MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome

Wang, Julia; Al‐Ouran, Rami; Hu, Yanhui; Kim, Seon‐Young; Wan, Ying-Wooi; Wangler, Michael F.; Yamamoto, Shinya; Chao, Hsiao‐Tuan; Comjean, Aram; Mohr, Stephanie E.; Adams, Christopher J.; Adams, David R.; Alejandro, Mercedes E.; Allard, Patrick; Ashley, Euan A.; Azamian, Mahshid S.; Bacino, Carlos A.; Balasubramanyam, Ashok; Barseghyan, Hayk; Beggs, Alan H.; Bellen, Hugo J.; Bernstein, Jonathan A.; Bican, Anna; Bick, David; Birch, Camille L.; Boone, Braden; Briere, Lauren C.; Brown, Donna M.; Brush, Matthew; Burke, Elizabeth; Burrage, Lindsay C.; Chao, Katherine R.; Clark, Gary D.; Cogan, Joy D.; Cooper, Cynthia; Craigen, William J.; Davids, Mariska; Dayal, Jyoti G.; Dell’Angelica, Esteban C.; Dhar, Shweta U.; Dipple, Katrina M.; Donnell‐Fink, Laurel A.; Dorrani, Naghmeh; Dorset, Daniel C.; Draper, David D.; Dries, Annika M.; Eckstein, David J.; Emrick, Lisa; Eng, Christine M.; Esteves, Cecilia; Estwick, Tyra; Fisher, Paul G.; Frisby, Trevor S.; Frost, Kate; Gahl, William A.; Gartner, Valerie; Godfrey, Rena A.; Goheen, Mitchell; Golas, Gretchen; Goldstein, David B.; Gordon, Mary “Gracie” G.; Gould, Sarah E.; Gourdine, Jean-Philippe; Graham, Brett H.; Groden, Catherine; Gropman, Andrea; Hackbarth, Mary E.; Haendel, Melissa; Hamid, Rizwan; Hanchard, Neil A.; Handley, Lori H.; Hardee, Isabel; Herzog, Matthew; Holm, Ingrid A.; Howerton, Ellen M.; Jacob, Howard J.; Jain, Mahim; Jiang, Yong‐Hui; Johnston, Jean M.; Jones, Angela L.; Koehler, Alanna E.; Koeller, David M.; Kohane, Isaac S.; Kohler, Jennefer N.; Krasnewich, Donna M.; Krieg, Elizabeth L.; Krier, Joel B.; Kyle, Jennifer; Lalani, Seema R.; Latham, Lea; Latour, Yvonne L.; Lau, Chuen-Yen; Lazar, Jozef; Lee, Brendan; Lee, Hane; Lee, Paul R.; Levy, Shawn; Levy, Denise J.; Lewis, Richard A.; Liebendorfer, Adam; Lincoln, Sharyn A.; Loomis, Carson R.; Loscalzo, Joseph; Maas, Richard L.; Macnamara, Ellen; MacRae, Calum A.; Maduro, Valerie V.; Malicdan, May Christine V.; Mamounas, Laura A.; Manolio, Teri A.; Markello, Thomas C.; Mazur, Paul M.; McCarty, Alexandra J.; McConkie‐Rosell, Allyn; McCray, Alexa T.; Metz, Thomas O.; Might, Matthew; Moretti, Paolo; Mulvihill, John J.; Murphy, Jennifer L.; Muzny, Donna M.; Nehrebecky, Michele; Nelson, Stan F.; Newberry, J. Scott; Newman, John H.; Nicholas, Sarah K.; Novacic, Donna; Orange, Jordan S.; Pallais, J. Carl; Palmer, Christina G.S.; Papp, Jeanette C.; Peña, Loren; Phillips, John A.; Posey, Jennifer E.; Postlethwait, John H.; Potocki, Lorraine; Pusey, Barbara N.; Ramoni, Rachel; Robertson, Amy K.; Rodan, Lance H.; Rosenfeld, Jill A.; Sadozai, Sarah; Schaffer, Katherine; Schoch, Kelly; Schroeder, Molly C.; Scott, Daryl A.; Sharma, Prashant; Shashi, Vandana; Silverman, Edwin K.; Sinsheimer, Janet S.; Soldatos, Ariane; Spillmann, Rebecca C.; Splinter, Kimberly; Stoler, Joan M.; Stong, Nicholas; Strong, Kimberly A.; Sullivan, Jennifer; Sweetser, David A.; Thomas, Sara; Tifft, Cynthia J.; Tolman, Nathanial J.; Toro, Camilo; Tran, Alyssa A.; Valivullah, Zaheer; Vilain, Éric; Waggott, Daryl; Wahl, Colleen E.; Walley, Nicole M.; Walsh, Christopher A.; Warburton, Mike; Ward, Patricia A.; Waters, Katrina M.; Webb-Robertson, Bobbie-Jo M.; Weech, A. Ashley; Westerfield, Monte; Wheeler, Matthew T.; Wise, Anastasia L.; Wolfe, Lynne A.; Worthey, Elizabeth A.; Yang, Yaping; Yu, Guoyun; Zornio, Patricia A.; Perrimon, Norbert; Liu, Zhandong

doi:10.1016/j.ajhg.2017.04.010

Cited by 188 publications

(139 citation statements)

References 49 publications

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“…Toward this end, we used data from the Model Organism Aggregated Resources for Rare Variant Exploration (MARRVEL; Wang et al, 2017b) to examine the orthologs of the retina regulatorygenes we identified. As a group, the genes we assessed in this study were quite conserved across species, and the majority had clear orthologs in humans (101 of 102), zebrafish (85 of 102), fly (55 of 102), and worm (43 of 102) (Table S1).…”

Section: Resultsmentioning

confidence: 99%

Rapid and Integrative Discovery of Retina Regulatory Molecules

et al. 2018

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SUMMARY Retinal function relies on precisely organized neurons and synapses and a properly patterned vasculature to support them. Alterations in these features can result in vision loss. However, our understanding of retinal organization pathways remains incomplete because of a lack of methods to rapidly identify neuron and vasculature regulators in mammals. Here we developed a pipeline for the identification of neural and synaptic integrity genes by high-throughput retinal screening (INSiGHT) that analyzes candidate expression, vascular patterning, cellular organization, and synaptic arrangement. Using this system, we examined 102 mutant mouse lines and identified 16 unique retinal regulatory genes. Fifteen of these candidates are identified as novel retina regulators, and many (9 of 16) are associated with human neural diseases. These results expand the genetic landscape involved in retinal circuit organization and provide a road map for continued discovery of mammalian retinal regulators and disease-causing alleles.

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Section: Resultsmentioning

confidence: 99%

Rapid and Integrative Discovery of Retina Regulatory Molecules

et al. 2018

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“…Importantly, results obtained from CC2 (i.e. "hits" identified in the screen) can then be immediately linked to other CRISPR/Cas9 screen analysis tools such as GenomeCRISPR 36 , CRISPRTools 37 , as well as MARRVEL 38 . The latter approach allows the user to query the identified hits for their human disease relevance and functional annotation in model organisms, thus promoting functional prioritization.…”

Section: Discussionmentioning

confidence: 99%

CRISPRCloud2: A cloud-based platform for deconvolving CRISPR screen data

Jeong

Kim

Rousseaux

et al. 2018

Preprint

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The simplicity and cost-effectiveness of CRISPR technology have made high-throughput pooled screening approaches available to many. However, the large amount of sequencing data derived from these studies yields often unwieldy datasets requiring considerable bioinformatic resources to deconvolute data; a feature which is simply not accessible to many wet labs. To address these needs, we have developed a cloud-based webtool CRISPRCloud2 that provides a state-of-the-art accuracy in mapping short reads to CRISPR library, a powerful statistical test that aggregates information across multiple sgRNAs targeting the same gene, a user-friendly data visualization and query interface, as well as easy linking to other CRISPR tools and bioinformatics resources for target prioritization. CRISPRCloud2 is a one-stop shop for labs analyzing CRISPR screen data.

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“…Information such as known gene function, expression patterns, physical interactors, available reagents and publication records can be obtained through these websites. A newly developed integrative online resource called MARRVEL (Model organism Aggregated Resources for Rare Variant ExpLoration) [392,393] integrates DIOPT [387], Flybase[368] as well as additional human genomics [292,394–398] and model organisms databases [399–404] to help the users to perform a wide survey of the gene and variant of interest. These searches are important to confirm that the gene/variant of interest is worth investigating in depth prior to initiating the any experiments in model organisms.…”

Section: Using Drosophila To Study Rare Functional Variants In Genesmentioning

confidence: 99%

Integration of Drosophila and Human Genetics to Understand Notch Signaling Related Diseases

Salazar

Yamamoto

2018

Advances in Experimental Medicine and Biology

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Notch signaling research dates back to more than one hundred years, beginning with the identification of the Notch mutant in the fruit fly Drosophila melanogaster. Since then, research on Notch and related genes in flies has laid the foundation of what we now know as the Notch signaling pathway. In the 1990s, basic biological and biochemical studies of Notch signaling components in mammalian systems, as well as identification of rare mutations in Notch signaling pathway genes in human patients with rare Mendelian diseases or cancer, increased the significance of this pathway in human biology and medicine. In the 21st century, Drosophila and other genetic model organisms continue to play a leading role in understanding basic Notch biology. Furthermore, these model organisms can be used in a translational manner to study underlying mechanisms of Notch-related human diseases and to investigate the function of novel disease associated genes and variants. In this chapter, we first briefly review the major contributions of Drosophila to Notch signaling research, discussing the similarities and differences between the fly and human pathways. Next, we introduce several biological contexts in Drosophila in which Notch signaling has been extensively characterized. Finally, we discuss a number of genetic diseases caused by mutations in genes in the Notch signaling pathway in humans and we expand on how Drosophila can be used to study rare genetic variants associated with these and novel disorders. By combining modern genomics and state-of-the art technologies, Drosophila research is continuing to reveal exciting biology that sheds light onto mechanisms of disease.

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MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome

Cited by 188 publications

References 49 publications

Rapid and Integrative Discovery of Retina Regulatory Molecules

Rapid and Integrative Discovery of Retina Regulatory Molecules

CRISPRCloud2: A cloud-based platform for deconvolving CRISPR screen data

Integration of Drosophila and Human Genetics to Understand Notch Signaling Related Diseases

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