Integer programming framework for pangenome-based genome inference DOI Creative Commons
Ghanshyam Chandra,

Md Helal Hossen,

Stephan Scholz

et al.

Published: Oct. 29, 2024

Abstract Affordable genotyping methods are essential in genomics. Commonly used primarily support single nucleotide variants and short indels but neglect structural variants. Additionally, accuracy of read alignments to a reference genome is unreliable highly polymorphic repetitive regions, further impacting performance. Recent works highlight the advantage haplotype-resolved pangenome graphs addressing these challenges. Building on developments, we propose rigorous alignment-free framework. Our formulation seeks path through graph that maximizes matches between substrings sequencing reads (e.g., k -mers) while minimizing recombination events (haplotype switches) along path. We prove this problem NP-Hard develop efficient integer-programming solutions. benchmarked algorithm using downsampled short-read datasets from homozygous human cell lines with coverage ranging 0.1× 10×. accurately estimates complete major histocompatibility complex (MHC) haplotype sequences small edit distances ground-truth sequences, providing significant over existing low-coverage inputs. Although our designed for haploid samples, discuss future extensions diploid samples. Implementation https://github.com/at-cg/PHI

Language: Английский

The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity DOI Creative Commons
María Cerezo, Elliot Sollis, Yue Ji

et al.

Nucleic Acids Research, Journal Year: 2024, Volume and Issue: 53(D1), P. D998 - D1005

Published: Nov. 12, 2024

The NHGRI-EBI GWAS Catalog serves as a vital resource for the genetic research community, providing access to most comprehensive database of human results. Currently, it contains close 7 000 publications >15 traits, from which more than 625 lead associations have been curated. Additionally, 85 full genome-wide summary statistics datasets-containing association data all variants in analysis-are available downstream analyses such meta-analysis, fine-mapping, Mendelian randomisation or development polygenic risk scores. As centralised repository results, sets and implements standards submission harmonisation, encourages use consistent descriptors samples methodologies. We share processes vocabulary with PGS Catalog, improving interoperability growing user group. Here, we describe latest changes content, improvements our interface, implementation GWAS-SSF standard format statistics. address challenges handling rapid increase large-scale molecular quantitative trait need sensitivity population cohort while maintaining reusability.

Language: Английский

Citations

13
Genetics and Population Analysis DOI

Prachi Balyan,

Nismabi A Nisamudheen,

Jan Zainab

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Genetic Susceptibility of Type 2 Diabetes and Metabolic Syndrome DOI Creative Commons
Vladimir Ercegović, Monika Džimbeg, Andrea Gelemanović

et al.

Diabetology, Journal Year: 2025, Volume and Issue: 6(2), P. 11 - 11

Published: Feb. 6, 2025

Type 2 diabetes (T2D) and metabolic syndrome (MetS) represent complex, multifactorial conditions that pose significant challenges to public health healthcare costs worldwide. These two share common risk factors such as obesity, dyslipidemia, hypertension and, a consequence, are frequently jointly diagnosed in an individual. More specifically, it is estimated around 85% of T2D patients also have MetS, while with MetS five times likely develop T2D. While lifestyle environmental factors, poor diet physical inactivity, play crucial role, genetic susceptibility has substantial influence on the overall risk. Recent advancements genome-wide association studies (GWAS) had major impact identifying numerous loci associated these conditions. This narrative review summarizes key findings from studies, highlighting pathways their clinical implications. The objective this provide comprehensive understanding known underpinnings inform future research open potential therapeutic preventive strategies.

Language: Английский

Citations

0
The Genomics Revolution in Nonmodel Species: Predictions vs. Reality for Salmonids DOI Creative Commons
Samuel A. May, Samuel W. Rosenbaum, Devon E. Pearse

et al.

Molecular Ecology, Journal Year: 2025, Volume and Issue: unknown

Published: April 18, 2025

ABSTRACT The increasing feasibility of whole‐genome sequencing has been highly anticipated, promising to transform our understanding the biology nonmodel species. Notably, dramatic cost reductions beginning around 2007 with advent high‐throughput inspired publications heralding ‘genomics revolution’, predictions about its future impacts. Although such served as useful guideposts, value is added when statements are evaluated benefit hindsight. Here, we review 10 key made early in genomics revolution, highlighting those realised while identifying challenges limiting others. We focus on concerning applied aspects and examples involving salmonid species which, due their socioeconomic ecological significance, have frontrunners applications Predicted outcomes included enhanced analytical power, deeper insights into genetic basis phenotype fitness variation, disease management breeding program advancements. many materialised, several expectations remain unmet technological, knowledge barriers. Additionally, largely unforeseen advancements, including identification applicability large‐effect loci, close‐kin mark–recapture, environmental DNA gene editing under‐anticipated value. Finally, emerging innovations artificial intelligence bioinformatics offer new directions. This retrospective evaluation impacts genomic revolution offers for

Language: Английский

Citations

0
The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity DOI Creative Commons
María Cerezo, Elliot Sollis, Yue Ji

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 23, 2024

Abstract The NHGRI-EBI GWAS Catalog serves as a vital resource for the genetic research community, providing access to most comprehensive database of human results. Currently, it contains close 7,000 publications more than 15,000 traits, from which 625,000 lead associations have been curated. Additionally, 85,000 full genome-wide summary statistics datasets - containing association data all variants in analysis are available downstream analyses such meta-analysis, fine-mapping, Mendelian randomisation or development polygenic risk scores. As centralised repository results, sets and implements standards submission harmonisation, encourages use consistent descriptors samples methodologies. We share processes vocabulary with PGS Catalog, improving interoperability growing user group. Here, we describe latest changes content, improvements our interface, implementation GWAS-SSF standard format statistics. address challenges handling rapid increase large-scale molecular quantitative trait need sensitivity population cohort while maintaining reusability.

Language: Английский

Citations

1
Integer programming framework for pangenome-based genome inference DOI Creative Commons
Ghanshyam Chandra,

Md Helal Hossen,

Stephan Scholz

et al.

Published: Oct. 29, 2024

Abstract Affordable genotyping methods are essential in genomics. Commonly used primarily support single nucleotide variants and short indels but neglect structural variants. Additionally, accuracy of read alignments to a reference genome is unreliable highly polymorphic repetitive regions, further impacting performance. Recent works highlight the advantage haplotype-resolved pangenome graphs addressing these challenges. Building on developments, we propose rigorous alignment-free framework. Our formulation seeks path through graph that maximizes matches between substrings sequencing reads (e.g., k -mers) while minimizing recombination events (haplotype switches) along path. We prove this problem NP-Hard develop efficient integer-programming solutions. benchmarked algorithm using downsampled short-read datasets from homozygous human cell lines with coverage ranging 0.1× 10×. accurately estimates complete major histocompatibility complex (MHC) haplotype sequences small edit distances ground-truth sequences, providing significant over existing low-coverage inputs. Although our designed for haploid samples, discuss future extensions diploid samples. Implementation https://github.com/at-cg/PHI

Language: Английский

Citations

0