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Mark Yandell

Professor of Human Genetics and
Adjunct Associate Professor of Biomedical Informatics

Mark Yandell

B.S. University of Texas, Austin

Ph.D. University of Colorado, Boulder

Research

References

myandell@genetics.utah.edu

Mark Yandell's Website

Mark Yandell's PubMed Literature Search

Mark Yandell's Google Scholar Link

Molecular Biology Program

Bioinformatics and Comparative Genomics

Research

Sequenced genomes contain a treasure trove of information about how genes function and evolve. Getting at this information, however, is challenging and requires novel approaches that combine computer science and experimental molecular biology. My lab works at the intersection of both domains, and research in our group can be summarized as follows: generate hypotheses concerning gene function and evolution by computational means, and then test these hypotheses at the bench. This is easier said than done, as serious barriers still exist to using sequenced genomes and their annotations as starting points for experimental work.  Some of these barriers lie in the computational domain, others in the experimental. Though challenging, overcoming these barriers offers exciting training opportunities in both computer science and molecular genetics, especially for those seeking a future at the intersection of both fields. Ongoing projects in the lab are centered on genome annotation and comparative genomics. New areas of inquiry include high-throughput biological image analysis, and exploring the relationships between sequence variation and human disease.

Genome annotation

One of the great ironies of the DNA sequencing revolution is that genome annotation, not genome sequencing, has become the bottleneck in genomics today. New genomes are being sequenced at a far faster rate than they are being annotated. As of 2007, there are nearly 700 eukaryotic genomes in the sequencing pipeline. Many of these genomes are associated with relatively small research communities who are finding themselves left in the lurch when it comes to annotating their genomes.

Over the past year my lab has been working on an easy-to-use genome annotation pipeline called MAKER. Our goal is to provide research communities without extensive bioinformatics expertise the means to independently annotate their genomes and to distribute the results to the larger biomedical community.  For proof of principle, we have collaborated with the S. mediterranea genome project lead by Prof. Alejandro Sánchez Alvarado, Dept. of Neurobiology & Anatomy, University of Utah School of Medicine. To date, our successful annotation of this genome has produced three papers—one describing MAKER, one describing the genome database that we constructed from MAKER's outputs, and another paper describing the our analyses of the S. mediterranea genome and its contents. The first two papers are now in press at Genome Research and Nucleic Acids Research respectively; the third is under review at Science. Going forward, we plan to use the S. mediterranea genome annotations for functional genomics screens. This work will provide many opportunities for research with both computational and experimental components.

High-throughput biological image analysis

The production and analysis large numbers of digital images is an emerging field of bioinformatics. High-throughput imaging screens typically involve placing living cells or embryos in 96 well plates, and then adding different RNAi constructs or small molecules to each well. An automated microscope is then used to capture the results as digital images. These screens combine computation, genomics and molecular biology in new ways—genome annotations are used to design RNAi constructs; cell-lines and embryos expressing various fluorescent markers must be constructed; and software must be written to process the results. My lab is currently engaged in active collaborations with other groups on campus working in this area, as there is a pressing need to develop image-processing pipelines to analyze the data these screens produce.

In 2006, I helped to organize an R21 large-equipment grant to purchase an automated confocal microscope for high-throughput image based screens. The application was successful, and the university has now acquired a BD Pathway Bioimager.  This instrument will provide a basic resource for university researchers carrying out high-throughput image-based screens.

In a continuation of my collaboration with the S. mediterranea genome project, Prof. Sánchez Alvarado and I are using the S. mediterranea genome annotations for a genome-wide, image-based RNAi screen for genes involved in cellular regeneration and wound healing. The Bioimager is essential equipment for this work. Our results to date demonstrate that S. mediterranea is an ideal organism for high-throughput image-based screening, in part because it is literally a flatworm. This fact allows us to circumvent some of the technological problems that limit the scope and power of image-based screens of (not so flat) D. melanogaster and C. elegans.

Sequence Variation and Human disease

The Utah Population database (UTPD) and associated phenotype & clinical data collected through the Utah Genetic Reference Project (UGRP) offer unique resources for human genomics research. Tying the clinical and phenotypic data contained within these databases to the genome and genome annotations, however, is a challenging task. My is lab interested in characterizing large-scale trends in the UTPD & UGRP data, both with respect to sequence variation and demographics; developing methods to identify cohorts for clinical studies; and the development of diagnostic devices for purposes of personalized medicine.

References

  1. Majoros WH, Holt C, Campbell MS, Ware D, Yandell M, Reddy TE (2018). Predicting Gene Structure Changes Resulting from Genetic Variants via Exon Definition Features.LID - 10.1093/bioinformatics/bty324 [doi]. (Epub ahead of print) Bioinformatics.

  2. Al-Agha AE, Ahmed IA, Nuebel E, Moriwaki M, Moore B, Peacock KA, Mosbruger T, Neklason DW, Jorde LB, Yandell M, Welt CK (2018). Primary Ovarian Insufficiency and Azoospermia in Carriers of a Homozygous PSMC3IP Stop Gain Mutation. J Clin Endocrinol Metab103(2), 555-563.

  3. Smith JJ, Timoshevskaya N, Ye C, Holt C, Keinath MC, Parker HJ, Cook ME, Hess JE, Narum SR, Lamanna F, Kaessmann H, Timoshevskiy VA, Waterbury CKM, Saraceno C, Wiedemann LM, Robb SMC, Baker C, Eichler EE, Hockman D, Sauka-Spengler T, Yandell M, Krumlauf R, Elgar G, Amemiya CT (2018). The sea lamprey germline genome provides insights into programmed genome rearrangement and vertebrate evolution. Nat Genet50(2), 270-277.

  4. Flygare S, Hernandez EJ, Phan L, Moore B, Li M, Fejes A, Hu H, Eilbeck K, Huff C, Jorde L, G Reese M, Yandell M (2018). The VAAST Variant Prioritizer (VVP): ultrafast, easy to use whole genome variant prioritization tool. BMC Bioinformatics19(1), 57.

  5. Holt C, Campbell M, Keays DA, Edelman N, Kapusta A, Maclary E, Domyan E, Suh A, Warren WC, Yandell M, Gilbert MTP, Shapiro MD (2018). Improved Genome Assembly and Annotation for the Rock Pigeon (Columba livia).LID - g3.300443.2017 [pii]LID - 10.1534/g3.117.300443 [doi]. (Epub ahead of print) G3 (Bethesda).

  6. Manuck TA, Watkins WS, Esplin MS, Biggio J, Bukowski R, Parry S, Zhan H, Huang H, Andrews W, Saade G, Sadovsky Y, Reddy UM, Ilekis J, Yandell M, Varner MW, Jorde LB (2018). Pharmacogenomics of 17-alpha hydroxyprogesterone caproate for recurrent preterm birth: a case-control study. BJOG125(3), 343-350.

  7. Yu Y, Hu H, Bohlender RJ, Hu F, Chen JS, Holt C, Fowler J, Guthery SL, Scheet P, Hildebrandt MA, Yandell M, Huff CD (2017). XPAT: a toolkit to conduct cross-platform association studies with heterogeneous sequencing datasets.LID - 10.1093/nar/gkx1280 [doi]. (Epub ahead of print) Nucleic Acids Res.

  8. Moriwaki M, Moore B, Mosbruger T, Neklason DW, Yandell M, Jorde LB, Welt CK (2017). POLR2C Mutations Are Associated With Primary Ovarian Insufficiency in Women. J Endocr Soc1(3), 162-173.

  9. Robinson SD, Li Q, Lu A, Bandyopadhyay PK, Yandell M, Olivera BM, Safavi-Hemami H (2017). The Venom Repertoire of Conus gloriamaris (Chemnitz, 1777), the Glory of the Sea.LID - E145 [pii]LID - 10.3390/md15050145 [doi]. Mar Drugs15(5).

  10. Neale DB, McGuire PE, Wheeler NC, Stevens KA, Crepeau MW, Cardeno C, Zimin AV, Puiu D, Pertea GM, Sezen UU, Casola C, Koralewski TE, Paul R, Gonzalez-Ibeas D, Zaman S, Cronn R, Yandell M, Holt C, Langley CH, Yorke JA, Salzberg SL, Wegrzyn JL (2017). The Douglas-Fir Genome Sequence Reveals Specialization of the Photosynthetic Apparatus in Pinaceae. G3 (Bethesda)7(9), 3157-3167.

  11. Li Q, Barghi N, Lu A, Fedosov AE, Bandyopadhyay PK, Lluisma AO, Concepcion GP, Yandell M, Olivera BM, Safavi-Hemami H (2017). Divergence of the Venom Exogene Repertoire in Two Sister Species of Turriconus. Genome Biol Evol9(9), 2211-2225.

  12. Schlaberg R, Ampofo K, Tardif KD, Stockmann C, Simmon KE, Hymas W, Flygare S, Kennedy B, Blaschke A, Eilbeck K, Yandell M, McCullers JA, Williams DJ, Edwards K, Arnold SR, Bramley A, Jain S, Pavia AT (2017). Human Bocavirus Capsid Messenger RNA Detection in Children With Pneumonia. J Infect Dis216(6), 688-696.

  13. Jin SC, Homsy J, Zaidi S, Lu Q, Morton S, DePalma SR, Zeng X, Qi H, Chang W, Sierant MC, Hung WC, Haider S, Zhang J, Knight J, Bjornson RD, Castaldi C, Tikhonoa IR, Bilguvar K, Mane SM, Sanders SJ, Mital S, Russell MW, Gaynor JW, Deanfield J, Giardini A, Porter GA Jr, Srivastava D, Lo CW, Shen Y, Watkins WS, Yandell M, Yost HJ, Tristani-Firouzi M, Newburger JW, Roberts AE, Kim R, Zhao H, Kaltman JR, Goldmuntz E, Chung WK, Seidman JG, Gelb BD, Seidman CE, Lifton RP, Brueckner M (2017). Contribution of rare inherited and de novo variants in 2,871 congenital heart disease probands. Nat Genet49(11), 1593-1601.

  14. Campbell M, Oakeson KF, Yandell M, Halpert JR, Dearing D (2016). The draft genome sequence and annotation of the desert woodrat Neotoma lepida. Genom Data9, 58-9.

  15. Robinson SD, Li Q, Bandyopadhyay PK, Gajewiak J, Yandell M, Papenfuss AT, Purcell AW, Norton RS, Safavi-Hemami H (2017). Hormone-like peptides in the venoms of marine cone snails. Gen Comp Endocrinol244, 11-18.

  16. Cone KR, Kronenberg ZN, Yandell M, Elde NC (2017). Emergence of a Viral RNA Polymerase Variant during Gene Copy Number Amplification Promotes Rapid Evolution of Vaccinia Virus.LID - e01428-16 [pii]LID - 10.1128/JVI.01428-16 [doi]. J Virol91(4).

  17. Majoros WH, Campbell MS, Holt C, DeNardo EK, Ware D, Allen AS, Yandell M, Reddy TE (2017). High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE. Bioinformatics33(10), 1437-1446.

  18. Schlaberg R, Queen K, Simmon K, Tardif K, Stockmann C, Flygare S, Kennedy B, Voelkerding K, Bramley A, Zhang J, Eilbeck K, Yandell M, Jain S, Pavia AT, Tong S, Ampofo K (2017). Viral Pathogen Detection by Metagenomics and Pan-Viral Group Polymerase Chain Reaction in Children With Pneumonia Lacking Identifiable Etiology. J Infect Dis215(9), 1407-1415.

  19. Mason CC, Khorashad JS, Tantravahi SK, Kelley TW, Zabriskie MS, Yan D, Pomicter AD, Reynolds KR, Eiring AM, Kronenberg Z, Sherman RL, Tyner JW, Dalley BK, Dao KH, Yandell M, Druker BJ, Gotlib J, OHare T, Deininger MW (2016). Age-related mutations and chronic myelomonocytic leukemia. Leukemia30(4), 906-13.

  20. Graf EH, Simmon KE, Tardif KD, Hymas W, Flygare S, Eilbeck K, Yandell M, Schlaberg R (2016). Unbiased Detection of Respiratory Viruses by Use of RNA Sequencing-Based Metagenomics: a Systematic Comparison to a Commercial PCR Panel. J Clin Microbiol54(4), 1000-7.

  21. Braasch I, Gehrke AR, Smith JJ, Kawasaki K, Manousaki T, Pasquier J, Amores A, Desvignes T, Batzel P, Catchen J, Berlin AM, Campbell MS, Barrell D, Martin KJ, Mulley JF, Ravi V, Lee AP, Nakamura T, Chalopin D, Fan S, Wcisel D, Canestro C, Sydes J, Beaudry FE, Sun Y, Hertel J, Beam MJ, Fasold M, Ishiyama M, Johnson J, Kehr S, Lara M, Letaw JH, Litman GW, Litman RT, Mikami M, Ota T, Saha NR, Williams L, Stadler PF, Wang H, Taylor JS, Fontenot Q, Ferrara A, Searle SM, Aken B, Yandell M, Schneider I, Yoder JA, Volff JN, Meyer A, Amemiya CT, Venkatesh B, Holland PW, Guiguen Y, Bobe J, Shubin NH, Di Palma F, Alfoldi J, Lindblad-Toh K, Postlethwait JH (2016). The spotted gar genome illuminates vertebrate evolution and facilitates human-teleost comparisons. Nat Genet48(4), 427-37.

  22. Safavi-Hemami H, Li Q, Jackson RL, Song AS, Boomsma W, Bandyopadhyay PK, Gruber CW, Purcell AW, Yandell M, Olivera BM, Ellgaard L (2016). Rapid expansion of the protein disulfide isomerase gene family facilitates the folding of venom peptides. Proc Natl Acad Sci U S A113(12), 3227-32.

  23. Domyan ET, Kronenberg Z, Infante CR, Vickrey AI, Stringham SA, Bruders R, Guernsey MW, Park S, Payne J, Beckstead RB, Kardon G, Menke DB, Yandell M, Shapiro MD (2016). Molecular shifts in limb identity underlie development of feathered feet in two domestic avian species. Elife5, e12115.

  24. Yandell MB, Zelik KE (2016). Preferred Barefoot Step Frequency is Influenced by Factors Beyond Minimizing Metabolic Rate. Sci Rep6, 23243.

  25. Barber MF, Kronenberg Z, Yandell M, Elde NC (2016). Antimicrobial Functions of Lactoferrin Promote Genetic Conflicts in Ancient Primates and Modern Humans. PLoS Genet12(5), e1006063.

  26. Flygare S, Simmon K, Miller C, Qiao Y, Kennedy B, Di Sera T, Graf EH, Tardif KD, Kapusta A, Rynearson S, Stockmann C, Queen K, Tong S, Voelkerding KV, Blaschke A, Byington CL, Jain S, Pavia A, Ampofo K, Eilbeck K, Marth G, Yandell M, Schlaberg R (2016). Taxonomer: an interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling. Genome Biol17(1), 111.

  27. Safavi-Hemami H, Lu A, Li Q, Fedosov AE, Biggs J, Showers Corneli P, Seger J, Yandell M, Olivera BM (2016). Venom Insulins of Cone Snails Diversify Rapidly and Track Prey Taxa. Mol Biol Evol33(11), 2924-2934.

  28. Hu H, Coon H, Li M, Yandell M, Huff CD (2016). VARPRISM: incorporating variant prioritization in tests of de novo mutation association. Genome Med8(1), 91.

  29. Manuck TA, Watkins S, Esplin MS, Parry S, Zhang H, Huang H, Biggio JR, Bukowski R, Saade G, Andrews W, Baldwin D, Sadovsky Y, Reddy U, Ilekis J, Varner MW, Yandell M, Jorde LB (2016). Genetic variation may influence response to 17-alpha hydroxyprogesterone caproate (17P) for recurrent preterm birth (PTB) prevention. Am J Obstet Gynecol214(1), S9-S10.

  30. Manuck TA, Watkins S, Eplin MS, Parry S, Zhang H, Huang H, Biggio JR, Bukowski R, Saade G, Andrews W, Baldwin D, Sadovsky Y, Reddy U, Ilekis J, Varner MW, Jorde LJ, Yandell M (01/01/2016). Gene set enrichment investigation of maternal exome variation in spontaneous preterm birth (SPTB). Am J Obstet Gynecol241(1), S142-S143. 

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Last Updated: 9/8/18