scholarly journals The Medical Genome Initiative: moving whole-genome sequencing for rare disease diagnosis to the clinic

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Christian R. Marshall ◽  
◽  
David Bick ◽  
John W. Belmont ◽  
Stacie L. Taylor ◽  
...  
2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Brent S. Pedersen ◽  
Joe M. Brown ◽  
Harriet Dashnow ◽  
Amelia D. Wallace ◽  
Matt Velinder ◽  
...  

AbstractIn studies of families with rare disease, it is common to screen for de novo mutations, as well as recessive or dominant variants that explain the phenotype. However, the filtering strategies and software used to prioritize high-confidence variants vary from study to study. In an effort to establish recommendations for rare disease research, we explore effective guidelines for variant (SNP and INDEL) filtering and report the expected number of candidates for de novo dominant, recessive, and autosomal dominant modes of inheritance. We derived these guidelines using two large family-based cohorts that underwent whole-genome sequencing, as well as two family cohorts with whole-exome sequencing. The filters are applied to common attributes, including genotype-quality, sequencing depth, allele balance, and population allele frequency. The resulting guidelines yield ~10 candidate SNP and INDEL variants per exome, and 18 per genome for recessive and de novo dominant modes of inheritance, with substantially more candidates for autosomal dominant inheritance. For family-based, whole-genome sequencing studies, this number includes an average of three de novo, ten compound heterozygous, one autosomal recessive, four X-linked variants, and roughly 100 candidate variants following autosomal dominant inheritance. The slivar software we developed to establish and rapidly apply these filters to VCF files is available at https://github.com/brentp/slivar under an MIT license, and includes documentation and recommendations for best practices for rare disease analysis.


2020 ◽  
Vol 117 (6) ◽  
pp. 3053-3062 ◽  
Author(s):  
Ying-Chen Claire Hou ◽  
Hung-Chun Yu ◽  
Rick Martin ◽  
Elizabeth T. Cirulli ◽  
Natalie M. Schenker-Ahmed ◽  
...  

Genome sequencing has established clinical utility for rare disease diagnosis. While increasing numbers of individuals have undergone elective genome sequencing, a comprehensive study surveying genome-wide disease-associated genes in adults with deep phenotyping has not been reported. Here we report the results of a 3-y precision medicine study with a goal to integrate whole-genome sequencing with deep phenotyping. A cohort of 1,190 adult participants (402 female [33.8%]; mean age, 54 y [range 20 to 89+]; 70.6% European) had whole-genome sequencing, and were deeply phenotyped using metabolomics, advanced imaging, and clinical laboratory tests in addition to family/medical history. Of 1,190 adults, 206 (17.3%) had at least 1 genetic variant with pathogenic (P) or likely pathogenic (LP) assessment that suggests a predisposition of genetic risk. A multidisciplinary clinical team reviewed all reportable findings for the assessment of genotype and phenotype associations, and 137 (11.5%) had genotype and phenotype associations. A high percentage of genotype and phenotype associations (>75%) was observed for dyslipidemia (n = 24), cardiomyopathy, arrhythmia, and other cardiac diseases (n = 42), and diabetes and endocrine diseases (n = 17). A lack of genotype and phenotype associations, a potential burden for patient care, was observed in 69 (5.8%) individuals with P/LP variants. Genomics and metabolomics associations identified 61 (5.1%) heterozygotes with phenotype manifestations affecting serum metabolite levels in amino acid, lipid and cofactor, and vitamin pathways. Our descriptive analysis provides results on the integration of whole-genome sequencing and deep phenotyping for clinical assessments in adults.


2019 ◽  
Author(s):  
James M. Holt ◽  
Camille L. Birch ◽  
Donna M. Brown ◽  
Manavalan Gajapathy ◽  
Nadiya Sosonkina ◽  
...  

AbstractPurposeClinical whole genome sequencing is becoming more common for determining the molecular diagnosis of rare disease. However, standard clinical practice often focuses on small variants such as single nucleotide variants and small insertions/deletions. This leaves a wide range of larger “structural variants” that are not commonly analyzed in patients.MethodsWe developed a pipeline for processing structural variants for patients who received whole genome sequencing through the Undiagnosed Diseases Network (UDN). This pipeline called structural variants, stored them in an internal database, and filtered the variants based on internal frequencies and external annotations. The remaining variants were manually inspected and then interesting findings were reported as research variants to clinical sites in the UDN.ResultsOf 477 analyzed UDN cases, 286 cases (≈ 60%) received at least one structural variant as a research finding. The variants in 16 cases (≈ 4%) are considered “Certain” or “Highly likely” molecularly diagnosed and another 4 cases are currently in review. Of those 20 cases, at least 13 were identified originally through our pipeline with one finding leading to identification of a new disease. As part of this paper, we have also released the collection of variant calls identified in our cohort along with heterozygous and homozygous call counts. This data is available at https://github.com/HudsonAlpha/UDN_SV_export.ConclusionStructural variants are key genetic features that should be analyzed during routine clinical genomic analysis. For our UDN patients, structural variants helped solve ≈ 4% of the total number of cases (≈ 13% of all genome sequencing solves), a success rate we expect to improve with better tools and greater understanding of the human genome.


2012 ◽  
Vol 4 (154) ◽  
pp. 154ra135-154ra135 ◽  
Author(s):  
C. J. Saunders ◽  
N. A. Miller ◽  
S. E. Soden ◽  
D. L. Dinwiddie ◽  
A. Noll ◽  
...  

2018 ◽  
Author(s):  
Lisha Zhu ◽  
Kaiyu Jiang ◽  
Laiping Wong ◽  
Michael J. Buck ◽  
Yanmin Chen ◽  
...  

AbstractBackgroundJuvenile idiopathic arthritis (JIA) is one of the most common chronic conditions of childhood. Like many common chronic human illnesses, JIA likely involves complex interactions between genes and the environment, mediated by the epigenome. Such interactions are best understood through multi-dimensional genomic maps that identify critical genetic and epigenetic components of the disease. However, constructing such maps in a cost-effective way is challenging, and this challenge is further complicated by the challenge of obtaining biospecimens from pediatric patients at time of disease diagnosis, prior to therapy, as well as the limited quantity of biospecimen that can be obtained from children,particularly those who are unwell. In this paper, we demonstrate the feasibility and utility of creating multi-dimensional genomic maps for JIA from limited sample numbers.MethodsTo accomplish our aims, we used an approach similar to that used in the ENCODE and Roadmap Epigenomics projects, which used only 2 replicates for each component of the genomic maps. We used genome-wide DNA methylation sequencing, whole genome sequencing on the Illumina 10x platform, RNA sequencing, and chromatin immunoprecipitation-sequencing for informative histone marks (H3K4me1 and H3K27ac) to construct a multi-dimensional map of JIA neutrophils, a cell we have shown to be important in the pathobiology of JIA.ResultsThe epigenomes of JIA neutrophils display numerous differences from those from healthy children. DNA methylation changes, however, had only a weak effect on differential gene expression. In contrast, H3K4me1 and H3K27ac, commonly associated with enhancer functions, strongly correlated with gene expression. Furthermore, although unique/novel enhancer marks were associated with insertion-deletion events (indels) identified on whole genome sequencing, we saw no strong association between epigenetic changes and underlying genetic variation. The initiation of treatment in JIA is associated with a re-ordering of both DNA methylation and histone modifications, demonstrating the plasticity of the epigenome in this setting.ConclusionsThese findings, generated from a small number of patient samples, demonstrate how multidimensional genomic studies may yield new understandings of biology of JIA and provide insight into how therapy alters gene expression patterns.


2019 ◽  
Author(s):  
Willem H Ouwehand ◽  

Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and mediating genes for more than half such disorders remain to be discovered. We implemented whole-genome sequencing (WGS) in a national healthcare system to streamline diagnosis and to discover unknown aetiological variants, in the coding and non-coding regions of the genome. In a pilot study for the 100,000 Genomes Project, we generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065 patients with detailed phenotypic data. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed aetiological. Using WGS of UK Biobank1, we showed that rare alleles can explain the presence of some individuals in the tails of a quantitative red blood cell (RBC) trait. Finally, we reported 4 novel non-coding variants which cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare.


Plant Disease ◽  
2016 ◽  
Vol 100 (6) ◽  
pp. 1093-1100 ◽  
Author(s):  
Martha Malapi-Wight ◽  
Catalina Salgado-Salazar ◽  
Jill E. Demers ◽  
David L. Clement ◽  
Karen K. Rane ◽  
...  

Early and accurate diagnosis of new plant pathogens is vital for the rapid implementation of effective mitigation strategies and appropriate regulatory responses. Most commonly, pathogen identification relies on morphology and DNA marker analysis. However, for new diseases, these approaches may not be sufficient for precise diagnosis. In this study, we used whole-genome sequencing (WGS) to identify the causal agent of a new disease affecting Sarcococca hookeriana (sarcococca). Blight symptoms were observed on sarcococca and adjacent Buxus sempervirens (boxwood) plants in Maryland during 2014. Symptoms on sarcococca were novel, and included twig dieback and dark lesions on leaves and stems. A Calonectria sp. was isolated from both hosts and used to fulfill Koch’s postulates but morphology and marker sequence data precluded species-level identification. A 51.4-Mb WGS was generated for the two isolates and identified both as Calonectria pseudonaviculata. A single-nucleotide polymorphism at a noncoding site differentiated between the two host isolates. These results indicate that the same C. pseudonaviculata genotype has the ability to induce disease on both plant species. This study marks the first application of WGS for fungal plant pathogen diagnosis and demonstrates the power of this approach to rapidly identify causal agents of new diseases.


2018 ◽  
Vol 26 (5) ◽  
pp. 652-659 ◽  
Author(s):  
Michael P Mackley ◽  
Edward Blair ◽  
Michael Parker ◽  
Jenny C Taylor ◽  
Hugh Watkins ◽  
...  

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