RNAi validation

2022
Shue Chen, Leah F Rosin, Gianluca Pegoraro, Nellie Moshkovich, Patrick J Murphy, Guoyun Yu, and Elissa P Lei. 8/12/2022. “NURF301 contributes to gypsy chromatin insulator-mediated nuclear organization.” Nucleic Acids Res, 50, 14, Pp. 7906-7924.Abstract
Chromatin insulators are DNA-protein complexes that can prevent the spread of repressive chromatin and block communication between enhancers and promoters to regulate gene expression. In Drosophila, the gypsy chromatin insulator complex consists of three core proteins: CP190, Su(Hw), and Mod(mdg4)67.2. These factors concentrate at nuclear foci termed insulator bodies, and changes in insulator body localization have been observed in mutants defective for insulator function. Here, we identified NURF301/E(bx), a nucleosome remodeling factor, as a novel regulator of gypsy insulator body localization through a high-throughput RNAi imaging screen. NURF301 promotes gypsy-dependent insulator barrier activity and physically interacts with gypsy insulator proteins. Using ChIP-seq, we found that NURF301 co-localizes with insulator proteins genome-wide, and NURF301 promotes chromatin association of Su(Hw) and CP190 at gypsy insulator binding sites. These effects correlate with NURF301-dependent nucleosome repositioning. At the same time, CP190 and Su(Hw) both facilitate recruitment of NURF301 to chromatin. Finally, Oligopaint FISH combined with immunofluorescence revealed that NURF301 promotes 3D contact between insulator bodies and gypsy insulator DNA binding sites, and NURF301 is required for proper nuclear positioning of gypsy binding sites. Our data provide new insights into how a nucleosome remodeling factor and insulator proteins cooperatively contribute to nuclear organization.
gkac600.pdf
2021
Jiunn Song, Arda Mizrak, Chia-Wei Lee, Marcelo Cicconet, Zon Weng Lai, Chieh-Han Lu, Stephanie E. Mohr, Jr Robert V. Farese, and Tobias C. Walther. 9/15/2021. “Identification of two pathways mediating protein targeting from ER to lipid droplets [NOTE: a modified final version was published in Nat Cell Biol and is now available]”. Publisher's VersionAbstract
Pathways localizing proteins to their sites of action within a cell are essential for eukaryotic cell organization and function. Although mechanisms of protein targeting to many organelles have been defined, little is known about how proteins, such as key metabolic enzymes, target from the ER to cellular lipid droplets (LDs). Here, we identify two distinct pathways for ER-to-LD (ERTOLD) protein targeting: early ERTOLD, occurring during LD formation, and late ERTOLD, targeting mature LDs after their formation. By using systematic, unbiased approaches, we identified specific membrane-fusion machinery, including regulators, a tether, and SNARE proteins, that are required for late ERTOLD targeting. Components of this fusion machinery localize to LD-ER interfaces and appear to be organized at ER exit sites (ERES) to generate ER-LD membrane bridges. We also identified multiple cargoes for early and late ERTOLD. Collectively, our data provide a new model for how proteins target LDs from the ER.
2021.09.14.460330v1.full_.pdf
Xiangzhao Yue, Yongkang Liang, Zhishuang Wei, Jun Lv, Yongjin Cai, Xiaobin Fan, Wenqing Zhang, and Jie Chen. 2021. “Genome-wide in vitro and in vivo RNAi screens reveal Fer3 to be an important regulator of kkv transcription in Drosophila.” Insect Sci.Abstract
Krotzkopf verkehrt (kkv) is a key enzyme that catalyzes the synthesis of chitin, an important component of the Drosophila epidermis, trachea, and other tissues. Here, we report the use of comprehensive RNA interference (RNAi) analyses to search for kkv transcriptional regulators. A cell-based RNAi screen identified 537 candidate kkv regulators on a genome-wide scale. Subsequent use of transgenic Drosophila lines expressing RNAi constructs enabled in vivo validation, and we identified six genes as potential kkv transcriptional regulators. Weakening of the kkvDsRed signal, an in vivo reporter indicating kkv promoter activity, was observed when the expression of Akirin, NFAT, 48 related 3 (Fer3), or Autophagy-related 101(Atg101) was knocked down in Drosophila at the 3rd-instar larval stage; whereas we observed disoriented taenidial folds on larval tracheae when Lines (lin) or Autophagy-related 3(Atg3) was knocked down in the tracheae. Fer3, in particular, has been shown to be an important factor in the activation of kkv transcription via specific binding with the kkv promoter. The genes involved in the chitin synthesis pathway were widely affected by the downregulation of Fer3. Furthermore, Atg101, Atg3, Akirin, Lin, NFAT, Pnr and Abd-A showed the potential complex mechanism of kkv transcription are regulated by an interaction network with bithorax complex components. Our study revealed the hitherto unappreciated diversity of modulators impinging on kkv transcription and opens new avenues in the study of kkv regulation and chitin biosynthesis. This article is protected by copyright. All rights reserved.
2020
Yanhui Hu, Aram Comjean, Jonathan Rodiger, Yifang Liu, Yue Gao, Verena Chung, Jonathan Zirin, Norbert Perrimon, and Stephanie E Mohr. 2020. “FlyRNAi.org-the database of the Drosophila RNAi screening center and transgenic RNAi project: 2021 update.” Nucleic Acids Res.Abstract
The FlyRNAi database at the Drosophila RNAi Screening Center and Transgenic RNAi Project (DRSC/TRiP) provides a suite of online resources that facilitate functional genomics studies with a special emphasis on Drosophila melanogaster. Currently, the database provides: gene-centric resources that facilitate ortholog mapping and mining of information about orthologs in common genetic model species; reagent-centric resources that help researchers identify RNAi and CRISPR sgRNA reagents or designs; and data-centric resources that facilitate visualization and mining of transcriptomics data, protein modification data, protein interactions, and more. Here, we discuss updated and new features that help biological and biomedical researchers efficiently identify, visualize, analyze, and integrate information and data for Drosophila and other species. Together, these resources facilitate multiple steps in functional genomics workflows, from building gene and reagent lists to management, analysis, and integration of data.
gkaa936.pdf
2019
Spencer E. Escobedo, Jonathan Zirin, and Vikki M. Weake. 4/4/2019. “TRiP stocks contain a previously uncharacterized loss-of-function sevenless allele.” microPublication Biology. Publisher's Version escobedotripsev_lof_2019_final.pdf
2016
Benjamin E Housden, Matthias Muhar, Matthew Gemberling, Charles A Gersbach, Didier YR Stainier, Geraldine Seydoux, Stephanie E Mohr, Johannes Zuber, and Norbert Perrimon. 10/31/2016. “Loss-of-function genetic tools for animal models: cross-species and cross-platform differences.” Nat Rev Genet. Publisher's VersionAbstract

Our understanding of the genetic mechanisms that underlie biological processes has relied extensively on loss-of-function (LOF) analyses. LOF methods target DNA, RNA or protein to reduce or to ablate gene function. By analysing the phenotypes that are caused by these perturbations the wild-type function of genes can be elucidated. Although all LOF methods reduce gene activity, the choice of approach (for example, mutagenesis, CRISPR-based gene editing, RNA interference, morpholinos or pharmacological inhibition) can have a major effect on phenotypic outcomes. Interpretation of the LOF phenotype must take into account the biological process that is targeted by each method. The practicality and efficiency of LOF methods also vary considerably between model systems. We describe parameters for choosing the optimal combination of method and system, and for interpreting phenotypes within the constraints of each method.

2016_Nat Rev Gene_Housden.pdf
Yanhui Hu, Aram Comjean, Charles Roesel, Arunachalam Vinayagam, Ian Flockhart, Jonathan Zirin, Lizabeth Perkins, Norbert Perrimon, and Stephanie E Mohr. 10/11/2016. “FlyRNAi.org—the database of the Drosophila RNAi screening center and transgenic RNAi project: 2017 update.” Nucleic Acids Research. Publisher's VersionAbstract

The FlyRNAi database of the Drosophila RNAi Screening Center (DRSC) and Transgenic RNAi Project (TRiP) at Harvard Medical School and associated DRSC/TRiP Functional Genomics Resources website (http://fgr.hms.harvard.edu) serve as a reagent production tracking system, screen data repository, and portal to the community. Through this portal, we make available protocols, online tools, and other resources useful to researchers at all stages of high-throughput functional genomics screening, from assay design and reagent identification to data analysis and interpretation. In this update, we describe recent changes and additions to our website, database and suite of online tools. Recent changes reflect a shift in our focus from a single technology (RNAi) and model species (Drosophila) to the application of additional technologies (e.g. CRISPR) and support of integrated, cross-species approaches to uncovering gene function using functional genomics and other approaches.

2016_Nucl Acids Res_Hu.pdf
Arunachalam Vinayagam, Meghana M Kulkarni, Richelle Sopko, Xiaoyun Sun, Yanhui Hu, Ankita Nand, Christians Villalta, Ahmadali Moghimi, Xuemei Yang, Stephanie E Mohr, Pengyu Hong, John M Asara, and Norbert Perrimon. 9/13/2016. “An Integrative Analysis of the InR/PI3K/Akt Network Identifies the Dynamic Response to Insulin Signaling.” Cell Reports, 16, 11, Pp. 3062-3074.Abstract

Insulin regulates an essential conserved signaling pathway affecting growth, proliferation, and meta- bolism. To expand our understanding of the insulin pathway, we combine biochemical, genetic, and computational approaches to build a comprehensive Drosophila InR/PI3K/Akt network. First, we map the dynamic protein-protein interaction network sur- rounding the insulin core pathway using bait-prey interactions connecting 566 proteins. Combining RNAi screening and phospho-specific antibodies, we find that 47% of interacting proteins affect pathway activity, and, using quantitative phospho- proteomics, we demonstrate that $10% of interact- ing proteins are regulated by insulin stimulation at the level of phosphorylation. Next, we integrate these orthogonal datasets to characterize the structure and dynamics of the insulin network at the level of protein complexes and validate our method by iden- tifying regulatory roles for the Protein Phosphatase 2A (PP2A) and Reptin-Pontin chromatin-remodeling complexes as negative and positive regulators of ribosome biogenesis, respectively. Altogether, our study represents a comprehensive resource for the study of the evolutionary conserved insulin network. 

2016_Cell Rep_Vinayagam.pdf Supplement.pdf
Chen X and Xu L. 2016. “Genome-Wide RNAi Screening to Dissect the TGF-β Signal Transduction Pathway.” Methods in Molecular Biology. Publisher's VersionAbstract

The transforming growth factor-β (TGF-β) family of cytokines figures prominently in regulation of embryonic development and adult tissue homeostasis from Drosophila to mammals. Genetic defects affecting TGF-β signaling underlie developmental disorders and diseases such as cancer in human. Therefore, delineating the molecular mechanism by which TGF-β regulates cell biology is critical for understanding normal biology and disease mechanisms. Forward genetic screens in model organisms and biochemical approaches in mammalian tissue culture were instrumental in initial characterization of the TGF-β signal transduction pathway. With complete sequence information of the genomes and the advent of RNA interference (RNAi) technology, genome-wide RNAi screening emerged as a powerful functional genomics approach to systematically delineate molecular components of signal transduction pathways. Here, we describe a protocol for image-based whole-genome RNAi screening aimed at identifying molecules required for TGF-β signaling into the nucleus. Using this protocol we examined >90 % of annotated Drosophila open reading frames (ORF) individually and successfully uncovered several novel factors serving critical roles in the TGF-β pathway. Thus cell-based high-throughput functional genomics can uncover new mechanistic insights on signaling pathways beyond what the classical genetics had revealed.

Joel M Swenson, Serafin U Colmenares, Amy R Strom, Sylvain V Costes, and Gary H Karpen. 2016. “The composition and organization of Drosophila heterochromatin are heterogeneous and dynamic.” Elife, 5.Abstract

Heterochromatin is enriched for specific epigenetic factors including Heterochromatin Protein 1a (HP1a), and is essential for many organismal functions. To elucidate heterochromatin organization and regulation, we purified Drosophila melanogaster HP1a interactors, and performed a genome-wide RNAi screen to identify genes that impact HP1a levels or localization. The majority of the over four hundred putative HP1a interactors and regulators identified were previously unknown. We found that 13 of 16 tested candidates (83%) are required for gene silencing, providing a substantial increase in the number of identified components that impact heterochromatin properties. Surprisingly, image analysis revealed that although some HP1a interactors and regulators are broadly distributed within the heterochromatin domain, most localize to discrete subdomains that display dynamic localization patterns during the cell cycle. We conclude that heterochromatin composition and architecture is more spatially complex and dynamic than previously suggested, and propose that a network of subdomains regulates diverse heterochromatin functions.

2016_eLife_Swenson.pdf
2015
J Zanet, E Benrabah, T Li, A Pélissier-Monier, H Chanut-Delalande, B Ronsin, HJ Bellen, F Payre, and S Plaza. 2015. “Pri sORF peptides induce selective proteasome-mediated protein processing.” Science, 349, 6254, Pp. 1356-8.Abstract

A wide variety of RNAs encode small open-reading-frame (smORF/sORF) peptides, but their functions are largely unknown. Here, we show that Drosophila polished-rice (pri) sORF peptides trigger proteasome-mediated protein processing, converting the Shavenbaby (Svb) transcription repressor into a shorter activator. A genome-wide RNA interference screen identifies an E2-E3 ubiquitin-conjugating complex, UbcD6-Ubr3, which targets Svb to the proteasome in a pri-dependent manner. Upon interaction with Ubr3, Pri peptides promote the binding of Ubr3 to Svb. Ubr3 can then ubiquitinate the Svb N terminus, which is degraded by the proteasome. The C-terminal domains protect Svb from complete degradation and ensure appropriate processing. Our data show that Pri peptides control selectivity of Ubr3 binding, which suggests that the family of sORF peptides may contain an extended repertoire of protein regulators.

1356.full_.pdf
Stephanie E Mohr, Yanhui Hu, Kirstin Rudd, Michael Buckner, Quentin Gilly, Blake Foster, Katarzyna Sierzputowska, Aram Comjean, Bing Ye, and Norbert Perrimon. 2015. “Reagent and Data Resources for Investigation of RNA Binding Protein Functions in Drosophila melanogaster Cultured Cells.” G3 (Bethesda), 5, 9, Pp. 1919-24.Abstract

RNA binding proteins (RBPs) are involved in many cellular functions. To facilitate functional characterization of RBPs, we generated an RNA interference (RNAi) library for Drosophila cell-based screens comprising reagents targeting known or putative RBPs. To test the quality of the library and provide a baseline analysis of the effects of the RNAi reagents on viability, we screened the library using a total ATP assay and high-throughput imaging in Drosophila S2R+ cultured cells. The results are consistent with production of a high-quality library that will be useful for functional genomics studies using other assays. Altogether, we provide resources in the form of an initial curated list of Drosophila RBPs; an RNAi screening library we expect to be used with additional assays that address more specific biological questions; and total ATP and image data useful for comparison of those additional assay results with fundamental information such as effects of a given reagent in the library on cell viability. Importantly, we make the baseline data, including more than 200,000 images, easily accessible online.

2015_G3_Mohr.pdf Reagent Table S1.xlsx
2014
2014. “Protein kinase shRNA phosphoproteomics data from D. melanogaster embryos (data portal for Sopko et al. "Combining genetic perturbations and proteomics to examine kinase-phosphatase networks in Drosophila embryos" in Dev Cell)”.
Stephanie E Mohr, Yanhui Hu, Kevin Kim, Benjamin E Housden, and Norbert Perrimon. 2014. “Resources for functional genomics studies in Drosophila melanogaster.” Genetics, 197, 1, Pp. 1-18.Abstract

Drosophila melanogaster has become a system of choice for functional genomic studies. Many resources, including online databases and software tools, are now available to support design or identification of relevant fly stocks and reagents or analysis and mining of existing functional genomic, transcriptomic, proteomic, etc. datasets. These include large community collections of fly stocks and plasmid clones, "meta" information sites like FlyBase and FlyMine, and an increasing number of more specialized reagents, databases, and online tools. Here, we introduce key resources useful to plan large-scale functional genomics studies in Drosophila and to analyze, integrate, and mine the results of those studies in ways that facilitate identification of highest-confidence results and generation of new hypotheses. We also discuss ways in which existing resources can be used and might be improved and suggest a few areas of future development that would further support large- and small-scale studies in Drosophila and facilitate use of Drosophila information by the research community more generally.

2014_Genetics_Mohr.pdf
2013
Max V Staller, Dong Yan, Sakara Randklev, Meghan D Bragdon, Zeba B Wunderlich, Rong Tao, Lizabeth A Perkins, Angela H Depace, and Norbert Perrimon. 2013. “Depleting gene activities in early Drosophila embryos with the "maternal-Gal4-shRNA" system.” Genetics, 193, 1, Pp. 51-61.Abstract

In a developing Drosophila melanogaster embryo, mRNAs have a maternal origin, a zygotic origin, or both. During the maternal-zygotic transition, maternal products are degraded and gene expression comes under the control of the zygotic genome. To interrogate the function of mRNAs that are both maternally and zygotically expressed, it is common to examine the embryonic phenotypes derived from female germline mosaics. Recently, the development of RNAi vectors based on short hairpin RNAs (shRNAs) effective during oogenesis has provided an alternative to producing germline clones. Here, we evaluate the efficacies of: (1) maternally loaded shRNAs to knockdown zygotic transcripts and (2) maternally loaded Gal4 protein to drive zygotic shRNA expression. We show that, while Gal4-driven shRNAs in the female germline very effectively generate phenotypes for genes expressed maternally, maternally loaded shRNAs are not very effective at generating phenotypes for early zygotic genes. However, maternally loaded Gal4 protein is very efficient at generating phenotypes for zygotic genes expressed during mid-embryogenesis. We apply this powerful and simple method to unravel the embryonic functions of a number of pleiotropic genes.

2013_Genetics_Staller.pdf Table S1.pdf
Yanhui Hu, Richelle Sopko, Marianna Foos, Colleen Kelley, Ian Flockhart, Noemie Ammeux, Xiaowei Wang, Lizabeth Perkins, Norbert Perrimon, and Stephanie E Mohr. 2013. “FlyPrimerBank: an online database for Drosophila melanogaster gene expression analysis and knockdown evaluation of RNAi reagents.” G3 (Bethesda), 3, 9, Pp. 1607-16.Abstract

The evaluation of specific endogenous transcript levels is important for understanding transcriptional regulation. More specifically, it is useful for independent confirmation of results obtained by the use of microarray analysis or RNA-seq and for evaluating RNA interference (RNAi)-mediated gene knockdown. Designing specific and effective primers for high-quality, moderate-throughput evaluation of transcript levels, i.e., quantitative, real-time PCR (qPCR), is nontrivial. To meet community needs, predefined qPCR primer pairs for mammalian genes have been designed and sequences made available, e.g., via PrimerBank. In this work, we adapted and refined the algorithms used for the mammalian PrimerBank to design 45,417 primer pairs for 13,860 Drosophila melanogaster genes, with three or more primer pairs per gene. We experimentally validated primer pairs for ~300 randomly selected genes expressed in early Drosophila embryos, using SYBR Green-based qPCR and sequence analysis of products derived from conventional PCR. All relevant information, including primer sequences, isoform specificity, spatial transcript targeting, and any available validation results and/or user feedback, is available from an online database (www.flyrnai.org/flyprimerbank). At FlyPrimerBank, researchers can retrieve primer information for fly genes either one gene at a time or in batch mode. Importantly, we included the overlap of each predicted amplified sequence with RNAi reagents from several public resources, making it possible for researchers to choose primers suitable for knockdown evaluation of RNAi reagents (i.e., to avoid amplification of the RNAi reagent itself). We demonstrate the utility of this resource for validation of RNAi reagents in vivo.

2013_G3_Hu.pdf Supplemental Files.zip
Yanhui Hu, Charles Roesel, Ian Flockhart, Lizabeth Perkins, Norbert Perrimon, and Stephanie E Mohr. 2013. “UP-TORR: online tool for accurate and Up-to-Date annotation of RNAi Reagents.” Genetics, 195, 1, Pp. 37-45.Abstract

RNA interference (RNAi) is a widely adopted tool for loss-of-function studies but RNAi results only have biological relevance if the reagents are appropriately mapped to genes. Several groups have designed and generated RNAi reagent libraries for studies in cells or in vivo for Drosophila and other species. At first glance, matching RNAi reagents to genes appears to be a simple problem, as each reagent is typically designed to target a single gene. In practice, however, the reagent-gene relationship is complex. Although the sequences of oligonucleotides used to generate most types of RNAi reagents are static, the reference genome and gene annotations are regularly updated. Thus, at the time a researcher chooses an RNAi reagent or analyzes RNAi data, the most current interpretation of the RNAi reagent-gene relationship, as well as related information regarding specificity (e.g., predicted off-target effects), can be different from the original interpretation. Here, we describe a set of strategies and an accompanying online tool, UP-TORR (for Updated Targets of RNAi Reagents; www.flyrnai.org/up-torr), useful for accurate and up-to-date annotation of cell-based and in vivo RNAi reagents. Importantly, UP-TORR automatically synchronizes with gene annotations daily, retrieving the most current information available, and for Drosophila, also synchronizes with the major reagent collections. Thus, UP-TORR allows users to choose the most appropriate RNAi reagents at the onset of a study, as well as to perform the most appropriate analyses of results of RNAi-based studies.

2013_Genetics_Hu.pdf Supplement.pdf
2012
Ian T Flockhart, Matthew Booker, Yanhui Hu, Benjamin McElvany, Quentin Gilly, Bernard Mathey-Prevot, Norbert Perrimon, and Stephanie E Mohr. 2012. “FlyRNAi.org--the database of the Drosophila RNAi screening center: 2012 update.” Nucleic Acids Res, 40, Database issue, Pp. D715-9.Abstract

FlyRNAi (http://www.flyrnai.org), the database and website of the Drosophila RNAi Screening Center (DRSC) at Harvard Medical School, serves a dual role, tracking both production of reagents for RNA interference (RNAi) screening in Drosophila cells and RNAi screen results. The database and website is used as a platform for community availability of protocols, tools, and other resources useful to researchers planning, conducting, analyzing or interpreting the results of Drosophila RNAi screens. Based on our own experience and user feedback, we have made several changes. Specifically, we have restructured the database to accommodate new types of reagents; added information about new RNAi libraries and other reagents; updated the user interface and website; and added new tools of use to the Drosophila community and others. Overall, the result is a more useful, flexible and comprehensive website and database.

2012_Nuc Acids Res_Flockhart.pdf
Stephanie E Mohr and Norbert Perrimon. 2012. “RNAi screening: new approaches, understandings, and organisms.” Wiley Interdiscip Rev RNA, 3, 2, Pp. 145-58.Abstract

RNA interference (RNAi) leads to sequence-specific knockdown of gene function. The approach can be used in large-scale screens to interrogate function in various model organisms and an increasing number of other species. Genome-scale RNAi screens are routinely performed in cultured or primary cells or in vivo in organisms such as C. elegans. High-throughput RNAi screening is benefitting from the development of sophisticated new instrumentation and software tools for collecting and analyzing data, including high-content image data. The results of large-scale RNAi screens have already proved useful, leading to new understandings of gene function relevant to topics such as infection, cancer, obesity, and aging. Nevertheless, important caveats apply and should be taken into consideration when developing or interpreting RNAi screens. Some level of false discovery is inherent to high-throughput approaches and specific to RNAi screens, false discovery due to off-target effects (OTEs) of RNAi reagents remains a problem. The need to improve our ability to use RNAi to elucidate gene function at large scale and in additional systems continues to be addressed through improved RNAi library design, development of innovative computational and analysis tools and other approaches.

2012_Wiley Interdis Rev_Mohr.pdf
2011
Matthew Booker, Anastasia A Samsonova, Young Kwon, Ian Flockhart, Stephanie E Mohr, and Norbert Perrimon. 2011. “False negative rates in Drosophila cell-based RNAi screens: a case study.” BMC Genomics, 12, Pp. 50.Abstract

BACKGROUND: High-throughput screening using RNAi is a powerful gene discovery method but is often complicated by false positive and false negative results. Whereas false positive results associated with RNAi reagents has been a matter of extensive study, the issue of false negatives has received less attention. RESULTS: We performed a meta-analysis of several genome-wide, cell-based Drosophila RNAi screens, together with a more focused RNAi screen, and conclude that the rate of false negative results is at least 8%. Further, we demonstrate how knowledge of the cell transcriptome can be used to resolve ambiguous results and how the number of false negative results can be reduced by using multiple, independently-tested RNAi reagents per gene. CONCLUSIONS: RNAi reagents that target the same gene do not always yield consistent results due to false positives and weak or ineffective reagents. False positive results can be partially minimized by filtering with transcriptome data. RNAi libraries with multiple reagents per gene also reduce false positive and false negative outcomes when inconsistent results are disambiguated carefully.

2011_BMCGenomics_Booker.pdf Supplement 1.xls Supplement 2.xls

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