Identification of novel direct targets of Drosophila Sine oculis and Eyes absent by integration of genome-wide data sets

Introduction Chronic migraine (CM) is at the severe end of the clinical migraine spectrum, but its genetic background is unknown. Our study searched for evidence that genetic factors are involved in the chronification process. Methods We initially selected 144 single-nucleotide polymorphisms (SNPs) from 48 candidate genes, which we tested for association in two stages: The first stage encompassed 262 CM patients, the second investigated 226 patients with high-frequency migraine (HFM). Subsequently, SNPs with p values < 0.05 were forwarded to the replication stage containing 531 patients with CM or HFM. Results Eight SNPs were significantly associated with CM and HFM in the two-stage phase. None survived replication in the third stage. Discussion We present the first comprehensive genetic association study for migraine chronification. There were no significant findings. Future studies may benefit from larger, genome-wide data sets or should use other genetic approaches to identify genetic factors involved in migraine chronification.

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Treasures and traps in genome-wide data sets: case examples from yeast

Nature Reviews Genetics ◽

10.1038/nrg886 ◽

2002 ◽

Vol 3 (9) ◽

pp. 653-661 ◽

Cited By ~ 49

Author(s):

Björn Grünenfelder ◽

Elizabeth A. Winzeler

Keyword(s):

Data Sets ◽

Case Examples ◽

Genome Wide ◽

Genome Wide Data

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Genome Redux for Hematologists: a Graphical User Interface for Visualizing and Reducing Genome-Wide Data Sets Into Clinically Actionable Information

Blood ◽

10.1182/blood.v116.21.2558.2558 ◽

2010 ◽

Vol 116 (21) ◽

pp. 2558-2558

Author(s):

Thomas Gage ◽

Ali Kazeroonian ◽

German A. Pihan

Keyword(s):

Gene Expression ◽

User Interface ◽

Graphical Representation ◽

Conflicts Of Interest ◽

Data Sets ◽

Complex Data ◽

Genome Wide ◽

A Genome ◽

Study Gene Expression ◽

Genome Wide Data

Abstract Abstract 2558 Background: The increasing use in the clinic of genome-wide analyses has placed a greater burden on, and need for novel informatics tools. Ideally such tools should be capable of reducing the vast amount of information generated per patient into integrated, simplified, intuitive, and preferably, visual data that can be easily translated into diagnostic, prognostic and theranostic actionable information. With the overarching goal of clarity and user-friendliness in mind we have co-opted a genome-wide representational tool used widely in non-clinical discovery genomics and tailored it to achieve its intended clinical use, i.e. simple graphical representation of complex data enabling clinicians to quickly derive meaning from robust clinical laboratory modalities, such as next-generation sequencing technologies and next-gen microarrays. Materials & Methods: For a proof of concept rendition, we collected cytogenetics, array CGH, and gene expression data on a subset of well-characterized core binding factor positive leukemias. Leukemias containing CBFA2 [t(8;21)(q22;q22)] or CBFB [inv(16)(p13q22)] fusion proteins were included in the study. Gene expression profiling data sets were extracted from Stanford Microarray Database. The associated karyotypes were obtained from the linked PubMed papers and directly from the authors. aCGH data sets were extracted from the SKY/M-FISH and CGH database at NCBI. All datasets for each case of CBF+ leukemia represented in this study were unified into a Microsoft Access Database, which contained the numeric coordinates of all genes included, and their associated cytogenetic band position. Results: By subjecting the data to customized subroutines, it was possible to extract and display relevant subsets of data into a customizable visually intuitive display, which allowed naïve observers to quickly assimilate all the clinically relevant genetic information on a particular AML case. From such a representation, heat maps of subsets of genes, structural and numerical chromosome abnormalities, copy-number changes and subsets of relevant point mutations could be displayed, all in a single integrated genome anchored image. Discussion: Our graphic user interface displays positionally-anchored genome-wide data and could be customized to represent CNVs, miRNA expression and DNA methylation patterns, associated phenotypes, etc, in addition to those shown in this study. Furthermore, any of these parameters can be segmented into functionally related groups to display, for instance, regulators of transcription, cell lineage or differentiation, proliferation, apoptosis, DNA repair, expression of genes that govern response or sensitivity to chemotherapy or entire signaling pathways. Conclusion: Integrated graphical representation of relevant genome-wide data facilitates and harmonizes communication among physicians with different expertise and facilitates patient stratification into defined risk groups, which is critically important in enabling risk-adapted and/or targeted therapies. Disclosures: No relevant conflicts of interest to declare.

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ClusTrack: Feature Extraction and Similarity Measures for Clustering of Genome-Wide Data Sets

PLoS ONE ◽

10.1371/journal.pone.0123261 ◽

2015 ◽

Vol 10 (4) ◽

pp. e0123261 ◽

Cited By ~ 2

Author(s):

Halfdan Rydbeck ◽

Geir Kjetil Sandve ◽

Egil Ferkingstad ◽

Boris Simovski ◽

Morten Rye ◽

...

Keyword(s):

Feature Extraction ◽

Similarity Measures ◽

Data Sets ◽

Genome Wide ◽

Genome Wide Data

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A Neural Network Method for Identification of Prokaryotic and Eukaryotic Signal Peptides and Prediction of their Cleavage Sites

International Journal of Neural Systems ◽

10.1142/s0129065797000537 ◽

1997 ◽

Vol 08 (05n06) ◽

pp. 581-599 ◽

Cited By ~ 463

Author(s):

Henrik Nielsen ◽

Jacob Engelbrecht ◽

Søren Brunak ◽

Gunnar Von Heijne

Keyword(s):

Neural Network ◽

Data Sets ◽

Signal Peptides ◽

Cleavage Sites ◽

Genome Wide ◽

Network Method ◽

Genome Wide Data ◽

Signal Anchor ◽

Better Than ◽

Previous Prediction

We have developed a new method for the identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs significantly better than previous prediction schemes, and can easily be applied to genome-wide data sets. Discrimination between cleaved signal peptides and uncleaved N-terminal signal-anchor sequences is also possible, though with lower precision. Predictions can be made on a publicly available WWW server: .

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Connecting myelin-related and synaptic dysfunction in schizophrenia with SNP-rich gene expression hubs

10.1101/080044 ◽

2016 ◽

Author(s):

Hedi Hegyi

Keyword(s):

Gene Expression ◽

Gene Networks ◽

Human Life ◽

Pearson Correlation ◽

Data Sets ◽

Genome Wide ◽

Differentially Methylated Genes ◽

Genome Wide Data ◽

Schizophrenic Patients ◽

Genomic Regions

AbstractThe recent availability of several genome-wide data sets such as genome-wide mapping of SNP-rich regions and differentially methylated genes in schizophrenic individuals and gene expression data in all brain compartments across the span of human life prompted us to integrate these datasets to gain a better insight into the underlying gene networks driving this enigmatic disease.We summed up the differentially methylated “expression neighbors” (i.e. genes with positively or negatively correlating expression values) of genes that fall into one of 108 distinct schizophrenia-associated genetic loci with high number of SNPs in schizophrenic patients derived from a large cohort of pooled sequencing experiments. Surprisingly, the number of expression neighbors (with a Pearson correlation of R>=0.8 or R<=−0.7) of the genes falling into the 108 genomic regions were about 35 times higher for the positively correlating genes and 32 times higher for the negatively correlating ones than for the rest of the ~16000 genes outside these loci. While the genes in the 108 loci have relatively little known impact in schizophrenia, using this approach we identified many more known schizophrenia-related important genes with a high degree of connectedness to other genes and high scores of differentially methylated probes for their expression neighbors (such as MBP, MOBP, GRIA1, COMT, SYNGR1, MAP2 and DGCR6), validating our approach.The analysis revealed that the most positively correlating as well as the most negatively correlating genes affect synapse-related genes the most, offering an explanation and a unified view into the root cause of schizophrenia.

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Functional Annotation of Animal Genomes (FAANG): Current Achievements and Roadmap

Annual Review of Animal Biosciences ◽

10.1146/annurev-animal-020518-114913 ◽

2019 ◽

Vol 7 (1) ◽

pp. 65-88 ◽

Cited By ~ 37

Author(s):

Elisabetta Giuffra ◽

Christopher K. Tuggle ◽

Keyword(s):

Functional Annotation ◽

Chromatin Modification ◽

Chromatin Accessibility ◽

Genomic Research ◽

Data Sets ◽

Genome Wide ◽

Data Collection And Analysis ◽

Genome Wide Data ◽

Animal Genomics ◽

Animal Genomes

Functional annotation of genomes is a prerequisite for contemporary basic and applied genomic research, yet farmed animal genomics is deficient in such annotation. To address this, the FAANG (Functional Annotation of Animal Genomes) Consortium is producing genome-wide data sets on RNA expression, DNA methylation, and chromatin modification, as well as chromatin accessibility and interactions. In addition to informing our understanding of genome function, including comparative approaches to elucidate constrained sequence or epigenetic elements, these annotation maps will improve the precision and sensitivity of genomic selection for animal improvement. A scientific community–driven effort has already created a coordinated data collection and analysis enterprise crucial for the success of this global effort. Although it is early in this continuing process, functional data have already been produced and application to genetic improvement reported. The functional annotation delivered by the FAANG initiative will add value and utility to the greatly improved genome sequences being established for domesticated animal species.

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Genetic analysis of amyotrophic lateral sclerosis identifies contributing pathways and cell types

Science Advances ◽

10.1126/sciadv.abd9036 ◽

2021 ◽

Vol 7 (3) ◽

pp. eabd9036

Author(s):

Sara Saez-Atienzar ◽

Sara Bandres-Ciga ◽

Rebekah G. Langston ◽

Jonggeol J. Kim ◽

Shing Wan Choi ◽

...

Keyword(s):

Amyotrophic Lateral Sclerosis ◽

Membrane Trafficking ◽

Molecular Mechanisms ◽

Cell Types ◽

Polygenic Risk Score ◽

Genome Wide ◽

Genome Wide Data ◽

Data Driven Approach ◽

Single Nucleus ◽

Lateral Sclerosis

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely, neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated six differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, MAPKAPK3, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

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Ancient genomic time transect from the Central Asian Steppe unravels the history of the Scythians

Science Advances ◽

10.1126/sciadv.abe4414 ◽

2021 ◽

Vol 7 (13) ◽

pp. eabe4414

Author(s):

Guido Alberto Gnecchi-Ruscone ◽

Elmira Khussainova ◽

Nurzhibek Kahbatkyzy ◽

Lyazzat Musralina ◽

Maria A. Spyrou ◽

...

Keyword(s):

Bronze Age ◽

Iron Age ◽

Gene Pools ◽

Social Rules ◽

Eurasian Steppe ◽

Central Asian ◽

Genome Wide ◽

Genome Wide Data ◽

History Of ◽

First Millennium

The Scythians were a multitude of horse-warrior nomad cultures dwelling in the Eurasian steppe during the first millennium BCE. Because of the lack of first-hand written records, little is known about the origins and relations among the different cultures. To address these questions, we produced genome-wide data for 111 ancient individuals retrieved from 39 archaeological sites from the first millennia BCE and CE across the Central Asian Steppe. We uncovered major admixture events in the Late Bronze Age forming the genetic substratum for two main Iron Age gene-pools emerging around the Altai and the Urals respectively. Their demise was mirrored by new genetic turnovers, linked to the spread of the eastern nomad empires in the first centuries CE. Compared to the high genetic heterogeneity of the past, the homogenization of the present-day Kazakhs gene pool is notable, likely a result of 400 years of strict exogamous social rules.

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Genome diversity in Ukraine

GigaScience ◽

10.1093/gigascience/giaa159 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Taras K Oleksyk ◽

Walter W Wolfsberger ◽

Alexandra M Weber ◽

Khrystyna Shchubelka ◽

Olga T Oleksyk ◽

...

Keyword(s):

Sequence Data ◽

Copy Number Variations ◽

Genomic Variation ◽

High Coverage ◽

Genome Data ◽

New Information ◽

Genome Wide ◽

Public Data ◽

Genome Wide Data ◽

Multiple Samples

Abstract Background The main goal of this collaborative effort is to provide genome-wide data for the previously underrepresented population in Eastern Europe, and to provide cross-validation of the data from genome sequences and genotypes of the same individuals acquired by different technologies. We collected 97 genome-grade DNA samples from consented individuals representing major regions of Ukraine that were consented for public data release. BGISEQ-500 sequence data and genotypes by an Illumina GWAS chip were cross-validated on multiple samples and additionally referenced to 1 sample that has been resequenced by Illumina NovaSeq6000 S4 at high coverage. Results The genome data have been searched for genomic variation represented in this population, and a number of variants have been reported: large structural variants, indels, copy number variations, single-nucletide polymorphisms, and microsatellites. To our knowledge, this study provides the largest to-date survey of genetic variation in Ukraine, creating a public reference resource aiming to provide data for medical research in a large understudied population. Conclusions Our results indicate that the genetic diversity of the Ukrainian population is uniquely shaped by evolutionary and demographic forces and cannot be ignored in future genetic and biomedical studies. These data will contribute a wealth of new information bringing forth a wealth of novel, endemic and medically related alleles.

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