Misha Moldovan

Our work on sperm sequencing is now published! See below for: 🧑‍🔬Scientific tweetorial 📰 Accessible articles discussing implications for aging fathers [1/3] nature.com/articles/s4158…

Our paper on clonal expansions in Sperm is out in Nature nature.com/articles/s4158… If you are interested in working at an intersection of Mendelian genomics/Population genetics/Clonal expansions +Cancer genetics/ and of course mutagenesis, please rich out about postdoc in my lab

Our latest work is out in Nature today. In this paper, we introduce an improved version of NanoSeq, a duplex sequencing protocol with <5 errors per billion bp in single DNA molecules, and use it to study the oral somatic mutation landscape in >1000 people. nature.com/articles/s4158…

Excited to share our preprint: Cohort-level analysis of human de novo mutations points to drivers of clonal expansion in spermatogonia! We developed methods to uncover drivers of clonal expansions in sperm (CES) using 55k disease trios & gnomAD SNV data. medrxiv.org/content/10.110…

We know that DNA introgressed from one population into another is often deleterious, but why? @carl_veller and I show that stabilizing selection, by itself, can induce selection against introgressed ancestry. doi.org/10.1101/2024.0…

I am excited to share that I will be starting a lab at @EmoryUniversity this September. We will aim to understand evolution by studying genomes of things ranging from viruses to humans. Looking for talented students and postdocs to do computational genomics. Get in touch! 1/2

Discussed Spence et al. [biorxiv.org/content/10.110…] for journal club. Very nicely draws the connection between estimating posterior GWAS effect sizes and many downstream parameters we care about: polygenic scores, genetic correlation, fine-mapping, etc.

1/ We’re excited to share our new preprint “Dissecting the contribution of common variants to risk of rare neurodevelopmental conditions” available on medRxiv! medrxiv.org/content/10.110…

Really excited to talk at #TAGC24 about our project with @Evan_M_Koch on population genetics of effect size correlations in GWAS

Our story about interactions between anti-phage defense systems is now in Cell Host & Microbe: sciencedirect.com/science/articl…

Huge thanks to Shilpa @shilpanads, the main engine behind this project, all other co-authors, Shamil Sunyaev and @zakkohane for their ideas and leadership, members of Sunyaev and Kohane labs, the UDN consortium @UDNconnect and all the patients enrolled in the UDN.

1/10 [My first Twitter/X post] Our preprint about the joint statistical analysis of the Undiagnosed Diseases Network patients is finally out: biorxiv.org/content/10.110…

10/10 Last but not least, we now have a public-facing browser containing various information about the variant- and gene-level findings in the UDN cohort: dbmi-bgm.github.io/udn-browser/

9/10 We developed a tool, RaMeDiES, which implements our statistics. Check it out on GitHub: github.com/hms-dbmi/RaMeD…

8/10 In addition, we developed an individual-level test for the inference of deleterious coumpound heterozygotes and a strategy for the analysis of biological pathways implicated in rare diseases

7/10 Also, focusing on mutational targets enables cross-cohort metaanalyses and simultaneous analyses of different types of data

6/10 The cool thing is that focusing on mutational targets allows to de-personalize the variant data, thus the data may be shared across the cohorts

5/10 Our statistics work at the level of mutational targets, defined as mutation rates associated with bins of certain functionality scores

4/10 Our methods focus on the inference of both deleterious dominant de novo and recessive compound heterozygous variants.

3/10 There, we develop several new statistical methods for the inference of disease-causing genes in cohorts of patients with suspected rare Mendelian conditions

2/10 This work shows that, since the genome is finite, the joint analysis of cohorts of all types of undiagnosed patients has a lot of promise.