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Alamut visual 2

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Alamut Visual 2.7.1 is a software application designed for the visualization and analysis of genomic data. It provides a user-friendly interface for displaying and interpreting genetic sequences, variants, and annotations.

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Lab products found in correlation

Ion 318 v2 chip, by Thermo Fisher Scientific (2 mentions) Ion pgm sequencer, by Thermo Fisher Scientific (2 mentions) Miseq reporter, by Illumina (1 mentions) Alamut, by Sophia Genetics (1 mentions) Alamut batch, by Sophia Genetics (1 mentions) Dneasy blood tissue kit, by Qiagen (1 mentions)

13 protocols using alamut visual 2

1

Comprehensive Genetic Screening for aHUS Variants

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Variant screening of CFH, CFI, CFB, C3, and CD46 was undertaken using Sanger sequencing, as previously described.27 (link)-31 (link) Screening for chromosomal rearrangements affecting CFH, CFHR1, CFHR2, CFHR3, CFHR4, CFHR5, CFI, and CD46 was undertaken using multiplex ligation-dependent probe amplification, as previously described.32 (link),33 (link) To assess for genetic abnormalities in noncomplement genes associated with aHUS including DGKE,34 (link)MMACHC, VTN, PLG, THBD, and IFN235 (link) Sanger sequencing was performed (Tables S3A–C, SDC, http://links.lww.com/TP/C577) in selected patients.
Rare genetic variants were evaluated using Alamut Visual 2.10 (2017 Interactive Biosoftware). Variants were classified in 2019 according to American College of Medical Genetics and Genomics guidelines36 (link) with refinement developed by Sequence Variant Interpretation Working Group.37
Glover E.K., Smith-Jackson K., Brocklebank V., Wilson V., Walsh P.R., Montgomery E.K., Wong E.K., Johnson S., Malina M., Kavanagh D, & Sheerin N.S. (2023). Assessing the Impact of Prophylactic Eculizumab on Renal Graft Survival in Atypical Hemolytic Uremic Syndrome. Transplantation, 107(4), 994-1003.
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2

Bioinformatics Variant Pathogenicity Analysis

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Three consensual bioinformatics programs (Polyphen-2 [ref. 8 ], SIFT 9 via Alamut Visual 2.10 [Interactive Biosoftware, France], and UMD-Predictor 10 ) were used to predict pathogenicity of missense variants. Effect on splicing was analyzed through different tools including Human Splicing Finder, 11 splicing prediction algorithm NNSPLICE, 12 and MaxEntScan method. 13 The UMD locus-specific databases and Human Gene Mutation Database (HGMD®) were queried for each identified variant (see URLs). The existence of each molecular event was looked for in the Genome Aggregation Database (gnomAD). 14 However, the laboratory has been performing molecular diagnosis of MFS and TAAD for over 20 years and a population of over 5000 probands has been sequenced for the disease-causing genes. This has led to an in-house reference database of molecular events identified in each gene for which we have robust French population frequencies. Variants were classified according to recommendations of the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP). 15
Arnaud P., Hanna N., Benarroch L., Aubart M., Bal L., Bouvagnet P., Busa T., Dulac Y., Dupuis-Girod S., Edouard T., Faivre L., Gouya L., Lacombe D., Langeois M., Leheup B., Milleron O., Naudion S., Odent S., Tchitchinadze M., Ropers J., Jondeau G, & Boileau C. (2019). Genetic diversity and pathogenic variants as possible predictors of severity in a French sample of nonsyndromic heritable thoracic aortic aneurysms and dissections (nshTAAD). Genetics in medicine : official journal of the American College of Medical Genetics, 21(9).
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3

Pathogenicity Prediction of Genetic Variants

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Four traditional bioinformatics programs (Grantham score, Polyphen-2, 11 SIFT 12 via Alamut Visual 2.7 (Interactive Biosoftware, Rouen, France) and UMD-Predictor 13 ) were used to predict pathogenicity of missense variants. Effect on splicing was analysed through different tools including Human Splicing Finder, 14 splicing prediction algorithm NNSPLICE 15 and MaxEntScan method. 16 The locus-specific database UMD-FBN1 3 was consulted for each identified variant. The existence of each molecular event was looked for in the Exome Aggregation Consortium (ExAC) database.
Arnaud P., Hanna N., Aubart M., Leheup B., Dupuis-Girod S., Naudion S., Lacombe D., Milleron O., Odent S., Faivre L., Bal L., Edouard T., Collod-Beroud G., Langeois M., Spentchian M., Gouya L., Jondeau G, & Boileau C. (2017). Homozygous and compound heterozygous mutations in the FBN1 gene: unexpected findings in molecular diagnosis of Marfan syndrome. Journal of medical genetics, 54(2).
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4

Comprehensive Germline and Somatic Variant Analysis in PPGL

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Demultiplexing was performed using MiSeq Reporter (Illumina, California, USA). Alignment and variant calling were performed using SeqNext (JSI Medical Systems) and PolyDiag (Paris Descartes University) software. PolyDiag software used BWA-MEM as a read aligner and Freebayes, Samtools and GATK as variant callers. The 17 genes included in the 'MASTR Plus SDHv2' panel were analysed on tumour DNAs. As, in PPGL, ATRX and HRAS genes have been reported as somatically mutated only, 14 15 they were not analysed in germline DNAs of patients. The variant analysis was mainly performed using Alamut Visual 2.7 (Interactive Biosoftware) as an interface. Variant classification into five classes 16 was based on the framework published by the NGSnPPGL group taking into account multiple criteria including the frequency of the variant in the general population and disease databases, its description in the literature, the variant type, the co-segregation with the disease in families if any, the co-occurrence with known pathogenic mutation, the in silico predictions and the results of functional or supplemental studies. 2 Additional information can be found in the online supplementary methods.
Ben Aim L., Pigny P., Castro-Vega L.J., Buffet A., Amar L., Bertherat J., Drui D., Guilhem I., Baudin E., Lussey-Lepoutre C., Corsini C., Chabrier G., Briet C., Faivre L., Cardot-Bauters C., Favier J., Gimenez-Roqueplo A.P, & Burnichon N. (2019). Targeted next-generation sequencing detects rare genetic events in pheochromocytoma and paraganglioma. Journal of medical genetics, 56(8).
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5

Genetic Variant Analysis Using Public Databases

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In the reads mapping against the human genome 19 (hg19) reference sequence to reveal potential genetic differences, we used single nucleotide polymorphism (SNP) databases such as HapMap project, 1000 Genome Project, Exome Variant Server (EVS), Exome Aggregation Consortium (EXAC), and Genome Aggregation Database (GnomAD). Alamut Visual 2.11 (Interactive Biosoftware, Rouen, France) was used to estimate the pathogenicity of detected variants. The amino acid change was considered potentially disease causing if predicted by at least one of the programs (PolyPhen2), Sorting Intolerant From Tolerant (SIFT), and Mutation Taster. Amino acid conservation across species was studied with the UCSC Genome Browser.
Approval for this study was given by the ethics committee of the University of Sciences, Technologies and Medicine, Nouakchott, Mauritania. The purpose of the study was explained to the participants, and their informed and signed consent taken. For children, the parents’ approval was obtained. This study was carried out in accordance with the ethical principles for medical research involving human subjects defined by the World Medical Association Declaration of Helsinki.
Hadrami M., Bonnet C., Zeitz C., Veten F., Biya M., Hamed C.T., Condroyer C., Wang P., Sidi M.M., Cheikh S., Zhang Q., Audo I., Petit C, & Houmeida A. (2019). Mutation profile of glaucoma candidate genes in Mauritanian families with primary congenital glaucoma. Molecular Vision, 25, 373-381.
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6

Comprehensive Genomic Variant Analysis of KDM6A

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All detected point variants were harmonized according to the canonical KDM6A transcript NM_021140.3 using MutationTaster2 (http://www.mutationtaster.org/). InterVar (http://wintervar.wglab.org/) was used to apply the 2015 American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for variant interpretation.19 (link) Protein altering variants (PAVs) were analyzed by the Variant Effect Predictor (http://grch37.ensembl.org/Homo_sapiens/Tools/VEP) to obtain minor allele frequencies (MAFs) in controls, exon location, in silico predictions, previous reports, and evolutionary conservation. Alamut® Visual 2.11 (Interactive Biosoftware, France) and UniProtKB (https://www.uniprot.org/uniprot/O15550) were used for exon-skipping analyses and determining affected domains, respectively. PAVs with decreased in vitro demethylation were obtained from the work of Shpargel et al.20 (link) To analyze copy-number variants (CNVs) encompassing KDM6A, the University of California–Santa Cruz (UCSC) Genome Browser (GRCh37) was used.
Faundes V., Goh S., Akilapa R., Bezuidenhout H., Bjornsson H.T., Bradley L., Brady A.F., Brischoux-Boucher E., Brunner H., Bulk S., Canham N., Cody D., Dentici M.L., Digilio M.C., Elmslie F., Fry A.E., Gill H., Hurst J., Johnson D., Julia S., Lachlan K., Lebel R.R., Byler M., Gershon E., Lemire E., Gnazzo M., Lepri F.R., Marchese A., McEntagart M., McGaughran J., Mizuno S., Okamoto N., Rieubland C., Rodgers J., Sasaki E., Scalais E., Scurr I., Suri M., van der Burgt I., Matsumoto N., Miyake N., Benoit V., Lederer D, & Banka S. (2021). Clinical delineation, sex differences, and genotype–phenotype correlation in pathogenic KDM6A variants causing X-linked Kabuki syndrome type 2. Genetics in Medicine, 23(7), 1202-1210.
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7

Ion PGM Sequencing and Variant Confirmation

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Sequencing was performed using an Ion PGM sequencer (Life Technologies) with Ion 318™ Chip v2. 25 microlitres of a pool of DNA at 20 pM was used for emulsion PCR. Quality of sequencing was assessed by the PGM sequencer by providing the Ion Sphere Particle (ISP) density, number of total reads, percentage of usable reads, percentages of monoclonal and polyclonal reads, mean read length (AQ17, AQ20 and perfect), percentages of low quality sequences, adapter dimers and aligned bases. Bam files were loaded on Alamut Visual 2.5 (Interactive Biosoftware) and variant detection was performed manually by setting the variant detection threshold to 0.04. Gained stop, splice site, frameshift and rare missense variants (at a frequency of less than 0.1% in the Exome Variant Server http://evs.gs.washington.edu/EVS/) were selected for Sanger sequencing of the six individual DNAs composing the pool carrying each selected variant. Variants of interest were confirmed on a second dilution of DNA and on an independent sample. Subsequently, relatives were tested for variant segregation analysis.
Guimier A., Gabriel G.C., Bajolle F., Tsang M., Liu H., Noll A., Schwartz M., El Malti R., Smith L.D., Klena N.T., Jimenez G., Miller N.A., Oufadem M., Moreau de Bellaing A., Yagi H., Saunders C.J., Baker C.N., Di Filippo S., Peterson K.A., Thiffault I., Bole-Feysot C., Cooley L.D., Farrow E.G., Masson C., Schoen P., Deleuze J.F., Nitschké P., Lyonnet S., de Pontual L., Murray S.A., Bonnet D., Kingsmore S.F., Amiel J., Bouvagnet P., Lo C.W, & Gordon C.T. (2015). MMP21 is mutated in human heterotaxy and is required for normal left-right asymmetry in vertebrates. Nature genetics, 47(11), 1260-1263.
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8

Ion PGM Sequencing and Variant Confirmation

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Sequencing was performed using an Ion PGM sequencer (Life Technologies) with Ion 318™ Chip v2. 25 microlitres of a pool of DNA at 20 pM was used for emulsion PCR. Quality of sequencing was assessed by the PGM sequencer by providing the Ion Sphere Particle (ISP) density, number of total reads, percentage of usable reads, percentages of monoclonal and polyclonal reads, mean read length (AQ17, AQ20 and perfect), percentages of low quality sequences, adapter dimers and aligned bases. Bam files were loaded on Alamut Visual 2.5 (Interactive Biosoftware) and variant detection was performed manually by setting the variant detection threshold to 0.04. Gained stop, splice site, frameshift and rare missense variants (at a frequency of less than 0.1% in the Exome Variant Server http://evs.gs.washington.edu/EVS/) were selected for Sanger sequencing of the six individual DNAs composing the pool carrying each selected variant. Variants of interest were confirmed on a second dilution of DNA and on an independent sample. Subsequently, relatives were tested for variant segregation analysis.
Guimier A., Gabriel G.C., Bajolle F., Tsang M., Liu H., Noll A., Schwartz M., El Malti R., Smith L.D., Klena N.T., Jimenez G., Miller N.A., Oufadem M., Moreau de Bellaing A., Yagi H., Saunders C.J., Baker C.N., Di Filippo S., Peterson K.A., Thiffault I., Bole-Feysot C., Cooley L.D., Farrow E.G., Masson C., Schoen P., Deleuze J.F., Nitschké P., Lyonnet S., de Pontual L., Murray S.A., Bonnet D., Kingsmore S.F., Amiel J., Bouvagnet P., Lo C.W, & Gordon C.T. (2015). MMP21 is mutated in human heterotaxy and is required for normal left-right asymmetry in vertebrates. Nature genetics, 47(11), 1260-1263.
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9

Variant Classification in Genetic Disorders

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Variants were classified as recommended by the American College of Medical Genetics and Genomics (ACMG) standards and guidelines and the Association for Molecular Pathology (AMP) Clinical Practice Guidelines. The recommendations were based on population data, computational data and previous publications. Variant frequencies were taken from the Browser of the Exome Aggregation Consortium (ExAC), variants with a minor allele frequency (MAF) > 0.005 were excluded from further analysis. Rare missense mutations were tested for disease relevance by prediction algorithms of the programs MutationTaster, SIFT and PolyPhen-2. When at least two of the three programs predicted a pathogenic effect, the variants were classified as “likely pathogenic”. Stop mutations were classified as pathogenic. Intronic and synonymous variants were further analyzed for a potential effect on correct splicing by using the interface provided by the software package Alamut (Interactive Biosoftware, Rouen, France, Alamut Visual 2.7.1) which combines five algorithms (SpliceSiteFnder, MaxEntScan, NNSPLICE, GeneSplicer and Human Splicing Finder). All tools provide prediction scores for the normal and the mutant allele.
Brandl C., Schulz H.L., Charbel Issa P., Birtel J., Bergholz R., Lange C., Dahlke C., Zobor D., Weber B.H, & Stöhr H. (2017). Mutations in the Genes for Interphotoreceptor Matrix Proteoglycans, IMPG1 and IMPG2, in Patients with Vitelliform Macular Lesions. Genes, 8(7), 170.
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10

Predicting Pathogenic Mechanism with Bioinformatics Tools

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To predict pathogenic mechanism, a software program (Alamut Visual 2.7-1, Interactive Biosoftware) was used, combining different programs such as Sorting Intolerant From Tolerant (SIFT, http://sift.jcvi.org/), [35 (link)], Polymorphism Phenotyping v2 (PolyPhen-2, http://genetics.bwh.harvard.edu/pph2/), [36 (link)], and Mutation Taster (http://www.mutationtaster.org/) [37 (link)]. This analysis also delivers frequencies in known databases such as Database of Single Nucleotide Polymorphisms (dbSNP, https://www.ncbi.nlm.nih.gov/snp), Exome Aggregation Consortium (ExAC, http://exac.broadinstitute.org/), and Exome Variants Server (EVS, http://evs.gs.washington.edu/EVS/). In addition, the presence of the variant in common databases was investigated using 1000 Genomes (http://www.1000genomes.org/) and gnomAD (http://gnomad.broadinstitute.org/). The Human Gene Mutation Database HGMD® Pro was consulted to investigate for known variants implicated in disease.
Zeitz C., Méjécase C., Stévenard M., Michiels C., Audo I, & Marmor M.F. (2018). A Novel Heterozygous Missense Mutation in GNAT1 Leads to Autosomal Dominant Riggs Type of Congenital Stationary Night Blindness. BioMed Research International, 2018, 7694801.
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