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Veera Rajagopal @doctorveera.bsky.social · Mar 20

Congratulations!

Veera Rajagopal @doctorveera.bsky.social · Jan 9

There seems to be another companion manuscript with this one discussing the long read dataset in a much broader context. The current one is focussed on TRs. This data release marks exciting progress in human genetics in 2025. 9/

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

Interestingly, these extremely polymorphic repeat loci identified in humans are monomorphic in apes based on available data, suggesting that human-specific expansion. 8/

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

This observation goes against the concept of mutation constraint: disease loci are usually depleted of variations. It seems for repeat loci it's more complex. 7/

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

The second most polymorphic repeat at this same locus--CAG repeat in THAP11--is also disease-causing. 6/

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

For e.g., last year GGC exonic repeat in ZFHX3 was discovered (after nearly 25 years) to be the causal variant in SCA4 locus. The authors find that around the SCA4 locus, GGC repeat is the 5th most polymorphic repeat. 5/

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

The authors suggest we can actually use this logic to identify causal repeat variants at unresolved disease loci. Just search for the most variable repeats within the linkage region and most likely one of them is the culprit. 4/

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

Many interesting results in the preprint. One surprising revelation is the authors find that known pathogenic repeat loci are the most variable in the genome (of course, within the benign range). 3/

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

I remember hearing about this dataset first time at ASHG 2022. Great to see the data out finally. Using 1027 long read genomes, the authors have identified >3.6 billion TR alleles (!) at 1.7 million loci. 2/

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

Profiling tandem repeats variations in the population using 1027 long read genomes from All of Us cohort. All the samples are from individuals of African and African American ancestries. 1/

Danxi, Xu et al. bioRxiv
www.biorxiv.org/content/10.1...

Detailed tandem repeat allele profiling in 1,027 long-read genomes reveals genome-wide patterns of pathogenicity

Tandem repeats are a highly polymorphic class of genomic variation that play causal roles in rare diseases but are notoriously difficult to sequence using short-read techniques. Most previous studies ...

www.biorxiv.org

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

Great News and Views explaining the background and discovery in simple accessible language by Sardar and Kutateladze.
www.nature.com/articles/d41...

Circadian rhythms are set by epigenetic marks in neurons

Exchanger enzyme modifies histones in histamine-releasing neurons.

www.nature.com

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

Fascinating discovery and may have implications in psychiatric and sleep related disorders. I wonder how many more PTMs are there waiting to be discovered.

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

Addition and removal of histamine to histones in the neurons in brain circadian rhythm center seems to control the sleep wake cycle.

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

This adds to the list of histone monoaminylations recently discovered (serotonylation in 2019, dopaminylation in 2020 by the same group of authors).

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Veera Rajagopal @doctorveera.bsky.social · Jan 9

A new type of post-translational modification (PTM) revealed: histaminylation.

Zheng, Weekley, Vinson, Zhao, Bastle, et al. Nature
www.nature.com/articles/s41...

Bidirectional histone monoaminylation dynamics regulate neural rhythmicity - Nature

TG2 functions as an eraser and exchanger of H3 monoaminylations, including histaminylation of Gln5 of histone H3.

www.nature.com

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Veera Rajagopal @doctorveera.bsky.social · Dec 23

Another great discovery before we close the year, highlighting the underappreciated role of retroelements in human disease and traits. 5/

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Veera Rajagopal @doctorveera.bsky.social · Dec 23

This also would mean the target population for ASPA gene therapy (currently in trials by Myrtelle Inc.) might be much larger than expected. 4/

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Veera Rajagopal @doctorveera.bsky.social · Dec 23

Unlike the recurrent mutations previously found, which were mostly restricted to Ashkenazi Jewish ancestry, the SVA insertion seems to be occurring across all ancestries, making it the most common cause worldwide. 3/

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Veera Rajagopal @doctorveera.bsky.social · Dec 23

Due to the limitations of short read sequencing, this mutation has remained hidden for more than 25 years since ASPA mutations were first characterized in individuals Canavan disease. 2/

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Veera Rajagopal @doctorveera.bsky.social · Dec 23

A homozygous SVA retrotransposon insertion is discovered to be likely the most common mutation in ASPA (encodes aspartoacylase) underlying Canavan disease. 1/

Gonzalez, Bell, et al. medRxiv
www.medrxiv.org/content/10.1...

A Diagnostic Blind Spot: Deep intronic SVA_E Insertion identified as the most Common Pathogenic Variant Associated with Canavan Disease

Canavan disease (CD) is a neurodegenerative disorder caused by biallelic disease-causing variants in the ASPA gene. Here, we utilized long-read sequencing (LRS) to investigate eight individuals clinic...

www.medrxiv.org

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Reposted by Veera Rajagopal

Emily Moin @emilymoin.com · Dec 17

Can't comment on the genetics but agree this is a huge "so what?" for clinical practice – we already use patient-specific trends for diagnosis and management and have for decades. The specific examples given in the article (like HCT and CKD) are... amusingly obvious.

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Reposted by Veera Rajagopal

James 🎃cello 🌉 @jamespirruccello.com · Dec 17

Arguably the reason that GWAS for blood traits have ever worked is that we are proxying the individual set point. So yes the clinical discussion is neat. The genetic implications seem nil.

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Veera Rajagopal @doctorveera.bsky.social · Dec 17

Exactly.

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Veera Rajagopal @doctorveera.bsky.social · Dec 17

Likewise, the GWAS of blood count setpoints is almost the same as past GWASs of blood counts, just the phenotypes are a little more precise leading to slightly increased genetic signals. 5/

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Veera Rajagopal @doctorveera.bsky.social · Dec 17

The extra thing here is the blood counts are measured in terms of "setpoints" (a fancy term for the mean of multiple measurements per individual, excluding outliers) instead of the simple arithmetic mean of all measurements per individuals (which is what we typically do in the UK Biobank). 4/

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