NLM DIR Seminar Schedule
UPCOMING SEMINARS
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May 12, 2026 John Bridgers
A bi-partition function algorithm to evaluate inferred subclonal structures in single-cell sequencing data -
May 14, 2026 Brandon Colelough
TBD -
May 19, 2026 Leann Lindsey
Are Genomic Language Models Learning? Insights from Tokenization Analysis and Prophage Detection in Bacterial Genomes -
May 26, 2026 Harutyun Saakyan
TBD -
May 27, 2026 Brian Abraham
Cis-Regulatory Organization and Transcription Factor Control of Cell Identity and Disease
RECENT SEMINARS
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May 5, 2026 Benjamin Hou
Machine Learning for Craniofacial Malocclusion Prediction -
April 28, 2026 Niccolo Marini
From Unimodal Datasets to Multimodal Foundation Models: Synthetic Clinical Notes for Dermatology AI -
April 21, 2026 Yoshitaka Inoue
Drug Response Prediction: Generalization using Graph Neural Networks & Reasoning over Predictions using LLMs -
April 16, 2026 Matthew Diller
Analyzing Similarity in Common Data Elements in the NIH CDE Repository via Semantic Clustering -
April 7, 2026 Henry Secaira Morocho
Toward a systematic method of database enrichment for reference-based metagenomics
Scheduled Seminars on March 17, 2026
In-person: Building 38A/B2N14 NCBI Library or Meeting Link
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
Evolution of prokaryote genomes appears to be defined by the interplay of selection for genome streamlining, deletion bias and selection for functional diversification. The previously observed overall positive correlation between the strength of selection, measured as the ratio of non-synonymous to synonymous nucleotide substitutions (dN/dS), points to diversification as the primary factor of prokaryote genome evolution. Here, we investigated the interplay between genome size and selection pressure by analyzing an expanded collection of closely related prokaryotic genomes, evaluating genome-wide selection by measuring dN/dS by using an accurate, phylogeny-based method and decomposing the resulting values into lineage-specific and gene-specific components. These analyses reveal a pronounced heterogeneity in the relationship between genome size and the strength of selection across the diversity of prokaryotes. Most bacteria display a positive correlation consistent with selection for diversification, whereas all analyzed archaeal lineages show strong negative correlation which is the signature of streamlining. These findings indicate that the selection regimes broadly vary across the diversity of prokaryotes rather than following a single, universal pattern. Genome streamlining, selection for functional diversity and drift in small populations are all important factors of evolution, their relative contributions depending on the population genetics and ecology of a given lineage.