Polymorphic Inversions Underlie the Shared Genetic Susceptibility of Obesity-Related Diseases

González, Juan R.; Ruiz‐Arenas, Carlos; Cáceres, Alejandro; Morán, Ignasi; López-Sánchez, Marcos; Alonso, Lorena; Tolosana, Ignacio; Guindo-Martínez, Marta; Mercader, Josep M.; Esko, Tõnu; Torrents, David; González, Josefa; Pérez-Jurado, Luís A.

doi:10.1016/j.ajhg.2020.04.017

Cited by 17 publications

(24 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The 17q21.31 inversion stands out for its pleiotropic phenotypic effects and it has been involved in an increasing number of diverse traits [ 12 , 14 , 19 , 20 , 28 , 29 ]. To update and understand better these effects, we have done an exhaustive analysis and manual curation of the GWAS hits ( p < 5 × 10 −8 ) corresponding to all SNPs in high LD ( r 2 > 0.8) with the inversion listed in the GWAS Catalog [ 30 ] (summarized together with their supporting studies in the electronic supplementary material, table S2).…”

Section: The 17q2131 Inversionmentioning

confidence: 99%

“…Moreover, the presence of the inversion has been associated with neuroticism [ 62 ] and several risky behaviour traits [ 63 ]. However, it has been related to a reduction of different metabolic risk factors, such as hypertension, obesity and the co-occurrence of diabetes, hypertension or asthma with obesity, and to an increase of triglyceride levels [ 28 , 58 ].…”

Section: The 8p231 Inversionmentioning

confidence: 99%

“…With regard to gene expression, previous studies have suggested that the 8p23.1 inversion influences the expression of more than 20 genes [ 18 , 28 , 62 , 64 ]. Apart from one spanning multiple tissues [ 28 ], most analysis were done in blood-derived cells, and consistent expression differences were found for BLK, NEIL2, MSRA, CTSB, FDFT1, MFHAS1, MTMR9, FAM167A and PPP1R3B .…”

Section: The 8p231 Inversionmentioning

confidence: 99%

See 2 more Smart Citations

Genomic architecture and functional effects of potential human inversion supergenes

Campoy

Puig

Yakymenko

et al. 2022

Phil. Trans. R. Soc. B

View full text Add to dashboard Cite

Supergenes are involved in adaptation in multiple organisms, but they are little known in humans. Genomic inversions are the most common mechanism of supergene generation and maintenance. Here, we review the information about two large inversions that are the best examples of potential human supergenes. In addition, we do an integrative analysis of the newest data to understand better their functional effects and underlying genetic changes. We have found that the highly divergent haplotypes of the 17q21.31 inversion of approximately 1.5 Mb have multiple phenotypic associations, with consistent effects in brain-related traits, red and white blood cells, lung function, male and female characteristics and disease risk. By combining gene expression and nucleotide variation data, we also analysed the molecular differences between haplotypes, including gene duplications, amino acid substitutions and regulatory changes, and identify CRHR1, KANLS1 and MAPT as good candidates to be responsible for these phenotypes. The situation is more complex for the 8p23.1 inversion, where there is no clear genetic differentiation. However, the inversion is associated with several related phenotypes and gene expression differences that could be linked to haplotypes specific of one orientation. Our work, therefore, contributes to the characterization of both exceptional variants and illustrates the important role of inversions. This article is part of the theme issue ‘Genomic architecture of supergenes: causes and evolutionary consequences’.

show abstract

Section: The 17q2131 Inversionmentioning

confidence: 99%

Section: The 8p231 Inversionmentioning

confidence: 99%

Section: The 8p231 Inversionmentioning

confidence: 99%

See 1 more Smart Citation

Genomic architecture and functional effects of potential human inversion supergenes

Campoy

Puig

Yakymenko

et al. 2022

Phil. Trans. R. Soc. B

View full text Add to dashboard Cite

show abstract

“…Relevant findings of mosaic detection include their contribution to Autism Spectrum Disorder risk [ 242 ], predisposition to infections [ 243 ] and clonal hematopoiesis [ 143 ]. Recent applications on the detection of inversions, included the genotyping of 20 inversions with scoreInvHap to study their role in obesity-related diseases [ 244 ], while a similar study in admixed population in Brazil used invClust [ 245 ].…”

Section: Recent Studies Applying Inference Methods Of Snp Datamentioning

confidence: 99%

Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure

Balagué-Dobón

Cáceres

González

2022

Briefings in Bioinformatics

Self Cite

View full text Add to dashboard Cite

Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.

show abstract

“…Despite these advances, a large fraction of the genetic variability underlying complex diseases still remains unexplored, as studies have been mostly restricted to single nucleotide variants (SNVs) and small insertions and deletions (indels) (<50bp). Large structural variants (SVs) are known to play an important role in disease [4][5][6][7] and could actually explain part of the well-known missing heritability paradox 8,9 . However, the technical and methodological challenges associated with the identification and classification of this type of variation from whole-genome sequences (WGS) have left this type of variation out from GWASs.…”

Section: Introductionmentioning

confidence: 99%

GCAT|Panel, a comprehensive structural variant haplotype map of the Iberian population from high-coverage whole-genome sequencing

Valls-Margarit

Galván-Femenía

Matías-Sánchez

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

The combined analysis of haplotype panels with phenotype clinical cohorts is a common approach to explore the genetic architecture of human diseases. However, genetic studies are mainly based on single nucleotide variants (SNVs) and small insertions and deletions (indels). Here, we contribute to fill this gap by generating a dense haplotype map focused on the identification, characterization and phasing of structural variants (SVs). By integrating multiple variant identification methods and Logistic Regression models, we present a catalogue of 35,431,441 variants, including 89,178 SVs (≥50bp), 30,325,064 SNVs and 5,017,199 indels, across 785 Illumina high coverage (30X) whole-genomes from the Iberian GCAT Cohort, containing 3.52M SNVs, 606,336 indels and 6,393 SVs in median per individual. The haplotype panel is able to impute up to 14,360,728 SNVs/indels and 23,179 SVs, showing a 2.7-fold increase for SVs compared with available genetic variation panels. The value of this panel for SVs analysis is shown through an imputed rare Alu element located in a new locus associated with mononeuritis of lower limb, a rare neuromuscular disease. This study represents the first deep characterization of genetic variation within the Iberian population and the first operational haplotype panel to systematically include the SVs into genome-wide genetic studies.

show abstract

Polymorphic Inversions Underlie the Shared Genetic Susceptibility of Obesity-Related Diseases

Cited by 17 publications

References 51 publications

Genomic architecture and functional effects of potential human inversion supergenes

Genomic architecture and functional effects of potential human inversion supergenes

Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure

GCAT|Panel, a comprehensive structural variant haplotype map of the Iberian population from high-coverage whole-genome sequencing

Contact Info

Product

Resources

About