RNA-Seq has been used consistently for years as a way to determine gene expression by correlating mRNA levels to protein levels. However, the actual translation process in vivo cannot be completely captured by this method. This is because each mRNA molecule isn’t necessarily translated into protein by ribosomes. Ribosome Profiling was developed to help complete this picture.

In this blog, we’ll go over what Ribosome Profiling is, some real-world applications, a typical workflow, and how Genohub can help you with your Ribo-Seq project.

What is Ribosome Profiling?

In order to synthesize proteins, cells transcribe mRNA from DNA and then translate proteins from mRNA. Many researchers who want to study this gene expression process have used RNA-Seq, which provides data on the relative levels of mRNA within a cell. While the levels of specific mRNA often do correlate with the levels of particular proteins, standard RNA-Seq cannot provide actual data regarding gene regulation at the translational level. This is where Ribosome Profiling (Ribo-Seq) comes in.

Ribo-Seq is a sequencing method that uses specific ribosome-protected mRNA fragments (RPFs) to determine the mRNAs that are actively being translated in vivo. This snapshot can then be compared to parallel RNA-Seq done for the transcriptome to reveal the positions and amounts of ribosomes on any specific mRNA.

What are the applications of Ribo-Seq?

Ribo-Seq can help identify alternative mRNA translation start sites, confirm annotated open reading frames (ORFs) and upstream ORFs that may be involved in translation regulation, the distribution of ribosomes on an mRNA and the rate at which ribosomes decode codons. As Ribo-Seq can provide data about gene expression, protein synthesis and protein abundance, it can be useful in almost every type of research, including research on cancer, autoimmune disease, heart disease, neurological disorders, and psychiatric disorders.

The following are examples where Ribo-Seq was used in different types of research.

• Scheckel et al. used Ribo-Seq in combination with another technique to discover that aberrant translation within the glia only may be enough to cause severe neurological symptoms and may be a primary driver of prion disease.

• In this paper, the authors summarize multiple studies where Ribo-Seq was used to identify novel genes within plants that could be useful to increase yield through biotic and abiotic stress tolerance if manipulated.

• In this article, Ribo-Seq was used to reveal translated sequences within long noncoding RNAs and to identify other micropeptides within two herpesviruses, human cytomegalovirus and Kaposi’s sarcoma-associated herpesvirus. Understanding viral gene regulation and other aspects of the proteome are important for understanding their life cycle and identifying epitopes they may present for immune surveillance.

What is the typical Ribo-Seq workflow?

The typical Ribo-Seq workflow begins with collecting and preparing the lysate. First, the cells or tissue samples are harvested and flash-frozen to halt translation. Then, the samples are resuspended in a lysis buffer that includes a salt to stabilize the ribosomes, detergent to puncture the cell membrane, a deoxyribonuclease to degrade genomic DNA, a translation-inhibiting drug to halt the ribosome, and a reducing agent to stop oxidative compounds from interfering with RNA. After lysis, ribonucleases are added to digest the RNA that is not protected inside of the ribosomes. These fragments are called RNA protected fragments (RPFs). Then size selection is performed to identify the ~28 nucleotide RPFs on a gel, and RNA extraction is extracted. Any contaminating rRNA is removed, the RPFs are reverse-transcribed to cDNA, amplified by PCR and then made into libraries that are sequenced.

The data analysis done will ultimately depend on the researcher’s personal aim, but in general, ribosome profiling mapping would include data QC, demultiplexing and then removal of adapter sequences and any remaining rRNA contaminants. The samples would then be aligned to an annotated genome/transcriptome and then counts of the number of reads aligned to each gene would be obtained. These mapped RPFs can then be visualized and compared with what other researchers have done. More specific analysis can include uORF detection, differential gene expression, global translation rates, ribosome stalling, and codon decoding rates.

Where can I get help with my Ribo-Seq project?

As of now the Illumina kit for Ribo-Seq, TruSeq Ribo Profile or ART-Seq, has been discontinued. There is a commercially available all-inclusive library preparation kit, called LACESeq by IMMAGINA Biotechnology. However, Ribo-Seq sample and library preparation is so complex and sample-specific that many labs have their own protocols optimized for their specific samples and then use their favorite commercial small RNA-Seq kit for the last part of library prep. For labs that don’t focus on this type of work, optimizing such a protocol can be very time-intensive and expensive.

Genohub’s Ribo-Seq partners are experts in every step of the Ribo-Seq process, from lysis to custom data analysis, including preparing and running RNA-Seq libraries in parallel, allowing for the measurement of translation efficiency. Our in-network partners also have experience in isolating ribosome-bound mRNA from many different types of samples, including bacteria and eukaryotic cells, and animal and plant tissue. Their proprietary optimized Ribo-Seq protocols means they routinely produce high-quality libraries efficiently and effectively. All you would have to do is provide your frozen cell or tissue samples and let us do the rest.We will be with you every step of the way, from extraction to data analysis! Get started today by letting us know about your Ribo-Seq project here: https://genohub.com/ngs/ .

Illumina sequencing is by far the most common next-generation sequencing technique used today, as it extremely accurate and allows for massively parallel data generation, which is incredibly important when you’re working with a dataset the size of a human genome!

That said, there are inherent shortcomings that exist in the typical Illumina sequencing workflow. Illumina uses a very high number of short sequencing reads (usually about 150 bp for whole genome sequencing) that are then assembled together to cover the entirety of the genome. The fact that traditional Illumina can’t be used to identify long-range interactions can cause issues in some cases, such as samples with large structural variants or in phasing haplotypes.

However, a revolutionary new library preparation method designed by 10x Genomics can effectively solve these types of issues. The 10X Genomics GemCode technology is a unique reagent delivery system that allows for long-range information to be gathered from short-read sequencing. It does through usage of a high efficiency microfluidic device which releases gel beads containing unique barcodes and enzymes for library preparation. It then takes high molecular weight DNA, and partitions it into segments that are about 1M bp long; from here, these segments of DNA are combined with the gel beads. This means that each read that comes from that segment of DNA has its own unique barcode, which gives us knowledge about long-range interactions from traditional short reads.

Another application of 10X Genomics GemCode comes in the form of single-cell sequencing, which also uses the microfluidics device, but combines individual cells with the gel beads instead of DNA fragments. This allows for sequencing and barcoding of individual cells from a larger heterogeneous sample. This can work for DNA or RNA sequencing. 10c Genomics recently published an application of this technology using the Chromium Single Cell 3’ Solution on a mouse brain. Cells from embryonic mice brains were sequenced and profiled using this technique; principal component analysis and clustering was then performed on the resulting data to separate out the distinct cell types, identifying 7 major classes of cell types, as seen in Figure 1 [1].

Traditional Illumina sequencing will still likely reign supreme for run-of-the-mill applications, since at this point it is still more cost effective. However, the 10x system is gaining in popularity for specialized applications where understanding structural variants or single cell sequencing is important to the goals of the project. We’ve certainly noticed an uptick in projects that require 10x technology recently, and we look forward to seeing the advances that can be made with this amazing technology.

If you’re interested in projects using 10x Genomics sequencing tech, please contact us at projects@genohub.com for more information!

While a lot of attention has been paid in recent years to the advances made in sequencing the human genome, next-generation sequencing has also led to an explosion of sequencing used to study microbiomes. There are two common methods of sequencing performed to study the microbiome: 16S rDNA sequencing and shotgun metagenomics.

What is 16S sequencing?

The 16S ribosomal gene is thought to exist in all bacteria, but still has regions that are highly variable between species. Because of this, primers have been created to amplify conserved regions that surround variable regions, allowing researchers to target the areas of the genes that are similar to observe the areas that are distinct. Because this approach allows us to observe very specific regions of the genome, we can drop the sequencing needed per sample dramatically, only needing around 50,000 – 100,000 reads to identify different bacterial species in a sample.

The main drawback of this technique is that it can only identify bacteria, and does not identify viruses or fungi.

What is shotgun metagenomics?

Shotgun metagenomics surveys the entire genomes of all the organisms present in the sample, as opposed to only the 16S sequences. One of the main advantages of this over 16S sequencing is that it can capture sequences from all the organisms, including viruses and fungi, which cannot be captured with 16S sequencing. Additionally, it’s less susceptible to the biases that are inherent in targeted gene amplification.

Perhaps most interestingly, it can also provide direct information about the presence or absence of specific functional pathways in sample, also known as the ‘hologenome’. This can provide potentially important information about the capabilities of the organisms in the community. Furthermore, shotgun metagenomics can be used to identify rare or novel organisms in the community, which 16S cannot do.

So which one should I use?

Like anything else, it really depends. 16S studies can be incredibly useful for comparison across different samples (like different environments, or different time points). And some studies have found that 16S sequencing is superior in these types of studies for identifying a higher number of phyla in a particular sample [1], while other studies have of course found the exact opposite [2].

When it comes down to it, it’s really important to evaluate your project needs carefully depending on what you’re trying to accomplish. For example, a large scale project that looks to examine hundreds of samples in order to evaluate the differences in microbiota across different environments might very well prefer to use 16S sequencing, since it is so much more cost-efficient than metagenomics sequencing. On the other hand, a project that is looking to deeply investigate a smaller number of samples might be a better candidate for metagenomics sequencing, which would allow them uncover all the organisms that are present in a particular sample (including viruses and fungi), as well as identify the most dominant gene pathways that are present in that particular sample.

Day 2 of the of the FOGM conference showcased some truly fascinating breakthrough talks, particularly related to how we diagnose and treat cancer.

Dr. Todd Golub of the Broad Institute gave a phenomenal talk on the need for better pre-clinical models in order to get drugs to market faster. He and his team utilized a high-throughput screening method called PRISM (Profiling Relative Inhibition Simultaneously in Mixtures), which relies on 24 nucleotide long biological barcodes that are stably integrated into genetically distinct tumor cell lines that allows screening drug candidates against a large number of cancer cell lines.

Hillary Theakston of the Clearity Foundation spoke about the importance of helping patients and families to ‘live in the future of genomic medicine’. Her foundation focuses on helping women suffering from ovarian cancer, which really lags behind in terms of survival compared to to other cancers. It’s mostly diagnosed in stage 3 or 4, and only 30% of women make it past 10 years. Clearity helps these women by spending hours of individual counseling on their unique case, including performing genetic testing of their tumor and trying to get them into drug trials that may be beneficial for their specific type of cancer–in fact, 27% of Clearity patients end up in a clinical trial. I found this talk particularly moving–while the science at the conference was incredible, it’s so important that we not forget about the patients in the process.

Dr. Mickey Kertesz, the CEO of Karius, spoke about the importance of effective clinical diagnoses. While most of the FOGM talks were cancer-related, Dr. Kertesz spoke about how we can use genomic testing to inform infectious disease diagnostics and treatments. Infectious diseases are the cause of ⅔ of the deaths of all children under 5 years old, so getting the proper treatment in a timely manner is absolutely crucial. Currently, even after 8 days in a clinical setting, only 38% of patients are diagnosed. Karius aims to improve that with their end-to-end sample processing that is able to detect circulating microbe DNA samples in the patient blood and check it for over 1,000 pathogens (possibly using 16S or metagenomic sequencing), leading to 50% of patients diagnosed in just ONE day–an enormous improvement.

Dr. C. Jimmy Lin of Natera spoke about his company’s new personalized liquid biopsy, Signatera. Signatera aims to increase the speed at which we detect cancer relapses by determining the unique clonal mutations in each patients tumor. They can then look for circulating cell-free DNA in the blood and sequence it deeply only on those specific genes (i.e., custom amplicon sequencing), looking for those same clonal mutations in the blood. Using this pipeline, they are able to detect relapses up to 100 days before they can be clinically diagnosed. The next step will be show that this can improve clinical outcomes. I wish them the best of luck with this–this could be a game-changer for diagnostics.

Dr. Kate Rubins is the first person to sequence DNA in space! It’s hard to describe how amazing this is. There are a lot of technical challenges to overcome when working in a vacuum, but Kate was able to successfully pull this off. Be able to sequence samples during space flight will certainly prove to be useful when we eventually take our first long-term mission and want to be able to sequence the samples we find ASAP!

That’s it for the Future of Genomic Medicine conference! Of course, all of the talks were fantastic and I didn’t have the space to summarize them all here. Check out the course overview here for more details.

 

 

It’s hard to imagine a better conference setting than the Scripps Research Institute, where you can listen to scientific talks while literally sitting right next to the beach! It’s even better when those talks are as interesting as they were. The FOGM conference covered a lot of ground:

Dr. Juan Carlos Izpisua Belmonte discussed his latest findings using the homology-independent targeted integration (or HITI) to target non-dividing cells–a key feature that means it could be used to treat adults and not just embryos. He has previously shown that they could insert treat rats with retinitis pigmentosa using this system, and they showed improvement in their ability to respond to light and healing in their eyes. In his talk at the conference, he was also able to use this same technique to alter the epigenetic landscape of mice suffering from progeria, a genetic condition that induces rapid aging, and show improved organ function and lifespan. He hopes to use this discovery to move us towards eventual treatments for the symptoms of aging–the one disease that we all suffer from. See here for the full picture.

Dr. Paul Knoepfler presented an elegant model of epigenetic effects in pediatric glioma. Pediatric gliomas are nearly 100% fatal even with the best treatments, and the treatments are incredibly severe. Children with this disease are given the same treatments as adults, but what if the tumors are different?

Well, it turns out that they are different. Dr. Knoepfler showed that pediatric gliomas frequently possess two unique point mutations in histone H3.3, and that these mutations aren’t seen in the adult gliomas. It seems astonishing that these two point mutation can convey such incredible lethality, but in fact, even small histone mutations can be incredibly lethal because of the effect on the epigenetic landscape (seen via ChIP-seq by Bjerke et al).

So, Dr. Knoepfler wanted to see if reversing these two mutations in these cancer cells could reverse the phenotype, and additionally, if doing the opposite (causing those two mutations in normal brain cells) would induce the cancer phenotype. In fact, in both cases, either reversing or causing those mutations caused an immense transcriptional shift in the opposing direction, indicating that these two point mutations are enormously important in this cancer type. Dr. Knoepfler wants to use this information to create mouse models and test new drug treatments to see which of them can be most effective against this particularly aggressive cancer.

ROC curves for Dr. Mesirov’s predictive models, which outperform current clinical predictions.

Dr. Jill Mesirov also gave a very informative talk regarding pediatric brain tumors. Her lab applies machine learning and statistical techniques to find molecular markers to aid in the identification and stratification of cancer subtypes. She examined the RNA profiles from several pediatric medulloblastoma tumors using RNA-seq and found 6 different subtypes in the RNA profiles with vastly different survival rates. Using this model, she was able to categorize 15 patients that were diagnosed as ‘low-risk’ using traditional diagnostic methods as actually being ‘high-risk’–and 6 of these patients went on relapse within 3 years. Dr. Mesirov wants to use this model to help identify novel therapeutics for the particularly deadly myc-driven cancer subtype, and hopefully improve clinical outcomes.

Bonnie Rochman’s talk focused more on the sociological effects of modern genomic medicine, particularly with respects to having children. She asked some tough questions of the audience regarding prenatal testing for Down’s syndrome, or early childhood screening for genes like the BRCA1/2 genes, which predispose a person to breast cancer. Additionally, our ability to gather genomic data far outpaces our ability to accurately interpret said data, which leads to a lot of anxiety around what all this genetic testing actually means. She concludes that ultimately, there are no right or wrong answers regarding this subject–everyone has their own thoughts and feelings, shaped by their experiences with their own genetics. You can read more in her book here. 

Those were my favorite talks from the first day….check out the Day 2 summary tomorrow!

The first day of the FOGM conference was absolutely incredible! I learned so much and heard some fascinating science, as well as met some truly amazing scientists and entrepreneurs. Here are the talks I’m most looking forward to today!

Todd Golub, MD, Speaking on Cancer Genomics

Dr. Golub has been a key member of important institutions such as the Broad Institute and Harvard Medical School, and made important discoveries in the genetic basis for childhood leukemia.

Mickey Kertesz, PhD, Speaking on Circulating DNA and RNA

Dr. Kertesz is the CEO of Karius, a company dedicated to making pathogen detection easier to implement for patients. He has a PhD in computational biology and did postdoctoral work at Stanford in investigating the genetic diversity of viruses.

Ash Alizadeh, MD, Phd, Speaking on Circulating DNA and RNA

Dr. Alizadeh studies the genomic biomarkers of tumors, particularly looking at non-invasive methods of detecting cancer such as looking for circulating tumor DNA (ctDNA in the blood). Shouldn’t be missed!

Jimmy Lin, MD, PhD, MHS, CSO, Speaking on Circulating DNA and RNA

Dr. Lin led the first ever exome sequencing studies in cancer and is the CSO of Natera.

Alicia Zhou, PhD, Speaking on Predictive and Preventative Genetics

Dr. Zhou studied the effects of the c-Myc oncogene in triple negative breast cancer, and currently works as the Head of Research at Color Genomics to bring population genetics to full populations.

Leslie Biesecker, MD, Speaking on Predictive and Preventative Genetics

Dr. Biesecker developed the ClinSeq® program in 2006, before the wide availability of NGS. I’m looking forward to hearing his perspective on preventative genetics.

Robert Gould, PhD, Speaking on Epigenetics

Dr. Gould has had an incredibly distinguished career. He’s currently President and CEO of Fulcrum Therapeutics–prior to that, he served as the director of novel therapeutics at the Broad Institute and spent 23 years at Merck.

Kathleen Rubins, PhD, Speaking on Our Genomics Past and Future

Dr. Rubins is the first person to sequence DNA in space! Need I say anything more?

Many of the most difficult to treat diseases that exist today have genetic origins, and one of the most difficult things about devising new treatments is the lack of connection between the research and clinical sides of biology. Because of that, the Future of Genomic Medicine conference is one of the most interesting ones to attend, because a truly fantastic mix of PhDs, MDs, and others (which this year includes journalists, CEOs and an astronaut!) have an opportunity to present and create new connections in this community.

There are so many fascinating speakers that it’s difficult to narrow it down, but here are some to watch out for on Day 1:

Eric Topol, MD, Speaking on the Future of Individualized Medicine

Dr. Topol is the founder and direction of the Scripps Translation Science Institute and in 2016 was awarded a $207M grant to lead a part of the Precision Medicine Initiative. He is one of the organizers of the Future of Genomic Medicine and has been voted the #1 influential physician leader in the US by Modern Healthcare.

Andre Choulika, PhD, Speaking on Genome Editing

In his post-doctoral work, Dr. Choulika was one of the inventors of nuclease-based genome editing and currently serves as CEO of Cellectis. We’re very interested in what he has to say on the current state of genome editing!

Paul Knoepfler, PhD, Speaking on Genome Editing

Dr. Knoepfler is not just a cancer researcher, but also a cancer survivor. He is currently studying the epigenetics of cancer and stem cells, using many techniques including CRISPR. It will be interesting to see how he uses genome editing and CRISPR in his research! He is also an active blogger and author.

Mark DePristo, PhD, Speaking on Data Science in Genomics

Dr. DePristo was part of the team that developed the GATK, one of the most prominent softwares for processing next-generation sequencing data. He currently is the head of the Genomics team at Google.

Jill P. Mesirov, PhD, Speaking on Data Science in Genomics

Dr. Mesirov does fascinating work applying machine learning to cancer genomics to stratify cancer patients according to their risk of relapse and identifying potential compounds for treatments.

Viviane Slon, Graduate Student, Speaking on Genetics of Human Origins

It’s so great to see a graduate student speaking at a conference! Viviane studies the DNA of our closest extinct relatives. It should be interesting to see her new data!

Eske Willerslev, DSc, Speaking on Genetics of Human Origins

Dr. Willerslev is an evolutionary geneticist most known for sequencing the first ancient human genome–it should be interesting to hear his perspective on human origins!

Keep an eye out for my highlights for Day 2 coming tomorrow!