scholarly journals Variant Interpretation: UCSC Genome Browser Recommended Track Sets

Author(s):  
Anna Benet-Pagès ◽  
Kate Rosenbloom ◽  
Luis Nassar ◽  
Christopher Lee ◽  
Brian Raney ◽  
...  

The UCSC Genome Browser has been an important tool for genomics and clinical genetics since the sequence of the human genome was first released in 2000. As it has grown in scope to display more types of data it has also grown more complicated. The data, which are dispersed at many locations worldwide, are collected into one view on the Browser, where the graphical interface presents the data in one location. This supports the expertise of the researcher to interpret variants in the genome. Because the analysis of Single Nucleotide Variants (SNVs) and Copy Number Variants (CNVs) require interpretation of data at very different genomic scales, different data resources are required. We present here several Recommended Track Sets designed to facilitate the interpretation of variants in the clinic, offering quick access to datasets relevant to the appropriate scale.

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Leandro de Araújo Lima ◽  
Ana Cecília Feio-dos-Santos ◽  
Sintia Iole Belangero ◽  
Ary Gadelha ◽  
Rodrigo Affonseca Bressan ◽  
...  

Abstract Many studies have attempted to investigate the genetic susceptibility of Attention-Deficit/Hyperactivity Disorder (ADHD), but without much success. The present study aimed to analyze both single-nucleotide and copy-number variants contributing to the genetic architecture of ADHD. We generated exome data from 30 Brazilian trios with sporadic ADHD. We also analyzed a Brazilian sample of 503 children/adolescent controls from a High Risk Cohort Study for the Development of Childhood Psychiatric Disorders, and also previously published results of five CNV studies and one GWAS meta-analysis of ADHD involving children/adolescents. The results from the Brazilian trios showed that cases with de novo SNVs tend not to have de novo CNVs and vice-versa. Although the sample size is small, we could also see that various comorbidities are more frequent in cases with only inherited variants. Moreover, using only genes expressed in brain, we constructed two “in silico” protein-protein interaction networks, one with genes from any analysis, and other with genes with hits in two analyses. Topological and functional analyses of genes in this network uncovered genes related to synapse, cell adhesion, glutamatergic and serotoninergic pathways, both confirming findings of previous studies and capturing new genes and genetic variants in these pathways.


ESC CardioMed ◽  
2018 ◽  
pp. 669-671
Author(s):  
Eric Schulze-Bahr

The human genome consists of approximately 3 billion (3 × 109) base pairs of DNA (around 20,000 genes), organized as 23 chromosomes (diploid parental set), and a small mitochondrial genome (37 genes, including 13 proteins; 16,589 base pairs) of maternal origin. Most human genetic variation is natural, that is, common or rare (minor allele frequency >0.1%) and does not cause disease—apart from every true disease-causing (bona fide) mutation each individual genome harbours more than 3.5 million single nucleotide variants (including >10,000 non-synonymous changes causing amino acid substitutions) and 200–300 large structural or copy number variants (insertions/deletions, up to several thousands of base-pairs) that are non-disease-causing variations and scattered throughout coding and non-coding genomic regions.


Author(s):  
Alexander Charney ◽  
Pamela Sklar

Schizophrenia and bipolar disorder are the classic psychotic disorders. Both diseases are strongly familial, but have proven recalcitrant to genetic methodologies for identifying the etiology until recently. There is now convincing genetic evidence that indicates a contribution of many DNA changes to the risk of becoming ill. For schizophrenia, there are large contributions of rare copy number variants and common single nucleotide variants, with an overall highly polygenic genetic architecture. For bipolar disorder, the role of copy number variation appears to be much less pronounced. Specific common single nucleotide polymorphisms are associated, and there is evidence for polygenicity. Several surprises have emerged from the genetic data that indicate there is significantly more molecular overlap in copy number variants between autism and schizophrenia, and in common variants between schizophrenia and bipolar disorder.


Author(s):  
Pamela Sklar

Schizophrenia and bipolar disorder are the classic psychotic disorders. Both diseases are strongly familial, but have proven recalcitrant to genetic methodologies for identifying the etiology until recently. The explosion of strong and convincing genetic evidence indicates a contribution of many DNA changes to the risk of becoming ill. For schizophrenia, there are large contributions of rare copy number variants and common single nucleotide variants, with an overall highly polygenic genetic architecture. There is a role for rare single nucleotide variation as well as de novo genetic variation being pointed to in new sequencing studies, but their overall contribution to risk is less clear. For bipolar disorder, the role of copy number variation appears to be much less pronounced. Specific common single nucleotide polymorphisms are associated, there is evidence for polygenicity and as yet no deep sequencing surveys have been published. Several intriguing biological pathways are suggested by these genetic findings related to microRNAs and calcium channel signaling. Several surprises have emerged from the genetic data that indicate there is significantly more molecular overlap in copy number variants between autism and schizophrenia, and in common variants between schizophrenia and bipolar disorder. Translating these results into biological and etiological understanding has not yet advanced, and will likely only do so when experimental methods are developed than can address the large numbers of genes and variants within them that, along with environmental and stochastic effects, result in the development of disease for a particular person.


2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Farah Qaiser ◽  
Tara Sadoway ◽  
Yue Yin ◽  
Quratulain Zulfiqar Ali ◽  
Charlotte M Nguyen ◽  
...  

Abstract Epilepsies are a group of common neurological disorders with a substantial genetic basis. Despite this, the molecular diagnosis of epilepsies remains challenging due to its heterogeneity. Studies utilizing whole-genome sequencing may provide additional insights into genetic causes of epilepsies of unknown aetiology. Whole-genome sequencing was used to evaluate a cohort of adults with unexplained developmental and epileptic encephalopathies (n = 30), for whom prior genetic tests, including whole-exome sequencing in some cases, were negative or inconclusive. Rare single nucleotide variants, insertions/deletions, copy number variants and tandem repeat expansions were analysed. Seven pathogenic or likely pathogenic single nucleotide variants, and two pathogenic deleterious copy number variants were identified in nine patients (32.1% of the cohort). One of the copy number variants, identified in a patient with Lennox–Gastaut syndrome, was too small to be detected by chromosomal microarray techniques. We also identified two tandem repeat expansions with clinical implications in two other patients with Lennox–Gastaut syndrome: a CGG repeat expansion in the 5′untranslated region of DIP2B, and a CTG expansion in ATXN8OS (previously implicated in spinocerebellar ataxia type 8). Three patients had KCNA2 pathogenic variants. One of them died of sudden unexpected death in epilepsy. The other two patients had, in addition to a KCNA2 variant, a second de novo variant impacting potential epilepsy-relevant genes (KCNIP4 and UBR5). Overall, whole-genome sequencing provided a genetic explanation in 32.1% of the total cohort. This is also the first report of coding and non-coding tandem repeat expansions identified in patients with Lennox–Gastaut syndrome. This study demonstrates that using whole-genome sequencing, the examination of multiple types of rare genetic variation, including those found in the non-coding region of the genome, can help resolve unexplained epilepsies.


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