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1.
Bioinformatics ; 38(13): 3327-3336, 2022 06 27.
Artículo en Inglés | MEDLINE | ID: mdl-35575355

RESUMEN

MOTIVATION: Bioinformatics software tools operate largely through the use of specialized genomics file formats. Often these formats lack formal specification, making it difficult or impossible for the creators of these tools to robustly test them for correct handling of input and output. This causes problems in interoperability between different tools that, at best, wastes time and frustrates users. At worst, interoperability issues could lead to undetected errors in scientific results. RESULTS: We developed a new verification system, Acidbio, which tests for correct behavior in bioinformatics software packages. We crafted tests to unify correct behavior when tools encounter various edge cases-potentially unexpected inputs that exemplify the limits of the format. To analyze the performance of existing software, we tested the input validation of 80 Bioconda packages that parsed the Browser Extensible Data (BED) format. We also used a fuzzing approach to automatically perform additional testing. Of 80 software packages examined, 75 achieved less than 70% correctness on our test suite. We categorized multiple root causes for the poor performance of different types of software. Fuzzing detected other errors that the manually designed test suite could not. We also created a badge system that developers can use to indicate more precisely which BED variants their software accepts and to advertise the software's performance on the test suite. AVAILABILITY AND IMPLEMENTATION: Acidbio is available at https://github.com/hoffmangroup/acidbio. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Asunto(s)
Genómica , Programas Informáticos , Genómica/métodos
3.
Nat Commun ; 15(1): 7640, 2024 Sep 02.
Artículo en Inglés | MEDLINE | ID: mdl-39223139

RESUMEN

Genetic parasites, including viruses and transposons, exploit components from the host for their own replication. However, little is known about virus-transposon interactions within host cells. Here, we discover a strategy where human cytomegalovirus (HCMV) hijacks L1 retrotransposon encoded protein during its replication cycle. HCMV infection upregulates L1 expression by enhancing both the expression of L1-activating transcription factors, YY1 and RUNX3, and the chromatin accessibility of L1 promoter regions. Increased L1 expression, in turn, promotes HCMV replicative fitness. Affinity proteomics reveals UL44, HCMV DNA polymerase subunit, as the most abundant viral binding protein of the L1 ribonucleoprotein (RNP) complex. UL44 directly interacts with L1 ORF2p, inducing DNA damage responses in replicating HCMV compartments. While increased L1-induced mutagenesis is not observed in HCMV for genetic adaptation, the interplay between UL44 and ORF2p accelerates viral DNA replication by alleviating replication stress. Our findings shed light on how HCMV exploits host retrotransposons for enhanced viral fitness.


Asunto(s)
Citomegalovirus , Replicación del ADN , Elementos de Nucleótido Esparcido Largo , Proteínas Virales , Replicación Viral , Humanos , Citomegalovirus/genética , Citomegalovirus/fisiología , Replicación Viral/genética , Proteínas Virales/metabolismo , Proteínas Virales/genética , Replicación del ADN/genética , Elementos de Nucleótido Esparcido Largo/genética , Infecciones por Citomegalovirus/virología , Infecciones por Citomegalovirus/genética , Interacciones Huésped-Patógeno/genética , Retroelementos/genética , Proteínas de Unión al ADN
4.
Bioinform Adv ; 3(1): vbad031, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-37033469

RESUMEN

Summary: Chromatin immunoprecipitation-sequencing is widely used to find transcription factor binding sites, but suffers from various sources of noise. Knocking out the target factor mitigates noise by acting as a negative control. Paired wild-type and knockout (KO) experiments can generate improved motifs but require optimal differential analysis. We introduce peaKO-a computational method to automatically optimize motif analyses with KO controls, which we compare to two other methods. PeaKO often improves elucidation of the target factor and highlights the benefits of KO controls, which far outperform input controls. Availability and implementation: PeaKO is freely available at https://peako.hoffmanlab.org. Contact: michael.hoffman@utoronto.ca.

5.
Cell Genom ; 1(2)2021 Nov 10.
Artículo en Inglés | MEDLINE | ID: mdl-35072136

RESUMEN

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

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