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Dive into the research topics where John P. Didion is active.

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Featured researches published by John P. Didion.


Nature Genetics | 2011

Subspecific origin and haplotype diversity in the laboratory mouse

Hyuna Yang; Jeremy R. Wang; John P. Didion; Ryan J. Buus; Timothy A. Bell; Catherine E. Welsh; Franãois Bonhomme; Alex Hon-Tsen Yu; Michael W. Nachman; Jaroslav Piálek; Priscilla K. Tucker; Pierre Boursot; Leonard McMillan; Gary A. Churchill; Fernando Pardo-Manuel de Villena

Here we provide a genome-wide, high-resolution map of the phylogenetic origin of the genome of most extant laboratory mouse inbred strains. Our analysis is based on the genotypes of wild-caught mice from three subspecies of Mus musculus. We show that classical laboratory strains are derived from a few fancy mice with limited haplotype diversity. Their genomes are overwhelmingly Mus musculus domesticus in origin, and the remainder is mostly of Japanese origin. We generated genome-wide haplotype maps based on identity by descent from fancy mice and show that classical inbred strains have limited and non-randomly distributed genetic diversity. In contrast, wild-derived laboratory strains represent a broad sampling of diversity within M. musculus. Intersubspecific introgression is pervasive in these strains, and contamination by laboratory stocks has played a role in this process. The subspecific origin, haplotype diversity and identity by descent maps can be visualized using the Mouse Phylogeny Viewer (see URLs).


Nature Communications | 2015

Coexistent ARID1A–PIK3CA mutations promote ovarian clear-cell tumorigenesis through pro-tumorigenic inflammatory cytokine signalling

Ronald L. Chandler; Jeffrey S. Damrauer; Jesse R. Raab; Jonathan C. Schisler; Matthew D. Wilkerson; John P. Didion; Joshua Starmer; Daniel W. Serber; Della Yee; Jessie Xiong; David B. Darr; Fernando Pardo-Manuel de Villena; William Y. Kim; Terry Magnuson

Ovarian clear-cell carcinoma (OCCC) is an aggressive form of ovarian cancer with high ARID1A mutation rates. Here we present a mutant mouse model of OCCC. We find that ARID1A inactivation is not sufficient for tumor formation, but requires concurrent activation of the phosphoinositide 3-kinase catalytic subunit, PIK3CA. Remarkably, the mice develop highly penetrant tumors with OCCC-like histopathology, culminating in hemorrhagic ascites and a median survival period of 7.5 weeks. Therapeutic treatment with the pan-PI3K inhibitor, BKM120, prolongs mouse survival by inhibiting tumor cell growth. Cross-species gene expression comparisons support a role for IL-6 inflammatory cytokine signaling in OCCC pathogenesis. We further show that ARID1A and PIK3CA mutations cooperate to promote tumor growth through sustained IL-6 overproduction. Our findings establish an epistatic relationship between SWI/SNF chromatin remodeling and PI3K pathway mutations in OCCC and demonstrate that these pathways converge on pro-tumorigenic cytokine signaling. We propose that ARID1A protects against inflammation-driven tumorigenesis.


Nature Genetics | 2015

Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance

James J. Crowley; Vasyl Zhabotynsky; Wei Sun; Shunping Huang; Isa Kemal Pakatci; Yunjung Kim; Jeremy R. Wang; Andrew P. Morgan; John D. Calaway; David L. Aylor; Zaining Yun; Timothy A. Bell; Ryan J. Buus; Mark Calaway; John P. Didion; Terry J. Gooch; Stephanie D. Hansen; Nashiya N. Robinson; Ginger D. Shaw; Jason S. Spence; Corey R. Quackenbush; Cordelia J. Barrick; Randal J. Nonneman; Kyungsu Kim; James Xenakis; Yuying Xie; William Valdar; Alan B. Lenarcic; Wei Wang; Catherine E. Welsh

Complex human traits are influenced by variation in regulatory DNA through mechanisms that are not fully understood. Because regulatory elements are conserved between humans and mice, a thorough annotation of cis regulatory variants in mice could aid in further characterizing these mechanisms. Here we provide a detailed portrait of mouse gene expression across multiple tissues in a three-way diallel. Greater than 80% of mouse genes have cis regulatory variation. Effects from these variants influence complex traits and usually extend to the human ortholog. Further, we estimate that at least one in every thousand SNPs creates a cis regulatory effect. We also observe two types of parent-of-origin effects, including classical imprinting and a new global allelic imbalance in expression favoring the paternal allele. We conclude that, as with humans, pervasive regulatory variation influences complex genetic traits in mice and provide a new resource toward understanding the genetic control of transcription in mammals.


BMC Genomics | 2012

Discovery of novel variants in genotyping arrays improves genotype retention and reduces ascertainment bias

John P. Didion; Hyuna Yang; Keith Sheppard; Chen-Ping Fu; Leonard McMillan; Fernando Pardo-Manuel de Villena; Gary A. Churchill

BackgroundHigh-density genotyping arrays that measure hybridization of genomic DNA fragments to allele-specific oligonucleotide probes are widely used to genotype single nucleotide polymorphisms (SNPs) in genetic studies, including human genome-wide association studies. Hybridization intensities are converted to genotype calls by clustering algorithms that assign each sample to a genotype class at each SNP. Data for SNP probes that do not conform to the expected pattern of clustering are often discarded, contributing to ascertainment bias and resulting in lost information - as much as 50% in a recent genome-wide association study in dogs.ResultsWe identified atypical patterns of hybridization intensities that were highly reproducible and demonstrated that these patterns represent genetic variants that were not accounted for in the design of the array platform. We characterized variable intensity oligonucleotide (VINO) probes that display such patterns and are found in all hybridization-based genotyping platforms, including those developed for human, dog, cattle, and mouse. When recognized and properly interpreted, VINOs recovered a substantial fraction of discarded probes and counteracted SNP ascertainment bias. We developed software (MouseDivGeno) that identifies VINOs and improves the accuracy of genotype calling. MouseDivGeno produced highly concordant genotype calls when compared with other methods but it uniquely identified more than 786000 VINOs in 351 mouse samples. We used whole-genome sequence from 14 mouse strains to confirm the presence of novel variants explaining 28000 VINOs in those strains. We also identified VINOs in human HapMap 3 samples, many of which were specific to an African population. Incorporating VINOs in phylogenetic analyses substantially improved the accuracy of a Mus species tree and local haplotype assignment in laboratory mouse strains.ConclusionThe problems of ascertainment bias and missing information due to genotyping errors are widely recognized as limiting factors in genetic studies. We have conducted the first formal analysis of the effect of novel variants on genotyping arrays, and we have shown that these variants account for a large portion of miscalled and uncalled genotypes. Genetic studies will benefit from substantial improvements in the accuracy of their results by incorporating VINOs in their analyses.


Mammalian Genome | 2013

Deconstructing Mus gemischus: advances in understanding ancestry, structure, and variation in the genome of the laboratory mouse

John P. Didion; Fernando Pardo-Manuel de Villena

The laboratory mouse is an artificial construct with a complex relationship to its natural ancestors. In 2002, the mouse became the first mammalian model organism with a reference genome. Importantly, the mouse genome sequence was assembled from data on a single inbred laboratory strain, C57BL/6. Several large-scale genetic variant discovery efforts have been conducted, resulting in a catalog of tens of millions of SNPs and structural variants. High-density genotyping arrays covering a subset of those variants have been used to produce hundreds of millions of genotypes in laboratory stocks and a small number of wild mice. These landmark resources now enable us to determine relationships among laboratory mice, assign local ancestry at fine scale, resolve important controversies, and identify a new set of challenges—most importantly, the troubling scarcity of genetic data on the very natural populations from which the laboratory mouse was derived. Our aim with this review is to provide the reader with an historical context for the mouse as a model organism and to explain how practical decisions made in the past have influenced both the architecture of the laboratory mouse genome and the design and execution of current large-scale resources. We also provide examples on how the accomplishments of the past decade can be used by researchers to streamline the use of mice in their experiments and correctly interpret results. Finally, we propose future steps that will enable the mouse community to extend its successes in the decade to come.


G3: Genes, Genomes, Genetics | 2016

The Mouse Universal Genotyping Array: From Substrains to Subspecies

Andrew P. Morgan; Chen Ping Fu; Chia Yu Kao; Catherine E. Welsh; John P. Didion; Liran Yadgary; Leeanna Hyacinth; Martin T. Ferris; Timothy A. Bell; Darla R. Miller; Paola Giusti-Rodriguez; Randal J. Nonneman; Kevin D. Cook; Jason K. Whitmire; Lisa E. Gralinski; Mark P. Keller; Alan D. Attie; Gary A. Churchill; Petko M. Petkov; Patrick F. Sullivan; J. Brennan; Leonard McMillan; Fernando Pardo-Manuel de Villena

Genotyping microarrays are an important resource for genetic mapping, population genetics, and monitoring of the genetic integrity of laboratory stocks. We have developed the third generation of the Mouse Universal Genotyping Array (MUGA) series, GigaMUGA, a 143,259-probe Illumina Infinium II array for the house mouse (Mus musculus). The bulk of the content of GigaMUGA is optimized for genetic mapping in the Collaborative Cross and Diversity Outbred populations, and for substrain-level identification of laboratory mice. In addition to 141,090 single nucleotide polymorphism probes, GigaMUGA contains 2006 probes for copy number concentrated in structurally polymorphic regions of the mouse genome. The performance of the array is characterized in a set of 500 high-quality reference samples spanning laboratory inbred strains, recombinant inbred lines, outbred stocks, and wild-caught mice. GigaMUGA is highly informative across a wide range of genetically diverse samples, from laboratory substrains to other Mus species. In addition to describing the content and performance of the array, we provide detailed probe-level annotation and recommendations for quality control.


Nature Communications | 2016

The genetic regulatory signature of type 2 diabetes in human skeletal muscle

Laura J. Scott; Michael R. Erdos; Jeroen R. Huyghe; Ryan P. Welch; Andrew T. Beck; Brooke N. Wolford; Peter S. Chines; John P. Didion; Heather M. Stringham; D. Leland Taylor; Anne U. Jackson; Swarooparani Vadlamudi; Lori L. Bonnycastle; Leena Kinnunen; Jouko Saramies; Jouko Sundvall; Ricardo D'Oliveira Albanus; Anna Kiseleva; John Hensley; Gregory E. Crawford; Hui Jiang; Xiaoquan Wen; Richard M. Watanabe; Timo A. Lakka; Karen L. Mohlke; Markku Laakso; Jaakko Tuomilehto; Heikki A. Koistinen; Michael Boehnke; Francis S. Collins

Type 2 diabetes (T2D) results from the combined effects of genetic and environmental factors on multiple tissues over time. Of the >100 variants associated with T2D and related traits in genome-wide association studies (GWAS), >90% occur in non-coding regions, suggesting a strong regulatory component to T2D risk. Here to understand how T2D status, metabolic traits and genetic variation influence gene expression, we analyse skeletal muscle biopsies from 271 well-phenotyped Finnish participants with glucose tolerance ranging from normal to newly diagnosed T2D. We perform high-depth strand-specific mRNA-sequencing and dense genotyping. Computational integration of these data with epigenome data, including ATAC-seq on skeletal muscle, and transcriptome data across diverse tissues reveals that the tissue-specific genetic regulatory architecture of skeletal muscle is highly enriched in muscle stretch/super enhancers, including some that overlap T2D GWAS variants. In one such example, T2D risk alleles residing in a muscle stretch/super enhancer are linked to increased expression and alternative splicing of muscle-specific isoforms of ANK1.


Proceedings of the National Academy of Sciences of the United States of America | 2017

Genetic regulatory signatures underlying islet gene expression and type 2 diabetes.

Arushi Varshney; Laura J. Scott; Ryan P. Welch; Michael R. Erdos; Peter S. Chines; Ricardo D'Oliveira Albanus; Peter Orchard; Brooke N. Wolford; Romy Kursawe; Swarooparani Vadlamudi; Maren E. Cannon; John P. Didion; John Hensley; Anthony Kirilusha; Lori L. Bonnycastle; D. Leland Taylor; Richard M. Watanabe; Karen L. Mohlke; Michael Boehnke; Francis S. Collins; Stephen C. J. Parker; Michael L. Stitzel

Significance The majority of genetic variants associated with type 2 diabetes (T2D) are located outside of genes in noncoding regions that may regulate gene expression in disease-relevant tissues, like pancreatic islets. Here, we present the largest integrated analysis to date of high-resolution, high-throughput human islet molecular profiling data to characterize the genome (DNA), epigenome (DNA packaging), and transcriptome (gene expression). We find that T2D genetic variants are enriched in regions of the genome where transcription Regulatory Factor X (RFX) is predicted to bind in an islet-specific manner. Genetic variants that increase T2D risk are predicted to disrupt RFX binding, providing a molecular mechanism to explain how the genome can influence the epigenome, modulating gene expression and ultimately T2D risk. Genome-wide association studies (GWAS) have identified >100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition.


PLOS Genetics | 2015

A Multi-Megabase Copy Number Gain Causes Maternal Transmission Ratio Distortion on Mouse Chromosome 2

John P. Didion; Andrew P. Morgan; Amelia M.-F. Clayshulte; Rachel C. McMullan; Liran Yadgary; Petko M. Petkov; Timothy A. Bell; Daniel M. Gatti; James J. Crowley; Kunjie Hua; David L. Aylor; Ling Bai; Mark Calaway; Elissa J. Chesler; John E. French; Thomas R. Geiger; Terry J. Gooch; Theodore Garland; Alison H. Harrill; Kent W. Hunter; Leonard McMillan; Matt Holt; Darla R. Miller; Deborah A. O'Brien; Kenneth Paigen; Wenqi Pan; Lucy B. Rowe; Ginger D. Shaw; Petr Simecek; Patrick F. Sullivan

Significant departures from expected Mendelian inheritance ratios (transmission ratio distortion, TRD) are frequently observed in both experimental crosses and natural populations. TRD on mouse Chromosome (Chr) 2 has been reported in multiple experimental crosses, including the Collaborative Cross (CC). Among the eight CC founder inbred strains, we found that Chr 2 TRD was exclusive to females that were heterozygous for the WSB/EiJ allele within a 9.3 Mb region (Chr 2 76.9 – 86.2 Mb). A copy number gain of a 127 kb-long DNA segment (designated as responder to drive, R2d) emerged as the strongest candidate for the causative allele. We mapped R2d sequences to two loci within the candidate interval. R2d1 is located near the proximal boundary, and contains a single copy of R2d in all strains tested. R2d2 maps to a 900 kb interval, and the number of R2d copies varies from zero in classical strains (including the mouse reference genome) to more than 30 in wild-derived strains. Using real-time PCR assays for the copy number, we identified a mutation (R2d2WSBdel1) that eliminates the majority of the R2d2WSB copies without apparent alterations of the surrounding WSB/EiJ haplotype. In a three-generation pedigree segregating for R2d2WSBdel1, the mutation is transmitted to the progeny and Mendelian segregation is restored in females heterozygous for R2d2WSBdel1, thus providing direct evidence that the copy number gain is causal for maternal TRD. We found that transmission ratios in R2d2WSB heterozygous females vary between Mendelian segregation and complete distortion depending on the genetic background, and that TRD is under genetic control of unlinked distorter loci. Although the R2d2WSB transmission ratio was inversely correlated with average litter size, several independent lines of evidence support the contention that female meiotic drive is the cause of the distortion. We discuss the implications and potential applications of this novel meiotic drive system.


PLOS Genetics | 2013

Genetic Architecture of Skewed X Inactivation in the Laboratory Mouse

John D. Calaway; Alan B. Lenarcic; John P. Didion; Jeremy R. Wang; Jeremy B. Searle; Leonard McMillan; William Valdar; Fernando Pardo-Manuel de Villena

X chromosome inactivation (XCI) is the mammalian mechanism of dosage compensation that balances X-linked gene expression between the sexes. Early during female development, each cell of the embryo proper independently inactivates one of its two parental X-chromosomes. In mice, the choice of which X chromosome is inactivated is affected by the genotype of a cis-acting locus, the X-chromosome controlling element (Xce). Xce has been localized to a 1.9 Mb interval within the X-inactivation center (Xic), yet its molecular identity and mechanism of action remain unknown. We combined genotype and sequence data for mouse stocks with detailed phenotyping of ten inbred strains and with the development of a statistical model that incorporates phenotyping data from multiple sources to disentangle sources of XCI phenotypic variance in natural female populations on X inactivation. We have reduced the Xce candidate 10-fold to a 176 kb region located approximately 500 kb proximal to Xist. We propose that structural variation in this interval explains the presence of multiple functional Xce alleles in the genus Mus. We have identified a new allele, Xcee present in Mus musculus and a possible sixth functional allele in Mus spicilegus. We have also confirmed a parent-of-origin effect on X inactivation choice and provide evidence that maternal inheritance magnifies the skewing associated with strong Xce alleles. Based on the phylogenetic analysis of 155 laboratory strains and wild mice we conclude that Xcea is either a derived allele that arose concurrently with the domestication of fancy mice but prior the derivation of most classical inbred strains or a rare allele in the wild. Furthermore, we have found that despite the presence of multiple haplotypes in the wild Mus musculus domesticus has only one functional Xce allele, Xceb. Lastly, we conclude that each mouse taxa examined has a different functional Xce allele.

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Andrew P. Morgan

University of North Carolina at Chapel Hill

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Timothy A. Bell

University of North Carolina at Chapel Hill

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Fernando Pardo-Manuel de Villena

University of North Carolina at Chapel Hill

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Leonard McMillan

University of North Carolina at Chapel Hill

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James J. Crowley

University of North Carolina at Chapel Hill

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Liran Yadgary

University of North Carolina at Chapel Hill

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David L. Aylor

North Carolina State University

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Elissa J. Chesler

University of Tennessee Health Science Center

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Rachel C. McMullan

University of North Carolina at Chapel Hill

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Daniel M. Gatti

University of North Carolina at Chapel Hill

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