RetiGene is an expert‑curated, openly accessible atlas integrating variant data, bulk and single‑cell RNA‑seq, and functional annotations for genes linked to inherited retinal diseases to aid diagnosis and research.
0:19Welcome to Base by Base, the paper cast that brings genomics to you wherever you are. Thanks for listening, and don't forget to follow and rate us in your podcast app. So imagine for a moment that you are sitting in a doctor's office.
0:32You've noticed your vision has been deteriorating for a while. Right, like maybe it starts with something small, like night blindness. Exactly. You know, you couldn't see well in dimly lit restaurants or driving at dusk was getting a bit scary.
0:45But now it's worse. Your peripheral vision is actually closing in, almost like you're looking through a tunnel. Which is a terrifying experience for anyone to go through. Yeah, and the doctor looks at you and delivers the news.
0:57You are losing your sight. And naturally, you ask why, right? The doctor says it's genetic. It's written right there into your DNA. But then comes the truly frustrating part of the whole process. Right, because when you ask them to pinpoint exactly which gene is causing it, they kind of hesitate.
1:13They tell you that they know it's a genetic condition, but their map of the human genome is, well, it's incomplete. Yeah, they simply can't find the specific typo in your DNA that's actually causing your blindness.
1:28It's just wild to me. Today we celebrate the work of the Institute of Molecular and Clinical Ophthalmology in Basel, along with a massive global consortium of researchers, who have advanced our understanding of inherited retinal diseases, because they've basically set out to fix this exact problem.
1:45And it is a massive problem. I mean, it is a devastating position for a patient. We go into a medical clinic expecting modern medicine to have a very precise binary answer for us. Right, we want a clear label.
1:57We wanna know what we're fighting. Exactly. But the diagnostic landscape for these specific conditions is incredibly murky. Patients often spend years, sometimes decades, in a diagnostic odyssey. Just jumping from specialist to specialist, without a clear answer.
2:11So welcome to our deep dive for today. We are on a mission to unpack a groundbreaking 2025 paper published in the American Journal of Human Genetics. And we are going to try and solve this diagnostic mystery for you.
2:22Yeah, so this international research consortium has created something called Redigene, which is this definitively curated gene atlas for inherited retinal diseases or IRDs. And it's desperately needed.
2:34Our goal today is to figure out why the old genetic maps were failing patients so badly, how this new map was built, and what it reveals about the incredibly strange biology of blindness. So to grasp the magnitude of what the Redigene team has achieved, I feel like we 1st need to define the sheer scale of the problem.
2:54Yeah, we really do. Inherited retinal diseases are characterized by what is quite possibly the highest genetic heterogeneity of all human genetic diseases. Wait, meaning there's just a ton of different genes involved?
3:06Exactly. We are talking about a dizzying array of completely different genetic variations that can all lead to very similar clinical outcomes. Right, which usually present as stationary or progressive visual impairment.
3:19But we should probably define what we're actually looking at here, anatomically speaking. Good point. We're talking about the retina, which is that paper thin, photosensitive tissue lining the very back of your eye.
3:29It operates a lot like the biological center of a digital camera, right? Converting light into electrical signals, so our brain can actually process an image. That's a great way to think about it. And it relies on some highly specialized cells to pull that off.
3:43You have your rods, which handle vision in low light conditions and your peripheral vision. And then the cones. Right, your cones, which are packed tight in the center of the retina. Those give you sharp central vision and color perception.
3:57There's also the layer behind them, right? The RPE. Yes, the retinal pigment, epithelium, or RPE. This is a crucial support layer. It nourishes the photoreceptors, clears away their waste, and recycles the molecules they need to detect light.
4:11So basically, when mutations happen in the genes that build or maintain any of these cellular structures, you get an IRD. Exactly. But reading through the sources, these diseases aren't all uniform at all.
4:23The paper makes a really clear distinction between non-syndromeic and syndromeic diseases. Right, so non-syndramic diseases strictly affect the eye. Like retinitis pigmentosa, which I think the paper said is the most common one.
4:35Yep, that's correct. And then syndromic means the eye is effective. But so are other major organ systems in the body. Like Usher Syndrome. Right, where patients experience progressive vision loss, but it's combined with deafness.
4:47Exactly. The clinical distinctions are well known by doctors, but here is where we hit that diagnostic wall you mentioned in the intro. The missing typo in the DNA. Right. We are living in the golden age of genomics.
4:59We have next generation sequencing, whole exome sequencing, whole genome sequencing. We have all these amazing tools. We do. Yet the diagnostic rate for IRDs in the scientific literature is stubbornly stuck between 53% and 76%.
5:15That is just wild to me. I mean, we have supercomputers and advanced sequencing technologies that can literally read an entire human genome in hours. And still, at least a quarter of patients are walking away without a definitive molecular diagnosis.
5:29It's like, okay, it's like trying to run a spell check on a massive manuscript. Yeah, but your dictionary is missing half the words. Or even worse, your dictionary has words in it that are spelled wrong to begin with.
5:39Right. So how did the data get so messy in the 1st place? Why is the dictionary broken? It really comes down to the relentless, almost chaotic pace of genomic discovery over the last few decades. Like we were just moving too fast.
5:52Exactly. Since the genomic revolution kicked off, researchers have been finding new disease associated genes at breakneck speed. Which sounds like a good thing, right? It is, but without constant, rigorous manual curation by human experts, these diagnostic catalogs become obsolete very, very quickly.
6:10Oh, I see. So laboratories end up using incomplete or outdated list of disease associated genes to design their commercial testing panels. Precisely. So a lab might run a massive, expensive genetic test on a patient, but they are looking for the wrong thing.
6:25Or completely ignoring a newly discovered gene because it simply hasn't been added to their specific software update yet. Right. So to fix this broken dictionary, the researchers behind Reddigene systematically mined public databases, sequencing data, and published literature to create a definitive expert curated list. And they pin down exactly 470 genes.
6:46and 4 specific low sci that have strong proven links to IRDs. Which is a huge achievement. It really is. But what caught my attention in this study is the history of how we actually found these 470 genes.
6:59It paces really clear picture of how our technology has evolved. Yeah, the historical trend they mapped out is fascinating. So the very 1st IRD gene, which is called OAT, is linked to a condition called gyrate atrophy.
7:13And that was identified back in 1988, right? Correct. And for a couple decades after that, gene discovery grew at this very steady linear pace of about 13 new genes per year. Because researchers were largely relying on older, really painstaking methods like linkage analysis.
7:29So let's break linkage analysis down for a 2nd because it sounds incredibly tedious compared to what we do today. Like, how are we actually finding genes in the 80s and 90s? Well, imagine trying to track a physical trait through a massive family tree.
7:41Linkage analysis requires huge families with clear inheritance of a disease across generations. Okay, so you need a lot of people who are related and share the condition. Exactly. And researchers would look for physical markers on the chromosomes that seem to be passed down alongside the blindness.
7:56So they were hunting for physical proximity of DNA markers. Right. Right. Narrowing down the region chromosome by chromosome. It was incredibly slow, almost analog detective work. Wow. And then 2010 happened.
8:07The researchers note that in 2010, the 1st IRD gene, FM 161A, was identified using next generation sequencing, or NGS. And that kicked off a massive boom in discovery. Suddenly, we were finding roughly 26 new IRD genes every single year.
8:24It was a total genomic gold rush. But how is NGS so fundamentally different from that old linkage analysis? Why was it so much faster? Well, instead of tracing markers through multi-generational families over years, next generation sequencing allows us to shatter the patient's genome into millions of tiny pieces.
8:42Literally breaking it apart. Right. And then we read all those pieces simultaneously using fluorescent tags, and let supercomputers stitch the massive puzzle back together. So we went from reading a book letter by letter to taking a high-definition photograph of every single page in the library at once.
8:57That's exactly what it was like. But wait, I'm looking at the timeline in the paper. And after that massive boom, discoveries have completely plummeted. Yeah, there's a sharp drop off. Like, in 2024, they only found 6 new genes.
9:10I'm really stuck on this. We have AI, we have massive global databases, our sequencing tech is cheaper and faster than ever before. You're telling me we only found 6 genes. Are we sure our tech isn't just failing to see complex mutations?
9:26That's a really valid question. Like, what about massive structural variance where entire chunks of DNA are flipped or missing or mutations hidden deep in the non-coding regions of our DNA that standard tests just ignore.
9:39So those complex structural variants and deep intronic mutations certainly play a role, and researchers are actively building new tools to find them. But the primary driver for this crash in discovery is actually a statistical concept known as gene specific genetic prevalence.
9:53Meaning what, exactly? Essentially it means the easy genes have already been found. Ah, but easy, you mean the most common ones. Yes. The genes that account for large numbers of patients are the ones that show up in large, easily trackable pedigrees, those were all scooped up during that 2010 boom.
10:11So the undiscovered genes that are left are just incredibly rare. Extremely rare. A mutation in one of these unknown genes might only cause disease and a single family on the entire planet. Oh, wow. So the haystack isn't getting bigger, but the needles are getting infinitely smaller and rarer.
10:27That's a perfect analogy. And our older methods heavily biased what we found first, too. Like mitochondrial diseases. Right, right. Mitochondrial diseases and excellent conditions were discovered earlier because their inheritance patterns are visual obvious in a family tree.
10:41And I imagine dominant mutations were easier to spot than recessive ones. Exactly, because you need fewer affected people in a family to trace a dominant trait. So we are now living in the long tale of discovery, basically hunting for the most elusive, ultra rare, recessive mutations.
10:57Okay, so we finally have this accurate, definitive list of 470 genes. But my immediate question is, what are all these Gs actually doing in the eye? That's where the data gets really surprising. Yeah, because once the Reddigene team pinned these genes down.
11:12They categorize them by their biological function. Right. And if you had asked me before I read this paper, I would have assumed most of the genes causing blindness were specifically built for seeing like the biological camera lens or the actual phototransduction process of catching a photon of light.
11:32And you wouldn't be alone in that. That is a widespread assumption, and historically, early genetic researchers thought the exact same way. Really? Yeah, they actively designed their experiments to target genes involved in the visual cycle, but this modern, unbiased mapping by the Redigene team completely upended those expectations.
11:51It totally did. The number one functional category for these disease genes isn't processing light at all. It's the pilium. Yes. Almost 18% of the genes are dedicated to building and maintaining cilia. Meanwhile, genes linked to the visual cycle and photo trans section, the actual light catching process.
12:08Make up less than 7% of the genes. It's a massive shift in how we understand these diseases. I have to admit, when I hear the word cilium. I picture those tiny hairs on a paramecium from, like, high school biology?
12:21What is this cilium doing inside my eye? It's a great question. To understand why the cilium is so critical. You have to picture the microscopic anatomy of a photoreceptor cell. Okay, I'm picturing it.
12:33A rod or a cone cell has 2 main parts. The outer segment is packed with thousands of membranous disks that physically catch the light. Got it. And then the inner segment houses the cell's nucleus and all its manufacturing machinery.
12:48Right, the factory. Connecting those 2 massive segments is a tiny, incredibly narrow structure called a connecting cilium. So it's like a single narrow hallway connecting a massive factory to a massive warehouse.
12:58That is a perfect way to visualize it. And the photoreceptor has to transport an immense amount of newly manufactured proteins and lipids through that narrow hallway every single day just to keep the outer segment functioning.
13:10Wow. Every single day. Yes. So if the genes that build that pelium or the genes involved in transmembrane transport or lipid metabolism are mutated, the whole cellular transport system just backs up. It gets clogged.
13:25Exactly. The cell effectively chokes on its own metabolic demands and undergoes programmed cell death. So IRDs are largely diseases of broken cellular plumbing and structural transport. Rather than a broken camera lens.
13:39Precisely. And that structural failure ties perfectly into how these diseases are passed down through families. Right, because the paper notes that a massive 68.9% of these 470 genes follow an autosomal recessive inheritance pattern.
13:52Which tells us a lot about the mechanism of the disease itself. Autosomal recessive inheritance usually implies a loss of function variant. unpack that. Yeah, because you inherit 2 copies of every gene, right?
14:03One from each parent. Correct. In autosomal dominant conditions, sometimes inheriting just one mutated copy is enough to actively cause havoc. Because the mutated protein might become toxic and interfere with the cell.
14:14Exactly. But in autosomal recessive conditions, you need both copies to be broken to get the disease. Right, because of Apple sufficiency. Yes. Appless efficiency means that as long as you have one good working copy of the gene, your cells can manufacture enough normal protein to get by.
14:31But if both copies are broken, the protein is just completely absent. It's just not there at all. So going back to the plumbing analogy. And autosomal dominant mutation is like a pipe that's actively leaking toxic sludge into the cell.
14:45Right. But an autosomal recessive mutation means the pipe is just completely missing from the blueprint entirely. It a structural void. That's a great analogy, which aligns perfectly with why so many of these diseases stem from failing cilia and transport systems.
14:58The cell just loses a crucial piece of its basic infrastructure. But this revelation introduces a fascinating paradox, which the researchers explore deeply using RNA sequencing data. They looked at bulk RNA data from across the entire human body using the Phantom M5 data set.
15:15The Phantom 5 data set. Let's clarify that for a second. That's a massive global research project that mapped exactly how genes are turned on and off in different tissues across the human body. Correct.
15:25It provides a map of where in the body a specific gene is actually active. And this leads to the housekeeping paradox, which honestly blew my mind when I read it. It is pretty counterintuitive at first glance.
15:36Because if IRDs are largely caused by basic cellular plumbing issues, missing pipes, broken transport corridors, why do these genetic mutations only cause blindness? You would logically assume that if your basic cellular plumbing is completely missing, your liver, your heart, and your kidneys would be failing too.
15:54Exactly. But the data highlights this paradox beautifully. It shows that 40.1% of the genes linked strictly to non-syndromic IRDs. Meaning diseases that only affect the eye and nowhere else. Right. 40% of those genes are actually ubiquitously expressed.
16:12They are known as basic housekeeping genes. Meaning they are active in tissues all over your body, doing core metabolic tax, like nucleotide metabolism, basic RNA splicing, or running the TCA cycle. Let's define the TCA cycle simply.
16:26We're talking about the cell's basic energy engine, right? The Krebs cycle, producing ATP for the cell to run on. That is the core of it. These are fundamental processes required by almost every cell just to stay alive.
16:37So if every single cell in my body has this exact same broken gene for its energy engine, Why is only my retina degenerating? That's a great question. It feels like having a corrupted file in your computer's core operating system, but somehow, only your web browser crashes while everything else runs perfectly fine.
16:56Yeah, the body is weird like that. I kept thinking about this in terms of cars, actually. The retina is basically the high performance Formula One racing engine of the human body. Okay, I like where this is going.
17:07If you put slightly degraded, low quality oil into a standard commuter car, it probably runs fine. It adapts to the inefficiency. Right, right. It gets you to the grocery store. Exactly. But if you put that same degraded oil into an F1 engine, screaming at 15,000 RPMs.
17:23The entire thing just shatters. Yes, the whole thing explodes. And the metabolic demands of the retina back that analogy up completely. The retina has arguably the highest metabolic demand of any tissue in the human body per gram of weight.
17:35Really? The highest? Yes. It is constantly firing electrical signals. Furthermore, photoreceptors show about 10% of their outer segment volume every single day. Meaning the cell has to constantly manufacture and transport new proteins just to rebind itself over and over.
17:52Exactly. Add to that, the massive oxidative stress of constant light exposure. Because it operates at such extreme biological limits, the retina is exquisitely vulnerable to minimal metabolic disturbances.
18:07So your liver or your skin can easily tolerate a slight inefficiency in housekeeping gene. Right. The retina simply cannot survive it. Okay, so we know these genes are broken everywhere in the body, but the eye fails because it's so demanding.
18:20But how did the researchers actually prove which specific cells inside the eye were failing? Well, they moved from bulk tissue data to single cell RNA sequencing. which is a huge leap in technology. It really is.
18:31This technology allows researchers to look at individual cells within the retina and see exactly which genes are turned on in a rod versus a cone versus the RPE. And the single cell data provided confirmation of what doctors actually see in the clinic, right?
18:43Exactly. For example, they saw that genes causing pure color vision disorders were exclusively expressed in cones, the cells responsible for color. makes total sense. And genes causing retinitis pigmentosa, which usually starts with night blindness, were heavily expressed in rods.
18:59But this brings up another tricky part of this whole map. Sometimes the exact type of mutation inside a single gene changes the entire flavor of the disease. Oh, absolutely. How does a single gene cause two entirely different conditions?
19:14This brings us to the mechanics of the mutation itself. The researchers highlighted genes like CRB1. Let's look at how the DNA code is disrupted. A patient could have a truncating variant or they could have a mis sense variant.
19:26Let me guess. Truncating means the code just stops. It's cut off prematurely. Literally a premature stop sign in the DNA. The protein is either entirely absent or completely destroyed before it can even function.
19:39And what does that do to the patient? In the case of CRB1, a complete loss of function leads to labor congenital amorosis, which is an incredibly severe form of blindness that appears in early infancy.
19:49Oh, wow. And what about a mis sense variant? A mis sense variant is like a single typo in a massive word. One amino acid is swapped for another. So the protein is still built by the cell. It is. It just folds slightly incorrectly.
20:04The structure is wonky, but it retains some partial function. And that partial function is enough to prevent infancy blindness. Right, but the inefficiency leads to a milder later onsa condition, like retinitis pigmentosis.
20:18So it's not just if the gene is broken, it's how it's broken. And this is exactly why this entire deep dive isn't just an academic exercise in mapping DNA. This database, retigene is actively changing patient diagnoses in real time.
20:30It's having an immediate clinical impact. Because the team didn't just add 470 genes to the map. They aggressively cleaned house. They actually excluded 17 genes that were previously thought to cause blindness, but actually had conflicting or bad data.
20:44And the clinical impact of throwing up bad data cannot be overstated. We discussed earlier how clinical labs sometimes use outlated lists containing false positives. The researchers highlight a specific gene called UNC 119.
20:57Currently, UNC 119 is included on many real world diagnostic panels for dominant retinal diseases. But the Redigene team, classified UNC 119 as discarded. They completely threw it out. How did a gene like UNC 119 get falsely blamed for blindness in the 1st place?
21:15Did early researchers just guess? Not a guess, but a casualty of the era it was discovered in. Decades ago a researcher might find a genetic mutation in one or 2 small families suffering from blindness.
21:26At the time, they didn't have massive global databases of healthy people to compare it against. They saw the mutation in the sick patients, saw it track with the disease in that tiny sample, and assumed it was a cause.
21:39But now we have those massive global databases. Yes, resources like Nomad A, which aggregates sequence genomes from 100s of 1000s of individuals worldwide. So what happened when they checked it? When the Redaging team checked UNC 119 against these modern databases, they found that those supposedly disease causing mutations are actually floating around everywhere in perfectly healthy people with 2020 vision.
22:00Oh wow. Yeah. The mutations didn't clearly co-segregate with the disease in newly studied families, and the gene itself seems completely tolerant to having truncating variants. The modern evidence proves the old association was just a false alarm.
22:14Imagine you're the patient who was told five years ago that UNC 119 was the cause of your blindness. It's heartbreaking. You get a lab report blaming this gene, and Redigene is basically raising its hand and saying, keep looking, your real mutation is still hiding.
22:30The psychological and clinical impact of a misdiagnosis is massive. It really is. If a patient is told they have a dominant mutation in UNC 119, their genetic counselor will inform them that their children have a 50% chance of inheriting the disease.
22:45Wow, so they might make major family planning decisions based on completely false information. Exactly. Furthermore, they might be excluded from future clinical trials for the actual gene causing their disease, simply because they have the wrong label on their medical chart.
22:59Discarding incorrect genes is fundamentally a matter of patient safety. It ensures that when a family finally gets an answer, it's the real answer. So to synthesize the journey we've taken today. The international team behind Redigene has given the medical community a dynamically updated, expertly curated map of 470 definitively linked genes.
23:20An incredible tool. By meticulously cataloguing the inheritance patterns, the cellular functions, proving that this is largely a disease of structural plumbing, and the specific cellular expression of these genes, they're breaking through that 53% diagnostic bottleneck.
23:34And as we move into an era of highly targeted gene therapies where we are literally using viral vectors to deliver healthy copies of specific genes directly into the retina to restore site, we absolutely must have a flawless map.
23:47You can't fix it if you don't know what's broken. Right. You cannot design a precision therapy if you do not know exactly which genetic target to hit. It is the absolute foundation of precision medicine.
23:57But as we wrap up, I want to leave you with a thought to mull over. We talked about the housekeeping paradox, how the retina is so uniquely demanding, functioning like that, Formula One engine, that it breaks down from tiny genetic glitches in basic housekeeping genes that the rest of your body completely ignores.
24:14It's a fascinating concept. If that is true, could studying the eye give us a window into our future? Could the retina, because of its extreme vulnerability and high metabolic turnover, actually serve as an early warning system to predict how other major organs might age, degrade, or fail over a lifetime?
24:33If a housekeeping gene is slightly inefficient, the eye might fail at age 30. But could that precise failure tell us what the heart or brain will inevitably do at age 80. It's a fascinating lens through which to view human biology.
24:45It truly is This episode was based on an open access article under the CCBY 4.0 license. You can find a direct link to the paper and the license in our episode description. If you enjoyed this, follow or subscribe in your podcast app and leave a 5 star rating.
25:00If you'd like to support our work, use the donation link in the description. Now stay with us for an original track created, especially for this episode, and inspired by the article you've just heard about.
25:10Thanks for listening and join us next time as we explore more science base by base. Late nights on the bright screens, Jason, what we miss? Static in the family tree, a hidden signature. I draw a map and laid. Where the signals coexist.
25:54Rising comas are singing. Even when the world goes burner In the parks, I'm by line, that the patterns are line, line, from the cilium to the membrane. Watch the pathway shine. The stories scatter We can still connect the sunshine.
26:17We got an atlas too light. Turning noise into meaning. A 1000 tiny sparks. Now the picture starts breathing. And the codes don't speak. Teach them how to sing. Yeah, we got it now, there's a lie, lie, lie, lie.
26:44So we can see again. Yeah, yeah, yeah, yeah, yeah, yeah, yeah. Some things stand in the spotlight, red and deep and clear, some drifting to syndrome. And going far from here, we sort from babies from the midst.
27:13The evidence tight. And every careful annotation The next step you ride. Drop outs in the transcript brain, caption coverage too, still we keep the doors open for the candidates coming through a living list of moving line updated as we learn.
27:30So the loss can find a marker, and the darkness can return, and today. Yeah, yeah, yeah. Now let's do life. Turning noise into meaning. Functional constellations. Every cluster is revealing. From the lab to the clinic.
27:55Let the right answer ring. Yeah, we've got enough, there's a lie, lie, lie. So we can see again. yeah yeah yeah yeah
