scholarly journals Big data and innovative bioinformatics approaches in personalized genomic medicine

2021 ◽  
Vol 41 ◽  
pp. 01003
Author(s):  
Joris A. Veltman
Keyword(s):  
Genetic Variation ◽  
Genome Sequence ◽  
Developmental Disorders ◽  
Genomic Medicine ◽  
Population Variation ◽  
Biological Information ◽  
Management Approach ◽  
Specific Information ◽  
A Genome ◽  
The Impact

The field of human genetics has been radically changed by the introduction of massive parallel sequencing, also called next generation sequencing, approaches. Instead of studying a single gene or a few genetic variants, nowadays we can study genetic variation present in all genes and even throughout the entire human genome. For the first time in history, we can really study what makes us unique and use that to explain differences in for example disease susceptibility or response to treatment. In rare disease, genetics research is essential to identify the molecular diagnosis that provides the basis for a personalized patient management approach. It allows for more precise answers about the underlying cause and family recurrence risk, but also aids in optimizing treatment plans aimed at reducing co-morbidities and providing information about potential drugs or participation in drug trials, with an increasing number focused on gene therapy. These high-throughput sequencing technologies generate enormous amounts of data in order to assemble a genome and identify all of the variation present at different levels, from single nucleotide variations to chromosomal abnormalities. In addition, a genome sequence of a person in itself is not very useful. Value is derived from annotation of all the variation, and integration of the genome sequence with information about the patient involved (clinical information, disease-specific information, family history) as well as biological information (gene as well as variant-specific information, including population variation frequency, pathogenicity predictions, gene-expression information, etc). In this presentation, I will give an overview of the impact of genomics on the diagnosis of patients with rare developmental disorders and fertility disorders. I will highlight the importance of innovative bioinformatics approaches to detect and interpret genetic variation in a clinical context. Also, I will highlight some of the challenges that individual research and diagnostics units face in dealing with the data generated, discuss some of the ethical/privacy issues related to these approaches and discuss some of the latest genomics technologies being developed and validated.

scholarly journals Short Tandem Repeats as a High-Resolution Marker for Capturing Recent Orangutan Population Evolution

2021 ◽  
Vol 1 ◽  
Author(s):  
Alina-Alexandra Voicu ◽  
Michael Krützen ◽  
Tugce Bilgin Sonay
Keyword(s):  
Population Genetics ◽  
Genetic Variation ◽  
Short Tandem Repeats ◽  
Tandem Repeats ◽  
Demographic History ◽  
Population Variation ◽  
Local Adaptations ◽  
A Genome ◽  
The Impact ◽  
Short Tandem

The genus Pongo is ideal to study population genetics adaptation, given its remarkable phenotypic divergence and the highly contrasting environmental conditions it’s been exposed to. Studying its genetic variation bears the promise to reveal a motion picture of these great apes’ evolutionary and adaptive history, and also helps us expand our knowledge of the patterns of adaptation and evolution. In this work, we advance the understanding of the genetic variation among wild orangutans through a genome-wide study of short tandem repeats (STRs). Their elevated mutation rate makes STRs ideal markers for the study of recent evolution within a given population. Current technological and algorithmic advances have rendered their sequencing and discovery more accurate, therefore their potential can be finally leveraged in population genetics studies. To study patterns of population variation within the wild orangutan population, we genotyped the short tandem repeats in a population of 21 individuals spanning four Sumatran and Bornean (sub-) species and eight Southeast Asian regions. We studied the impact of sequencing depth on our ability to genotype STRs and found that the STR copy number changes function as a powerful marker, correctly capturing the demographic history of these populations, even the divergences as recent as 10 Kya. Moreover, gene ontology enrichments for genes close to STR variants are aligned with local adaptations in the two islands. Coupled with more advanced STR-compatible population models, and selection tests, genomic studies based on STRs will be able to reduce the gap caused by the missing heritability for species with recent adaptations.

scholarly journals A Flow Procedure for the Linearization of Genome Sequence Graphs

2017 ◽  
Author(s):  
David Haussler ◽  
Maciej Smuga-Otto ◽  
Benedict Paten ◽  
Adam M Novak ◽  
Sergei Nikitin ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Genome Sequence ◽  
Graph Representation ◽  
Graph Visualization ◽  
Human Genetic Variation ◽  
A Genome ◽  
Sequence Graph ◽  
Reference Genomes ◽  
Single Graph ◽  
Reference Human Genome

1AbstractEfforts to incorporate human genetic variation into the reference human genome have converged on the idea of a graph representation of genetic variation within a species, a genome sequence graph. A sequence graph represents a set of individual haploid reference genomes as paths in a single graph. When that set of reference genomes is sufficiently diverse, the sequence graph implicitly contains all frequent human genetic variations, including translocations, inversions, deletions, and insertions.In representing a set of genomes as a sequence graph one encounters certain challenges. One of the most important is the problem of graph linearization, essential both for efficiency of storage and access, as well as for natural graph visualization and compatibility with other tools. The goal of graph linearization is to order nodes of the graph in such a way that operations such as access, traversal and visualization are as efficient and effective as possible.A new algorithm for the linearization of sequence graphs, called the flow procedure, is proposed in this paper. Comparative experimental evaluation of the flow procedure against other algorithms shows that it outperforms its rivals in the metrics most relevant to sequence graphs.

scholarly journals The Impact of Population Variation in the Analysis of microRNA Target Sites

2019 ◽  
Vol 5 (2) ◽  
pp. 42 ◽  
Author(s):  
Mohab Helmy ◽  
Andrea Hatlen ◽  
Antonio Marco
Keyword(s):  
Genome Sequence ◽  
Reference Genome ◽  
Target Prediction ◽  
Regulatory Elements ◽  
Population Variation ◽  
Microrna Target ◽  
Reference Genome Sequence ◽  
Microrna Target Prediction ◽  
Target Sites ◽  
The Impact

The impact of population variation in the analysis of regulatory interactions is an underdeveloped area. MicroRNA target recognition occurs via pairwise complementarity. Consequently, a number of computational prediction tools have been developed to identify potential target sites that can be further validated experimentally. However, as microRNA target predictions are done mostly considering a reference genome sequence, target sites showing variation among populations are neglected. Here, we studied the variation at microRNA target sites in human populations and quantified their impact in microRNA target prediction. We found that African populations carry a significant number of potential microRNA target sites that are not detectable in the current human reference genome sequence. Some of these targets are conserved in primates and only lost in Out-of-Africa populations. Indeed, we identified experimentally validated microRNA/transcript interactions that are not detected in standard microRNA target prediction programs, yet they have segregating target alleles abundant in non-European populations. In conclusion, we show that ignoring population diversity may leave out regulatory elements essential to understand disease and gene expression, particularly neglecting populations of African origin.

scholarly journals Population differentiation of polygenic score predictions under stabilizing selection

2021 ◽  
Author(s):  
Sivan Yair ◽  
Graham Coop
Keyword(s):  
Genetic Variation ◽  
Large Scale ◽  
Association Studies ◽  
Genomic Medicine ◽  
Evolutionary Model ◽  
Stabilizing Selection ◽  
Genome Wide Association Studies ◽  
Polygenic Score ◽  
Polygenic Scores ◽  
The Impact

1AbstractGiven the many loci uncovered by genome-wide association studies (GWAS), polygenic scores have become central to the drive for genomic medicine and have spread into various areas including evolutionary studies of adaptation. While promising, these scores are fraught with issues of portability across populations, due to the mis-estimation of effect sizes and missing causal loci across populations not represented in large-scale GWAS. The poor portability of polygenic scores at first seems at odds with the view that much of common genetic variation is shared among populations (Lewontin, 1972). Here we investigate one potential cause of this discrepancy: phenotypic stabilizing selection drives the turnover of genetic variation shared between populations at causal loci. Somewhat counter-intuitively, while stabilizing selection to the same optimum phenotype leads to lower phenotypic differentiation among populations, it increases genetic differentiation at GWAS loci and reduces the portability of polygenic scores constructed for unrepresented populations. We also find that stabilizing selection can lead to potentially misleading signals of the differentiation of average polygenic scores among populations. We extend our baseline model to investigate the impact of pleiotropy, gene-by-environment interactions, and directional selection on polygenic score predictions. Our work emphasizes stabilizing selection as a null evolutionary model to understand patterns of allele frequency differentiation and its impact on polygenic score portability and differentiation.

scholarly journals Deciphering the Impact of Common Genetic Variation on Lung Cancer Risk: A Genome-Wide Association Study

2009 ◽  
Vol 69 (16) ◽  
pp. 6633-6641 ◽  
Author(s):  
Peter Broderick ◽  
Yufei Wang ◽  
Jayaram Vijayakrishnan ◽  
Athena Matakidou ◽  
Margaret R. Spitz ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Genetic Variation ◽  
Cancer Risk ◽  
Genome Wide Association Study ◽  
Lung Cancer Risk ◽  
Genome Wide Association ◽  
Common Genetic Variation ◽  
Genome Wide ◽  
A Genome ◽  
The Impact

scholarly journals The impact of population variation in the analysis of microRNA target sites

2019 ◽  
Author(s):  
Mohab Helmy ◽  
Andrea Hatlen ◽  
Antonio Marco
Keyword(s):  
Genome Sequence ◽  
Reference Genome ◽  
Target Prediction ◽  
Regulatory Elements ◽  
Population Variation ◽  
Microrna Target ◽  
Reference Genome Sequence ◽  
Microrna Target Prediction ◽  
Target Sites ◽  
The Impact

AbstractThe impact of population variation in the analysis of regulatory interactions is an underdeveloped area. MicroRNA target recognition occurs via pairwise complementarity. Consequently, a number of computational prediction tools have been developed to identify potential target sites, that can be further validated experimentally. However, as microRNA target predictions are done mostly considering a reference genome sequence, target sites showing variation among populations are neglected. Here we study variation at microRNA target sites in human populations and quantify their impact in microRNA target prediction. We found that African populations carry a significant number of potential microRNA target sites that are not detectable in the current human reference genome sequence. Some of these targets are conserved in primates and only lost in Out-of-Africa populations. Indeed, we identified experimentally validated microRNA/transcript interactions that are not detected in standard microRNA target prediction programs, yet they have segregating target alleles abundant in non-European populations. In conclusion, here we show that ignoring population diversity may leave out regulatory elements essential to understand disease and gene expression, particularly neglecting populations of African origin.

The adoption of IFRS 8 – no headway made? Evidence from segment reporting practices in Germany

2015 ◽  
Vol 16 (1) ◽  
pp. 88-113 ◽  
Author(s):  
Nina Franzen ◽  
Barbara E. Weißenberger
Keyword(s):  
Economic Benefits ◽  
Future Research ◽  
Management Approach ◽  
Specific Information ◽  
Content Type ◽  
Reporting Practices ◽  
Segment Reporting ◽  
Ifrs 8 ◽  
Segment Disclosures ◽  
The Impact

Purpose – The purpose of this paper is to assess the changes in segment reporting practices of German listed firms under the new segment reporting standard IFRS 8. Design/methodology/approach – The authors compare hand-collected segment disclosures of German firms in the first IFRS 8 year with those reported in the last IAS 14R year. Findings – The authors do not find substantial changes in the segment disclosures of German firms under IFRS 8. While the number of reportable segments slightly increased, the amount of information disclosed for each reportable segment decreased. The same applies to geographic areas reported as secondary segments under IAS 14R compared to entity-wide disclosures under IFRS 8. Furthermore, even though more country-specific information was provided, many firms still disclosed only broad geographic areas. Research limitations/implications – Future research should extend the analysis to consider more than one year of data following IFRS 8’s adoption and to examine the impact of the standard on smaller firms. Moreover, investigating economic benefits for investors and other financial statement users following IFRS 8’s adoption could be an avenue for future research. Practical implications – The findings indicate that the International Accounting Standards Board’s (IASB) expectations regarding changes in segment reporting practices under IFRS 8 have only partially been met. The results also reveal some cases of segment reporting practice where compliance is at least questionable. Both findings are of interest to standard-setters and regulators. Originality/value – The paper provides new insights into the effects of IFRS 8’s adoption in Germany and thus contributes to the post-implementation review of IFRS 8 carried out by the IASB in 2012/2013. The study sheds light on the consequences of applying the “management approach” to segment reporting, thereby contributing to the theoretical discussion on the adequacy of the different concepts for disclosing segment information.

scholarly journals Integrating genome sequence and structural data for statistical learning to predict transcription factor binding sites

2020 ◽  
Vol 48 (22) ◽  
pp. 12604-12617
Author(s):  
Pengpeng Long ◽  
Lu Zhang ◽  
Bin Huang ◽  
Quan Chen ◽  
Haiyan Liu
Keyword(s):  
Genome Sequence ◽  
Energy Function ◽  
Structural Information ◽  
Structural Data ◽  
P Values ◽  
A Genome ◽  
Z Scores ◽  
Transcription Regulators ◽  
Dna Specificity ◽  
Tetracycline Repressor

Abstract We report an approach to predict DNA specificity of the tetracycline repressor (TetR) family transcription regulators (TFRs). First, a genome sequence-based method was streamlined with quantitative P-values defined to filter out reliable predictions. Then, a framework was introduced to incorporate structural data and to train a statistical energy function to score the pairing between TFR and TFR binding site (TFBS) based on sequences. The predictions benchmarked against experiments, TFBSs for 29 out of 30 TFRs were correctly predicted by either the genome sequence-based or the statistical energy-based method. Using P-values or Z-scores as indicators, we estimate that 59.6% of TFRs are covered with relatively reliable predictions by at least one of the two methods, while only 28.7% are covered by the genome sequence-based method alone. Our approach predicts a large number of new TFBs which cannot be correctly retrieved from public databases such as FootprintDB. High-throughput experimental assays suggest that the statistical energy can model the TFBSs of a significant number of TFRs reliably. Thus the energy function may be applied to explore for new TFBSs in respective genomes. It is possible to extend our approach to other transcriptional factor families with sufficient structural information.

scholarly journals The psychological impact of the COVID-19 pandemic on adults with autism: a survey study across three countries

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Danna Oomen ◽  
Annabel D. Nijhof ◽  
Jan R. Wiersema
Keyword(s):  
Mental Health ◽  
Social Life ◽  
Social Stress ◽  
Mental Health Problems ◽  
Survey Study ◽  
Specific Information ◽  
Long Term Effects ◽  
Adults With Autism ◽  
Psychological Burden ◽  
The Impact

Abstract Background Previous studies have reported a negative psychological and mental health impact of the COVID-19 pandemic. This impact is likely to be stronger for people with autism as they are at heightened risk of mental health problems and because the pandemic directly affects social functioning and everyday routines. We therefore examined COVID-19 pandemic-related changes in mental health, the impact of the pandemic on their social life and routines, satisfaction with pandemic-related information and tips, and participants’ wishes for guidance. Methods We used a mixed-method approach, collecting quantitative and qualitative survey data from adults with and without autism across three European countries: Belgium, the Netherlands, and the UK (N = 1044). Results We found an increase in depression and anxiety symptoms in response to the pandemic for both the non-autism and the autism group, which was greater for adults with autism. Furthermore, adults with autism showed a greater increase in worries about their pets, work, getting medication and food, and their own safety/security. They felt more relieved from social stress, yet experienced the loss of social contact as difficult. Adults with autism also felt more stressed about the loss of routines. Pleasant changes noted by adults with autism were the increase in solidarity and reduced sensory and social overload. Adults with autism frequently reported problems with cancellation of guidance due to the pandemic and expressed their wish for (more) autism-specific information and advice. Limitations Our sample is likely to reflect some degree of selection bias, and longitudinal studies are needed to determine long-term effects. Conclusions Results highlight the psychological burden of the pandemic on adults with autism and shed light on how to support them during this COVID-19 pandemic, which is especially important now that the pandemic is likely to have a prolonged course. There is a need for accessible, affordable (continued) support from health services. Guidance may focus on the maintenance of a social network, and adjusting routines to the rapid ongoing changes. Finally, we may learn from the COVID-19 pandemic-related changes experienced as pleasant by adults with autism to build a more autism-friendly society post-pandemic.

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