The Genomics Sequencing Center (GSC) is a dedicated multi-user resource for the development and application of state-of-the-art, Next-Generation Sequencing (NGS) technologies. GSC is a “one-stop shop” providing rapid, cost-effective, and high quality experimental design consultation, and genomic, transcriptomic, and functional-genomics services.

 
 

Genomics Sequencing Center Facts

The Genomics Sequencing Center offers the necessary combination of highly-skilled molecular biologists and the latest in Next-Generation Sequencing technologies to help research clients realize successful end goals.  The 6,500 sq. ft. NGS center houses the Illumina NovaSeq 6000 and NextSeq, MiSeq, Thermo Ion S5, library prep and liquid dispensing robots, ABI 3730 for Sanger sequencing and ABI’s ViiA7 for qPCR.  The GSC specializes in customizing NGS services to suit investigators’ needs and now offers a New! GSC LIMS that can accept samples for Sanger sequencing.  The new LIMS allows for easy sample submission and a faster data download for investigators, and will soon expand to include sample submissions for all GSC platforms.

The New GSC LIMS upgrade is now available for Sanger Sequencing requests.

We are pleased to announce, as of Monday, July 9, 2018, the GSC went live with the new Clarity Laboratory Information Management System (LIMS). 

The new GSC LIMS can be accessed at https://lims.bi.vt.edu/lablink.

As of July 2018, only requests for Sanger Sequencing, RNA and DNA QC (TapeStation analysis), Qubit analysis, and Covaris shearing services will be accepted via the new LIMS.
 
LIMS for NextGen sequencing is in development and will be added at a later date. Please follow the current workflow for the submission for Next-Gen sequencing.  

If you have not yet registered in the Clarity LIMS, please do so as soon as possible. Registration instructions are included in the LabLink User Guide.

When submitting samples via the new LIMS, you must use the specific submission forms available within the LIMS. They are Excel spreadsheets in a specific format which must not be altered except for entering your sample information and deleting unused rows (unused rows MUST be deleted).

Save your sample sheet on your computer under the name of your project and then upload it into the LIMS.

Samples must be submitted into the Clarity LIMS prior to 7:00 AM in order to have them processed that day. Anything submitted after that time will be processed the following day.

The samples themselves may be dropped off at our collection box at the main reception desk at the Biocomplexity Institute up until 9:00 AM and be processed that same day.

All previously run data which is currently stored in the "old" LIMS will not be accessible through the Clarity LIMS. Please access and download this data now as the "old" LIMS will be shut down completely as of August 1, 2018.

We appreciate your patience as we transition to the new system. If you encounter any problems or have any questions, feel free to contact us by email at bi-sangerseq-g@vt.edu or by telephone at (540) 231-1229.

Next-Generation Sequencing Services


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Platforms | Services | Sample Submission | Deliverables | Turnover Times | Pricing | Request a Quote

Overview

GSC scientists specialize in the development and application of cutting-edge Next-Generation Sequencing (NGS) technologies and bioinformatics analyses. The following NGS technologies and services are offered: 

 

NGS Platforms

  • Illumina NovaSeq 6000: This is Illumina’s groundbreaking platform, which enables scalable throughput and flexibility for any sequencing method, genome, and scale of project. GSC can leverage this instrument using 1, 2, 3, and 4 lane flow cells, to multiplex 96-384 samples or more per run, thus providing the best cost-to-benefit NGS services to VT researchers. NovaSeq can generate 8-10 billion sequencing reads (Single Reads) on a S4 flow cell and sequence 2 x 150 bp read lengths. Specifications are available at this link.
  • Illumina NextSeq 500: This system brings GSC the flexibility for a fast turnaround for smaller projects. With tunable output and high data quality, it provides flexibility for whole-genome, transcriptome, and targeted resequencing. NextSeq can generate up to 400 million sequencing reads (Single Reads) on a High Output flow cell and sequence 2 x 150 bp read lengths. Specifications of NextSeq are available at this link.
  • Illumina MiSeq: This system is focused on applications such as targeted sequencing, 16S metagenomics, small genome sequencing, targeted gene expression profiling and other amplicon sequencing. Miseq can generated up to 25 million sequencing reads (Single Reads) on a High Output flow cell and sequence 2 x 300 bp read lengths. Specifications of MiSeq are available at this link.
  • Thermo Ion S5: The Ion S5™ next-generation sequencing system enables simple targeted sequencing workflows at an affordable price, without compromising on performance or reliability. Specifications of Ion S5 are available at this link.

Services

Transcriptomics

  • mRNA-Seq: Stranded and non-stranded, high levels of multiplexing up to 96 or more samples on NovaSeq
    • Standard amounts, Stranded-Seq: 500 ng total RNA, RIN =>8
    • Low Input amounts, Stranded-Seq: 5 ng – 100 ng total RNA
    • Ultra Low Input amounts, Non-Stranded-Seq: 1-1000 cells or 10 pg - 10 ng
  • Total RNA-Seq - Stranded: 5-250 ng
  • Small RNA-Seq: 1 ug, multiplexing up to 48 samples/NextSeq run
  • Partially degraded samples - Stranded and Non-Stranded: LCM, FFPE samples, both stranded and non-stranded, 50 -100 ng
  • Microbial rRNA depletion and RNA-Seq with amounts as low as 1-5 ug of total RNA

Genomics

  • Whole Genome Sequencing
    • Human / Animal / Plant
    • Microbial
    • As low as 1 ng
  • De novo Sequencing
  • Exome/Targeted capture re-sequencing: Enables high sequencing depths
    • Agilent and Illumina platforms
    • Human, Mouse, Canine and other species
  • Targeted re-sequencing: High levels of multiplexing up to 200 samples / MiSeq run
    • PCR Amplicon sequencing
    • Illumina and Agilent platforms

Gene Regulation

  • ChIP-Seq
    • Transcription factor analysis
    • Histone modifications
  • DNA Methylation
    • MeDIP- and MBD-Seq
    • MethylC-Seq
    • Agilent SureSelect MethylC-Seq
    • Nucleosome Mapping
      • FAIRE-Seq and DNAse I-Seq

Metagenomics

  • 16S / 18S / ITS amplicon sequencing
  • Whole Genome Metagenomic sequencing
  • Metatranscriptomic analysis

Other Services

  • DNA/chromatin fragmentation by Covaris
  • DNA / RNA quality analysis:  BioAnalyzer / TapeStation assay, Qubit (Picogreen) assays
  • qPCR services

Sample Submission

To submit a sample, please complete the appropriate forms and send them to our NGS representative at bi-illuminaseq-g@vt.edu.

 

Deliverables

Illumina lists a range of specifications and GSC tries its best to deliver within these specifications. The deliverables also depend on the type (RNA, DNA, low diversity samples etc.) and quality of samples submitted (sub optimal amounts, sample degradation, contamination, whether recommended protocols were used for sample extraction, whether libraries were customer generated etc.). These issues will be discussed before, during and after completion of the project.


NovaSeq 6000 Specifications

Sequencing performance parameters
Sequencing Output Per Flow Cell
Flow Cell Type S1* S2 S4
2 x 50 bp 134-167 Gb 280-333 Gb N/A
2 x 100 bp 266-333 Gb 560-667 Gb N/A
2 x 150 bp 400-500 Gb 850-1000 Gb 2400-3000 Gb
Reads Passing Filter Per Flow Cell (Single Reads)
Flow Cell Type S1* S2 S4
  1.3-1.6 billion 2.8-3.3 billion 8-10 billion
Quality Scores† and Run Time‡
Flow Cell Type S1* S2 S4
Quality Scores
2 x 50 bp  ≥ 85%
2 x 100 bp ≥ 80%
2 x 150 bp ≥ 75%
Run Time
2 x 50 bp ~13 hours ~16 hours N/A
2 x 100 bp ~18 hours ~25 hours N/A
2 x 150 bp ~24 hours ~36 hours ~44 hours

Specifications based on Illumina PhiX control library at supported cluster densities. These numbers vary with customer samples

* NovaSeq S1 Reatgent Kits are not available.
† A quality score (Q-Score) is a prediction of the probability of an error in base calling. The percentage of bases > Q30 is averaged across the entire run. Quality scores are based on NovaSeq Reagent Kits run on the NovaSeq 6000 System using an Illumina PhiX control library. Performance may vary based on library type and quality, insert size, loading concentration, and other experimental factors.
‡ Run time includes cluster generation, sequencing, and base calling. Run times are based on running 2 flow cells of the same type; starting two different flow cells will impact run time


NextSeq 500 Specifications and Deliverables

Sequencing Performance Perameters
High-Output Kit* Mid-Output Kit*
Read Length Total Time† Output Read Length Total Time† Output
2x150 bp 29 hours 100-120 Gb 2 x 150 bp 26 hours 32.5-39 Gb
2 x 75 bp 18 hours 50-60 Gb 2 x 75 bp 15 hours 16.3-19.5 Gb
1 x 75 bp 11 hours 25-30 Gb      
Reads Passing Filter
High-Output Kit* Mid-Output Kit*
Up to 400 million single reads Up to 130 million single reads
Up to 800 million paired-end reads Up to 260 million paired-end reads
Quality Scores
High-Output Kit* Mid-Output Kit
> 75% bases higher than Q30 at 2 x 150 bp > 75% bases higher than Q30 at 2 x 150 bp
> 80% bases higher than Q30 at 2 x 75 bp > 80% bases higher than Q30 at 2 x 75 bp
> 80% bases higher than Q30 at 1 x 75 bp  


*Install specifications based on Illumina PhiX control library at supported cluster densities (between 129 and 165 k/mm² clusters passing filter). Actual performance parameters may vary based on sample type, sample quality, and clusters passing filter. All NextSeq 500 kits are paired-end capable.
†Total time includes cluster generation, sequencing, and base calling on a NextSeq 550 System enabled with dual-surface scanning.
‡ A quality score (Q-score) is a prediction of the probability of an error in base calling. The percentage of bases > Q30 is averaged across the entire run.


MiSeq Specifications and Deliverables

sequencing performance perameters
Read Length †Reads Passing Filter Output Quality Scores (Q-Score)(% bases above Q30) *Run Time
MiSeq Reagent Kit V2
1 x 50 12-15 million single reads or 24-30 million paired end reads 750-850 Mb > 90% 5 hrs
2 x 25 750-850 Mb > 90% 5.5 hrs
2 x 150 4.5-5.1 Gb > 80% 24 hrs
2 x 250 7.5-8.5 Gb > 75% 39 hrs
MiSeq Reagent Kit V3
1 x 150 22-25 million
single reads or
44-50 million
paired end reads
3.3-3.8 Gb > 80% 19 hrs
2 x 75 3.3-3.8 Gb > 85% 20 hrs
2 x 300 13.2-15 Gb > 70% 55 hrs

*Total time includes cluster generation, sequencing, and base calling on a MiSeq system.
†Performance may vary based on samples quality, cluster density, applications, and other experimental factors. Low diversity libraries are run at a lower cluster density.
 

Turnover Times

RNA and DNA QC

  • Includes NanoDrop, Qubit, BioAnalyzer, or TapeStation
  • 2 days to 1 week
  • GSC will send the QC data, and discuss whether the samples can move forward for library preps and sequencing

Library Preparation

  • Includes library preps, QC and quantitation
  • 1-3 weeks depending on sample quality, sample number, type of library prep, and previous samples in the queue.
  • The clock is reset if the library preps fail and the user submits replacement samples

Sequencing

  • NextSeq: Sequencing times of 1-2 days depending on the length of sequencing. There is no lane sharing in NextSeq.
  • NovaSeq: Sequencing times of 1-2 days depending on the length of sequencing. 
  • MiSeq: 1-3 days depending on the length of sequencing. 

Pricing

For up-to-date information on the pricing structure of GSC services, as well as official refund and delivery policies, please reference our downloadable pricing guide.

 

Request a Quote

For project, experimental design, and grant-support consultation:
Saikumar Karyala
skaryala@bi.vt.edu
(540) 231-7294

For Quote:
bi-illuminaseq-g@vt.edu
(540) 231-1229

For General Inquiries:
Megan Friar and Jennifer Jenrette
bi-illuminaseq-g@vt.edu
(540) 231-1229

Sanger Services

Navigation

Services | Sample Requirements | Sample Submission | Deliverables | Turnover Times

Overview

The researcher isolates DNA templates from a variety of sources, including plasmids and PCR reactions and submits samples pre-mixed with primers, based on the requirements specified by GSC. GSC performs sequencing on ABI 3730 DNA Analyzer and deliver the ab1 files electronically. 

 

Services

Sanger Full Reactions

GSC staff set up cycle sequencing reactions, perform clean-up, run the samples on the ABI 3730, and deliver the sequence data electronically.

 

Sample Requirements

In order to ensure the best quality results, samples submitted for analysis must meet certain requirements. Detailed guidelines for sample preparation can be found in our downloadable Sample Submission Requirements Guide

 

Sample Submission

Creating and Managing New Projects (NEW GSC LIMS)

All Sanger sequencing requests must now go through our NEW GSC Laboratory Information Management System (LIMS). If this is your first time using LIMS, please follow the instructions in our NEW LIMS User Guide to create a new account and verify your payment method. You must have a GSC LIMS account and login to access the new submission forms.

 

If you have any questions about your LIMS account or the sample submission process, please email Kris Lee at  bi-sangerseq-g@vt.edu or call (540) 231-1229.
 

Sample Drop-Off

Customers who wish to drop off their samples in person can do so at the institute’s main reception desk between the hours of 8:00 AM and 5:00 PM. In most cases, samples received by 8:30 AM will be processed that same day.

If sending samples via mail, pack the samples with ice packs and include an information sheet with the researcher’s name and contact information and indicate that the samples are intended for Sanger sequencing. Send the package to:

Genomics Sequencing Center
Biocomplexity Institute of Virginia Tech
1015 Life Science Circle 
Blacksburg, VA 24061
Phone: (540) 231-1229

Deliverables

Upon completion of the sequencing run, you will be notified via email through the LIMS that your results are available for you to download. Log into your LIMS account and save these files (.ab1 files) to your computer. There are several software programs available online for viewing this type of sequencing file. For Sanger sequencing, we use Sequence Scanner 2 which is free downloadable software available from ABI.

 

Turnover Times

Monday through Friday, our turnaround time is 48 hours, but we make every effort to complete the work within 24 hours. Our lab is closed on weekends so any Sanger samples submitted after 8:30 AM on Friday will not be processed until Monday, with results going out on Tuesday.

Contact:

Kris Lee

bi-sangerseq-g@vt.edu

Phone: (540) 231-1229

Quality Control Services

Overview

The GSC offers a wide variety of quality control services to suit the needs of our clients. The samples must be submitted through our NEW LIMS. The requirements for sample submission are listed in the submission forms that can be downloaded from our new LIMS.

 

Services

Qubit Quantification

NanoDrop Spectrophotometer

  • DNA quantitation by Qubit Fluorometer

RNA/DNA Quality Check

RNA quantation by NanoDrop: GSC routinely performs NanoDrop quantitation for samples submitted for RNA quality check by TapeStation and for NGS samples.

 

Agilent Tape Station

Researchers can submit both RNA and Illumina libraries for quality check. Please check the Sample Submission forms for more details.

 

RNA QC

  • RNA with RIN ≥ 8.0 are best for NGS and other projects.
  • Standard RNA TapeStation
  • High Sensitivity RNA TapeStation

DNA QC

  • DNA 1000
  • High Sensitivity DNA1000

DNA Shearing

Samples for Covaris must be submitted through our NEW LIMS.

Covaris M220: GSC provides shearing of both DNA and chromatin. For Chromatin shearing we recommend an optimization before submitting experimental samples.

Publications

GSC-Authored Research


1.  Monson M.S., Settlage R.E., McMahon K.W., Mendoza K.M., Rawal S., El-Nezami H.S., Coulombe R.A., Reed K.M., Response of the hepatic transcriptome to aflatoxin B1 in domestic turkey (Meleagris gallopavo). PLoS One. 2014 Jun 30;9(6).

2.  Dalloul R.A., Zimin A.V., Settlage R.E., Kim S., Reed K.M., Next-generation sequencing strategies for characterizing the turkey genome. Poult Sci. 2014 Feb;93(2):479-84.

3.  Monson M.S., Settlage R.E., Mendoza K.M., Rawal S., El-Nezami H.S., Coulombe R.A., Reed K.M., Modulation of the spleen transcriptome in domestic turkey (Meleagris gallopavo) in response to aflatoxin B1 and probiotics. Immunogenetics. 2015 Mar;67(3):163-78.

4.  Ding J, Reynolds LM, Zeller T, et al. Alterations of a Cellular Cholesterol Metabolism Network is a Molecular Feature of Obesity-Related Type 2 Diabetes and Cardiovascular Disease. Diabetes. 2015; 64: 3464-74.

5.  Liao X, Li S, Settlage RE, Sun S, Ren J, Reihl AM, Zhang H, Karyala SV, Reilly CM, Ahmed SA, Luo XM. (2015) Cutting Edge: Plasmacytoid Dendritic Cells in Late-Stage Lupus Mice Defective in Producing IFN-α. Journal of Immunology. 195:4578-4582.

6.  Zhang H, Sparks JB, Karyala SV, Settlage R, Luo XM. (2014) Host adaptive immunity alters gut microbiota. ISME Journal 9(3):770-81.

GSC-Impacted Research


7.   Metch JW, Burrows ND, Murphy CJ,  Pruden A, Vikesland PJ. Metagenomic analysis of microbial communities yields insight into impacts of nanoparticle design. Nature. 2018

8.  Reynolds LM, Ding J, Taylor JR, et al. Transcriptomic profiles of aging in purified human immune cells. BMC Genomics. 2015;16:333.  

9.  Yi H, Breheny P, Imam N, Liu Y, Hoeschele I. Penalized multimarker vs. single-marker regression methods for genome-wide association studies of quantitative traits. Genetics. 2015; 199:205–222.

10.  Liu Y, Ding J, Reynolds LM, et al. Methylomics of gene expression in human monocytes. Human Molecular Genetics. 2013:ddt356. 

11.  Zhang H, Liao X, Sparks JB, Luo XM. (2014) Dynamics of gut microbiota in autoimmune lupus. Applied Environmental Microbiology 80(24):7551-60.

12.  Mu Q, Zhang H, Luo XM (2015) SLE: Another Autoimmune Disorder Influenced by Microbes and Diet? Frontiers in Immunology doi: 10.3389/fimmu.2015.00608

13.  Zhang H, Luo XM (2015) Control of commensal microbiota by the adaptive immune system. Gut Microbes 6(2):156-60.

14.  Tae, H., Shallom, S., Settlage, R.E., Preston, D., Adams, L.G., Garner, H.R, Revised Genome Sequence of Brucella suis 1330. J. Bacteriology, 193(22), 2011, 6410.

15.  Tae, H., Shallom, S., Settlage, R.E., Hawkins, G.N., Adams, L.G., Garner, H.R, Complete Genome Sequence of Brucella suis VBI22, Isolated from Bovine Milk. J. Bacteriology, 194(4), 2012, 910.

16.  Tae H, Settlage RE, Shallom S, Bavarva JH, Preston D, Hawkins GN, Adams LG, Garner HR. Genomics.  Improved variation calling via an iterative backbone remapping and local assembly method for bacterial genomes. 2012 Nov;100(5):271-6.

17.  Radakovits, R., Jinkerson, R.E., Fuerstenberg, S.I., Tae, H., Settlage, R.E., Boore, J.L., Posewitz, M.C, Draft genome sequence and genetic transformation of the oleaginous alga Nannochloropsis gaditana, Nature Communications, 3:686, 2012.

18.  Bavarva J.H., Tae H., Settlage R.E., Garner H.R., Characterizing the Genetic Basis for Nicotine Induced Cancer Development: A Transcriptome Sequencing Study. PLoS One. 2013 Jun 18;8(6):e67252.

19.  Tae H., McMahon K.W., Settlage R.E., Bavarva J.H., Garner H.R., ReviSTER: an automated pipeline to revise misaligned reads to simple tandem repeats. Bioinformatics. 2013 Jul 15;29(14):1734-41.

20.  Zhang H., Wang H., Shepherd M., Wen K., Li G., Yang X., Kocher J., Giri-Rachman E., Dickerman A., Settlage R., Yuan L., Probiotics and virulent human rotavirus modulate the transplanted human gut microbiota in gnotobiotic pigs. Gut Pathog. 2014 Sep 9;6:39.

21.  Jiang X., Peery A., Hall A.B., Sharma A., Chen X.G., Waterhouse R.M., Komissarov A., Riehle M.M., Shouche Y., Sharakhova M.V., Lawson D., Pakpour N., Arensburger P., Davidson V.L., Eiglmeier K., Emrich S., George P., Kennedy R.C., Mane S.P., Maslen G., Oringanje C., Qi Y., Settlage R., Tojo M., Tubio J.M., Unger M.F., Wang B., Vernick K.D., Ribeiro J.M., James A.A., Michel K., Riehle M.A., Luckhart S., Sharakhov I.V., Tu Z.., Genome analysis of a major urban malaria vector mosquito, Anopheles stephensi. Genome Biol. 2014 Sep 23;15(9):459.

22.  Zhang H., Sparks J.B., Karyala S.V., Settlage R., Luo X.M., Host adaptive immunity alters gut microbiota. ISME J. 2015 Mar;9(3):770-81.

23.  Monson M.S., Settlage R.E., McMahon K.W., Mendoza K.M., Rawal S., El-Nezami H.S., Coulombe R.A., Reed K.M., Response of the hepatic transcriptome to aflatoxin B1 in domestic turkey (Meleagris gallopavo). PLoS One. 2014 Jun 30;9(6).

24.  Dalloul R.A., Zimin A.V., Settlage R.E., Kim S., Reed K.M., Next-generation sequencing strategies for characterizing the turkey genome. Poult Sci. 2014 Feb;93(2):479-84.

25.  Tae H., Kim D.Y., McCormick J., Settlage R.E., Garner H.R., Discretized Gaussian mixture for genotyping of microsatellite loci containing homopolymer runs. Bioinformatics. 2014 Mar 1;30(5):652-9.

26.  Monson M.S., Settlage R.E., Mendoza K.M., Rawal S., El-Nezami H.S., Coulombe R.A., Reed K.M., Modulation of the spleen transcriptome in domestic turkey (Meleagris gallopavo) in response to aflatoxin B1 and probiotics. Immunogenetics. 2015 Mar;67(3):163-78.

27.  Zhang W., Kim S., Settlage R., McMahon W., Sumners L.H., Siegel P.B., Dorshorst B.J., Cline M.A., Gilbert E.R., Hypothalamic differences in expression of genes involved in monoamine synthesis and signaling pathways after insulin injection in chickens from lines selected for high and low body weight. Neurogenetics. 2015 Apr;16(2):133-44.

28.  Zalenskaya I.A., Joseph T., Bavarva J., Yousefieh N., Jackson S.S., Fashemi T., Yamamoto H.S., Settlage R., Fichorova R.N., Doncel G.F., Gene Expression Profiling of Human Vaginal Cells In Vitro Discriminates Compounds with Pro-Inflammatory and Mucosa-Altering Properties: Novel Biomarkers for Preclinical Testing of HIV Microbicide Candidates. PLoS One. 2015 Jun 8;10(6).

29.  Ding J, Reynolds LM, Zeller T, Müller C, Lohman K, Nicklas BJ, Kritchevsky SB, Huang Z, de la Fuente A, Soranzo N, Settlage RE, Chuang CC, Howard T, Xu N, Goodarzi MO, Chen YD, Rotter JI, Siscovick DS, Parks JS, Murphy S, Jacobs DR Jr, Post W, et al. Alterations of a Cellular Cholesterol Metabolism Network Are a Molecular Feature of Obesity-Related Type 2 Diabetes and Cardiovascular Disease. Diabetes. 2015 Oct;64(10):3464-74.

30.  Hendrickson RC, Lee AY, Song Q, Liaw A, Wiener M, Paweletz CP, Seeburger JL, Li J, Meng F, Deyanova EG, Mazur MT, Settlage RE, Zhao X, Southwick K, Du Y, Holder  D, Sachs JR, Laterza OF, Dallob A, Chappell DL, Snyder K, Modur V, et al. High Resolution Discovery Proteomics Reveals Candidate Disease Progression Markers of  Alzheimer's Disease in Human Cerebrospinal Fluid. PLoS One. 2015;10(8):e0135365.

31.  Davis M, Jessee R, Close M, Fu X, Settlage R, Wang G, Cline MA, Gilbert ER. Fasting for 21days leads to changes in adipose tissue and liver physiology in juvenile checkered garter snakes (Thamnophis marcianus). Comp Biochem Physiol A Mol Integr Physiol. 2015 Sep 7;190:68-74. doi: 10.1016/j.cbpa.2015.09.001. [Epub ahead of print] PubMed [citation] PMID: 26358832

32.  Liao X, Li S, Settlage RE, Sun S, Ren J, Reihl AM, Zhang H, Karyala SV, Reilly CM, Ahmed SA, Luo XM. Cutting Edge: Plasmacytoid Dendritic Cells in Late-Stage Lupus Mice Defective in Producing IFN-α.  J Immunol. 2015 Nov 15;195(10):4578-82. doi: 10.4049/jimmunol.1501157. Epub 2015 Oct 7.

33.  Wang Z, Leary DH, Liu J, Settlage RE, Fears KP, North SH, Mostaghim A, Essock-Burns T, Haynes SE, Wahl KJ, Spillmann CM.  Molt-dependent transcriptomic analysis of cement proteins in the barnacle Amphibalanus amphitrite.  BMC Genomics. 2015 Oct 24;16(1):859. doi: 10.1186/s12864-015-2076-1.

34.  Zhan S, Merlin C, Boore JL, Reppert SM. The monarch butterfly genome yields insights into long-distance migration. Cell. 2011;147(5):1171–85.

35.  Kang L., Settlage R., McMahon W., Michalak K., Tae H., Garner H.R., Stacy E., Price D. & Michalak P. 2015. Genomic signatures of speciation in sympatric and allopatric Hawaiian picture-winged Drosophila. Genome Biology, under revision.

36.  Michalak K., Maciak S., Kim Y.B., Santopietro G., Oh J.H., Kang L., Garner H.R., & Michalak P. 20015. Nucleolar dominance and maternal control of 45S rDNA expression Proceedings of the Royal Society B: Biological Sciences, in press.

37.  Philipson C.W., Bassaganya-Riera J., Viladomiu M., Kronsteiner B., Abedi V., Hoops S., Michalak P., Kang L., Girardin S.E. & Hontecillas R. 2015. Modeling the regulatory mechanisms by which NLRX1 modulates innate immune responses to Helicobacter pylori infection. PLoS One 10(9):e0137839.

38.  Mechkarska M., Coquet L., Leprince J., Jouenne T., Vaudry H., Michalak K., Michalak P. &Conlon JM. 2014. Host-defense peptides from skin secretions of the octoploid frogs Xenopus vestitus and Xenopus wittei (Pipidae): Insights into evolutionary relationships. Comparative Biochemistry and Physiology – Part D Genomics Proteomics 11C: 20-28.

39.  Kim Y.B., Oh J.H., McIver L.J., Rashkovetsky E., Michalak K., Garner H.R., Kang L., Nevo E., Korol A.B. & Michalak P. 2014. Divergence of Drosophila melanogaster repeatomes in response to a sharp microclimate contrast in ‘Evolution Canyon’, Israel. Proceedings of the National Academy of Sciences USA 111: 10630-10635.

40.  Michalak K., Czesny S., Epifanio J., Snyder R.J., Schultz E.T., Velotta J.P., McCormick S.D., Brown B.L., Santopietro G., Michalak P. 2014. Beta-thymosin gene polymorphism associated with freshwater invasiveness of alewife (Alosa pseudoharengus). Journal of Experimental Zoology Part A: Ecological Genetics & Physiology 321: 233-240. [Cover]

41.  Michalak P. 2014. Evidence for maternal imprinting of 45S ribosomal RNA genes in Xenopus hybrids. Development Genes & Evolution 224: 125-128.

42.  Hübner S., Rashkovetsky E., Kim Y.B., Oh J.H., Michalak K., Weiner D., Korol A.B., Nevo E. & Michalak P. 2013. Genome differentiation of Drosophila melanogaster from a microclimate contrast in Evolution Canyon, Israel. Proceedings of the National Academy of Sciences USA 110: 21059-2164.

43.  Viladomiu M., Hontecillas R., Pedragosa M., Michalak P., Michalak K., Guerrant R., Roche J., Warren C. & Bassaganya-Riera J. 2012. Modulation of immune responses to Clostridium difficile by peroxisome proliferator-activated receptor gamma and miRNA-146b. Journal of Immunology 2012, 188.

44.  Zhang H, Wang H, Shepherd M, Wen K, Li G, et al. Probiotics and virulent human rotavirus modulate the transplanted human gut microbiota in gnotobiotic pigs. Gut Pathogens. 2014; 6:39.

45.  Huang YW, Dickerman AW, Piñeyro P, Li L, Fang L, et al. Origin, evolution, and genotyping of emergent porcine epidemic diarrhea virus strains in the United States. mBio. 2013; 4(5):e00737-13.

46.  Aulakh SS, Veilleux RE, Dickerman AW, Tang G, Flinn BS. Characterization and RNA-seq analysis of underperformer, an activation-tagged potato mutant. Plant Molecular Biology. 2014; 84(6):635-58.

47.  Yuan L., Zhi. W., Karyala, S., Vikesland, P.J., Chen, X., Zhang, J. Lead toxicity to the performance, viability, and community composition of activated sludge microorganisms, Environ Sci Tech. 2015 Jan 20;49(2):824-30.

48.  Cao, Z., Chen, C., He, B., Tan, K., & Lu, C. (2015). A microfluidic device for epigenomic profiling using 100 cells. Nature Methods. 2015 Oct;12(10):959-62

49.  Stepherd, ML, Swecker, WS, Jensen, RV, Ponder, MA.  Characterization of the fecal bacteria communities of forage-fed horses by pyrosequencing of 16S rRNA V4 gene amplicons. FEMS Microbiol Lett. 2012, 326:62-8.

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