Analytical and Translational Genomics
The ATG is accessible to all researchers at the University of New Mexico (UNM) and its related institutions. Nevertheless, it is essential for you to provide a citation for the P30CA118100 and also mention ATG, along with other UNMCCC shared resources that were utilized to produce the data.
In order to give credit to our contributions, we kindly request that you include the following line in the acknowledgment section of your manuscripts:
This study received partial funding from the UNM Comprehensive Cancer Center Support Grant NCI P30CA118100 and utilized the Analytical and Translational Genomics Shared Resource.
The Analytical and Translational Genomics Resource remains up-to-date on the latest assays and technology for addressing different research questions. If there is an application that you are interested in but cannot find on this website, please feel free to inquire.
ATG's primary focus is to offer advanced sequencing technology to assist researchers in comprehending biological conditions. Our services include spatial and single-cell genomic assays, bulk RNA-seq, Whole Genome Sequencing, targeted gene panel sequencing, and chromatin state assays such as ChIP-seq and ATAC-seq. We also offer expert bioinformatics analysis. The ATG Shared Resource is accessible to all faculty members at UNM and its affiliated institutions. We strongly urge investigators to contact us to explore how we can assist with their research and identify the most suitable assays to meet their goals.
Spatial genomics examine the transcriptome within the context of the 3D structure of the tissue. 10X Visium, Visium HD, and Xenium in situ assays can precisely determine the locations of transcripts within tissues and single cells. This enables gene expression analysis concerning neighboring cells, facilitating a deeper understanding of substructures, intercellular communication, and networking.
Single-cell assays enable researchers to evaluate the transcriptome and epigenetics at the level of individual cells. ATG employs the 10x Genomics Chromium platform to offer state-of-the-art single-cell sequencing. Various assays can be combined in multi-omic approach, enabling the analysis of a single sample in various ways. The source material might consist of live cells, isolated nuclei, or fixed samples. The use of fixed samples allows for the inclusion of archived material.
Immune cell profiling involves the analysis of immune cell diversity, which can be combined with transcriptomic assays.
Bulk Genomics refers to sequencing projects that analyze samples as a whole and do not necessitate the analysis of single cells or spatial information. Some examples of these techniques are RNA-seq, ChIP-seq, Whole Exome Sequencing (WES), and Whole Genome Sequencing (WGS).
Long read sequencing enables researchers to examine isoform usage within a sample. While we do not have a long read sequencer, we can provide some unrestricted read length (max length > 4Mb) using MinIONs from Nanopore Technologies.
Bioinformatics Data Analysis: The ATG Shared Resource staff employs advanced data analysis techniques to examine gene expression and genotyping data. Our goal is to offer our users high-quality figures suitable for publishing in their articles or grant applications. At present, we utilize R/Bioconductor software packages to analyze the extensive and intricate data sets produced by genomics techniques.
ATG can sequence the following types:
- Detection of mutations or gene variants. This could involve assessing the level of genetic mutations in a tumor, analyzing specific genetic variations in a particular cancer or disease, or evaluating how cells respond to DNA damage after injury or treatment. Typically, this is achieved by using targeted gene panel sequencing to analyze genes linked to cancer or certain diseases.
- Gene expression studies. Transcriptional profiling of cells, tissue, organoids, or patient samples, either as individual cells or in larger quantities.
- A range of chromatin state analysis assays, from DNA methylation studies to ATAC assays to ChIP-seq, are available.
- Studying non-coding RNAs such as ncRNAs, lincRNAs, and miRNAs.
Please contact either Kel Cook (kelcook@salud.unm.edu) or Kathryn Brayer (kbrayer@salud.unm.edu) to schedule a consultation.
ATG uses iLab for billing.
For questions regarding iLabs or for account/PR set-up for use in the shared resource, please email Mary Sherman or call 505-272-4539.
Genomics Instruments
The G4 Sequencer
- Flexible and fast paired-end sequencer
- Capable of producing up to 1.6 billion 2 x 150 bp reads in 24 hours
- Can be configured for a variety of read lengths
- Compatible with almost all libraries that can be sequenced on Illumina instruments.
For more information: https://singulargenomics.com/g4/
The 10x Genomics Chromium iX
- Partitions cells or nuclei for single-cell sequencing
- Captures RNA, protein, and/or chromatin
- Assay gene expression, immune cell repertoire, chromatin accessibility, CRISPR perturbations
- Inputs vary with assay, but include live cell suspensions, nuclei, fixed cells, frozen tissue, and FFPE blocks. Species agnostic assays available
For more information: https://www.10xgenomics.com/instruments/chromium-x-series
The 10x Genomics Xenium Analyzer
- Spatial transcriptomics imaging platform
- Sub-cellular resolution
- Capable of capturing up to 5,000 genes
- Multiple pre-designed gene panels that can be further customized (https://www.10xgenomics.com/products/xenium-panels)
For more information: https://www.10xgenomics.com/platforms/xenium
The 10x Genomics CytAssist
- Facilitates Visium and Visium HD spatial transcriptomics assays
- Start from FFPE blocks or pre-cut FFPE and fresh-frozen sections
- Compatible with H&E or immunofluorescence stained sections
For more information: https://www.10xgenomics.com/instruments/visium-cytassist
- Agilent Bioanalyzer: Analyze DNA and RNA quality/quantity using minimal inputs. (https://www.agilent.com/en/product/automated-electrophoresis/bioanalyzer-systems/bioanalyzer-instrument)
- Qubit II Fluorometer: DNA and RNA quantification.
- Invitrogen Countess II FL: Count cells and quantify proportion of live cells in a sample.
- Miltenyi Biotec gentle MACS Octo Dissociator with Heaters: Dissociate tissue samples prior to single-cell sequencing.
- Qiagen EZ2: Automated DNA and RNA extraction.
Select instruments are available for use by qualified and trained members of the UNM community. Shared instruments are available during regular working hours and at other times by special arrangement. Please get in touch with the ATG Facility staff for more information about assays and pricing.
ATG FAQs
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.
Bulk RNA-seq can be successfully performed with minimal amounts of RNA, as little as 1ng of mRNA. ATG checks their integrity (RIN) upon receiving RNAs, using the Agilent Bioanalyzer. Suggested inputs for RNA-seq are 150 ng of total RNA for high-quality RNAs and 250 ng for degraded RNAs (e.g. FFPE RNA). RNAs are then ribodepleted to remove unwanted rRNA, which makes up ~90% of RNA in cells.
NGS experiments can be expensive, and the costs vary depending on the assay in question. Additionally, the total cost depends on the kit being used to construct the libraries and the sequencing depth required. Please get in touch with the staff to get more information and to get a quote.
NGS assays produce extensive, complex data sets that contain enormous amounts of information but can also be challenging 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.
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). More in depth analysis, such as correlating results to patient information, should be performed with the input 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. Please discuss your analysis needs with staff members.
Verification is an integral part of each NGS experiment, and the requirements vary depending on the type of experiment. Please get in touch with the ATG staff to discuss options for verifying NGS results.
The facility Director, Viswanathan Palanisamy, Ph.D., can provide letters of support and advice about describing the ATG Shared Resource and potential NGS experiments in grant applications. Dr. Palanisamy has served on numerous NIH, ACS, and DOD study sections and reviewed many grant applications, including NGS experiments. His own funded grants have NGS experiments in them. He can help with writing sections of your grant regarding NGS experiments and 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.
- 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 hypothesize 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.
- 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?).
- 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.
- 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).