scholarly journals Genome-wide functional annotation of Phomopsis longicolla isolate MSPL 10-6

Genomics Data ◽  
2016 ◽  
Vol 8 ◽  
pp. 67-69 ◽  
Author(s):  
Omar Darwish ◽  
Shuxian Li ◽  
Benjamin Matthews ◽  
Nadim Alkharouf
Keyword(s):  
Functional Annotation ◽  
Phomopsis Longicolla ◽  
Genome Wide

scholarly journals Functional annotation of risk loci identified through genome-wide association studies for prostate cancer

The Prostate ◽  
2010 ◽  
Vol 71 (9) ◽  
pp. 955-963 ◽  
Author(s):  
Yizhen Lu ◽  
Zheng Zhang ◽  
Hongjie Yu ◽  
S. Lily Zheng ◽  
William B. Isaacs ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Functional Annotation ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Identification of Novel Genome-Wide Associations for Oral Inflammatory Traits

2020 ◽  
Author(s):  
Yanjiao Jin ◽  
Jie Yang ◽  
Shuyue Zhang ◽  
Jin Li ◽  
Songlin Wang
Keyword(s):  
Candidate Genes ◽  
Immune Regulation ◽  
Functional Annotation ◽  
Inflammatory Diseases ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Protein Protein Interaction ◽  
Genome Wide ◽  
Causal Variants

Abstract Background: Oral diseases impact the majority of the world’s population. The following traits are common in oral inflammatory diseases: mouth ulcers, painful gums, bleeding gums, loose teeth, and toothache. Despite the prevalence of genome-wide association studies, the associations between these traits and common genomic variants, and whether pleiotropic loci are shared by some of these traits remain poorly understood. Methods: In this work, we conducted multi-trait joint analyses based on the summary statistics of genome-wide association studies of these five oral inflammatory traits from the UK Biobank, each of which is comprised of over 10,000 cases and over 300,000 controls. We estimated the genetic correlations between the five traits. We conducted fine-mapping and functional annotation based on multi-omics data to better understand the biological functions of the potential causal variants at each locus. To identify the pathways in which the candidate genes were mainly involved, we applied gene-set enrichment analysis, and further performed protein-protein interaction (PPI) analyses.Results: We identified 39 association signals that surpassed genome-wide significance, including three that were shared between two or more oral inflammatory traits, consistent with a strong correlation. Among these genome-wide significant loci, two were novel for both painful gums and toothache. We performed fine-mapping and identified causal variants at each novel locus. Further functional annotation based on multi-omics data suggested IL10 and IL12A/TRIM59 as potential candidate genes at the novel pleiotropic loci, respectively. Subsequent analyses of pathway enrichment and protein-protein interaction networks suggested the involvement of candidate genes at genome-wide significant loci in immune regulation.Conclusions: Our results highlighted the importance of immune regulation in the pathogenesis of oral inflammatory diseases. Some common immune-related pleiotropic loci or genetic variants are shared by multiple oral inflammatory traits. These findings will be beneficial for risk prediction, prevention, and therapy of oral inflammatory diseases.

scholarly journals The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Naihui Zhou ◽  
Yuxiang Jiang ◽  
Timothy R. Bergquist ◽  
Alexandra J. Lee ◽  
Balint Z. Kacsoh ◽  
...  
Keyword(s):  
Protein Function ◽  
Functional Annotation ◽  
Protein Function Prediction ◽  
Mutation Screening ◽  
Function Prediction ◽  
Long Term Memory ◽  
Functional Annotations ◽  
Genome Wide ◽  
New Development ◽  
Working Together

Abstract Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.

scholarly journals Phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories revealed by AI-MiXeR

2020 ◽  
Vol 36 (18) ◽  
pp. 4749-4756 ◽  
Author(s):  
Alexey A Shadrin ◽  
Oleksandr Frei ◽  
Olav B Smeland ◽  
Francesco Bettella ◽  
Kevin S O'Connell ◽  
...  
Keyword(s):  
Functional Annotation ◽  
Association Studies ◽  
Effect Sizes ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Protein Coding ◽  
Genome Wide ◽  
Whole Exome ◽  
Causal Variants ◽  
Complex Human Traits

Abstract Motivation Determining the relative contributions of functional genetic categories is fundamental to understanding the genetic etiology of complex human traits and diseases. Here, we present Annotation Informed-MiXeR, a likelihood-based method for estimating the number of variants influencing a phenotype and their effect sizes across different functional annotation categories of the genome using summary statistics from genome-wide association studies. Results Extensive simulations demonstrate that the model is valid for a broad range of genetic architectures. The model suggests that complex human phenotypes substantially differ in the number of causal variants, their localization in the genome and their effect sizes. Specifically, the exons of protein-coding genes harbor more than 90% of variants influencing type 2 diabetes and inflammatory bowel disease, making them good candidates for whole-exome studies. In contrast, <10% of the causal variants for schizophrenia, bipolar disorder and attention-deficit/hyperactivity disorder are located in protein-coding exons, indicating a more substantial role of regulatory mechanisms in the pathogenesis of these disorders. Availability and implementation The software is available at: https://github.com/precimed/mixer. Supplementary information Supplementary data are available at Bioinformatics online.

Genome-wide identification and functional annotation of miRNAs in anti-inflammatory plant and their cross-kingdom regulation in Homo sapiens

2016 ◽  
Vol 35 (7) ◽  
pp. 1389-1400 ◽  
Author(s):  
Ankita Sharma ◽  
Sarika Sahu ◽  
Pooja Kumari ◽  
Soundhara Rajan Gopi ◽  
Rajesh Malhotra ◽  
...  
Keyword(s):  
Functional Annotation ◽  
Homo Sapiens ◽  
Genome Wide ◽  
Anti Inflammatory

scholarly journals Fast Genome-Wide Functional Annotation through Orthology Assignment by eggNOG-Mapper

2017 ◽  
Vol 34 (8) ◽  
pp. 2115-2122 ◽  
Author(s):  
Jaime Huerta-Cepas ◽  
Kristoffer Forslund ◽  
Luis Pedro Coelho ◽  
Damian Szklarczyk ◽  
Lars Juhl Jensen ◽  
...  
Keyword(s):  
Functional Annotation ◽  
Orthology Assignment ◽  
Genome Wide

Genome-wide identification and functional annotation of Plasmodium falciparum long noncoding RNAs from RNA-seq data

2014 ◽  
Vol 113 (4) ◽  
pp. 1269-1281 ◽  
Author(s):  
Qi Liao ◽  
Jia Shen ◽  
Jianfa Liu ◽  
Xi Sun ◽  
Guoguang Zhao ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Functional Annotation ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Rna Seq ◽  
Genome Wide

Genome-Wide Functional Annotation Environment for Thermus thermophilus in OBIGrid

2005 ◽  
pp. 82-91 ◽  
Author(s):  
Akinobu Fukuzaki ◽  
Takeshi Nagashima ◽  
Kaori Ide ◽  
Fumikazu Konishi ◽  
Mariko Hatakeyama ◽  
...  
Keyword(s):  
Functional Annotation ◽  
Thermus Thermophilus ◽  
Genome Wide

Genome-Wide Analysis Identifies Regulators of Hematologic Parameters

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. SCI-10-SCI-10
Author(s):  
Christian Gieger ◽  
Nicole Soranzo
Keyword(s):  
Blood Cells ◽  
Functional Annotation ◽  
Conflicts Of Interest ◽  
Hematological Parameters ◽  
White Blood Cells ◽  
Genome Wide Association ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
High Degree ◽  
Blood Elements

Abstract Abstract SCI-10 Recent genome-wide association scans published by ours and other groups have revealed > 50 genetic loci associated with hematological parameters, including the count and volume of red and white blood cells and platelets. These variants map to known and novel regulators of hematopoiesis, and provide evidence for a high degree of connectivity guiding differentiation of the different blood elements. I will review progress in the field as well as ongoing efforts within the HaemGen consortium, where we have used statistical analyses, animal models and genome-wide functional annotation to address the in-depth genetic exploration of such parameters. Disclosures: No relevant conflicts of interest to declare.

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