Phred Score Research Articles

Illumina SBS Sequencing and DNBSEQ Perform Similarly for Single-Cell Transcriptomics

Background/Objectives: High-throughput single-cell RNA sequencing (scRNA-seq) workflows produce libraries that demand extensive sequencing. However, standard next-generation sequencing (NGS) methods remain expensive, contributing to the high running costs of single-cell experiments and often negatively affecting the sample numbers and statistical strength of such projects. In recent years, a plethora of new sequencing technologies have become available to researchers through several manufacturers, often providing lower-cost alternatives to standard NGS. Methods: In this study, we compared data generated from mouse scRNA-seq libraries sequenced with both standard Illumina sequencing by synthesis (Illumina SBS) and MGI’s DNA nanoball sequencing (DNBSEQ). Results: Our findings reveal similar overall performance using both technologies. DNBSEQ exhibited mildly superior sequence quality compared to Illumina SBS, as evidenced by higher Phred scores, lower read duplication rates and a greater number of genes mapping to the reference genome. Yet these improvements did not translate into meaningful differences in single-cell analysis parameters in our experiments, including detection of additional genes within cells, gene expression saturation levels and numbers of identified cells, with both technologies demonstrating equally robust performance in these aspects. The data produced by both sequencing platforms also produced comparable analytical outcomes for single-cell analysis. No significant difference in the annotation of cells into different cell types was observed and the same top genes were differentially expressed between populations and experimental conditions. Conclusions: Overall, our data demonstrate that alternative technologies can be applied to sequence scRNA-seq libraries, generating virtually indistinguishable results compared to standard methods, and providing cost-effective alternatives.

The quality and detection limits of mitochondrial heteroplasmy by long read nanopore sequencing

This study evaluates long-read and short-read sequencing for mitochondrial DNA (mtDNA) heteroplasmy detection. 592,315 bootstrapped datasets generated from two single-nucleotide mismatched ultra-deep sequenced mtDNA samples were used to assess basecalling error and accuracy, limit of heteroplasmy detection, and heteroplasmy detection across various coverage depths. Results showed high Phred scores of data with GC-rich sequence bias for long reads. Limit of detection of 12% heteroplasmy was identified, showing strong correlation (R2 ≥ 0.955) with expected heteroplasmy but underreporting tendency of high-level variants. Nanopore sequencing shows potential for direct applicability in mitochondrial diseases diagnostics, but stringent validation processes to ensure diagnostic result quality are required.

Scifer: An R/Bioconductor package for large-scale integration of Sanger sequencing and flow cytometry data of index-sorted single cells

Sanger sequencing remains widely used in various experimental contexts, often in combination with flow cytometry for indexing specific cell populations. However, existing software lacks the capability to automate quality control (QC) of raw Sanger sequencing data and integrate it with flow cytometry information on a large scale. Here, we introduce scifer, an R package now available in the latest release of Bioconductor (3.20) showcasing its effectiveness in seamlessly integrating these types of data as demonstrated by analyses of B cell and T cell receptor sequences. Scifer preprocesses raw data from index sorts and immune receptor Sanger sequencing. It identifies high-quality sequences based on selected parameters, such as length, Phred scores, and heavy-chain complementarity-determining region 3 (HCDR3) quality. As a result, the quality of germline assignments is significantly increased and spurious variable gene mutations are reduced. Scifer is automated and can process thousands of sequences in less than an hour. Its output provides quality control reports, FASTA files, summarized tables, and electropherograms for manual inspection. In summary, scifer is a user-friendly software that speeds up the analysis of immune receptor repertoire sequences, offering wide applicability.

Leveraging the fundamentals of heat transfer and fluid mechanics in microscale geometries for automated next-generation sequencing library preparation

Next-generation sequencing (NGS) is emerging as a powerful tool for molecular diagnostics but remains limited by cumbersome and inefficient sample preparation. We present an innovative automated NGS library preparation system with a simplified mechanical design that exploits both macro- and microfluidic properties for optimizing heat transfer, reaction kinetics, mass transfer, fluid mechanics, adsorption–desorption rates, and molecular thermodynamics. Our approach introduces a unique two-cannula cylindrical capillary system connected to a programmable syringe pump and a Peltier heating element able to execute all steps with high efficiency. Automatic reagent movement, mixing, and magnetic bead-based washing with capillary-based thermal cycling (capillary-PCR) are completely integrated into a single platform. The manual 3-h library preparation process is reduced to less than 15 min of hands-on time via optimally pre-plated reagent plates, followed by less than 6 h of instrument run time during which no user interaction is required. We applied this method to two library preparation assays with different DNA fragmentation requirements (mechanical vs. enzymatic fragmentation), sufficiently limiting consumable use to one cartridge and one 384 well-plate per run. Our platform successfully prepared eight libraries in parallel, generating sequencing data for both human and Escherichia coli DNA libraries with negligible coverage bias compared to positive controls. All sequencing data from our libraries attained Phred (Q) scores > 30, mapping to reference genomes at 99% confidence. The method achieved final library concentrations and size distributions comparable with the conventional manual approach, demonstrating compatibility with downstream sequencing and subsequent data analysis. Our engineering design offers repeatability and consistency in the quality of sequence-able libraries, asserting the importance of mechanical design considerations that employ and optimize fundamental fluid mechanics and heat transfer properties. Furthermore in this work, we provide unique insights into the mechanisms of sample loss within NGS library preparation assays compared with automated adaptations and pinpoint areas in which the principles of thermodynamics, fluid mechanics, and heat transfer can improve future mechanical design iterations.

Whole-exome sequencing uncovers a novel EFEMP2 gene variant (c.C247T) associated with dominant nonsyndromic thoracic aortic aneurysm.

Thoracic aortic aneurysm (TAA) is a multifactorial disorder. Familial TAA, which is more clinically aggressive, is associated with a high risk of lethal dissection or rupture. Genetic evaluation can provide TAA patients with personalized treatment and help in predicting risk to family members. The purpose of this investigation was to report a likely pathogenic variant in the EFEMP2 gene that may contribute to TAA in a family with a documented history of the condition. In the index patient, the causative genetic predisposition was identified using whole-exome sequencing. The potential likely pathogenic effect of the candidate variant was further analyzed through bioinformatics analysis, homology modeling, and molecular docking. The results revealed a likely pathogenic heterozygous variant, c.247C>T p.Arg83Cys, in exon 4 of the EFEMP2 gene (NM_016938), which was predicted to have disease-causing effects by MutationTaster, PROVEAN, SIFT, and CADD (phred score = 27.6). In this study, a likely pathogenic variant in the EFEMP2 gene was identified in an Iranian family with a dominant pattern of autosomal inheritance of TAA. This finding underscores the importance of conducting molecular genetic evaluations in families with nonsyndromic TAA and the significance of early detection of at-risk family members.

Mutations in Histone Lysine Methyltransferase Genes Are Associated with Autoimmune Cytopenias

Introduction Epigenetic mechanisms are important in regulation of gene expression by modifying chromatin structure to facilitate DNA accessibility (Lau et al Nat Immunol. 2018). DNA methylation and histone modifications are critical for the pathogenesis of hematologic malignancies and autoimmune diseases (Surace et al Front Immunol. 2019) Alterations in enzymes involved in histone modification are associated with immunodeficiencies, including Kabuki syndrome (KS), a rare genetic disorder associated with autoimmune cytopenias, such as immune thrombocytopenia (ITP) and autoimmune hemolytic anemia (AIHA) (Margot et al J Am Coll Med Genet 2020) caused by loss-of-function KMT2D and KDM6A mutations. Somatic mutations in the KMT2D gene have also been observed in patients with Cold Agglutinin Disease. (Małecka et al Br J Haematol. 2018). Aims: The aims of this study are: 1) to identify the frequency of mutations in histone methyltransferase genes (MT) KMT2D, KMT2A, KMT2C and KDM6A in patients with autoimmune cytopenias, and 2) to compare clinical, laboratory and immunological characteristics, and response to therapy in patients with or without mutation in MT and autoimmune cytopenias (AIC). Methods Data mining software from the electronic medical record was used to identify patients ≥ 18 years with a diagnosis of AIC, including ITP, warm and cold AIHA, autoimmune neutropenia, and Evans Syndrome (ES), who had Next Generation Sequencing (NGS) performed. Cytopenias due to malignancy, nutritional deficiency, medications, pregnancy, or infection were excluded. Patients were categorized into two groups based on the presence or absence of mutation in the MT genes (MT+, MT-) with variant allelic frequency (VAF) > 2%. Demographic, laboratory, and clinical characteristics, treatment outcomes, and NGS sequencing data were collected and compared between groups. Next, KMT2 mutations seen in patients with AIC were cross-referenced against the 1000 Genome Project (1000GP) population database to evaluate the frequency of polymorphisms in the general population (Auton et al Nature 2015). CADD in silico prediction algorithm was used to score the potential deleterious effect of MT mutations (Kirchner Nat Genet. 2014). Chi-Square test was used for categorical variables. Statistical analysis was completed in R software. Results Among 495 patients who underwent NGS, 79 (16%) had a mutation in MT genes. These mutations were present in 36% of patients with AIC as compared to 13% in those without AIC (p=0.0005). Among 55 patients with AIC, mutations in the MT genes were present in 20 patients (MT+), 35 patients did not have these mutations (MT-). KMT2C mutations were seen in 10 (50%) patients, KMT2D mutations in 9 patients (45%, one patient had two KMT2D mutations), 1 patient (5%) had both KMT2C & KMT2D variants (Figure 1). The median VAF was 39.5% (IQR, 15.45 - 49.80). The MT+ group had a significantly higher proportion of Hispanic (60% vs 31%) and non-Hispanic White patients (25% vs 14%), p=0.038, Table 1. The median age at diagnosis for the MT+ cohort was younger compared to MT- (45.5 vs 58 years old, respectively), though not statistically significant. AIC diagnoses in both groups were ITP (44%) wAIHA (22%) cAIHA (9%) Autoimmune Neutropenia (2%), and ES (24%). Compared to the MT- group, the MT+ group had lower IgG levels (p=0.0041) and absolute lymphocyte count (p=0.041). MT+ patients with AIHA were more likely to have positive Direct Coombs and complement involvement. No significant differences were found in median nadir hemoglobin and platelet counts, need for therapy, or median number of lines of therapy. Best overall response to therapy was similar in the two groups (93%), with more complete responses in MT- group (55% vs 33%) though not statistically significant. Next, we assessed KMT2 polymorphisms in the general population. Most of the polymorphisms were not present in the 1000GP database and none had a frequency > 0.001. The average Phred score was 19.8; 12/20 patients had Phred score > 20, suggesting that most mutations are in the top 1% of the deleterious variants. Conclusion We report for the first time that patients with autoimmune cytopenias have a high frequency of variants in MT genes. Median allelic frequency close to 50% suggests potential germline predisposition to immune dysregulation and autoimmunity however further studies are needed to better understand the impact of these observations.

Transcriptome profiles of Streptomyces clavuligerus strains producing different titers of clavulanic acid

Streptomyces clavuligerus NRRL 3585 is a native producer of clavulanic acid (CA), a clinically used β-lactamase inhibitor, and is widely used as an industrial strain for the production of antibiotics. Selective random mutagenesis has successfully generated the improved CA-producing S. clavuligerus mutant strains as well as the strain with the loss of CA biosynthesis. To understand the molecular mechanisms associated with the improved CA-production potential, genome-scale RNA-sequencing-based transcriptional data were obtained for the wild-type S. clavuligerus strain and its three mutant strains. Total RNA samples for each strain were collected across four different growth stages, and all 32 sequencing data points exhibited an average Phred score of 36. The high-quality genome-scale transcriptional profile of S. clavuligerus strains with varied CA biosynthetic potential provides valuable insights and new opportunities for discovering efficient metabolic engineering strategies for the development of improved industrial strains.

Native American Ancestry Is Associated with Successful Immune Tolerance Induction in Admixed Brazilians with Hemophilia a

Immune tolerance induction (ITI) is the treatment of choice for eradicating neutralizing antibodies (inhibitors) against factor VIII (FVIII) in patients with hemophilia A (PwHA). Previous studies have investigated the association of ethnicity with inhibitor development with conflicting results. However, to our concern, studies targeting the role of ethnicity on ITI outcomes are still missing. Since unfavorable ITI response occurs in 30%-40% of these patients, establishing predictors of ITI response is needed. To evaluate genetic determinants of ITI outcome beyond FVIII genotype, we investigated the association of genomic ancestry and ITI response by analyzing the exomes of PwHA from the Brazilian Immune Tolerance Study (Camelo et al. 2021). PwHA were enrolled in 15 hemophilia treatment centers from all Brazilian regions. We collected clinical data and blood samples for DNA extraction. ITI was carried out using a single protocol, regardless of selection based on “good” or “bad” risk of ITI outcome. Inclusion criteria comprised patients with severe and moderately-severe (FVIII<2%) HA with high-responding inhibitors who completed a first course of ITI. Since the characteristics of PwHA who responded with partial and complete success yielded similar results, these groups were analyzed together. Exomes were obtained with high quality using the xGen Exome Research Panel v2 (Illumina). Quality control filters evaluated average coverage and deep coverage, phred score, genomic position, sex, heterozygosity, and duplicated SNPs. In a multiple regression analysis, we used geographic location, inhibitor levels, presence or absence of null mutations (i.e., frameshift, deletions, nonsense, and inversions; Oldenburg et al., 2002), and kinship coefficients as explanatory variables. Inhibitor levels were evaluated as historical inhibitor peak, titer immediately before the start of ITI, and inhibitor peak during ITI. We included 150 PwHA, of whom 136 (91%) had severe (FVIII<1%) HA, median age 0.9 years [IQR, 0.5,1.4] at diagnosis of HA. A total of 44 (29%) PwHA had ITI failure, 60 (40%) had partial success, and 46 (31%) had complete ITI success. Functional annotation showed that most SNPs were intronic (48%) and exonic (29%). We identified 808,706 variants, of which 90,075 were not reported in the dbSNP. Average ancestries of European, African, and Native American were 79.4% [IQR:75.4,83.4], 17.3% [IQR:17.0,17.6), and 3.3% [IQR:2.6,4.0], respectively (Table 1). There was an association between a higher Native American ancestry in patients with successful ITI (2% [IQR:1.95,2.05] ancestry mean) when compared with patients who failed ITI (1% [IQR:0.97,1.03] ancestry mean). A 1% increase in the Native American ancestry proportion was associated with a rise of ~10% in the probability of successful ITI ( odds ratio [OR], 10.43 [95% CI,7.45,13.41], p = 0.040 (Table 2). Neither European nor African ancestry was associated with ITI outcome. In conclusion, Native American ancestry was associated with successful ITI. To our concern, this is the first study to evaluate genomic ancestry as a predictor of ITI response and the first to enroll an admixed population of HA. Identifying ancestry as a predictor of ITI outcome may elicit different therapeutic approaches for inhibitor eradication. However, our findings may not apply to other populations due to a particular characteristic of admixture of the Brazilian population. REFERENCES Camelo, R.M. et al. (2021) ‘Predictors of the outcome of immune tolerance induction in patients with haemophilia A and inhibitors: The Brazilian Immune Tolerance (BRAZIT) study protocol’, PLOS ONE, 16(8). doi:10.1371/journal.pone.0256265. Oldenburg, J., El-Maarri, O. and Schwaab, R. (2002) ‘Inhibitor development in correlation to factor VIII genotypes’, Haemophilia, 8(s2), pp. 23-29. doi:10.1046/j.1351-8216.2001.00134.x.

B-234 The Quality in NGS: Do You Know How Much We Lost?

Abstract Background Next generation sequencing (NGS) is a new high throughput approach for genomic sequencing and variations detection. The consumption of NGS is numerous, such as times, money and human resource, therefore, some hospitals provided the service but delivered the specimen to other laboratories. Hence, we aimed to establish a procedure to monitor the quality and integrity of report. Method Here we used one clinical case to elucidate the whole process of raw sequence data analysis by free resource, a website usegalaxy.org and the IGV visualization software, with flowchart and quality control (QC) items. A delivered case will be an example to show how to monitor the QC. Results The flow chart showed the whole steps of analysis of NGS, including evaluation genetic variants in the report from individual laboratory. We processed the FASTQ file and analyzed the quality with three parameters. An overall picture of bases showed the phred score (QV) less than 28. Distribution of sequence lengths over all sequences highlighted a prominent peak at 110–119 bp. The mean QV of reads was around 26 with low quality (QV less than 20) in some reads. We then filtered the FASTQ file and the reads with length less than 45 bp or greater than 150 bp and QV less than 20 were filtered out. The data of the BAM file mapped to the designed panel were output. There were 8252 genome regions designed over 23 chromosomes (chr). A total number of reads was 1 085 653 with the average 131.6 reads (range: 0–31034; quartiles, IQ25: 1; IQ50: 27; IQ75: 152). 7746 of designed genome regions (93.9%) had reads less than 500 (quartiles, IQ25: 0; IQ50: 20; IQ75: 118). We further used IGV to check one of mutations which showed KRAS G12V in the report. KRAS G12V (chr.12: 25245350) was read 25 times with the variant allele frequency (C to A) of 24%. Conclusion We showed how to monitor the NGS quality by free resource. It is important to ensure high-quality data after we received the individual laboratory reports. That may help increase the quality of patient care and clinical service.

Error analysis of the PacBio sequencing CCS reads.

Third generation sequencing technologies such as Pacific Biosciences and Oxford Nanopore provide faster, cost-effective and simpler assembly process generating longer reads than the ones in the next generation sequencing. However, the error rates of these long reads are higher than those of the short reads, resulting in an error correcting process before the assembly such as using the Circular Consensus Sequencing (CCS) reads in PacBio sequencing machines. In this paper, we propose a probabilistic model for the error occurrence along the CCS reads. We obtain the error probability of any arbitrary nucleotide as well as the base calling Phred quality score of the nucleotides along the CCS reads in terms of the number of sub-reads. Furthermore, we derive the error rate distribution of the reads in relation to the pass number. It follows the binomial distribution which can be approximated by the normal distribution for long reads. Finally, we evaluate our proposed model by comparing it with three real PacBio datasets, namely, Lambda, and E. coli genomes, and Alzheimer's disease targeted experiment.

In Silico Analysis of MARS1 Gene to Elucidate Low- Frequency Variants Associated with Interstitial Lung and Liver Disease

Mutation in MARS1 gene is linked to the development of Interstitial lung and liver disease. The current study aimed in silico analysis to predict the most harmful missense and spliced variants of MARS1 that damage the functionality of Methionyl-tRNA synthetase 1 (MARS 1), catalyses the ligation of methionine to tRNA and is essential forprotein biosynthesis. A total of 492 variants were retrieved from the gnomAD database and analysed by CADD, 308 missense variants with PHRED score ≥ 20 were further analysed by CAPICE, META-SNP and CONDEL.85 SNPs detected with deleterious impact on protein structure by screening nsSNPs. Moreover, in-silico stability analysis was done by different tools like DynaMut, DUET, i-Stable2.0 and YASARA. MARS1 protein structure obtained from RCSB PDB (PDB ID: 5GL7) and UCSF Chimera was used for its visualisation. NetSurf-2.0 obtained the analysis of protein functioning by position of residue in the structure. Our results showed that the structure of proteins was significantly deleterious and protein motif and function were changed, we proceeded to use the PROSITE database to forecast the posttranslation modification sites and four significant nsSNPs with protein structure change effects. Splice analysis was conducted by SPiCE, Human Splice Finder. It concludes in silico analysis, genes can determine likely pathogenic variation for further in vitro experimental study.

Evaluation of cytosine conversion methods for whole-genome DNA methylation profiling

Background: DNA methylation, the most common epigenetic modification, is defined as the removal or addition of methyl groups to cytosine bases. Studying DNA methylation provides insight into the regulation of gene expression, transposon mobility, genomic stability, and genomic imprinting. Whole-genome DNA methylation profiling (WGDM) is a powerful tool to find DNA methylation. This technique combines standard whole-genome sequencing methodology (e.g., Illumina high-throughput sequencing) with additional steps where unmethylated cytosine is converted to uracil. However, factors such as low cytosine conversion efficiency and inadequate DNA recovery during sample preparation oftentimes render poor-quality data. It is therefore imperative to benchmark sample preparation protocols to increase sequencing data quality and reduce false positives in methylation detection. Methods: A survey analysis was performed to investigate the efficiency of the following commercially available cytosine conversion kits when coupled with the NEBNext® Ultra™ DNA Library Prep Kit for Illumina (NEB): Zymo Research EZ DNA Methylation™ kit (hereafter known as Zymo Conversion kit), QIAGEN EpiTect Bisulfite kit (hereafter known as QIAGEN Conversion kit), and NEBNext® Enzymatic Methyl-seq Conversion Module (hereafter known as NEB EM-seq kit). Input DNA was derived from soybean (Glycine max [L.] Merrill) leaf tissue. Results: Of those tested, the QIAGEN Conversion kit provided the best sample recovery and the highest number of sequencing reads, whereas the Zymo Conversion kit had the best cytosine conversion efficiency and the least duplication. The sequence library obtained with the NEB EM-seq kit had the highest mapping efficiency (percentage of reads mapped to the genome). The data quality (defined by Phred score) and methylated cytosine call were similar between kits. Conclusions: This study offers the groundwork for selecting an effective DNA methylation detection kit for crop genome research.

OA30 Genetic analysis of whole exome sequencing in a cohort of children with refractory JIA reveals genetic risk factors for rare juvenile diseases

Introduction/BackgroundJuvenile idiopathic arthritis (JIA) encompasses a group of heterogeneous rheumatic diseases of childhood onset. JIA can result in long term disability and remission is the main goal of treatment. However refractory disease can occur, which is defined as the absence of response to a standard disease therapy. A genetic basis for refractory disease has yet to explored, where deleterious rare variants complicate diagnosis or treatment outcome. This study aimed to investigate, through genetic analysis, whether children with JIA that is refractory carry rare genetic risk factors in genes linked to monogenic diseases.Description/MethodWhole exome sequencing of 99 children with JIA was performed with the Agilent SureSelect Human All ExonV6 kit. All quality control, variant filtering and annotation was performed in Varseq (version 2.2.1). Variants with a read depth <30 and genotype quality <80 were removed. Rarity and pathogenicity filters were then applied to remove variants with an allele frequency >1% (based on ExAC, gnomAD, gnomAD exome, NHLBI and 1KGp phase 3), classified as benign or likely benign on ClinVar, with a CADD PHRED score <15 and a REVEL score >0.7. Variants were annotated if they appeared in a gene from the primary immunodeficiency PanelApp (Martin et al., 2019), in a gene associated with an arthritis phenotype or in a gene that appeared on a paediatric monogenic gene list. The variants were then classified using ACMG guidelines (Richards et al., 2015) and benign, or likely benign, classified variants were removed.Discussion/ResultsA total of 470 variants were identified and we found that 20 out of the 99 children screened were heterozygous for at least one recognised variant in a gene linked to a monogenic disease. Five of these children carried more than one recognised variant linked to monogenic genes. Here we provide a number of illustrative examples: three genes, ADAR, ATP7B and MVK, were prioritised based on prior evidence of associated disease. The variant p.Pro193Ala (gnomAD allele frequency (GAD) 2.2x10-3) of ADAR has previously been deemed pathogenic in a homozygous or compound heterozygous state for Aicardi-Goutières syndrome. Adenosine deaminases (ADARs) catalyse the hydrolytic deamination of adenosine to inosine in dsRNA and is suggested to act as a suppressor of type 1 interferon-stimulated genes. Within ATP7B, two distinct variants were detected; p.Gln1142His (GAD 1.6x10-5) and p.Ile1148Thr (GAD 4.0x10-5) have previously been reported as pathogenic, in combination with a third variant, for Wilson’s disease and were carried by one individual in this cohort. ATP7B encodes copper-transporting ATPase 2, which supplies copper to ceruloplasmin. Variant p.Val377Ile (GAD 1.6x10-3) of MVK was detected in eight individuals in this cohort, interestingly five of these individuals also carried at least one HLA-DRB1 stop-gained variant. This MVK mutation has been confirmed as pathogenic in a homozygous or compound heterozygous state for mevalonate kinase deficiency. MVK converts mevalonic acid into mevalonate-5-phosphate in the cholesterol synthesis pathway. Additionally, two stop-gained loss of function HLA-DRB1 variants, p.Tyr107Ter and p.Gln125Ter, were detected in five and 20 individuals, respectively, in this cohort. HLA-DRB1 is a recognised susceptibility locus for JIA.Key learning points/ConclusionScreening of a cohort of 99 children with JIA that have refractory disease has revealed that individuals carry deleterious variants in genes linked to monogenic forms of disease. These results highlight that the genetic basis for refractory disease needs to be further investigated. Carrying additional genetic risk factors to disease may complicate disease outcome and genetic screening of children with refractory JIA may improve treatment outcome in the future.

PB1969: FUNCTIONAL CHARACTERIZATION OF SUSCEPTIBILITY LOCI TO MULTIPLE MYELOMA

Background: Multiple myeloma (MM) is the second most common blood malignancy, caused by an uncontrolled growth of plasma cells in the bone marrow, accounting for 20% of all newly diagnosed hematological cancers. Although the current 5-year survival rate is ranging between 40-60%, MM is still considered an incurable disease since most of the patients eventually relapse. While the causes of MM are incompletely understood, several genome-wide association studies (GWAS) have been conducted to identify germline variants that predispose to MM. Up to date, a total of 24 loci were found to be associated with MM risk, but very little information is available about their functional role. Aims: The principal goal is to explore in silico the function of the germline variants associated with MM risk. As we do not know if the GWAS-identified SNPs are the causal variants or just markers of risk, the functional characterization of the causal risk variants would lead to a better understanding of disease development. Methods: GWAS design takes advantage of the linkage disequilibrium (LD) structure of the human genome, thus the main GWAS findings are single-nucleotide polymorphisms (SNPs) that show the strongest association with MM risk (measured as the lowest p-values), but they are not necessarily the functionally causal variants. In this project, we used bioinformatics tools (GTEx, HaploReg v4.1, Roadmap, LDlinke, SNPnexus, RegulomeDB 2.0.3, SNP2TFBS, miRNASNP v3, GeneMANIA) to perform fine mapping of all GWAS-identified loci and to prioritize in each locus the polymorphism with the highest chance of being functionally relevant. In particular, we focused on the loci with the smallest number of SNPs in high LD (r2>0.8) in order to maximize the probability to capture the casual variant. Results: Four of the 24 MM risk loci had a relatively small number of SNPs in high LD and within them we found that the locus located at chromosome 16 contained the greatest number of functionally annotated SNPs. Of particular functional interest was rs3747481 (chr16:30666367 C/T) due to the following reasons: it is a missense variant (protein change: P359L), it is located in the PRR14 gene, that contributes to chromatin hierarchical organization and has a role in gene regulation, has a high CADD PHRED score (22.1). Additionally, according to GTEx portal, rs3747481 is associated with the expression level of the RNF40 gene (which plays a central role in histone code and gene regulation) in whole blood cells (p=3.02-12). It has a score of “1d” in RegulomeDB (eQTL+ TF binding + any motif + DNase peak), meaning that this variant has a high likelihood to affect binding of transcription factors. Some other SNPs (like rs35629860 and rs67128646) in the same LD block show the co-occurrence of H3K4me3 and H3K27me3 histone marks (associated with gene activation and repression, respectively) in promoters and enhancers in B lymphocytes. rs6565197 is predicted to affect the binding of the KLF4 and KLF5 transcription factors which play key roles in cell cycle regulation. Summary/Conclusion: Through a fine mapping of MM risk loci by bioinformatics tools, we found a variant in the locus 16p11.2 that shows in silico a very high probability to have biological role in the risk disease.

Abstract 5871: Genome wide association study of breast density among women of African ancestry

Abstract Introduction &amp; Purpose: Breast density, the relative amount of fibroglandular versus fatty tissue in the breast, is one of the strongest breast cancer risk factors. Understanding genetic factors associated with breast density may help clarify mechanisms by which breast density increases breast cancer risk. To date, 46 genetic loci have been associated with breast density, however, these studies have been performed among predominantly European ancestry populations. This study sought to identify genetic factors associated with breast density among women of African ancestry. Methods: We utilized a cohort of women aged 40-85 years who underwent screening mammography at the Hospital of the University of Pennsylvania from 2010-2014. The cohort was linked to the Penn Medicine BioBank (PMBB), a repository of DNA samples from consenting patients. We conducted a genome-wide association study (GWAS) of breast density among women with available genotypes who either self-reported their race as Black/African American, or had an African ancestry genotype (N = 1,323). For each mammogram, the publicly available “LIBRA” software (v1.0.4) was used to quantify dense area and area percent density (dense area divided by breast area) from raw (i.e., FOR PROCESSING) full-field digital mammograms (Selenia Dimensions, Hologic Inc.). Women completed a breast cancer risk factor questionnaire at the time of mammography and BMI was obtained from electronic health records. We tested for associations of dense area and area percent density with ~8.5M common variants, adjusting for age, BMI, menopausal status, and two principle components of ancestry as covariates. Results: We identified three novel loci associated with dense area at genome wide significance (p &amp;lt; 5e-08), including KCNA3 (rs61803939, p =3.40e-08, beta=3.26, SE=0.59) and two nearby loci on chromosome 19, ZNF486 (rs6511094, p =1.41e-08, beta=2.44, SE=0.43) and LOC100129265 (rs1428621382 p = 5.13E-08, beta=2.40, SE=0.44). Our results also replicated three previously reported signals near genes TET3 associated with dense area, TNS1 and SMIM25 associated with area percent density at nominally significant p &amp;lt; 1e-06. Conclusions: To our knowledge, this is the first breast density GWAS in women of African ancestry. Although the study had a small sample size, the analyses replicated associations of three known genes and also identified three novel breast density loci. Notably, variant rs61803939 mapping to KCNA3 gene is present in samples of African ancestry at a higher frequency (MAF=0.14) than in samples of European ancestry (MAF=0.09). Additionally, this variant also has a high oncogenecity score (Phred Score=21.9) and is estimated as likely driver of cancer. Further investigation of the role of variants in KCNA3 in breast density and in influencing the breast cancer risk are warranted, as are larger GWAS evaluating genetic variants for breast density among African ancestry populations. Citation Format: Shefali Verma, Lindsay Guare, Aimilia Gastounioti, Sarah Ehsan, Emily F. Conant, Marylyn Ritchie, Despina Kontos, Anne Marie McCarthy. Genome wide association study of breast density among women of African ancestry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5871.

Comparison of different sequencing techniques for identification of SARS-CoV-2 variants of concern with multiplex real-time PCR.

As different SARS-CoV-2 variants emerge and with the continuous evolvement of sub lineages of the delta variant, it is crucial that all countries carry out sequencing of at least >1% of their infections, in order to detect emergence of variants with higher transmissibility and with ability to evade immunity. However, due to limited resources as many resource poor countries are unable to sequence adequate number of viruses, we compared to usefulness of a two-step commercially available multiplex real-time PCR assay to detect important single nucleotide polymorphisms (SNPs) associated with the variants and compared the sensitivity, accuracy and cost effectiveness of the Illumina sequencing platform and the Oxford Nanopore Technologies' (ONT) platform. 138/143 (96.5%) identified as the alpha and 36/39 (92.3%) samples identified as the delta variants due to the presence of lineage defining SNPs by the multiplex real time PCR, were assigned to the same lineage by either of the two sequencing platforms. 34/37 of the samples sequenced by ONT had <5% ambiguous bases, while 21/37 samples sequenced using Illumina generated <5%. However, the mean PHRED scores averaged at 32.35 by Illumina reads but 10.78 in ONT. This difference results in a base error probability of 1 in 10 by the ONT and 1 in 1000 for Illumina sequencing platform. Sub-consensus single nucleotide variations (SNV) are highly correlated between both platforms (R2 = 0.79) while indels appear to have a weaker correlation (R2 = 0.13). Although the ONT had a slightly higher error rate compared to the Illumina technology, it achieved higher coverage with a lower number or reads, generated less ambiguous bases and was significantly less expensive than Illumina sequencing technology.

Benefits of merging paired-end reads before pre-processing environmental metagenomics data.

High throughput sequencing of environmental DNA has applications in biodiversity monitoring, taxa abundance estimation, understanding the dynamics of community ecology, and marine species studies and conservation. Environmental DNA, especially, marine eDNA, has a fast degradation rate. Aside from the good quality reads, the data could have a significant number of reads that fall slightly below the default PHRED quality threshold of 30 on sequencing. For quality control, trimming methods are employed, which generally precede the merging of the read pairs. However, in the case of eDNA, a significant percentage of reads within the acceptable quality score range are also dropped. To infer the ideal merge tool that is sensitive to eDNA, two Hiseq paired-end eDNA datasets were utilized to study the merging by the tools - FLASH (Fast Length Adjustment of SHort reads), PANDAseq, COPE, BBMerge, and VSEARCH without preprocessing. We assessed these tools on the following parameters: Time taken to process, the quality, and the number of merged reads. Trimmomatic, a widely-used preprocessing tool, was also assessed by preprocessing the datasets at different parameters for the two approaches of preprocessing: Sliding Window and Maximum Information. The preprocessed read pairs were then merged using the ideal merge tool identified earlier. FLASH is the most efficient merge tool balancing data conservation, quality of reads, and processing time. We compared Trimmomatic's two quality trimming options with increasing strictness with FLASH's direct merge. The raw reads processed with Trimmomatic then merged, yielded a significant drop in reads compared to the direct merge. An average of 29% of reads was dropped when directly merged with FLASH. Maximum Information option resulted in 30.7% to 68.05% read loss with lowest and highest stringency parameters, respectively. The Sliding Window approach conserves approximately 10% more reads at a PHRED score of 25 set as the threshold for a window of size 4. The lowered PHRED cut off conserves about 50% of the reads that could potentially be informative. We noted no significant reduction of data while optimizing the number of reads read in a window with the ideal quality (Q) score. Losing reads can negatively impact the downstream processing of the environmental data, especially for sequence alignment studies. The quality trim-first-merge-later approach can significantly decrease the number of reads conserved. However, direct merging of pair-end reads using FLASH conserved more than 60% of the reads. Therefore, direct merging of the paired-end reads can prevent potential removal of informative reads that do not comply by the trimming tool's strict checks. FLASH to be an efficient tool in conserving reads while carrying out quality trimming in moderation. Overall, our results show that merging paired-end reads of eDNA data before trimming can conserve more reads.

Evaluating whole-genome sequencing quality metrics for enteric pathogen outbreaks.

BackgroundWhole genome sequencing (WGS) has gained increasing importance in responses to enteric bacterial outbreaks. Common analysis procedures for WGS, single nucleotide polymorphisms (SNPs) and genome assembly, are highly dependent upon WGS data quality.MethodsRaw, unprocessed WGS reads from Escherichia coli, Salmonella enterica, and Shigella sonnei outbreak clusters were characterized for four quality metrics: PHRED score, read length, library insert size, and ambiguous nucleotide composition. PHRED scores were strongly correlated with improved SNPs analysis results in E. coli and S. enterica clusters.ResultsAssembly quality showed only moderate correlations with PHRED scores and library insert size, and then only for Salmonella. To improve SNP analyses and assemblies, we compared seven read-healing pipelines to improve these four quality metrics and to see how well they improved SNP analysis and genome assembly. The most effective read healing pipelines for SNPs analysis incorporated quality-based trimming, fixed-width trimming, or both. The Lyve-SET SNPs pipeline showed a more marked improvement than the CFSAN SNP Pipeline, but the latter performed better on raw, unhealed reads. For genome assembly, SPAdes enabled significant improvements in healed E. coli reads only, while Skesa yielded no significant improvements on healed reads.ConclusionsPHRED scores will continue to be a crucial quality metric albeit not of equal impact across all types of analyses for all enteric bacteria. While trimming-based read healing performed well for SNPs analyses, different read healing approaches are likely needed for genome assembly or other, emerging WGS analysis methodologies.

Germline and Somatic Variants Co-Ocurrence Profile in Early Onset Adult Myelodysplastic Syndromes without a Preexisting Disorder

Germline and Somatic Variants Co-Ocurrence Profile in Early Onset Adult Myelodysplastic Syndromes without a Preexisting Disorder

Nanopore Single-Molecule Sequencing for Mitochondrial DNA Methylation Analysis: Investigating Parkin-Associated Parkinsonism as a Proof of Concept.

Objective: To establish a workflow for mitochondrial DNA (mtDNA) CpG methylation using Nanopore whole-genome sequencing and perform first pilot experiments on affected Parkin biallelic mutation carriers (Parkin-PD) and healthy controls.Background: Mitochondria, including mtDNA, are established key players in Parkinson's disease (PD) pathogenesis. Mutations in Parkin, essential for degradation of damaged mitochondria, cause early-onset PD. However, mtDNA methylation and its implication in PD is understudied. Herein, we establish a workflow using Nanopore sequencing to directly detect mtDNA CpG methylation and compare mtDNA methylation between Parkin-related PD and healthy individuals.Methods: To obtain mtDNA, whole-genome Nanopore sequencing was performed on blood-derived from five Parkin-PD and three control subjects. In addition, induced pluripotent stem cell (iPSC)-derived midbrain neurons from four of these patients with PD and the three control subjects were investigated. The workflow was validated, using methylated and unmethylated 897 bp synthetic DNA samples at different dilution ratios (0, 50, 100% methylation) and mtDNA without methylation. MtDNA CpG methylation frequency (MF) was detected using Nanopolish and Megalodon.Results: Across all blood-derived samples, we obtained a mean coverage of 250.3X (SD ± 80.5X) and across all neuron-derived samples 830X (SD ± 465X) of the mitochondrial genome. We detected overall low-level CpG methylation from the blood-derived DNA (mean MF ± SD = 0.029 ± 0.041) and neuron-derived DNA (mean MF ± SD = 0.019 ± 0.035). Validation of the workflow, using synthetic DNA samples showed that highly methylated DNA molecules were prone to lower Guppy Phred quality scores and thereby more likely to fail Guppy base-calling. CpG methylation in blood- and neuron-derived DNA was significantly lower in Parkin-PD compared to controls (Mann-Whitney U-test p < 0.05).Conclusion: Nanopore sequencing is a useful method to investigate mtDNA methylation architecture, including Guppy-failed reads is of importance when investigating highly methylated sites. We present a mtDNA methylation workflow and suggest methylation variability across different tissues and between Parkin-PD patients and controls as an initial model to investigate.