Analytical and Translational Genomics

The Analytical and Translational Genomics (ATG) Shared Resource provides next-generation sequencing and other genomics related services to UNM Cancer Center members and other users at UNM and affiliated institutions. The primary services involve next-generation sequencing, using the two Ion Proton S5/XL instruments, and associated expert bioinformatics support. These include RNA-seq, targeted DNA sequencing, ChIP-seq and a variety of other assays, many of which can be performed with either research or clinical (e.g. FFPE) samples. The Ion Proton S5/XL instruments are especially suited for analyzing poor quality RNA, e.g. from FFPE material, which are difficult or impossible to analyze using other technologies. The instruments generate up to 100 million reads per sequencing chip, and we strive to provide a quick turnaround, if possible.

The Shared Resource is supported by the UNM Cancer Center, including the CCSG core grant P30CA118100 and other funds, as well as by funds from the State of NM and user fees.

The expert staff are available for consultations to help users design the best possible experiments, to maximize the quality of the data that are produced.

Dr. Ness works with his team in the ATG Shared Resource

Faculty Director

Scott A. Ness, Ph.D.
Professor, Internal Medicine/Molecular Medicine
Office: CRF 121; Tel: (505) 272-9883

Technical Director / Bioinformatics

Kathryn (Charlie) Brayer, PhD

Senior Technical Staff

Jamie Padilla CRF 118 Tel: (505) 272-5564
Jennifer Woods CRF 121 Tel: (505) 272-3464
Maggie Cyphery CRF 121 Tel: (505) 272-2464

Analytical and Translation Genomics

ATG is available for use by all researchers at UNM and affiliated institutions.

To acknowledge use of this shared resource, please include the following in your publications:

This research was partially supported by UNM Comprehensive Cancer Center Support Grant NCI P30CA118100 and made use of the Analytical and Translational Genomics Shared Resource, which receives additional support from the State of New Mexico.

These services are described in more detail below.

The Analytical and Translational Genomics Resource primarily provides next generation sequencing technologies such as RNA-seq, targeted gene panel sequencing, exome sequencing and epigenetics assays such as ChIP-seq and RRBS, coupled with expert bioinformatics analysis. Affymetrix microarray and real-time PCR services are also available. The ATG Shared Resource is available for use by all faculty at UNM and its affiliates, and all investigators are encouraged to contact us to find out how we can help with their research.

Ion Proton Next-Generation Sequencing: The powerful Life Technologies Ion Proton semiconductor sequencing instrument is ideal for next-generation sequencing assays including exome sequencing (all the proton-coding exons, about 2% of the genome), gene expression (RNA-seq) assays, epigenetics assays (ChIP-seq) and targeted sequencing (Ion Ampliseq Comprehensive Cancer Panel) of cancer-relevant genes, even from FFPE samples.

Expert Bioinformatics Data Analysis: ATG Shared Resource staff use sophisticated data analysis methods to analyze gene expression and genotyping data and strive to provide our users with publication-quality figures for their manuscripts or grant applications. We use R/Bioconductor and commercial software packages to explore the large and complicated data sets generated by genomics methods.  

Affymetrix: The ATG shared resource has a complete Affymetrix system including two automated hybridization/fluidics stations and a high-resolution GeneChip scanner with autoloader as well as a suite of specialized instruments for the analysis of nucleic acids. We have analyzed more than 4000 Affymetrix microarrays, which are useful for assessing expression of mRNAs or microRNAs, as well as for GWAS and CGH (Comparative Genome Hybridization) to identify deletions and/or duplications in genomic DNA samples.

Real-Time PCR: ATG Shared Resource performs TaqMan real-time PCR assays in 96 and 384 well plates. These are highly specific and the small volumes help save on expensive reagents and precious samples. The TaqMan assays are used for measuring the expression of small numbers (<100) of genes, or for detecting SNPs or other point mutations.

Applications of Next-Gen Sequencing

Next-generation (massively parallel) sequencing is useful for a variety of experimental approaches. It is not a replacement for normal (Sanger) sequencing of plasmids or PCR products. Instead, next-gen sequencing relies on capturing millions or billions of individual DNA molecules (e.g. genomic DNA fragments, cDNAs), which are then amplified separately and sequenced in parallel, generating millions or billions of sequencing "reads", each of which originated from a different template molecule. It is similar to individually cloning and sequencing millions or billions of independent DNA fragments, but it all happens at once and in just a few days.

The following types of scientific applications are easily adaptable to next-gen sequencing approaches:

  • Targeted gene panel sequencing of cancer- or disease-relevant genes • Gene expression studies using RNA-seq
  • Chromatin Immunoprecipitation - sequencing (ChIP-seq) for transcription factor or epigenetic studies
  • DNA methylation studies (e.g. RRBS)
  • Transcriptome sequencing (e.g. identification of alternatively-spiced RNAs)
  • Analysis of non-coding RNAs (ncRNAs, lincRNAs, miRs)

The ATG facility currently has or has access to several types of next-gen sequencing instruments:

• Ion S5/XL: A solid state NGS insturment generating up to 100 million reads per chip

These instruments provide cost-efficient and rapid next-generation sequencing for applications such as targeted sequencing, RNA-seq, ChIP-seq, MeDIP-seq and even low-pass whole-genome sequencing for copy number variant analysis.

Shared instruments available Mon-Fri 8:30 am - 5 pm

(other times may be available by special arrangement)

The KUGR Facility has several unique instruments that UNM researchers can arrange to use. Qualified laboratories pay an annual user fee and receive training and support from KUGR Staff. The instruments are available for use in the facility during normal working hours.

Agilent Bioanalyzer: An important instrument for molecular biologists, replaces gel electrophoresis for many types of applications. It is especially useful for analyzing the quality and/or quantity of RNA or DNA samples using very small amounts of material, instead of running large amounts of precious sample on a gel.

Nanodrop Spectrophotometer: A droplet spectrophotometer that measures absorbance in a small droplet of sample. This avoids the need to dilute samples into large cuvettes.

Qiagen Qiacube Robot: A dedicated sample preparation robot for performing RNA and DNA isolation and purification steps with Qiagen kits.

Please contact the KUGR Facility staff for more information about assays and pricing.

Use our iLab site for reservations and quotes. (Log-In Required)

The Analytical and Translational Genomics (ATG) Shared Resource (formerly Keck-UNM Genomics Resource, KUGR) provides access to next generation sequencing assays, microarrays, and other genomics technologies coupled with expert bioinformatics analysis. ATG is available for use by all faculty at UNM and its affiliates, and all investigators are encouraged to contact ATG to find out how we can help with their research.

ATG Services

The ATG Shared Resource provides the highest-quality bioinformatics analysis of genomics data sets, employing state-of-the-art tools such as custom scripts written in "R". The ATG staff has analyzed data sets for dozens of laboratories and have produced high quality figures for numerous publications and grant applications. The ATG Facility provides a full range of data analysis services including:

  • Pre-experiment consultation and assistance with experimental design issues related to genomics experiments
  • Customized data analysis using filtering and statistical methods that make use of stringent quality controls
  • Preparation of publication-quality figures for papers or grant applications
  • Storage of data and assistance with up-loading data sets to databases for publication

We strongly recommend that all users contact the facility staff before beginning their genomics experiments. We can provide information about the number of replicates that are required, how the DNA or RNA samples should be prepared and what the total cost is likely to be. A few minutes of discussion may save weeks and many dollars later.

Gene expression assays measure which genes are expressed in different samples, or how the expression of genes change over time or in response to specific treatments. The ATG Shared Resource specializes in using RNA-seq for measuring gene expression.

Next-Gen Sequencing and RNA-Seq

RNA-sequencing (RNA-seq) is a next-generation sequencing approach to measuring gene expression across all the genes at once. Briefly, RNA is isolated, fragmented, converted to cDNA then ligated to adaptors and sequenced. The resulting sequencing "reads" are aligned to the genome. The number of reads aligned to each gene is proportional to the gene expression level. RNA-seq may also provide information about mutations (e.g. SNPs) and alternative RNA splicing, and chromosomal translocations can be detected by analyzing the output for the presence of fusion transcripts that cross the translocation breakpoint. RNA-seq can be successfully performed with high-quality RNA from fresh or frozen tissues or cell lines, and with RNA isolated from pathology samples, such as Formaldehyde-Fixed, Paraffin-Embedded (FFPE) material.

Genotyping assays measure allelic differences, especially differences in Single Nucleotide Polymorphisms (SNPs), which are the differences in the DNA between individuals. The ATG shared resource can measure allelic differences in up to 100 SNPs using TaqMan real-time PCR assays. Alternatively, Affymetrix whole genome SNP arrays can be used to follow nearly 2 million SNPs across the whole genome. The latter assays are intended for mapping phenotypes to particular regions of the genome, experiments known as whole genome association studies.

The Analytical and Translational Genomics Shared Resource is a Certified Exome Sequencing provider using the Ion Ampliseq Exome Sequencing system and the Ion Proton sequencing instrument. The Ion Ampliseq system is a targeted multiplex-PCR assay that amplifies >250,000 amplicons from all of the exomes covering protein-coding regions in the human genome. The highly multiplexed products are then converted into sequencing libraries for the Ion Proton. The assays are usually barcoded and run two at a time on a P1 chip, which typically produces about 80 million "reads" and >100x average coverage across the targeted regions (about 2% of the human genome), which is more than adequate to detect germline variants (SNPs). The Ion Ampliseq assay is very robust and is ideal for the analysis of family units (trios) or genetic markers linked to ethnicity.

The ATG staff provide several types of bioinformatics analysis for exome sequencing data, including some standardized pipelines provided by the Life Technologies Ion Reporter tool, as well as customized analysis pipelines utilizing R/Bioconductor tools.

The level of coverage offered by the Ion Ampliseq Exome assay may be sufficient for analyzing tumor samples, but because tumors are a mixture of tumor cells and normal cells, and may include subclones (e.g. tumor heterogeneity), this coverage may not be sufficient to detect all tumor variants, especially those present in only a subset of tumor cells (i.e. tumor subclones). For "deep" sequencing of rare subpopulations in a tumor or to characterize tumor heterogeneity, it is preferable to use a targeted assay such as the Comprehensive Cancer Panel.

The ATG facility provides targeted sequencing of >400 cancer-relevant genes using the Ion Ampliseq Comprehensive Cancer Panel, a multiplexed PCR-based assay that results in the sequencing of all of the protein-coding regions for nearly all oncogenes, tumor suppressors and other genes important in cancer biology. These assays are usually barcoded and run four at a time on a single P1 chip on the Ion Proton sequencer, which typically produces about 80 million "reads" and produces >750x average read depth across the targeted regions. That makes these assays ideal for detecting rare variants (e.g. in <5% of the tumor cells) or for studying tumor heterogeneity (subclones within the tumor). The CCP assay is very robust and works well with DNA from FFPE material or fresh or frozen tissue.

The ATG facility uses some standard bioinformatics tools to detect variants (SNVs) identified by the CCP assay, and has developed customized scripts in R/Bioconductor to analyze other features such as tumor heterogeneity, loss of heterozygosity (LOH), copy number variants, etc. However, these assays also require analysis of normal tissue for comparison. An excellent combination is to use the CCP targeted assay for the tumor tissue, combined with the Ion Ampliseq Exome assay for normal tissue to detect germline (inherited) variants and markers linked to ethnicity.

The Analytical and Translational Genomics Shared Resource is currently developing several types of epigenetics assays based on next-generation sequencing assays, including Chromatin Immuno Precipitation sequencing (ChIP-seq) for the analysis of histone modifications and transcription factor binding sites. Please contact Dr. Ness if you are interested in developing or using these assays in your laboratory.


These are guidelines for researchers contemplating the use of Next-Generation Sequencing (NGS) services from the ATG Shared Resource. All researchers are urged to consult with the ATG staff before beginning to prepare or analyze samples. We can assist with experimental design and, if necessary, put you in touch with expert biostatisticians who can help with experimental design. It is very important to consider the experimental design before beginning NGS experiments, which can be quite expensive.

RNA-seq can be successfully performed with very small amounts of RNA. However, the amount required depends on the "read depth" required and whether there will be ribosomal RNA contamination. Ribosomal RNA is 90% of the RNA in cells, so it is necessary to remove or reduce the ribosomal RNA before performing RNA-seq. The two ways to do this are physical removal, through "Ribodepletion", in which biotinylated probes complementary to the ribosomal RNAs are hybridized with the RNA samples, then the complexes are captured and removed. Alternatively, a poly-A-directed library prep method (e.g. Smart-Seq) can be used that avoids sequencing the ribosomal RNA, but that excludes other RNAs that lack polyA tails and that might be of interest (e.g. microRNAs). Please contact the ATG Shared Resource staff to discuss options before beginning the experiments.

The ATG Shared Resource performs full service NGS analysis. However, due to the complexities of NGS library preparation, what ATG can provide depends on the type of experiment. For targeted panel sequencing and exome sequencing, we only need DNA samples and we will produce the libraries, perform the sequencing and the initial analysis. We will provide a quote for the expected cost before beginning the work. For RNA-seq and other approaches, there are many variations in the way libraries can be constructed. We urge users to contact the ATG staff to discuss options before beginning. Besides the complete Affymetrix system, the ATG Shared Resource has a Nanodrop spectrometer for quantifying RNA in small volumes, and an Agilent Bioanalyzer for rapidly analyzing the quality and quantity of RNA or DNA samples.

NGS experiments can be expensive. The total cost for most large experiments (exome sequencing, RNA-seq, etc.) is $500 to $800 per sample, plus a charge for bioinformatics. Some smaller targeted sequencing experiments cost less per sample. Please contact the staff for more information and to get a quote.

Yes! NGS experiments generate large, complex data sets. Bioinformatics analysis is not possible without duplicates. Triplicates are better. Replicates really are necessary to get good results that are meaningful and worth the cost.

The ATG Shared Resource follows strict quality control guidelines and standard operating procedures to insure that data is of the highest quality and meets or exceeds standards set by groups such as the ENCODE consortium. We use standard spike-in controls to monitor internal processes and perform quality control checks at every stage of library production and sequencing. Please contact the ATG staff to see examples of the data that we have successfully produced.

The quality of the starting RNA samples will be confirmed using the Agilent BioAnalyzer or by using real-time PCR. The libraries will be similarly checked before sequencing. Spike-in controls are added at several steps to monitor internal quality control.

NGS assays produce large, complex data sets that contain enormous amounts of information, but can also be difficult to analyze. The ATG Shared Resource provides the first level of analysis, including analysis of quality control parameters, alignment of the reads to the appropriate genome, identifying sequence variants or feature counts, as appropriate, and performing straightforward types of interpretation, such as the production of heatmaps for RNA-seq. However, more complicated types of data analysis, such as correlating results to patient information, should be performed with the input of experts from the Bioinformatics Shared Resource or the Biostatistics Shared Resource. The ATG staff can help set up interactions with the appropriate experts, who should be involved from the beginning to help with experimental design and quality control.

There is a possibility that the complex process involved in generating NGS data will produce a "day effect" or "batch effect", in which the samples processed or analyzed on the same data cluster together. This is a well-known artifact of high-dimensional data analysis, and we include spike-in controls to help us identify and remove these types of data problems.

The ATG Shared Resource has a team of bioinformatics experts who will perform the initial data analysis and who will manage and back-up the data. They can perform most straightforward types of analyses (e.g. gene expression from RNA-seq). However, complex or customized types of analyses will require input from additional experts from the Biostatistics or Bioinformatics Shared Resources. The ATG staff can help set up the required collaborations.

Verification is an important part of each NGS experiment, and the requirements vary depending on the type of experiment. Please contact the ATG staff to discuss options for verifying NGS results.

The facility Director, Scott A. Ness, Ph.D., can provide letters of support and advice about how to describe the ATG Shared Resource and potential NGS experiments in grant applications. Dr. Ness has served on numerous NIH, ACS and DOD study sections and has reviewed many grant applications that include NGS experiments. His own funded grants have NGS experiments in them. He can provide help with writing sections of your grant regarding NGS experiments and can point out potential pitfalls and things to avoid.

The easiest way to criticize an NGS experiment is to describe it as a fishing expedition. Here are some things you should definitely avoid.

  1. Do not propose to characterize genes that you have not yet identified. If you have no preliminary data, you don't know what genes or how many genes you will find. However, they will likely number in the hundreds. Simply saying that you will pick some interesting genes to study is a quick way to get a bad score on your grant. If possible, your experiment should test a hypothesis. For example, you might make the hypothesis that certain genes (e.g. apoptosis genes) will get induced. Then you can propose to use NGS assays to test that (and propose real-time PCR as a back-up approach). That way you can test a hypothesis, propose expected outcomes and controls (e.g. genes that should go up and down), which is a much better way of doing an NGS experiment (or any other experiment). Simply going fishing for genes is a bad approach and always draws the ire of the review committee.
  2. Simply saying that you will use some software program to analyze the data or group the genes into pathways is also going to get you in trouble. NGS data can be extremely complex, and will require statistical methods for analysis. The pathway data that is known is woefully incomplete. Most genes are not in the pathways, anyway.You will need a well-planned approach for analyzing the data. You should have a way of telling whether the experiment worked or not (e.g. did the expected apoptosis genes get activated?).
  3. The NGS experiment should not be merely a paragraph at the end of one of your aims. Whatever you do, absolutely do not add an NGS experiment to the end of a grant application as something that you "will also do". NGS experiments are big, expensive and complicated and they can't be done as an afterthought. Many, many grants have a one-paragraph description of an NGS experiment that the researchers will also do. That is a lightning rod for criticism from the reviewers.
  4. If you are looking for genes, you should be looking for them for a reason. Don't just propose to look for regulated genes without proposing to do something with them. Finding the genes that go up and down is not a significant enough goal. You need to be looking for genes with some purpose in mind (e.g. some hypothesis to be tested).