Jonathan A Shortt

Dr. Jonathan A Shortt

orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 July 2018 in Nature Communications
Verified
Journal Article
Open access
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GPGiulia I. M. Pasquesi
Giulia I. M. Pasquesi
RARichard H. Adams
Richard H. Adams
DCDaren C. Card
Daren C. Card
DSDrew R. Schield
Drew R. Schield
ACAndrew B. Corbin
Andrew B. Corbin
TCTodd A. Castoe
Todd A. Castoe
Broad paradigms of vertebrate genomic repeat element evolution have been largely shaped by analyses of mammalian and avian genomes. Here, based on analyses of genomes sequenced from over 60 squamate reptiles (lizards and snakes), we show that patterns of genomic repeat landscape evolution in squamates challenge such paradigms. Despite low variance in genome size, squamate genomes exhibit surprisingly high variation among species in abundance (ca. 25–73% of the genome) and composition of identifiable repeat elements. We also demonstrate that snake genomes have experienced microsatellite seeding by transposable elements at a scale unparalleled among eukaryotes, leading to some snake genomes containing the highest microsatellite content of any known eukaryote. Our analyses of transposable element evolution across squamates also suggest that lineage-specific variation in mechanisms of transposable element activity and silencing, rather than variation in species-specific demography, may play a dominant role in driving variation in repeat element landscapes across squamate phylogeny.

4 January 2024 in The American Journal of Human Genetics
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Journal Article
Open access
LWLaura K. Wiley
Laura K. Wiley
JSJonathan A Shortt
Jonathan A Shortt
EREmily R. Roberts
Emily R. Roberts
JLJan Lowery
Jan Lowery
EKElizabeth Kudron
Elizabeth Kudron
CGChristopher R. Gignoux
Christopher R. Gignoux
Precision medicine initiatives across the globe have led to a revolution of repositories linking large-scale genomic data with electronic health records, enabling genomic analyses across the entire phenome. Many of these initiatives focus solely on research insights, leading to limited direct benefit to patients. We describe the biobank at the Colorado Center for Personalized Medicine (CCPM Biobank) that was jointly developed by the University of Colorado Anschutz Medical Campus and UCHealth to serve as a unique, dual-purpose research and clinical resource accelerating personalized medicine. This living resource currently has more than 200,000 participants with ongoing recruitment. We highlight the clinical, laboratory, regulatory, and HIPAA-compliant informatics infrastructure along with our stakeholder engagement, consent, recontact, and participant engagement strategies. We characterize aspects of genetic and geographic diversity unique to the Rocky Mountain region, the primary catchment area for CCPM Biobank participants. We leverage linked health and demographic information of the CCPM Biobank participant population to demonstrate the utility of the CCPM Biobank to replicate complex trait associations in the first 33,674 genotyped individuals across multiple disease domains. Finally, we describe our current efforts toward return of clinical genetic test results, including high-impact pathogenic variants and pharmacogenetic information, and our broader goals as the CCPM Biobank continues to grow. Bringing clinical and research interests together fosters unique clinical and translational questions that can be addressed from the large EHR-linked CCPM Biobank resource within a HIPAA- and CLIA-certified environment.

28 January 2019 in Frontiers in Immunology
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Journal Article
Open access
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LLLaura A. Leaton
Laura A. Leaton
JSJonathan A Shortt
Jonathan A Shortt
KKKatherine M. Kichula
Katherine M. Kichula
STSudan Tao
Sudan Tao
NNNeda Nemat-Gorgani
Neda Nemat-Gorgani
PNPaul J. Norman
Paul J. Norman
Natural killer (NK) cell functions are modulated by polymorphic killer cell immunoglobulin-like receptors (KIR). Among 13 human KIR genes, which vary by presence and copy number, KIR3DL3 is ubiquitously present in every individual across diverse populations. No ligand or function is known for KIR3DL3, but limited knowledge of expression suggests involvement in reproduction, likely during placentation. With 157 human alleles, KIR3DL3 is also highly polymorphic and we show heterozygosity exceeds that of HLA-B in many populations. The external domains of catarrhine primate KIR3DL3 evolved as a conserved lineage distinct from other KIR. Accordingly, and in contrast to other KIR, we show the focus of natural selection does not correspond exclusively to known ligand binding sites. Instead, a strong signal for diversifying selection occurs in the D1 Ig domain at a site involved in receptor aggregation, which we show is polymorphic in humans worldwide, suggesting differential ability for receptor aggregation. Meanwhile in the cytoplasmic tail, the first of two inhibitory tyrosine motifs (ITIM) is conserved, whereas independent genomic events have mutated the second ITIM of KIR3DL3 alleles in all great apes. Together, these findings suggest that KIR3DL3 binds a conserved ligand, and a function requiring both receptor aggregation and inhibitory signal attenuation. In this model KIR3DL3 resembles other NK cell inhibitory receptors having only one ITIM, which interact with bivalent downstream signaling proteins through dimerization. Due to the extensive conservation across species, selection, and other unusual properties, we consider elucidating the ligand and function of KIR3DL3 to be a pressing question.

17 February 2020 in Mobile DNA
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Journal Article
Open access
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JSJonathan A Shortt
Jonathan A Shortt
RRRobert P. Ruggiero
Robert P. Ruggiero
CCCorey Cox
Corey Cox
AWAaron C. Wacholder
Aaron C. Wacholder
DPDavid D. Pollock
David D. Pollock
Background: Previously, 3% of the human genome has been annotated as simple sequence repeats (SSRs), similar to the proportion annotated as protein coding. The origin of much of the genome is not well annotated, however, and some of the unidentified regions are likely to be ancient SSR-derived regions not identified by current methods. The identification of these regions is complicated because SSRs appear to evolve through complex cycles of expansion and contraction, often interrupted by mutations that alter both the repeated motif and mutation rate. We applied an empirical, kmer-based, approach to identify genome regions that are likely derived from SSRs. Results: The sequences flanking annotated SSRs are enriched for similar sequences and for SSRs with similar motifs, suggesting that the evolutionary remains of SSR activity abound in regions near obvious SSRs. Using our previously described P-clouds approach, we identified ‘SSR-clouds’, groups of similar kmers (or ‘oligos’) that are enriched near a training set of unbroken SSR loci, and then used the SSR-clouds to detect likely SSR-derived regions throughout the genome. Conclusions: Our analysis indicates that the amount of likely SSR-derived sequence in the human genome is 6.77%, over twice as much as previous estimates, including millions of newly identified ancient SSR-derived loci. SSR-clouds identified poly-A sequences adjacent to transposable element termini in over 74% of the oldest class of Alu (roughly, AluJ), validating the sensitivity of the approach. Poly-A’s annotated by SSR-clouds also had a length distribution that was more consistent with their poly-A origins, with mean about 35 bp even in older Alus. This work demonstrates that the high sensitivity provided by SSR-Clouds improves the detection of SSR-derived regions and will enable deeper analysis of how decaying repeats contribute to genome structure.

20 January 2017 in PLOS Neglected Tropical Diseases
Verified
Journal Article
Open access
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JSJonathan A Shortt
Jonathan A Shortt
DCDaren C. Card
Daren C. Card
DSDrew R. Schield
Drew R. Schield
YLYang Liu
Yang Liu
BZBo Zhong
Bo Zhong
DPDavid D. Pollock
David D. Pollock
In areas where schistosomiasis control programs have been implemented, morbidity and prevalence have been greatly reduced. However, to sustain these reductions and move towards interruption of transmission, new tools for disease surveillance are needed. Genomic methods have the potential to help trace the sources of new infections, and allow us to monitor drug resistance. Large-scale genotyping efforts for schistosome species have been hindered by cost, limited numbers of established target loci, and the small amount of DNA obtained from miracidia, the life stage most readily acquired from humans. Here, we present a method using next generation sequencing to provide high-resolution genomic data from S. japonicum for population-based studies. We applied whole genome amplification followed by double digest restriction site associated DNA sequencing (ddRADseq) to individual S. japonicum miracidia preserved on Whatman FTA cards. We found that we could effectively and consistently survey hundreds of thousands of variants from 10,000 to 30,000 loci from archived miracidia as old as six years. An analysis of variation from eight miracidia obtained from three hosts in two villages in Sichuan showed clear population structuring by village and host even within this limited sample. This high-resolution sequencing approach yields three orders of magnitude more information than microsatellite genotyping methods that have been employed over the last decade, creating the potential to answer detailed questions about the sources of human infections and to monitor drug resistance. Costs per sample range from $50-$200, depending on the amount of sequence information desired, and we expect these costs can be reduced further given continued reductions in sequencing costs, improvement of protocols, and parallelization. This approach provides new promise for using modern genome-scale sampling to S. japonicum surveillance, and could be applied to other schistosome species and other parasitic helminthes. Schistosomiasis is a devastating tropical disease that affects more than 200 million people worldwide. Over the past several decades, transmission control strategies implemented in China have reduced the prevalence and morbidity of Schistosoma japonicum in many areas. Infections still persist, however, and it is therefore of great interest to determine the sources of recurring infections. Genetic analysis is a promising means to achieve this. Towards this aim, we conducted a pilot study to assess the feasibility of using high-throughput sequencing to assess the geographic distribution of schistosome genetic variants. Because DNA yields from miracidia, the most easily accessible life stage, are insufficient for high throughput sequencing, we first employed whole genome amplification to obtain sufficient quantities of DNA. We then employed a technique that reproducibly sequences the same fraction of a genome across numerous samples. We successfully sequenced 6-year old S. japonicum samples from Sichuan Province, China, easily and economically identifying tens of thousands of variable loci, a sufficient number to discriminate fine-scale population structure. Further population sampling will help answer important questions concerning the persistence of infections, the sources of new infections, and whether parasite populations have undergone incipient evolution of drug resistance.

8 September 2023 in The Journal of Clinical Endocrinology & Metabolism
Verified
Journal Article
Open access
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NPNikita Pozdeyev
Nikita Pozdeyev
MDManjiri Kiran Dighe
Manjiri Kiran Dighe
MBMartin Barrio
Martin Barrio
CRChristopher Raeburn
Christopher Raeburn
HSHarry A Smith
Harry A Smith
TCTrevor Cohen
Trevor Cohen
Context: Thyroid nodule ultrasound-based risk stratification schemas rely on the presence of high-risk sonographic features. However, some malignant thyroid nodules have benign appearance on thyroid ultrasound. New methods for thyroid nodule risk assessment are needed. Objective: We investigated polygenic risk score (PRS) accounting for inherited thyroid cancer risk combined with ultrasound-based analysis for improved thyroid nodule risk assessment. Methods: The convolutional neural network classifier was trained on thyroid ultrasound still images and cine clips from 621 thyroid nodules. Phenome-wide association study (PheWAS) and PRS PheWAS were used to optimize PRS for distinguishing benign and malignant nodules. PRS was evaluated in 73 346 participants in the Colorado Center for Personalized Medicine Biobank. Results: When the deep learning model output was combined with thyroid cancer PRS and genetic ancestry estimates, the area under the receiver operating characteristic curve (AUROC) of the benign vs malignant thyroid nodule classifier increased from 0.83 to 0.89 (DeLong, P value = .007). The combined deep learning and genetic classifier achieved a clinically relevant sensitivity of 0.95, 95% CI [0.88-0.99], specificity of 0.63 [0.55-0.70], and positive and negative predictive values of 0.47 [0.41-0.58] and 0.97 [0.92-0.99], respectively. AUROC improvement was consistent in European ancestry-stratified analysis (0.83 and 0.87 for deep learning and deep learning combined with PRS classifiers, respectively). Elevated PRS was associated with a greater risk of thyroid cancer structural disease recurrence (ordinal logistic regression, P value = .002). Conclusion: Augmenting ultrasound-based risk assessment with PRS improves diagnostic accuracy.