Advanced genetics (Hoboken, N.J.)最新文献

Fragile X syndrome is the most common genetic cause of intellectual disability (ID) and is also well known to have a role in primary ovarian insufficiency (POI) and fragile X-associated tremor ataxia syndrome (FXTAS) that expresses across generations. The objective was to compare the CGG repeat variants in FMR1 gene among three correlating cohorts of ID, autism and idiopathic POI. Thirty-six patients with ID, 12 with autism spectrum disorder (ASD) and 13 females with idiopathic POI were screened for FMR1 CGG repeat size by fluorescent methylation-specific PCR and GeneScan analysis, irrespective of Hagerman checklist clinical scores. Among 29 males and seven females, 11 FMR1 allelic variants ranging from 21 to >200 CGG repeats were observed. Three (CF2-3, 39-5, 44-2) out of 29 males had full mutation alleles accounting for a 10.34% incidence of FXS among idiopathic ID males. One of them was a mosaic for CGG repeats with both premutation and full mutation alleles. The frequency of fragile X syndrome is high among patients with idiopathic ID; they also had a high score for the clinical check list. A cascade testing that begins with checklist evaluation prior to DNA analysis will be cost-effective for establishing early diagnosis in South India. With the huge disease burden, there is a need for the establishment of more molecular diagnostics and self-help groups for fragile X syndrome.

“Enduring trust is essential for lifelong collection of phenotypes and traits. Good metadata, local ownership and fair reuse of genomic and outcome data can be sustained in partnership among well-resourced and well-peopled regions of the world.“

A Perspective in this issue recounts the endeavors of the collaborative Virus Outbreak Data Access Network (VODAN)—Africa² that collected SARS-CoV-2 outcomes using electronic case report forms (eCRFs) and other templates and organized the data with FAIR metadata models in linked data for clinical decision making and research queries. One use case employed temporal, numerical and geolocator metadata to connect de-identified interviews with displaced people in Tunisia about their COVID-19 infection outcomes to media reports that aggregate information on the same groups. The metadata model and the data it describes were stored as linked data that could be remotely queried across the network of nine African countries.

Genome data is cheap, plentiful, and concentrated in a few wealthy places, even relative to the information web, where less than 1% of the world's servers serve over 99% of the web content.¹ This situation arises because it is difficult to move petabytes of data (since it is hard drives rather than bytes that travel). Second, the need for efficient search over similar formats of data usually leads to centralized accumulation of resources. Third, trusted and secure sharing of data resources among distributed sites requires metadata standards and linked data conventions that permit both computer operations without parsing or data transformation and queries from human users who range from clinicians to bioinformaticians to government agencies. Finally, application of any agreed metadata standards needs to be rapid and very low cost if it is to be more than a specialized research and training exercise.

In contrast to genome data, personal experiences including exposures and clinical records are distributed across institutions, homes, families, and individuals. Lifelong trust that sharing this information brings better outcomes for the donors is essential if we are to use this living biobank of diverse experience to make sense of variation in both viral and human genomes. Information from affected and unaffected individuals is needed to understand the importance of even point mutations in small viral genomes—such as the SARS-CoV-2 variants that continue to cause so much disruption and disease worldwide. Yet this data has not been gathered from places where the disruption is occurring, largely because we do not yet have collection networks with the trust and capacity to sustainably return results within the region of study.

There are now several related functional technologies for linked data to deliver the aspirational goals laid out in the principles of FAIR data and services. These working together would amount to a mercanti

Stuttering is a childhood-onset fluency disorder, intertwined with physiological, emotional, and anxiety factors. The present study was designed to evaluate the recurrence of the reported mutations among three previously implicated (GNPTAB, GNPTG, NAGPA) candidate genes, in persons with stuttering from south India. Mutation screening was performed among 64 probands on 12 specific exons, by Sanger sequencing. A total of 12 variants were identified, which included five nonsynonymous, five synonymous, and two noncoding variants. Three unrelated probands harbored heterozygous missense variants at conserved coding positions across species (p. Glu1200Lys in GNPTAB, p. Ile268Leu in GNPTG and p. Arg44Pro in NAGPA). Of these, only one variant (p. Glu1200Lys in GNPTAB) cosegregated with the affected status while p. Ile268Leu in GNPTG gene was found to be a rare de novo variant. Although this study identified some previously reported variants that have been claimed to have a role in stuttering, we confirmed only one of these to be a likely causal de novo variant (p.Ile268Leu) in the GNPTG gene at an allele frequency of 0.8% (1/128) in the families with stuttering.

Regeneration is widespread across the animal kingdom but varies vastly across phylogeny and even ontogeny. Adult mammalian regeneration in most organs and appendages is limited, while vertebrates such as zebrafish and salamanders are able to regenerate various organs and body parts. Here, we focus on the regeneration of appendages, spinal cord, and heart—organs and body parts that are highly regenerative among fish and amphibian species but limited in adult mammals. We then describe potential genetic, epigenetic, and post-transcriptional similarities among these different forms of regeneration across vertebrates and discuss several theories for diminished regenerative capacity throughout evolution.

Targeted DNA methylation is important for understanding transcriptional modulation and epigenetic diseases. Although CRISPR-Cas9 has potential for this purpose, it has not yet been successfully used to efficiently introduce DNA methylation and induce epigenetic diseases. We herein developed a new system that enables the replacement of an unmethylated promoter with a methylated promoter through microhomology-mediated end joining-based knock-in. We successfully introduced an approximately 100% DNA methylation ratio at the cancer-associated gene SP3 in HEK293 cells. Moreover, engineered SP3 promoter hypermethylation led to transcriptional suppression in human B lymphocytes and induced B-cell lymphoma. Our system provides a promising framework for targeted DNA methylation and cancer initiation through epimutations.

Synthetic biology research and technology translation has garnered increasing interest from the governments and private investors in Asia, where the technology has great potential in driving a sustainable bio-based economy. This Perspective reviews the latest developments in the key enabling technologies of synthetic biology and its application in bio-manufacturing, medicine, food and agriculture in Asia. Asia-centric strengths in synthetic biology to grow the bio-based economy, such as advances in genome editing and the presence of biofoundries combined with the availability of natural resources and vast markets, are also highlighted. The potential barriers to the sustainable development of the field, including inadequate infrastructure and policies, with suggestions to overcome these by building public-private partnerships, more effective multi-lateral collaborations and well-developed governance framework, are presented. Finally, the roles of technology, education and regulation in mitigating potential biosecurity risks are examined. Through these discussions, stakeholders from different groups, including academia, industry and government, are expectantly better positioned to contribute towards the establishment of innovation and bio-economy hubs in Asia.

Genetics was supposed to move epidemiology beyond the original “Table 1 error” of assuming ancestry as surrogate genotype and ethnicity as surrogate environmental exposures—and to deliver precision in health prediction and healthcare.¹ Without methods to prioritize research around a person's everyday exposures and experiences of disease at scale, even sophisticated genetic epidemiology will deliver only an outline of contributory factors. Indeed, genetic research might even worsen existing ancestry-based health disparities in common and rare monogenic diseases.

Taking Sickle Cell Disease (SCD) as the classic example of a monogenic disease caused by a single mutation, a Perspective² in this issue of the journal suggests how an international collaboration can take advantage of the range of individual experiences of SCD in resource rich—but unequal—and less well-resourced environments to understand how a single mutation results in such a complex range of environmentally dependent experiences of disease and disability. At least for rarer but highly penetrant monogenic conditions with a small range of allelic variation that may be possible. Insights into the divergent phenotypes of SCD may be achieved by aggregating data globally to inform the research methods used to understand how gene-environment interactions result in different health outcomes. These collaborative research efforts may in turn ameliorate the effects of health disparities for people with rare diseases or people in any population living with conditions where there is a strong genetic component. The proposed approach is rooted in the detailed experience of individuals sharing a genotype. To make it useful for research the reporting needs to be in units suitable for statistical methods. The duration or frequency of an episode of disease requiring intervention is a universal measure of disease experience that is useful across the diversity of reporting, adaptable to differential missingness in data, and useful despite the use of reporting instruments of types that greatly exceed the variation in genotyping technologies and analytic pipelines.

One of the insights in this Perspective is the conceptual use of individual health timelines recording the temporal correlation and intensity of factors influencing health status.² These factors can be intrinsic (mutation, genotype, admixture) episodic (altitude, exercise, hospitalization) and continuing (geographic location, family, and community). There will be much redundancy and missingness in these datasets, but the aggregate will be rich in data to be mined for their patterns of correlation and causation. Since individuals with SCD will have most at stake in symptom mitigation, incentives for participation and guided self-reporting should be introduced in the methodology in its design.

The authors have chosen pain to model which is apt because it is a

Differences in health outcomes and treatment responses within and between global populations have been well documented. There is growing recognition of the need to move beyond simple inventories and descriptions of these differences and our linear explanations for them, and gain a better understanding of the multifaceted systems and networks underlying them in order to develop more precise and effective remedies. Typical targets for such integrative research have been common multifactorial diseases. We propose sickle cell disease, one of the most common monogenic diseases, as an ideal candidate for elucidating the complexity of the influences of endogenous and exogenous factors on disease pathophysiology, phenotypic diversity, and variations in responses to treatments at both the individual and population levels. We provide data-informed representations of diverse contributors to sickle cell disease complications that could guide innovative efforts to advance scientific knowledge, clinical practice, and policy formulation related to the disease; help improve outcomes for people worldwide with sickle cell disease; and inform approaches to studying and addressing other diseases.

Pathogenic constitutional genomic variants in the mismatch repair (MMR) genes are the drivers of Lynch syndrome; optimal variant interpretation is required for the management of suspected and confirmed cases. The International Society for Hereditary Gastrointestinal Tumours (InSiGHT) provides expert classifications for MMR variants for the US National Human Genome Research Institute's (NHGRI) ClinGen initiative and interprets variants with discordant classifications and those of uncertain significance (VUSs). Given the onerous nature of extracting information related to variants, literature searching tools which harness artificial intelligence may aid in retrieving information to allow optimum variant classification. In this study, we described the nature of discordance in a sample of 80 variants from a list of variants requiring updating by InSiGHT for ClinGen by comparing their existing InSiGHT classifications with the various submissions for each variant on the US National Centre for Biotechnology Information's (NCBI) ClinVar database. To identify the potential value of a literature searching tool in extracting information related to classification, all variants were searched for using a traditional method (Google Scholar) and literature searching tool (Mastermind) independently. Descriptive statistics were used to compare: the number of articles before and after screening for relevance and the number of relevant articles unique to either method. Relevance was defined as containing the variant in question as well as data informing variant interpretation. A total of 916 articles were returned by both methods and Mastermind averaged four relevant articles per search compared to Google Scholar's three. Of relevant Mastermind articles, 193/308 (62.7%) were unique to it, compared to 87/202, (43.0%) for Google Scholar. For 24 variants, either or both methods found no information. All 6/80 (20%) variants with pathogenic or likely pathogenic InSiGHT classifications have newer VUS assertions on ClinVar. Our study demonstrated that for a sample of variants with varying discordant interpretations, Mastermind was able to return on average, a more relevant and unique literature search. Google Scholar was able to retrieve information that Mastermind did not, which supports a conclusion that Mastermind could play a complementary role in literature searching for classification. This work will aid InSiGHT in its role of classifying MMR variants.

ERBB3 is a pseudokinase domain-containing member of the ERBB family of receptor tyrosine kinases (RTKs). Following ligand binding, ERBB receptors homo- or hetero-dimerize, leading to a head-to-tail arrangement of the intracellular kinase domains, where the “receiver” kinase domain of one ERBB is activated by the “activator” domain of the other ERBB in the dimer. In ERBB3, a conserved valine at codon 943 (V943) in the kinase C-terminal domain has been shown to be important for its function as an “activator” kinase in vitro. Here we report a knock-in mouse model where we have modified the endogenous Erbb3 allele to allow for tissue-specific conditional expression of Erbb3^V943R (Erbb3^CKI-V943R). Additionally, we generated an Erbb3^D850N (Erbb3^CKI-D850N) conditional knock-in mouse model where the conserved aspartate in the DFG motif of the pseudokinase domain was mutated to abolish any potential residual kinase activity. While Erbb3^D850N/D850N animals developed normally, homozygous Erbb3^V943R/V943R expression during development resulted in embryonic lethality. Further, tissue specific expression of Erbb3^V943R/V943R in the mammary gland epithelium following its activation using MMTV-Cre resulted in delayed elongation of the ductal network during puberty. Single-cell RNA-seq analysis of Erbb3^V943R/V943R mammary glands showed a reduction in a specific subset of fibrinogen-producing luminal epithelial cells.