Human genome sequencing in health and disease

Intricate Regulation of Phosphoenolpyruvate Carboxykinase (PEPCK) Isoforms in Normal Physiology and Disease

BACKGROUND

The phosphoenolpyruvate carboxykinase (PEPCK) isoforms are considered as rate-limiting enzymes for gluconeogenesis and glyceroneogenesis pathways. PEPCK exhibits several interesting features such as a) organelle-specific isoforms (cytosolic and a mitochondrial) in vertebrate clade, b) tissue-specific expression of isoforms and c) organism-specific requirement of ATP or GTP as a cofactor. In higher organisms, PEPCK isoforms are intricately regulated and activated through several physiological and pathological stimuli such as corticoids, hormones, nutrient starvation and hypoxia. Isoform-specific transcriptional/translational regulation and their interplay in maintaining glucose homeostasis remain to be fully understood. Mounting evidence indicates the significant involvement of PEPCK isoforms in physiological processes (development and longevity) and in the progression of a variety of diseases (metabolic disorders, cancer, Smith-Magenis syndrome).

OBJECTIVE

The present systematic review aimed to assimilate existing knowledge of transcriptional and translational regulation of PEPCK isoforms derived from cell, animal and clinical models.

CONCLUSION

Based on current knowledge and extensive bioinformatics analysis, in this review we have provided a comparative (epi)genetic understanding of PCK1 and PCK2 genes encompassing regulatory elements, disease-associated polymorphisms, copy number variations, regulatory miRNAs and CpG densities. We have also discussed various exogenous and endogenous modulators of PEPCK isoforms and their signaling mechanisms. A comprehensive review of existing knowledge of PEPCK regulation and function may enable identification of the underlying gaps to design new pharmacological strategies and interventions for the diseases associated with gluconeogenesis.

What is the right sequencing approach? Solo VS extended family analysis in consanguineous populations

Background

Testing strategies is crucial for genetics clinics and testing laboratories. In this study, we tried to compare the hit rate between solo and trio and trio plus testing and between trio and sibship testing. Finally, we studied the impact of extended family analysis, mainly in complex and unsolved cases.

Methods

Three cohorts were used for this analysis: one cohort to assess the hit rate between solo, trio and trio plus testing, another cohort to examine the impact of the testing strategy of sibship genome vs trio-based analysis, and a third cohort to test the impact of an extended family analysis of up to eight family members to lower the number of candidate variants.

Results

The hit rates in solo, trio and trio plus testing were 39, 40, and 41%, respectively. The total number of candidate variants in the sibship testing strategy was 117 variants compared to 59 variants in the trio-based analysis. We noticed that the average number of coding candidate variants in trio-based analysis was 1192 variants and 26,454 noncoding variants, and this number was lowered by 50–75% after adding additional family members, with up to two coding and 66 noncoding homozygous variants only, in families with eight family members.

Conclusion

There was no difference in the hit rate between solo and extended family members. Trio-based analysis was a better approach than sibship testing, even in a consanguineous population. Finally, each additional family member helped to narrow down the number of variants by 50–75%. Our findings could help clinicians, researchers and testing laboratories select the most cost-effective and appropriate sequencing approach for their patients. Furthermore, using extended family analysis is a very useful tool for complex cases with novel genes.

A new approach to identifying hypertension-associated genes in the mesenteric artery of spontaneously hypertensive rats and stroke-prone spontaneously hypertensive rats

Supplemental Digital Content is available in the text

Objective:

Hypertension is one of the most prevalent diseases in humans who live a modern lifestyle. Alongside more effective care, clarification of the genetic background of hypertension is urgently required. Gene expression in mesenteric resistance arteries of spontaneously hypertensive rats (SHR), stroke-prone SHR (SHRSP) and two types of renal hypertensive Wistar Kyoto rats (WKY), two kidneys and one clip renal hypertensive rat (2K1C) and one kidney and one clip renal hypertensive rat (1K1C), was compared using DNA microarrays.

Methods:

We used a simultaneous equation and comparative selection method to identify genes associated with hypertension using the Reactome analysis tool and GenBank database.

Results:

The expression of 298 genes was altered between SHR and WKY (44 upregulated and 254 downregulated), while the expression of 290 genes was altered between SHRSP and WKY (83 upregulated and 207 downregulated). For SHRSP versus SHR, the expression of 60 genes was altered (36 upregulated and 24 downregulated). Several genes expressed in SHR and SHRSP were also expressed in the renovascular hypertensive 2K1C and 1K1C rats, indicative of the existence of hyper-renin and/or hypervolemic pathophysiological changes in SHR and SHRSP.

Conclusion:

The overexpression of Kcnq1, Crlf1, Alb and Xirp1 and the inhibition of Galr2, Kcnh1, Ache, Chrm2 and Slc5a7 expression may indicate that a relationship exists between these genes and the cause and/or worsening of hypertension in SHR and SHRSP.

Next-generation sequencing and its application in diagnosis of retinitis pigmentosa

Retinitis Pigmentosa (RP) is a major cause of heritable human blindness with a high genetic heterogeneity. It is characterized by the initial degeneration of rod photoreceptors followed by cone photoreceptors. RP is also a prominent reason of visual impairment, by a global prevalence of 1:4000. RP is usually specified with nyctalopia in puberty, followed by concentric visual field loss, that reflects the main impairment of rod photoreceptors; later in the life, as disease progresses, because of cone dysfunction, central vision loss also occurs. A precise molecular diagnosis is crucial for disease characterization and clinical prognosis. DNA sequencing is a powerful tool for deciphering various causes of different human diseases. The arrival of next-generation sequencing (NGS) technologies has diminished sequencing cost and considerably augmented the throughput, making whole-genome sequencing (WGS) a conceivable way for obtaining comprehensive genomic data and a more precise clinical decision. Nevertheless, the advantages gained from NGS technologies are among a number of challenges that must be sufficiently addressed before this technique can be altered from an investigation tools to a helpful method in routine clinical practices. This article aims to provide an overview about NGS technology and its related platforms. The challenges in the analysis and choosing an appropriate NGS method likewise their potential applications in clinical diagnosis are also discussed. The merit of such technique has been reflected in some recent studies where it is shown that using NGS and molecular information could help with clinical diagnosis, providing potential treatment options or changes, up-to-date family counseling and management.

Dual Deep Sequencing Improves the Accuracy of Low-Frequency Somatic Mutation Detection in Cancer Gene Panel Testing

Cancer gene panel testing requires accurate detection of somatic mosaic mutations, as the test sample consists of a mixture of cancer cells and normal cells; each minor clone in the tumor also has different somatic mutations. Several studies have shown that the different types of software used for variant calling for next generation sequencing (NGS) can detect low-frequency somatic mutations. However, the accuracy of these somatic variant callers is unknown. We performed cancer gene panel testing in duplicate experiments using three different high-fidelity DNA polymerases in pre-capture amplification steps and analyzed by three different variant callers, Strelka2, Mutect2, and LoFreq. We selected six somatic variants that were detected in both experiments with more than two polymerases and by at least one variant caller. Among them, five single nucleotide variants were verified by CEL nuclease-mediated heteroduplex incision with polyacrylamide gel electrophoresis and silver staining (CHIPS) and Sanger sequencing. In silico analysis indicated that the FBXW7 and MAP3K1 missense mutations cause damage at the protein level. Comparing three somatic variant callers, we found that Strelka2 detected more variants than Mutect2 and LoFreq. We conclude that dual sequencing with Strelka2 analysis is useful for detection of accurate somatic mutations in cancer gene panel testing.

Returning Results in the Genomic Era: Initial Experiences of the eMERGE Network

A goal of the 3rd phase of the Electronic Medical Records and Genomics (eMERGE3) Network was to examine the return of results (RoR) of actionable variants in more than 100 genes to consenting participants and their healthcare providers. Each of the 10 eMERGE sites developed plans for three essential elements of the RoR process: Disclosure to the participant, notification of the health care provider, and integration of results into the electronic health record (EHR). Procedures and protocols around these three elements were adapted as appropriate to individual site requirements and limitations. Detailed information about the RoR procedures at each site was obtained through structured telephone interviews and follow-up surveys with the clinical investigator leading or participating in the RoR process at each eMERGE3 institution. Because RoR processes at each of the 10 sites allowed for taking into account differences in population, disease focus and institutional requirements, significant heterogeneity of process was identified, including variability in the order in which patients and clinicians were notified and results were placed in the EHR. This heterogeneity in the process flow for eMERGE3 RoR reflects the “real world” of genomic medicine in which RoR procedures must be shaped by the needs of the patients and institutional environments.

Efficient SNP editing in haploid human pluripotent stem cells

PURPOSE

To correct a potentially damaging mutation in haploid human embryonic stem cells.

METHODS

Exome sequencing was performed on DNA extracted from parthenogenetically derived embryonic stem cell line (pES12). An SLC10A2 gene mutation, which affects bile acid transport, was chosen as mutation of interest in this proof of concept study to attempt correction in human pluripotent haploid cells. Confirmation of the mutation was verified, and guide RNA and a correction template was designed in preparation of performing CRISPR. Haploid cells underwent serial fluorescence activated cell sorting (FACS) with Hoechst 33342 to create an increasingly haploid (1n) enriched culture. Nucleofection was performed on p. 37 and then cells were sorted for 1n DNA content with +GFP to identify the haploid cells that expressed Cas9 tagged with GFP.

RESULTS

104,686 haploid GFP + cells were collected. Cells were cultured, individual colonies picked, and 48 clones were sent for Sanger sequencing. CRIPSR efficiency was 77.1%, with 7/48 (14.6%) clones resulting in a corrected SLC10A2 mutation. Confirmation of persistence of haploid cells was achieved with repeated FACS sorting and centromere quantification. Given the large number of passages and exposure to CRISPR, we also performed analysis of karyotypes and of off-target effects. Cells evaluated were karyotypically normal and there was no evident off target effects.

CONCLUSIONS

CRISPR/Cas9 can be effectively utilized to edit mutations in haploid human embryonic stem cells. Establishment and maintenance of a haploid cell culture provides a novel way to utilize CRISPR/Cas9 in gene editing, particularly in the study of recessive alleles.

Clinical utility of NGS diagnosis and disease stratification in a multiethnic primary ciliary dyskinesia cohort

BACKGROUND

Primary ciliary dyskinesia (PCD), a genetically heterogeneous condition enriched in some consanguineous populations, results from recessive mutations affecting cilia biogenesis and motility. Currently, diagnosis requires multiple expert tests.

METHODS

The diagnostic utility of multigene panel next-generation sequencing (NGS) was evaluated in 161 unrelated families from multiple population ancestries.

RESULTS

Most (82%) families had affected individuals with biallelic or hemizygous (75%) or single (7%) pathogenic causal alleles in known PCD genes. Loss-of-function alleles dominate (73% frameshift, stop-gain, splice site), most (58%) being homozygous, even in non-consanguineous families. Although 57% (88) of the total 155 diagnostic disease variants were novel, recurrent mutations and mutated genes were detected. These differed markedly between white European (52% of families carry DNAH5 or DNAH11 mutations), Arab (42% of families carry CCDC39 or CCDC40 mutations) and South Asian (single LRRC6 or CCDC103 mutations carried in 36% of families) patients, revealing a striking genetic stratification according to population of origin in PCD. Genetics facilitated successful diagnosis of 81% of families with normal or inconclusive ultrastructure and 67% missing prior ultrastructure results.

CONCLUSIONS

This study shows the added value of high-throughput targeted NGS in expediting PCD diagnosis. Therefore, there is potential significant patient benefit in wider and/or earlier implementation of genetic screening.

VariantQC: a visual quality control report for variant evaluation

SUMMARY

Large scale genomic studies produce millions of sequence variants, generating datasets far too massive for manual inspection. To ensure variant and genotype data are consistent and accurate, it is necessary to evaluate variants prior to downstream analysis using quality control (QC) reports. Variant call format (VCF) files are the standard format for representing variant data; however, generating summary statistics from these files is not always straightforward. While tools to summarize variant data exist, they generally produce simple text file tables, which still require additional processing and interpretation. VariantQC fills this gap as a user friendly, interactive visual QC report that generates and concisely summarizes statistics from VCF files. The report aggregates and summarizes variants by dataset, chromosome, sample and filter type. The VariantQC report is useful for high-level dataset summary, quality control and helps flag outliers. Furthermore, VariantQC operates on VCF files, so it can be easily integrated into many existing variant pipelines.

AVAILABILITY AND IMPLEMENTATION

DISCVRSeq's VariantQC tool is freely available as a Java program, with the compiled JAR and source code available from https://github.com/BimberLab/DISCVRSeq/. Documentation and example reports are available at https://bimberlab.github.io/DISCVRSeq/.

Molecular dynamics simulations for genetic interpretation in protein coding regions: where we are, where to go and when

The increasing ease with which massive genetic information can be obtained from patients or healthy individuals has stimulated the development of interpretive bioinformatics tools as aids in clinical practice. Most such tools analyze evolutionary information and simple physical-chemical properties to predict whether replacement of one amino acid residue with another will be tolerated or cause disease. Those approaches achieve up to 80-85% accuracy as binary classifiers (neutral/pathogenic). As such accuracy is insufficient for medical decision to be based on, and it does not appear to be increasing, more precise methods, such as full-atom molecular dynamics (MD) simulations in explicit solvent, are also discussed. Then, to describe the goal of interpreting human genetic variations at large scale through MD simulations, we restrictively refer to all possible protein variants carrying single-amino-acid substitutions arising from single-nucleotide variations as the human variome. We calculate its size and develop a simple model that allows calculating the simulation time needed to have a 0.99 probability of observing unfolding events of any unstable variant. The knowledge of that time enables performing a binary classification of the variants (stable-potentially neutral/unstable-pathogenic). Our model indicates that the human variome cannot be simulated with present computing capabilities. However, if they continue to increase as per Moore's law, it could be simulated (at 65°C) spending only 3 years in the task if we started in 2031. The simulation of individual protein variomes is achievable in short times starting at present. International coordination seems appropriate to embark upon massive MD simulations of protein variants.

Precision medicine validation: identifying the MYBPC3 A31P variant with whole-genome sequencing in two Maine Coon cats with hypertrophic cardiomyopathy

OBJECTIVES

The objective of this study was to perform a proof-of-concept experiment that validates a precision medicine approach to identify variants associated with hypertrophic cardiomyopathy (HCM). We hypothesized that whole-genome sequencing would identify variant(s) associated with HCM in two affected Maine Coon/Maine Coon cross cats when compared with 79 controls of various breeds.

METHODS

Two affected and two control Maine Coon/Maine Coon cross cats had whole-genome sequencing performed at approximately × 30 coverage. Variants were called in these four cats and 77 cats of various breeds as part of the 99 Lives Cat Genome Sequencing Initiative ( http://felinegenetics.missouri.edu/99lives ) using Platypus v0.7.9.1, annotated with dbSNP ID, and variants' effect predicted by SnpEff. Strict filtering criteria (alternate allele frequency >49%) were applied to identify homozygous-alternate or heterozygous variants in the two HCM-affected samples when compared with 79 controls of various breeds.

RESULTS

A total of four variants were identified in the two Maine Coon/Maine Coon cross cats with HCM when compared with 79 controls after strict filtering. Three of the variants identified in genes MFSD12, BTN1A1 and SLITRK5 did not segregate with disease in a separate cohort of seven HCM-affected and five control Maine Coon/Maine Coon cross cats. The remaining variant MYBPC3 segregated with disease status. Furthermore, this gene was previously associated with heart disease and encodes for a protein with sarcomeric function.

CONCLUSIONS AND RELEVANCE

This proof-of-concept experiment identified the previously reported MYBPC3 A31P Maine Coon variant in two HCM-affected cases. This result validates and highlights the power of whole-genome sequencing for feline precision medicine.

Mutations in ANKLE2, a ZIKA Virus Target, Disrupt an Asymmetric Cell Division Pathway in Drosophila Neuroblasts to Cause Microcephaly

The apical Par complex, which contains atypical protein kinase C (aPKC), Bazooka (Par-3), and Par-6, is required for establishing polarity during asymmetric division of neuroblasts in Drosophila, and its activity depends on L(2)gl. We show that loss of Ankle2, a protein associated with microcephaly in humans and known to interact with Zika protein NS4A, reduces brain volume in flies and impacts the function of the Par complex. Reducing Ankle2 levels disrupts endoplasmic reticulum (ER) and nuclear envelope morphology, releasing the kinase Ballchen-VRK1 into the cytosol. These defects are associated with reduced phosphorylation of aPKC, disruption of Par-complex localization, and spindle alignment defects. Importantly, removal of one copy of ballchen or l(2)gl suppresses Ankle2 mutant phenotypes and restores viability and brain size. Human mutational studies implicate the above-mentioned genes in microcephaly and motor neuron disease. We suggest that NS4A, ANKLE2, VRK1, and LLGL1 define a pathway impinging on asymmetric determinants of neural stem cell division.

Future Preventive Gene Therapy of Polygenic Diseases from a Population Genetics Perspective

With the accumulation of scientific knowledge of the genetic causes of common diseases and continuous advancement of gene-editing technologies, gene therapies to prevent polygenic diseases may soon become possible. This study endeavored to assess population genetics consequences of such therapies. Computer simulations were used to evaluate the heterogeneity in causal alleles for polygenic diseases that could exist among geographically distinct populations. The results show that although heterogeneity would not be easily detectable by epidemiological studies following population admixture, even significant heterogeneity would not impede the outcomes of preventive gene therapies. Preventive gene therapies designed to correct causal alleles to a naturally-occurring neutral state of nucleotides would lower the prevalence of polygenic early- to middle-age-onset diseases in proportion to the decreased population relative risk attributable to the edited alleles. The outcome would manifest differently for late-onset diseases, for which the therapies would result in a delayed disease onset and decreased lifetime risk; however, the lifetime risk would increase again with prolonging population life expectancy, which is a likely consequence of such therapies. If the preventive heritable gene therapies were to be applied on a large scale, the decreasing frequency of risk alleles in populations would reduce the disease risk or delay the age of onset, even with a fraction of the population receiving such therapies. With ongoing population admixture, all groups would benefit over generations.

Diagnostic interpretation of genetic studies in patients with primary immunodeficiency diseases: A working group report of the Primary Immunodeficiency Diseases Committee of the American Academy of Allergy, Asthma & Immunology

Genetic testing has become an integral component of the diagnostic evaluation of patients with suspected primary immunodeficiency diseases. Results of genetic testing can have a profound effect on clinical management decisions. Therefore clinical providers must demonstrate proficiency in interpreting genetic data. Because of the need for increased knowledge regarding this practice, the American Academy of Allergy, Asthma & Immunology Primary Immunodeficiency Diseases Committee established a work group that reviewed and summarized information concerning appropriate methods, tools, and resources for evaluating variants identified by genetic testing. Strengths and limitations of tests frequently ordered by clinicians were examined. Summary statements and tables were then developed to guide the interpretation process. Finally, the need for research and collaboration was emphasized. Greater understanding of these important concepts will improve the diagnosis and management of patients with suspected primary immunodeficiency diseases.

Pharmacogenetics: Role of Single Nucleotide Polymorphisms

Genome sequencing methods have basically similar algorithms, although they show a few differences between the platforms. The human genome contains approximately three billion base pairs, and this amount is huge and therefore impossible to sequence at one step. However, this amount is not a problem for developed technology. Researchers break DNA into small random pieces and then sequence and reassemble. Library preparation, sequencing, bioinformatic approaches and reporting. High-quality library preparation is critical and the most important part of the next-generation sequencing workflow. Successful sequencing directly requires high-quality libraries. Sequencing is second step and all high-throughput sequencing approaches are generally based on conventional Sanger sequencing. After preparation of library and sequencing, later steps are completely computer-based (in silico) approaches called as bioinformatics.

Genetic variability analysis in a population from Bogotá: Towards a haplotype map

Introducción.

Los proyectos del mapa de haplotipos (HapMap) y de los 1.000 genomas han sido fundamentales para la compresión del componente genético de las enfermedades comunes y los fenotipos normales. Sin embargo, la variabilidad genética colombiana incluida en estos proyectos no es representativa del país.

Objetivo.

Contribuir al conocimiento de la variabilidad genética de la población colombiana a partir del estudio genómico de una muestra de individuos de Bogotá.

Materiales y métodos.

Se genotipificaron 2’372.784 marcadores genéticos de 32 individuos nacidos en Bogotá y de padres originarios de la misma ciudad utilizando la plataforma Illumina™. Los niveles de variabilidad genética se determinaron y se compararon con los datos disponibles de otras poblaciones del proyecto de los 1.000 genomas.

Resultados.

Los individuos analizados presentaron una variabilidad genética semejante a la de poblaciones con las que comparten ancestros. No obstante, a pesar de la poca diferenciación genética detectada en la población de Bogotá y en la de Medellín, el análisis de los componentes principales sugiere una composición genética diferente en las dos poblaciones.

Conclusiones.

El análisis genómico de la muestra de Bogotá permitió detectar similitudes y diferencias con otras poblaciones americanas. El aumento de tamaño de la muestra bogotana y la inclusión de muestras de otras regiones del país permitirán una mejor compresión de la variabilidad genética en Colombia, lo cual es fundamental para los estudios de salud humana, y la prevención y el tratamiento de enfermedades comunes en el país.

Clinical exome sequencing vs. usual care for hereditary colorectal cancer diagnosis: A pilot comparative effectiveness study

BACKGROUND

Clinical exome sequencing (CES) provides the advantage of assessing genetic variation across the human exome compared to a traditional stepwise diagnostic approach or multi-gene panels. Comparative effectiveness research methods offer an approach to better understand the patient-centered and economic outcomes of CES.

PURPOSE

To evaluate CES compared to usual care (UC) in the diagnostic work-up of inherited colorectal cancer/polyposis (CRCP) in a randomized controlled trial (RCT).

METHODS

The primary outcome was clinical sensitivity for the diagnosis of inherited CRCP; secondary outcomes included psychosocial outcomes, family communication, and healthcare resource utilization. Participants were surveyed 2 and 4 weeks after results return and at 3-month intervals up to 1 year.

RESULTS

Evolving outcome measures and standard of care presented critical challenges. The majority of participants in the UC arm received multi-gene panels [94.73%]. Rates of genetic findings supporting the diagnosis of hereditary CRCP were 7.5% [7/93] vs. 5.4% [5/93] in the CES and UC arms, respectively (P = 0.28). Differences in privacy concerns after receiving CRCP results were identified (0.88 in UC vs 0.38 in CES, P = 0.05); however, healthcare resource utilization, family communication and psychosocial outcomes were similar between the two arms. More participants with positive results (17.7%) intended to change their life insurance 1  month after the first return visit compared to participants returned a variant of uncertain significance (9.1%) or negative result (4.8%) (P = 0.09).

CONCLUSION

Our results suggest that CES provides similar clinical benefits to multi-gene panels in the diagnosis of hereditary CRCP.

Closing the 'phenotype gap' in precision medicine: improving what we measure to understand complex disease mechanisms

The central concept underlying precision medicine is a mechanistic understanding of each disease and its response to therapy sufficient to direct a specific intervention. To execute on this vision requires parsing incompletely defined disease syndromes into discrete mechanistic subsets and developing interventions to precisely address each of these etiologically distinct entities. This will require substantial adjustment of traditional paradigms which have tended to aggregate high-level phenotypes with very different etiologies. In the current environment, where diagnoses are not mechanistic, drug development has become so expensive that it is now impractical to imagine the cost-effective creation of new interventions for many prevalent chronic conditions. The vision of precision medicine also argues for a much more seamless integration of research and development with clinical care, where shared taxonomies will enable every clinical interaction to inform our collective understanding of disease mechanisms and drug responses. Ideally, this would be executed in ways that drive real-time and real-world discovery, innovation, translation, and implementation. Only in oncology, where at least some of the biology is accessible through surgical excision of the diseased tissue or liquid biopsy, has "co-clinical" modeling proven feasible. In most common germline disorders, while genetics often reveal the causal mutations, there still remain substantial barriers to efficient disease modeling. Aggregation of similar disorders under single diagnostic labels has directly contributed to the paucity of etiologic and mechanistic understanding by directly reducing the resolution of any subsequent studies. Existing clinical phenotypes are typically anatomic, physiologic, or histologic, and result in a substantial mismatch in information content between the phenomes in humans or in animal 'models' and the variation in the genome. This lack of one-to-one mapping of discrete mechanisms between disease and animal models causes a failure of translation and is one form of 'phenotype gap.' In this review, we will focus on the origins of the phenotyping deficit and approaches that may be considered to bridge the gap, creating shared taxonomies between human diseases and relevant models, using cardiovascular examples.

Exome-wide copy number variation analysis identifies a COL9A1 in frame deletion that is associated with hearing loss

Pathogenic variants in COL9A1 are primarily associated with autosomal recessive Stickler syndrome. Patients with COL9A1-associated Stickler syndrome (STL) present hearing loss (HL), ophthalmic manifestations and skeletal abnormalities. However, the clinical spectrum of patients with COL9A1 variants can also include multiple epiphyseal dysplasia, as well as non-syndromic HL that was observed in one previously reported proband. Exome sequencing was performed on the genomic DNA of an Iranian patient and his affected brother who both report non-syndromic HL. A 44.6 kb homozygous in-frame deletion spanning exons 6 to 33 of COL9A1 was detected via exome-based copy number variation analysis. The deleted exons were confirmed by PCR in the patient and his affected brother, who both have non-syndromic HL. Segregation analysis via qPCR confirmed the parents as heterozygous deletion carriers. Breakpoint analysis mapped the homozygous deletion spanning introns 5 to 33 (g.70,948,188_70,997,277del, NM_001851.4(COL9A1):c.697-3754_2112+769del, p.(Phe233_Ser704del), with an additional 67 bp of inserted intronic sequence that may have originated due to a fork stalling and template switching/microhomology-mediated break-induced replication (FoSTeS/MMBIR) mechanism. This mechanism has not been previously implicated in HL or STL. This is also the first reported copy number variation in COL9A1 that was identified through an exome data set in an Iranian family with apparent non-syndromic HL. The present study emphasizes the importance of exome-wide copy number variation analysis in molecular diagnosis and provides supporting evidence to associate COL9A1 with autosomal recessive non-syndromic HL.

Quantifying the Potential for Future Gene Therapy to Lower Lifetime Risk of Polygenic Late-Onset Diseases

Gene therapy techniques and genetic knowledge may sufficiently advance, within the next few decades, to support prophylactic gene therapy for the prevention of polygenic late-onset diseases. The risk of these diseases may, hypothetically, be lowered by correcting the effects of a subset of common low effect gene variants. In this paper, simulations show that if such gene therapy were to become technically possible; and if the incidences of the treated diseases follow the proportional hazards model with a multiplicative genetic architecture composed of a sufficient number of common small effect gene variants, then: (a) late-onset diseases with the highest familial heritability will have the largest number of variants available for editing; (b) diseases that currently have the highest lifetime risk, particularly those with the highest incidence rate continuing into older ages, will prove the most challenging cases in lowering lifetime risk and delaying the age of onset at a population-wide level; (c) diseases that are characterized by the lowest lifetime risk will show the strongest and longest-lasting response to such therapies; and (d) longer life expectancy is associated with a higher lifetime risk of these diseases, and this tendency, while delayed, will continue after therapy.

Quantifying the Potential for Future Gene Therapy to Lower Lifetime Risk of Polygenic Late-Onset Diseases

Gene therapy techniques and genetic knowledge may sufficiently advance, within the next few decades, to support prophylactic gene therapy for the prevention of polygenic late-onset diseases. The risk of these diseases may, hypothetically, be lowered by correcting the effects of a subset of common low effect gene variants. In this paper, simulations show that if such gene therapy were to become technically possible; and if the incidences of the treated diseases follow the proportional hazards model with a multiplicative genetic architecture composed of a sufficient number of common small effect gene variants, then: (a) late-onset diseases with the highest familial heritability will have the largest number of variants available for editing; (b) diseases that currently have the highest lifetime risk, particularly those with the highest incidence rate continuing into older ages, will prove the most challenging cases in lowering lifetime risk and delaying the age of onset at a population-wide level; (c) diseases that are characterized by the lowest lifetime risk will show the strongest and longest-lasting response to such therapies; and (d) longer life expectancy is associated with a higher lifetime risk of these diseases, and this tendency, while delayed, will continue after therapy.

Development of an Interactive Web Application "Shiny App for Frequency Analysis on Homo sapiens Genome (SAFA-HsG)"

The web application "Shiny App for Frequency Analysis on Homo sapiens Genome (SAFA-HsG)" was developed using R programming-based bioconductor packages and shiny framework. Through the app, preliminary descriptive data analysis on nucleotide frequency, and CpG island, CpG non-island, and CpG island shores and shelves (downstream and upstream) of human reference genome can be carried out, which will help biologists to work on human epigenomics. Table view of these analyses of all chromosomes can be visualized and downloaded by the end users. Similarly, the respective comparative plots can be used for CpG sites comparison. In addition, to introduce the personal genome project, the present study has done a preliminary work on few raw data and are included in the app, which will create interest on personal genome information. The app is hosted on https://SAFA-HsG.shinyapps.io/home/. It is a multi-platform application and can be initiated locally from any computer that has or has not installed R. It is a user-friendly interface, which will allow a biologist, even who has little computer knowledge to access and analyze further.

A functional assay to classify ZBTB24 missense variants of unknown significance

Increasing use of next‐generation sequencing technologies in clinical diagnostics allows large‐scale discovery of genetic variants, but also results in frequent identification of variants of unknown significance (VUSs). Their classification into disease‐causing and neutral variants is often hampered by the absence of robust functional tests. Here, we demonstrate that a luciferase reporter assay, in combination with ChIP‐qPCR, reliably separates pathogenic ZBTB24 missense variants in the context of immunodeficiency, centromeric instability, facial anomalies (ICF) syndrome from natural variants in healthy individuals and patients of other diseases. Application of our assay to two published ZBTB24 missense VUSs indicates that they are likely not to cause ICF2 syndrome. Furthermore, we show that rare gnomAD ZBTB24 missense variants in key residues of the C2H2‐ZF domain lead to a loss of function phenotype that resembles ICF2, suggesting that these individuals are carriers of ICF syndrome. In summary, we have developed a robust functional test to validate missense variants in ZBTB24.

Copy number variant and runs of homozygosity detection by microarrays enabled more precise molecular diagnoses in 11,020 clinical exome cases

Background

Exome sequencing (ES) has been successfully applied in clinical detection of single nucleotide variants (SNVs) and small indels. However, identification of copy number variants (CNVs) using ES data remains challenging. The purpose of this study is to understand the contribution of CNVs and copy neutral runs of homozygosity (ROH) in molecular diagnosis of patients referred for ES.

Methods

In a cohort of 11,020 consecutive ES patients, an Illumina SNP array analysis interrogating mostly coding SNPs was performed as a quality control (QC) measurement and for CNV/ROH detection. Among these patients, clinical chromosomal microarray analysis (CMA) was performed at Baylor Genetics (BG) on 3229 patients, either before, concurrently, or after ES. We retrospectively analyzed the findings from CMA and the QC array.

Results

The QC array can detect ~ 70% of pathogenic/likely pathogenic CNVs (PCNVs) detectable by CMA. Out of the 11,020 ES cases, the QC array identified PCNVs in 327 patients and uniparental disomy (UPD) disorder-related ROH in 10 patients. The overall PCNV/UPD detection rate was 5.9% in the 3229 ES patients who also had CMA at BG; PCNV/UPD detection rate was higher in concurrent ES and CMA than in ES with prior CMA (7.2% vs 4.6%). The PCNVs/UPD contributed to the molecular diagnoses in 17.4% (189/1089) of molecularly diagnosed ES cases with CMA and were estimated to contribute in 10.6% of all molecularly diagnosed ES cases. Dual diagnoses with both PCNVs and SNVs were detected in 38 patients. PCNVs affecting single recessive disorder genes in a compound heterozygous state with SNVs were detected in 4 patients, and homozygous deletions (mostly exonic deletions) were detected in 17 patients. A higher PCNV detection rate was observed for patients with syndromic phenotypes and/or cardiovascular abnormalities.

Conclusions

Our clinical genomics study demonstrates that detection of PCNV/UPD through the QC array or CMA increases ES diagnostic rate, provides more precise molecular diagnosis for dominant as well as recessive traits, and enables more complete genetic diagnoses in patients with dual or multiple molecular diagnoses. Concurrent ES and CMA using an array with exonic coverage for disease genes enables most effective detection of both CNVs and SNVs and therefore is recommended especially in time-sensitive clinical situations.

Electronic supplementary material

The online version of this article (10.1186/s13073-019-0639-5) contains supplementary material, which is available to authorized users.

Development, technical validation, and clinical application of a multigene panel for hereditary gastrointestinal cancer and polyposis

Introduction:

Recent advances in technology and research are rapidly changing the diagnostic approach to hereditary gastrointestinal cancer (HGIC) syndromes. Although the practice of clinical genetics is currently transitioning from targeted criteria-based testing to multigene panels, important challenges remain to be addressed. The aim of this study was to develop and technically validate the performance of a multigene panel for HGIC.

Methods:

CGT-colon-G14 is an amplicon-based panel designed to detect single nucleotide variants and small insertions/deletions in 14 well-established or presumed high-penetrance genes involved in HGIC. The assay parameters tested were sensitivity, specificity, accuracy, and inter-run and intra-run reproducibility. Performance and clinical impact were determined using 48 samples of patients with suspected HGIC/polyposis previously tested with the targeted approach.

Results:

The CGT-colon-G14 panel showed 99.99% accuracy and 100% inter- and intra-run reproducibility. Moreover, panel testing detected 1 actionable pathogenic variant and 16 variants with uncertain clinical impact that were missed by the conventional approach because they were located in genes not previously analyzed.

Conclusion:

Introduction of the CGT-colon-G14 panel into the clinic could provide a higher diagnostic yield than a step-wise approach; however, results may not always be straightforward without the implementation of new genetic counseling models.

Dynamic modeling and network approaches for omics time course data: overview of computational approaches and applications

Inferring networks and dynamics of genes, proteins, cells and other biological entities from high-throughput biological omics data is a central and challenging issue in computational and systems biology. This is essential for understanding the complexity of human health, disease susceptibility and pathogenesis for Predictive, Preventive, Personalized and Participatory (P4) system and precision medicine. The delineation of the possible interactions of all genes/proteins in a genome/proteome is a task for which conventional experimental techniques are ill suited. Urgently needed are rapid and inexpensive computational and statistical methods that can identify interacting candidate disease genes or drug targets out of thousands that can be further investigated or validated by experimentations. Moreover, identifying biological dynamic systems, and simultaneously estimating the important kinetic structural and functional parameters, which may not be experimentally accessible could be important directions for drug-disease-gene network studies. In this article, we present an overview and comparison of recent developments of dynamic modeling and network approaches for time-course omics data, and their applications to various biological systems, health conditions and disease statuses. Moreover, various data reduction and analytical schemes ranging from mathematical to computational to statistical methods are compared including their merits, drawbacks and limitations. The most recent software, associated web resources and other potentials for the compared methods are also presented and discussed in detail.

Insights into genetics, human biology and disease gleaned from family based genomic studies

Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in novel "disease gene" discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.

Allele-specific binding of RNA-binding proteins reveals functional genetic variants in the RNA

Allele-specific protein-RNA binding is an essential aspect that may reveal functional genetic variants (GVs) mediating post-transcriptional regulation. Recently, genome-wide detection of in vivo binding of RNA-binding proteins is greatly facilitated by the enhanced crosslinking and immunoprecipitation (eCLIP) method. We developed a new computational approach, called BEAPR, to identify allele-specific binding (ASB) events in eCLIP-Seq data. BEAPR takes into account crosslinking-induced sequence propensity and variations between replicated experiments. Using simulated and actual data, we show that BEAPR largely outperforms often-used count analysis methods. Importantly, BEAPR overcomes the inherent overdispersion problem of these methods. Complemented by experimental validations, we demonstrate that the application of BEAPR to ENCODE eCLIP-Seq data of 154 proteins helps to predict functional GVs that alter splicing or mRNA abundance. Moreover, many GVs with ASB patterns have known disease relevance. Overall, BEAPR is an effective method that helps to address the outstanding challenge of functional interpretation of GVs.

The genome-wide landscape of small insertion and deletion mutations in Monopterus albus

Insertion and deletion (indel) mutations, which can trigger single nucleotide substitutions on the flanking regions of genes, may generate abundant materials for disease defense, reproduction, species survival and evolution. However, genetic and evolutionary mechanisms of indels remain elusive. We establish a comparative genome-transcriptome-alignment approach for a large-scale identification of indels in Monopterus population. Over 2000 indels in 1738 indel genes, including 1-21 bp deletions and 1-15 bp insertions, were detected. Each indel gene had ∼1.1 deletions/insertions, and 2-4 alleles in population. Frequencies of deletions were prominently higher than those of insertions on both genome and population levels. Most of the indels led to in frame mutations with multiples of three and majorly occurred in non-domain regions, indicating functional constraint or tolerance of the indels. All indel genes showed higher expression levels than non-indel genes during sex reversal. Slide window analysis of global expression levels in gonads showed a significant positive correlation with indel density in the genome. Moreover, indel genes were evolutionarily conserved and evolved slowly compared to non-indel genes. Notably, population genetic structure of indels revealed divergent evolution of Monopterus population, as bottleneck effect of biogeographic isolation by Taiwan Strait, China.

Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences

Advances in the technologies and informatics used to generate and process large biological data sets (omics data) are promoting a critical shift in the study of biomedical sciences. While genomics, transcriptomics and proteinomics, coupled with bioinformatics and biostatistics, are gaining momentum, they are still, for the most part, assessed individually with distinct approaches generating monothematic rather than integrated knowledge. As other areas of biomedical sciences, including metabolomics, epigenomics and pharmacogenomics, are moving towards the omics scale, we are witnessing the rise of inter-disciplinary data integration strategies to support a better understanding of biological systems and eventually the development of successful precision medicine. This review cuts across the boundaries between genomics, transcriptomics and proteomics, summarizing how omics data are generated, analysed and shared, and provides an overview of the current strengths and weaknesses of this global approach. This work intends to target students and researchers seeking knowledge outside of their field of expertise and fosters a leap from the reductionist to the global-integrative analytical approach in research.

Targeting epigenetics for cancer therapy

Cancer can be identified as a chaotic cell state, which breaks the rules that govern growth and reproduction, with main characteristics such as uncontrolled division, invading other tissues, usurping resources, and eventually killing its host. It was once believed that cancer is caused by a progressive series of genetic aberrations, and certain mutations of genes, including oncogenes and tumor suppressor genes, have been identified as the cause of cancer. However, piling evidence suggests that epigenetic modifications working in concert with genetic mechanisms to regulate transcriptional activity are dysregulated in many diseases, including cancer. Cancer epigenetics explain a wide range of heritable changes in gene expression, which do not come from any alteration in DNA sequences. Aberrant DNA methylation, histone modifications, and expression of long non-coding RNAs (lncRNAs) are key epigenetic mechanisms associated with tumor initiation, cancer progression, and metastasis. Within the past decade, cancer epigenetics have enabled us to develop novel biomarkers and therapeutic target for many types of cancers. In this review, we will summarize the major epigenetic changes involved in cancer biology along with clinical and preclinical results developed as novel cancer therapeutics.

Generating mouse models for biomedical research: technological advances

Over the past decade, new methods and procedures have been developed to generate genetically engineered mouse models of human disease. This At a Glance article highlights several recent technical advances in mouse genome manipulation that have transformed our ability to manipulate and study gene expression in the mouse. We discuss how conventional gene targeting by homologous recombination in embryonic stem cells has given way to more refined methods that enable allele-specific manipulation in zygotes. We also highlight advances in the use of programmable endonucleases that have greatly increased the feasibility and ease of editing the mouse genome. Together, these and other technologies provide researchers with the molecular tools to functionally annotate the mouse genome with greater fidelity and specificity, as well as to generate new mouse models using faster, simpler and less costly techniques.

Returning a Genomic Result for an Adult-Onset Condition to the Parents of a Newborn: Insights From the BabySeq Project

The return of information from genomic sequencing in children, especially in early life, brings up complex issues around parental autonomy, the child's future autonomy, the best interest standard, and the best interests of the family. These issues are particularly important in considering the return of genomic results for adult-onset-only conditions in children. The BabySeq Project is a randomized trial used to explore the medical, behavioral, and economic impacts of integrating genomic sequencing into the care of newborns who are healthy or sick. We discuss a case in which a variant in a gene for an actionable, adult-onset-only condition was detected, highlighting the ethical issues surrounding the return of such finding in a newborn to the newborn's parents.

Cancer biomarker discovery and translation: proteomics and beyond

INTRODUCTION

Cancer is often diagnosed at late stages when the chance of cure is relatively low and although research initiatives in oncology discover many potential cancer biomarkers, few transition to clinical applications. This review addresses the current landscape of cancer biomarker discovery and translation with a focus on proteomics and beyond. Areas covered: The review examines proteomic and genomic techniques for cancer biomarker detection and outlines advantages and challenges of integrating multiple omics approaches to achieve optimal sensitivity and address tumor heterogeneity. This discussion is based on a systematic literature review and direct participation in translational studies. Expert commentary: Identifying aggressive cancers early on requires improved sensitivity and implementation of biomarkers representative of tumor heterogeneity. During the last decade of genomic and proteomic research, significant advancements have been made in next generation sequencing and mass spectrometry techniques. This in turn has led to a dramatic increase in identification of potential genomic and proteomic cancer biomarkers. However, limited successes have been shown with translation of these discoveries into clinical practice. We believe that the integration of these omics approaches is the most promising molecular tool for comprehensive cancer evaluation, early detection and transition to Precision Medicine in oncology.

The genetic basis of disease

Genetics plays a role, to a greater or lesser extent, in all diseases. Variations in our DNA and differences in how that DNA functions (alone or in combinations), alongside the environment (which encompasses lifestyle), contribute to disease processes. This review explores the genetic basis of human disease, including single gene disorders, chromosomal imbalances, epigenetics, cancer and complex disorders, and considers how our understanding and technological advances can be applied to provision of appropriate diagnosis, management and therapy for patients.

CRISPR-Cas9 human gene replacement and phenomic characterization in Caenorhabditis elegans to understand the functional conservation of human genes and decipher variants of uncertain significance

Our ability to sequence genomes has vastly surpassed our ability to interpret the genetic variation we discover. This presents a major challenge in the clinical setting, where the recent application of whole-exome and whole-genome sequencing has uncovered thousands of genetic variants of uncertain significance. Here, we present a strategy for targeted human gene replacement and phenomic characterization, based on CRISPR-Cas9 genome engineering in the genetic model organism Caenorhabditis elegans, that will facilitate assessment of the functional conservation of human genes and structure-function analysis of disease-associated variants with unprecedented precision. We validate our strategy by demonstrating that direct single-copy replacement of the C. elegans ortholog (daf-18) with the critical human disease-associated gene phosphatase and tensin homolog (PTEN) is sufficient to rescue multiple phenotypic abnormalities caused by complete deletion of daf-18, including complex chemosensory and mechanosensory impairments. In addition, we used our strategy to generate animals harboring a single copy of the known pathogenic lipid phosphatase inactive PTEN variant (PTEN-G129E), and showed that our automated in vivo phenotypic assays could accurately and efficiently classify this missense variant as loss of function. The integrated nature of the human transgenes allows for analysis of both homozygous and heterozygous variants and greatly facilitates high-throughput precision medicine drug screens. By combining genome engineering with rapid and automated phenotypic characterization, our strategy streamlines the identification of novel conserved gene functions in complex sensory and learning phenotypes that can be used as in vivo functional assays to decipher variants of uncertain significance.

From Genotype to Phenotype

Genomic variants associated with inherited cardiac conditions yet detected incidentally (‘secondary findings’) are likely to arise with increasing frequency as genome sequencing transitions into clinical practice. Since genotyping has until recently been directed by clinical diagnosis, assessment and management of individuals found to harbour such a variant as a secondary finding is unclear. Here we illustrate some diagnostic and psychosocial complexities of inherited cardiac condition secondary findings, exemplified by disclosure of a pathogenic variant in KCNQ1 , associated with long QT syndrome, to a healthy male enrolled in diagnostic genome sequencing as an unaffected relative. This early case represents a shift from ‘phenotype-to-genotype’ to ‘genotype-to-phenotype’; we describe clinical evaluation, family history and a qualitative research interview with the secondary finding recipient, discuss the role of specialist services in variant interpretation, genetic counselling and clinical assessment, and some challenges of realising improved health outcomes following disclosure of a secondary finding.

GENETICS IN ENDOCRINOLOGY: Genetic diagnosis of endocrine diseases by NGS: novel scenarios and unpredictable results and risks

The technological advancements in genetics produced a profound impact on the research and diagnostics of non-communicable diseases. The availability of next-generation sequencing (NGS) allowed the identification of novel candidate genes but also an in-depth modification of the understanding of the architecture of several endocrine diseases. Several different NGS approaches are available allowing the sequencing of several regions of interest or the whole exome or genome (WGS, WES or targeted NGS), with highly variable costs, potentials and limitations that should be clearly known before designing the experiment. Here, we illustrate the NGS scenario, describe the advantages and limitations of the different protocols and review some of the NGS results obtained in different endocrine conditions. We finally give insights on the terminology and requirements for the implementation of NGS in research and diagnostic labs.

Cost Analyses of Genomic Sequencing: Lessons Learned from the MedSeq Project

OBJECTIVE

To summarize lessons learned while analyzing the costs of integrating whole genome sequencing into the care of cardiology and primary care patients in the MedSeq Project by conducting the first randomized controlled trial of whole genome sequencing in general and specialty medicine.

METHODS

Case study that describes key methodological and data challenges that were encountered or are likely to emerge in future work, describes the pros and cons of approaches considered by the study team, and summarizes the solutions that were implemented.

RESULTS

Major methodological challenges included defining whole genome sequencing, structuring an appropriate comparator, measuring downstream costs, and examining clinical outcomes. Discussions about solutions addressed conceptual and practical issues that arose because of definitions and analyses around the cost of genomic sequencing in trial-based studies.

CONCLUSIONS

The MedSeq Project provides an instructive example of how to conduct a cost analysis of whole genome sequencing that feasibly incorporates best practices while being sensitive to the varied applications and diversity of results it may produce. Findings provide guidance for researchers to consider when conducting or analyzing economic analyses of whole genome sequencing and other next-generation sequencing tests, particularly regarding costs.

Gene editing in the context of an increasingly complex genome

The reporting of the first draft of the human genome in 2000 brought with it much hope for the future in what was felt as a paradigm shift toward improved health outcomes. Indeed, we have now mapped the majority of variation across human populations with landmark projects such as 1000 Genomes; in cancer, we have catalogued mutations across the primary carcinomas; whilst, for other diseases, we have identified the genetic variants with strongest association. Despite this, we are still awaiting the genetic revolution in healthcare to materialise and translate itself into the health benefits for which we had hoped. A major problem we face relates to our underestimation of the complexity of the genome, and that of biological mechanisms, generally. Fixation on DNA sequence alone and a 'rigid' mode of thinking about the genome has meant that the folding and structure of the DNA molecule -and how these relate to regulation- have been underappreciated. Projects like ENCODE have additionally taught us that regulation at the level of RNA is just as important as that at the spatiotemporal level of chromatin.In this review, we chart the course of the major advances in the biomedical sciences in the era pre- and post the release of the first draft sequence of the human genome, taking a focus on technology and how its development has influenced these. We additionally focus on gene editing via CRISPR/Cas9 as a key technique, in particular its use in the context of complex biological mechanisms. Our aim is to shift the mode of thinking about the genome to that which encompasses a greater appreciation of the folding of the DNA molecule, DNA- RNA/protein interactions, and how these regulate expression and elaborate disease mechanisms.Through the composition of our work, we recognise that technological improvement is conducive to a greater understanding of biological processes and life within the cell. We believe we now have the technology at our disposal that permits a better understanding of disease mechanisms, achievable through integrative data analyses. Finally, only with greater understanding of disease mechanisms can techniques such as gene editing be faithfully conducted.

Prioritization and functional assessment of noncoding variants associated with complex diseases

Unraveling functional noncoding variants associated with complex diseases is still a great challenge. We present a novel algorithm, Prioritization And Functional Assessment (PAFA), that prioritizes and assesses the functionality of genetic variants by introducing population differentiation measures and recalibrating training variants. Comprehensive evaluations demonstrate that PAFA exhibits much higher sensitivity and specificity in prioritizing noncoding risk variants than existing methods. PAFA achieves improved performance in distinguishing both common and rare recurrent variants from non-recurrent variants by integrating multiple annotations and metrics. An integrated platform was developed, providing comprehensive functional annotations for noncoding variants by integrating functional genomic data, which can be accessed at http://159.226.67.237:8080/pafa .

The BabySeq project: implementing genomic sequencing in newborns

BACKGROUND

The greatest opportunity for lifelong impact of genomic sequencing is during the newborn period. The "BabySeq Project" is a randomized trial that explores the medical, behavioral, and economic impacts of integrating genomic sequencing into the care of healthy and sick newborns.

METHODS

Families of newborns are enrolled from Boston Children's Hospital and Brigham and Women's Hospital nurseries, and half are randomized to receive genomic sequencing and a report that includes monogenic disease variants, recessive carrier variants for childhood onset or actionable disorders, and pharmacogenomic variants. All families participate in a disclosure session, which includes the return of results for those in the sequencing arm. Outcomes are collected through review of medical records and surveys of parents and health care providers and include the rationale for choice of genes and variants to report; what genomic data adds to the medical management of sick and healthy babies; and the medical, behavioral, and economic impacts of integrating genomic sequencing into the care of healthy and sick newborns.

DISCUSSION

The BabySeq Project will provide empirical data about the risks, benefits and costs of newborn genomic sequencing and will inform policy decisions related to universal genomic screening of newborns.

TRIAL REGISTRATION

The study is registered in ClinicalTrials.gov Identifier: NCT02422511 . Registration date: 10 April 2015.

Assessing the Accuracy of Variant Detection in Cost-Effective Gene Panel Testing by Next-Generation Sequencing

There is significant debate within the diagnostics community regarding the accuracy of variant identification by next-generation sequencing and the necessity of confirmatory testing of detected variants. Because the quality threshold to discriminate false positives depends on the workflow, no regulatory standard regarding this matter has yet been published. The goal of this study was to empirically determine the threshold to perform additional Sanger sequencing and to reduce the experimental cost to a practical level. Using 278 model genes, a hybridization capture-based protocol was examined to meet the clinical requirements of low cost, high efficiency, and high-quality data. To reduce excessive false-positive detection, filtering processes were introduced to remove mismapped reads and strand-biased detection to a published best-practices pipeline. With seven samples from the 1000 Genomes Project, 2750 single-nucleotide polymorphisms and 142 insertions/deletions were identified by our designed workflow. Compared with variants registered in the single nucleotide polymorphism database (dbSNP), a zero false-positive threshold value was determined (quality score > 1000). The variants satisfying these criteria accounted for 95.6% of single-nucleotide polymorphisms and 50.7% of insertions/deletions. Except for deletions located within the highly repeated sequences, the workflow achieved 100% sensitivity. The established threshold allowed us to discriminate between convincing variants and those requiring validation, a design that reconciles the competing objectives of cost minimization and quality maximization of clinical gene panel testing.

A theory-informed systematic review of clinicians' genetic testing practices

This systematic literature review investigates factors impacting on clinicians' decisions to offer genetic tests in their practice, and maps them to a theoretical behaviour change framework. Better understanding of these factors will inform the design of effective interventions to integrate genomics tests into clinical care. We conducted a narrative synthesis of empirical research of medical specialists' perspectives on and experiences of offering genetic tests to their patients. This review was based upon the PRISMA statement and guidelines for reviewing qualitative research. Four electronic data sources were searched-MEDLINE, EMBASE, CINAHL, PubMed. Studies were independently assessed by two authors. Content analysis was applied to map the findings of included studies to a framework validated for behaviour and implementation research, the Theoretical Domains Framework (TDF). The TDF describes 14 factors known to influence behaviour and has been applied in diverse clinical settings to understand and/or modify health professional behaviour. Thirty-four studies published in 39 articles met inclusion and quality criteria. Most studies were published after 2011 (54%), Northern American (82%), quantitative in design (68%) and addressed familial cancer genetic tests (53%). Of the 14 TDF factors, 13 were identified. The three most common factors were: Environmental Context and Resources (n = 33), Beliefs about Consequences (n = 26), and Knowledge (n = 23). To support the adoption of genomic tests beyond specialist services, nuanced interventions targeting considerations beyond clinician education are needed. For instance, interventions addressing organisational constraints which may restrict clinicians' ability to offer genomic tests are required alongside those targeting factors intrinsic to the clinician.