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#genomic

1 post1 participant0 posts today
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Daniel Dvorkin

My day job is all about #genes, so I applaud the #genomic revolution in #paleontology and #evolutionary #biology. But #evolution really is more than a shift in #allele frequencies over time. It's also change in the #phenotypes those alleles produce, and their #interaction with the world around them. 🧪🖥🧬🦖

cambridge.org/core/journals/pa

So I'm equally excited about the #quantitative revolution in describing and cataloguing #traits which until recently could only be analyzed #qualitatively. There's a whole new window opening into the history of life.

Cambridge CoreMorphological evolution in a time of phenomics | Paleobiology | Cambridge CoreMorphological evolution in a time of phenomics
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Jeff Gilchrist

#Ontario, Canada peeps or anyone have insight into why there was a sudden stop of uploading Ontario COVID #genomic sequence data to #GISAID? Last sequences dated Feb. 12, 2025 and nothing since. There was still 57-83 sequences a day being uploaded before that.

Now only a small # of sequences coming from NB & Quebec and periodically a few from AB, BC, and NS for all of Canada. You can see the big drop in Canada sequences when ON stopped submitting so very difficult to track what is going on.🧵1/

A line graph showing the lineage frequency of the top 7 COVID-19 genomes in Canada, up to March 3, 2025. The graph includes data from 1,034 sequenced genomes. The x-axis represents dates from Feb 2 to March 3, while the y-axis represents lineage frequency percentages from 0% to 29%. Different colored lines represent different genome lineages with LF.7.7.2 as most sequenced. Below the main graph, there is a bar chart showing the number of samples (n) collected each day, ranging from 0 to 100 samples, where is drops off drastically after Feb. 12, 2025 when Ontario stopped submitting genomic sequencing.
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Benjamin Carr, Ph.D. 👨🏻‍💻🧬

#Embryo editing debate is back:

Heritable polygenic editing: next frontier in #genomic #medicine?

In it Visscher suggest editing 10 bits of #DNA could reduce the prevalence of #Alzheimer’s or #schizophrenia by nearly 10-fold. Another 10 edits could diminish coronary artery #disease more than 30-fold, and 10 more edits could cut type 2 #diabetes by roughly 60-fold.
But doing so would be controversial, both at a scientific and moral level.
nature.com/articles/s41586-024 #genes #genetic #geneticediting

NatureHeritable polygenic editing: the next frontier in genomic medicine? - NatureWe discuss the potential consequences and ethical concerns of polygenic genome editing of human embryos to alter specific variants associated with polygenic diseases, highlighting the possibility of reducing disease susceptibility while exacerbating health inequalities.
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Giuseppe Michieli

#Genomic Characterization of #HPAI #H5N1 Virus Newly Emerged in Dairy #Cattle, Emerg Microbes Infect.: tandfonline.com/doi/full/10.10

B3.13 viruses underwent 2 #reassortment events since 2023 & exhibit critical #mutations in #HA, #M1, & #NS #genes but lack critical mutations in #PB2 & PB1 genes, which enhance virulence or adaptation to #mammals. #PB2 E627 K mutation in a #human case associated with cattle underscores the potential for rapid evolution post-infection...

Schematic representation of genomic composition and reassortment time of HPAI H5N1 viruses from dairy cattle and other animals and human in March 2024.
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Dr. Sarah Pohl

I've been on Mastodon since October '22, but I've just moved from chaos.social to norden.social, so let's have a new #introduction post!

I'm an academic who left #academia to do #DataEngineering for a #medical controlling service provider. I studied #biology and learned how to program and analyse data mostly online or via practice, doing my PhD in #DataAnalysis of #genomic data from Pseudomonas aeruginosa. Now my posts are mostly in German on a variety of topics.

Public
Nikos Tsardakas Renhuldt

I have #genomic variants called using #FreeBayes. I want to identify sex-linked regions of the genome. As a complement to visualization I’m considering doing some type of #statistical analysis, in part driven by wanting to learn more #stats. I’m less interested in allele differences (GWAS) and more in #heterozygosity, coverage depth, etc. Are there standard models to identify region differences? Could a #MixedModel be used for this?

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