses. We tested the tool with a guide RNA (gRNA) targeting the BCL11A erythroid enhancer that has shown therapeutic promise in clinical trials for sickle cell disease (SCD) and β-thalassemia (Frangoul et al. NEJM 2021). We find that the top predicted off-target site is produced by a non-reference allele common in African-ancestry populations (rs114518452, minor allele frequency (MAF) = 4.5%) that introduces a protospacer adjacent motif (PAM) for SpCas9. We validate that SpCas9 generates indels (~9.6% frequency) and chr2 pericentric inversions in a strictly allele-specific manner in edited CD34+ hematopoietic stem/progenitor cells (HSPCs), although a high-fidelity Cas9 variant mitigates this off-target. This report illustrates how population and private genetic variants should be considered as modifiers of genome editing outcomes. We expect that variant-aware off-target assessment will be required for therapeutic genome editing efforts going forward, including both ongoing and future clinical trials, and we provide a powerful approach for comprehensive off-target prediction. CRISPRme is available at crisprme.di.univr.it. DisclosuresNo relevant conflicts of interest to declare.

Disease-specific eQTL screening reveals an anti-fibrotic effect of AGXT2 in non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) poses an increasing clinical burden. Genome-wide association studies have revealed a limited contribution of genomic variants to the disease, requiring alternative but robust approaches to identify disease-associated variants and genes. We carried out a disease-specific expression quantitative trait loci (eQTL) screen to identify novel genetic factors that specifically act on NAFLD progression on the basis of genotype. We recruited 125 Korean patients (83 with biopsy-proven NAFLD and 42 without NAFLD) and performed eQTL analyses using 21,272 transcripts and 3,234,941 genotyped and imputed single nucleotide polymorphisms. We then selected eQTLs that were detected only in the NAFLD group, but not in the control group (i.e., NAFLD-eQTLs). An additional cohort of 162 Korean individuals with NAFLD was used for replication. The function of the selected eQTL toward NAFLD development was validated using HepG2, primary hepatocytes and NAFLD mouse models. The NAFLD-specific eQTL screening yielded 242 loci. Among them, AGXT2, encoding alanine-glyoxylate aminotransferase 2, displayed decreased expression in patients with NAFLD homozygous for the non-reference allele of rs2291702, compared to no-NAFLD individuals with the same genotype (p=4.79×10-6). This change was replicated in an additional 162 individuals, yielding a combined p value of 8.05 × 10-8 from a total of 245 patients with NAFLD and 42 controls. Knockdown of AGXT2 induced palmitate-overloaded hepatocyte death by increasing endoplasmic reticulum stress, and exacerbated NAFLD diet-induced liver fibrosis in mice, while overexpression of AGXT2 attenuated liver fibrosis and steatosis. We identified a new molecular role for AGXT2 in NAFLD. Our overall approach will serve as an efficient tool for uncovering novel genetic factors that contribute to liver steatosis and fibrosis in patients with NAFLD. Elucidating causal genes for non-alcoholic fatty liver disease (NAFLD) has been challenging due to limited tissue availability and the polygenic nature of the disease. Using liver and blood samples from 125 Korean individuals (83 with NAFLD and 42 without NAFLD), we devised a new analytic method to identify causal genes. Among the candidates, we found that AGXT2-rs2291702 protects against liver fibrosis in a genotype-dependent manner with the potential for therapeutic interventions. Our approach enables the discovery of causal genes that act on the basis of genotype.

Investigation of Genetic Modifiers of Copper Toxicosis in Labrador Retrievers

Copper toxicosis is a complex genetic disorder in Labrador retrievers characterized by hepatic copper accumulation eventually leading to liver cirrhosis. The variation of hepatic copper levels in Labrador retrievers has been partly explained by mutations in ATP7A c.980C>T and ATP7B c.4358G>A. To further elucidate the genetic background of this disease, we used targeted Next Generation Sequencing (NGS) in a cohort of 95 Labrador retrievers to analyze 72 potential modifier genes for variations associated with hepatic copper levels. Variants associated with copper levels were subsequently evaluated in a replication cohort of 144 Labrador retrievers. A total of 44 variants in 25 different genes were identified, of which four showed significant association with copper levels. Of the four variants found associated with hepatic copper levels in the NGS cohort, one was validated in the replication cohort. The non-reference allele of the variant NC_006602.3.g.52434480C>T in RETN resulting in amino-acid change p.Leu7Phe was associated with decreased hepatic copper levels. In humans, resistin is associated with severity of non-alcoholic fatty liver disease, fibrosis, cirrhosis and mitochondrial dysfunction in hepatocytes. Further studies are needed to investigate the biological function of RETN p.Leu7Phe in the development of copper toxicosis in Labrador retrievers.

Abstract 4433: Comprehensive characterization of nonreference allele occurring in high throughput sequencing of tumor sample

Abstract Background: As high throughput sequencing (HTS) technique advances, HTS has been routinely used in cancer research as well as in clinical setting. However, we often face the situation where we need to identify somatic variants from tumor tissue without matched normal control. This is challenging largely due to 1) Intrinsic nature of tumor such as purity, ploidy and clonality. 2) technical error introduced by imperfect experimental procedure. 3) The complexity of human genome. 4) unavailability of matched normal to distinguish germline variants from somatic variants. Several efforts have been made to resolve this issue such as SGZ and PureCN. However, their performance remains unsatisfactory. Most of these methods focused on tumor heterogeneity inference followed by variant allele frequency (VAF) estimation while largely ignored the manifestation of variant harboring alignment. A better understanding of the characteristics of non-reference allele in NGS pipeline is essential for developing an improved variant calling and filtering approach. Therefore, we present a comprehensive evaluation of the characteristic of non-reference alleles. Method: Whole Exome Sequencing (WES) was carried out. Three types of non-reference allele were identified as following: Somatic and germline variants were identified using MuTect (with matched normal) and HaplotypeCaller respectively according to GATK best practice. For artifacts identification, Pisces is used in tumor-only-mode. The retained variants were subtracted by somatic and germline dataset. Variants with either low VAF or low sequencing depth were excluded from all three datasets. In terms of feature engineering, we defined a set of features that may differentiate between variant types including VAF, population frequency, mappability related genomic element, alignment integrity, etc. Corresponding analysis were carried out to evaluate these features individually. Result and conclusion: The above analysis can be seen as the process of feature evaluation and prioritization. we fitted a selection of features to a number of supervised classifiers including random forest, adaptive boosting, gradient boosting and voting classifier (soft voting). Precision and recall were measured based on KFold (K=5) cross validation. Random forest achieved highest performance: 0.90 and 0.93 for germline prediction. 0.93 and 0.91 for somatic prediction. 0.95 and 0.94 for artifact prediction. This result suggests that, by carefully selecting relevant features, can we achieve acceptable accuracy of variant detection even when matched normal is not available. Admittedly, we found some drawbacks alone the way of our analysis, for example some repeatedly occurred artifacts that are unaccounted by our features. Besides, our approach may be compromised when analyzing tumor with extreme purity. Further research is required to include additional features to tackle these drawbacks and achieve better performance. Citation Format: Cheng Yan, Weihua Guo, Hongling Yuan, Yufei Yang. Comprehensive characterization of nonreference allele occurring in high throughput sequencing of tumor sample [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4433.

Abstract C050: Deleterious coding variants in African American Hereditary Prostate Cancer Study (AAHPC) families

Abstract Purpose: Prostate cancer is the most common cancer in males, with a ~1.5-2-fold higher incidence in African American men when compared with whites. Epidemiologic evidence supports a large heritable contribution to prostate cancer, with over 100 susceptibility loci identified to date that can explain ~33% of the familial risk. A portion of the undefined risk may be due to rare susceptibility variants. The African American Hereditary Prostate Cancer (AAHPC) Study, established in 1997, enrolled 77 African American families from seven clinical sites across the United States. The aim of this study is to identify rare, predictive, deleterious variants through exome sequencing of 99 cases from families selected from the AAHPC families and three 1000 Genome controls. Methods: To explore the contribution of rare variation in coding regions to prostate cancer risk, we sequenced the exomes of 99 AAHPC cases at a mean coverage of 30x. Post-variant calling quality control (QC) was implemented using Golden Helix SVS 8 software with filters set for removal of variants with Read Depth >10, Quality Score >10, and Quality Score: Read Depth Ratio > 0.5. Mendelian inconsistency was checked using PLINK. Prioritization of all candidate genes/variants was evaluated using online databases 1000 Genome and bioinformatics tool ANNOVAR for non-reference allele frequency and predictions of functional impact. Conclusions: Through exome sequencing of 99 AAHPC cases and three 1000 Genome controls, we identified 37 nonsynonymous single-nucleotide variants that are considered damaging by at least one predictive scoring tool in our candidate genes. Interesting candidate variants were found in known cancer susceptibility loci BRCA2, MSR1, PCNT, STAT3, WRN and ZFHX3. Future results are pending additional QC and analyses to determine which variants are shared by related individuals within each family compared to those not seen in the controls. Citation Format: Deyana D. Lewis, Shukmei Wong, Angela S. Baker, Joan E. Bailey-Wilson, John D. Carpten, Cheryl D. Cropp. Deleterious coding variants in African American Hereditary Prostate Cancer Study (AAHPC) families [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr C050.

4277 Functional consequences of the juvenile idiopathic arthritis risk variant at 1q24.3

OBJECTIVES/GOALS: Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatologic disease childhood and a cause of pain and potential disability. JIA has a strong genetic component and no known cure. The goal of this study is to evaluate allele-dependent effects of a novel JIA risk variant at 1q24.3. METHODS/STUDY POPULATION: JIA patients meeting criteria for the two most common disease subtypes (oligoarticular and RF neg polyarthritis) were genotyped using the Immunochip, an Illumina array with dense coverage of the HLA region and 186 other loci previously reported in autoimmune diseases. Phase I association findings (Hinks, 2013) and Phase II analysis (unpublished) of an expanded cohort (4,271 JIA and 14,390 controls) identified new risk loci, including rs78037977 at 1q24.3. We prioritized rs78037977 and predicted possible impacted mechanisms based on Bayesian predictions of attributable risk, the surrounding chromatin landscape, and transcription factor binding data. A luciferase reporter assay was used to assess allele-dependent enhancer activity. RESULTS/ANTICIPATED RESULTS: rs78037977 is located between FASLG and TNFSF18 at chromosome 1q24.3 is associated with JIA (p = 6.3x10−09), and explains 94% of the posterior probability at this locus; no other SNPs in linkage disequilibrium (r2>0.6). The chromatin landscape around rs78037977 contains H3K4Me1 and H3K27Ac marks, which are indicative of enhancer activity. Further, >160 transcription factors have chromatin immunoprecipitation followed by sequencing (ChIP-seq) peaks overlapping rs78037977 in various cellular contexts. In luciferase reporter assays, the region around rs78037977 containing the reference A allele had ~2-fold increased enhancer activity compared to the non-reference allele. DISCUSSION/SIGNIFICANCE OF IMPACT: This work provides in vitro evidence to support allele-dependent enhancer activity of a novel JIA-risk variant at 1q24.3. Our ongoing work investigates the effect of the DNA-containing region of rs78037977 on gene expression and differential transcription factor binding at rs78037977.

Investigation of DNA variants specific to ROBO2 Isoform \u2018a\u2019 in Irish vesicoureteric reflux patients reveals marked CpG island variation

ROBO2 gene disruption causes vesicoureteric reflux (VUR) amongst other congenital anomalies. Several VUR patient cohorts have been screened for variants in the ubiquitously expressed transcript, ROBO2b, but, apart from low levels in a few adult tissues, ROBO2a expression is confined to the embryo, and might be more relevant to VUR, a developmental disorder. ROBO2a has an alternative promoter and two alternative exons which replace the first exon of ROBO2b. We screened probands from 251 Irish VUR families for DNA variants in these. The CpG island of ROBO2a, which includes the non-coding first exon, was found to contain a run of six variants abolishing/creating CpG dinucleotides, including a novel variant, present in the VUR cases in one family, that was not present in 592 healthy Irish controls. In three of these positions, the CpG was created by the non-reference allele, and the reference allele was not the nucleotide that would result from spontaneous deamination of methylcytosine to thymine, suggesting that there might have been selection for variability in number of CpGs in this island. This is in marked contrast to the CpG island at the start of ROBO2b, which only contained a single variant that abolishes a CpG.

79: Genetic variants at AGTR2 locus increase risk of preterm birth

Preterm birth (PTB) complicates approximately 10% of pregnancies in the U.S. While genetic factors contribute to PTB, there has been limited replication of specific genetic risk loci associated with PTB. Recently, we conducted the first large-scale, maternal genome-wide association study (GWAS), utilizing 43,568 women from 23andMe, that identified a locus of variants near the angiotensin II receptor type 2 receptor (AGTR2) gene associated with both PTB and gestational length. We hypothesized that a causative variant in this locus influences expression of AGTR2. We assessed genetic variants previously identified in our GWAS located near AGTR2 (combined analysis p-value of 7.2x10-16 in association with gestational length) to identify genotype-dependent regulation of AGTR2 expression. We computationally prioritized disease variants using available functional genomics data. Implicated variants were then evaluated for possible effects on transcription factor (TF) binding using protein-binding microarray data. Selected variants predicted to alter TF binding were analyzed using electrophoretic mobility shift assays (EMSAs). Luciferase reporter assays were performed to identify rs7889204 genotype-dependent regulation of the AGTR2 promoter. Our computational analyses identified rs7889204 as the top functional candidate variant. EMSA analysis confirmed predicted allele-dependent binding for the transcription factors CEBPB and HOXA10. Luciferase reporter assays revealed allele-dependent reporter activity for rs7889204, with decreased expression for the non-reference “C” allele. We identified candidate mechanisms in which rs7889204 at the AGTR2 locus differentially binds CEBPB and HOXA10. Reporter assays demonstrate decreased enhancer activity for the non-reference allele at rs7889204. These results are consistent with a previously established eQTL for AGTR2 in the uterus, suggesting decreased binding of CEBPB and HOXA10 to the preterm birth rs7889204 risk allele results in decreased AGTR2 expression and possible downstream decidual implantation abnormalities leading to PTB.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Abstract 4240: Rare candidate variants shared among affected family members in the African American Hereditary Prostate Cancer Study families

Abstract Purpose: Prostate cancer is the most common cancer in males, but also exhibits a ∼1.5-2-fold higher incidence in African American men compared with whites. Epidemiologic evidence supports a large heritable contribution to prostate cancer, with over 100 susceptibility loci identified to date that can explain ∼33 % of the familial risk. A portion of the undefined risk may be due to rare susceptibility variants. The African American Hereditary Prostate Cancer (AAHPC) Study, established in 1997, enrolled 77 AA families from seven clinical sites across the United States (Ann Epidemiol, 2000). The aim of this study is to identify rare, predictive, deleterious variants through exome sequencing of 99 cases from 26 families selected from the AAHPC families (2 to 3 affected men sequenced per family) and three female 1000 Genome controls. Methods: To explore the contribution of rare variation in coding regions of 38 known cancer-causing genes to prostate cancer risk (PCa), we sequenced the exomes of 99 AAHPC cases at a mean coverage of 30x. Post-variant calling quality control (QC) was implemented using Golden Helix SVS 8 software with filters set for removal of variants with Read Depth >10, Quality Score >10, and Quality Score: Read Depth Ratio > 0.5. Mendelian inconsistency was checked using PLINK. Prioritization of all candidate genes/variants were evaluated using online databases including 1000 Genomes and ANNOVAR for non-reference allele frequency and predictions of functional impact. Conclusions. Through exome sequencing of 99 AAHPC cases and 3 female 1000 Genome controls, we identified 37 non-synonymous single nucleotide variants that are considered damaging by at least one predictive scoring tool in our 38 candidate genes. However, most of these variants were common and thus unlikely to be causal. We observed three rare variants that were considered damaging by three predictive scoring tools in two known PCa genes, PCNT and ZFHX3. These 3 variants were each observed in a single different family (in 1 of 3 affected individuals). Interesting rare candidate variants (MAF ≤ 0.01) rs190517526 & rs114692729 were found in known cancer susceptibility loci (CD82 and EZH2). The CD82 variant was observed in all 3 sequenced affecteds in one family and the EZH2 variant was observed in 2 of 3 sequenced affecteds in a different family. These predicted damaging variants in these four genes represent potentially novel causal candidates for some of the 26 AAHPC families sequenced here. Future work will carefully analyze the remainder of the genome in the other 21 sequenced families including planned sequencing of additional family members. Citation Format: Deyana D. Lewis, Shukmei Wong, Angela S. Baker, Isaac Powell, John D. Carpten, Joan E. Bailey-Wilson, Cheryl Cropp. Rare candidate variants shared among affected family members in the African American Hereditary Prostate Cancer Study families [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4240.

Abstract 4590: Larger family sizes improve stochastic error correction during untargeted searches of very-low frequency variant alleles in circulating cell-free DNA (ccfDNA)

Abstract Detection of ccfDNA derived from non-metastatic solid tumors requires discrimination of very-low frequency true variants from NGS library preparation and sequencing noise that commonly occurs at a similar frequency (<1%). Correction of NGS-related errors is particularly important during searches of unknown tumor-associated variants with multi-gene panels. Unique molecular identifiers (UMIs) have been used during in silico error correction by molecular barcoding and performing a consensus base calling at each position from DNA labelled with the same UMI (i.e., PCR duplicates). In this study, we sought to determine the utility of UMIs for error correction of stochastic noise in ccfDNA. ccfDNA was isolated from the plasma of 11 healthy participants. An eight base-pair random barcode (UMI) was ligated prior to library amplification. Libraries were enriched using a custom capture probe set (128 genes; 128 kb) and then sequenced (HiSeq 2500). Reads were aligned, grouped based on UMI similarity, and a consensus read sequence was determined. The number of PCR duplicates that yielded a single consensus sequence was defined as family size (FS). For non-reference alleles detected at a variant allele frequency (VAF) ≥ 0.1% and ≤ 1.0%, there was a significant reduction in observed counts with increasingly larger FSs (Table 1). This effect was observed for both unique and common non-reference allele counts (Table 1). Of note, counts of unique non-reference alleles (stochastic noise) were consistently greater than the common non-reference alleles regardless of family size (Table 1). The use of larger family sizes reduced the stochastic noise that may confound detection of very-low frequency variants present in ccfDNA during searches for unknown tumor-associated variants. Strategies that generate larger family sizes or suppress early PCR errors may further improve NGS specificity to broaden liquid biopsy clinical applications. Table 1. Mean (SD) Non-Reference Allele Counts with a VAF between 0.1% and 1.0% in Cell-Free DNAFS >= 1FS >= 5FS >= 10FS >= 15FS >= 20ANOVA Results F(4,50)P-valueAll Variants5536 (1230)3988 (881)2621 (805)1028 (552)1028 (552)49.8<0.001Unique Variants3597 (1107)2635 (766)1112 (526)709 (434)709 (434)27.6<0.001Common Variants1939 (161)1353 (188)521 (141)318 (121)318 (121)186.1<0.001 Citation Format: Preetida J. Bhetariya, David Nix, Sabine Hellwig, Gabor Marth, Mary Bronner, Hunter Underhill. Larger family sizes improve stochastic error correction during untargeted searches of very-low frequency variant alleles in circulating cell-free DNA (ccfDNA) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4590.

Characterization of Factors Affecting the Detection Limit of EGFR p.T790M in Circulating Tumor DNA.

Objective:Circulating tumor DNA is a promising noninvasive tool for cancer monitoring. One of the challenges in applying this tool is the detection of low-frequency mutations. The detection limit of these mutations varies between different molecular methods. The aim of this study is to characterize the factors affecting the limit of detection for epidermal growth factor receptor p.T790M mutation in circulating tumor DNA of patients with lung adenocarcinoma.Methods:DNA was extracted from plasma samples of 102 patients. For sequencing the DNA, we used 2 different next-generation sequencing–based platforms: Ion Torrent Personal Genome Machine (56 cases) and Roche/454 (46 cases). Serially diluted synthetic DNA samples carrying the p.T790M mutation were sequenced using the Ion Torrent Personal Genome Machine for validation. Limit of detection was determined through the analysis of non-hot-spot nonreference reads, which were regarded as sequencing artifacts.Results:The frequency of the non-hot-spot nonreference reads was higher in Ion Torrent Personal Genome Machine compared to Roche/454 (0.07% ± 0.08% and 0.03% ± 0.06%, respectively, P < .001). We found that different base type substitutions occur with different frequency. Since the base substitution leading to p.T790M mutation is C>T transition, its frequency was used to determine the limit of detection for the assay. Based on the C>T non-hot-spot nonreference allele frequency, we found that the limit of detection is 0.18% in Ion Torrent Personal Genome Machine and 0.1% in Roche/454. Based on these values, 48% and 56% of the cases were positive for T790M mutation in Ion Torrent Personal Genome Machine and Roche/454 groups, respectively. Agreement between duplicates was 76% in Ion Torrent Personal Genome Machine and 72% in Roche/454. Using serially diluted synthetic DNA samples carrying the p.T790M mutation, we could identify mutations with allele frequency of 0.18% or more using the Ion Torrent Personal Genome Machine, supporting our approach to determine the detection limit.Conclusion:Both the sequencing platform and the specific nucleotide change affect the limit of detection and should therefore be determined in the validation process of new assays.

Variational inference for rare variant detection in deep, heterogeneous next-generation sequencing data

BackgroundThe detection of rare single nucleotide variants (SNVs) is important for understanding genetic heterogeneity using next-generation sequencing (NGS) data. Various computational algorithms have been proposed to detect variants at the single nucleotide level in mixed samples. Yet, the noise inherent in the biological processes involved in NGS technology necessitates the development of statistically accurate methods to identify true rare variants.ResultsWe propose a Bayesian statistical model and a variational expectation maximization (EM) algorithm to estimate non-reference allele frequency (NRAF) and identify SNVs in heterogeneous cell populations. We demonstrate that our variational EM algorithm has comparable sensitivity and specificity compared with a Markov Chain Monte Carlo (MCMC) sampling inference algorithm, and is more computationally efficient on tests of relatively low coverage (27× and 298×) data. Furthermore, we show that our model with a variational EM inference algorithm has higher specificity than many state-of-the-art algorithms. In an analysis of a directed evolution longitudinal yeast data set, we are able to identify a time-series trend in non-reference allele frequency and detect novel variants that have not yet been reported. Our model also detects the emergence of a beneficial variant earlier than was previously shown, and a pair of concomitant variants.ConclusionsWe developed a variational EM algorithm for a hierarchical Bayesian model to identify rare variants in heterogeneous next-generation sequencing data. Our algorithm is able to identify variants in a broad range of read depths and non-reference allele frequencies with high sensitivity and specificity.

Homozygous PPT1 Splice Donor Mutation in a Cane Corso Dog With Neuronal Ceroid Lipofuscinosis

A 10‐month‐old spayed female Cane Corso dog was evaluated after a 2‐month history of progressive blindness, ataxia, and lethargy. Neurologic examination abnormalities indicated a multifocal lesion with primarily cerebral and cerebellar signs. Clinical worsening resulted in humane euthanasia. On necropsy, there was marked astrogliosis throughout white matter tracts of the cerebrum, most prominently in the corpus callosum. In the cerebral cortex and midbrain, most neurons contained large amounts of autofluorescent storage material in the perinuclear area of the cells. Cerebellar storage material was present in the Purkinje cells, granular cell layer, and perinuclear regions of neurons in the deep nuclei. Neuronal ceroid lipofuscinosis (NCL) was diagnosed. Whole genome sequencing identified a PPT1c.124 + 1G>A splice donor mutation. This nonreference assembly allele was homozygous in the affected dog, has not previously been reported in dbSNP, and was absent from the whole genome sequences of 45 control dogs and 31 unaffected Cane Corsos. Our findings indicate a novel mutation causing the CLN1 form of NCL in a previously unreported dog breed. A canine model for CLN1 disease could provide an opportunity for therapeutic advancement, benefiting both humans and dogs with this disorder.

An empirical Bayes method for genotyping and SNP detection using multi-sample next-generation sequencing data.

The development of next generation sequencing technology provides an efficient and powerful approach to rare variant detection. To identify genetic variations, the essential question is how to quantity the sequencing error rate in the data. Because of the advantage of easy implementation and the ability to integrate data from different sources, the empirical Bayes method is popularly employed to estimate the sequencing error rate for SNP detection. We propose a novel statistical model to fit the observed non-reference allele frequency data, and utilize the empirical Bayes method for both genotyping and SNP detection, where an ECM algorithm is implemented to estimate the model parameters. The performance of our proposed method is investigated via simulations and real data analysis. It is shown that our method makes less genotype-call errors, and with the parameter estimates from the ECM algorithm, it attains high detection power with FDR being well controlled. The proposed algorithm is wrapped in the R package ebGenotyping, which can be downloaded from http://cran.r-project.org/web/packages/ebGenotyping/ CONTACT: youn@mail.sysu.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online.

Genomic sequencing of a dyslexia susceptibility haplotype encompassing ROBO1

BackgroundThe DYX5 locus for developmental dyslexia was mapped to chromosome 3 by linkage study of a large Finnish family, and later, roundabout guidance receptor 1 (ROBO1) was implicated as a candidate gene at DYX5 with suppressed expression from the segregating rare haplotype. A functional magnetoencephalographic study of several family members revealed abnormal auditory processing of interaural interaction, supporting a defect in midline crossing of auditory pathways. In the current study, we have characterized genetic variation in the broad ROBO1 gene region in the DYX5-linked family, aiming to identify variants that would increase our understanding of the altered expression of ROBO1.MethodsWe have used a whole genome sequencing strategy on a pooled sample of 19 individuals in combination with two individually sequenced genomes. The discovered genetic variants were annotated and filtered. Subsequently, the most interesting variants were functionally tested using relevant methods, including electrophoretic mobility shift assay (EMSA), luciferase assay, and gene knockdown by lentiviral small hairpin RNA (shRNA) in lymphoblasts.ResultsWe found one novel intronic single nucleotide variant (SNV) and three novel intergenic SNVs in the broad region of ROBO1 that were specific to the dyslexia susceptibility haplotype. Functional testing by EMSA did not support the binding of transcription factors to three of the SNVs, but one of the SNVs was bound by the LIM homeobox 2 (LHX2) protein, with increased binding affinity for the non-reference allele. Knockdown of LHX2 in lymphoblast cell lines extracted from subjects from the DYX5-linked family showed decreasing expression of ROBO1, supporting the idea that LHX2 regulates ROBO1 also in human.ConclusionsThe discovered variants may explain the segregation of dyslexia in this family, but the effect appears subtle in the experimental settings. Their impact on the developing human brain remains suggestive based on the association and subtle experimental support.Electronic supplementary materialThe online version of this article (doi:10.1186/s11689-016-9136-y) contains supplementary material, which is available to authorized users.