Protein length distribution is remarkably consistent across Life

Nevers, Yannis; Glover, Natasha; Dessimoz, Christophe; Lecompte, Odile

doi:10.1101/2021.12.03.470944

Cited by 8 publications

(7 citation statements)

References 60 publications

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“…While natural proteins often span between 200 to 400 residues [33], ESM therm is fine-tuned on sequences no longer than 72 residues in length. To explore its performance under this limitation, we benchmarked our model against six stability-related datasets on larger proteins and compared our results with state-of-the-art covering different methodologies.…”

Section: Resultsmentioning

confidence: 99%

Protein Stability Prediction by Fine-tuning a Protein Language Model on a Mega-scale Dataset

Chu,

Siegel

2023

Preprint

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The stability of a protein is crucial to its utility in industrial applications. While engineering campaigns can now be routinely used to enhance protein thermal stability to the level needed in an industrial setting, there is a significant desire to fast-track these efforts through predictive tools allowing one to jump in a minimal number of design iterations to a highly stabilized protein. In this work, we explore utilizing a mega-scale dataset for development of a protein language model tuned for stability. This model is trained on the folding stability of 528k sequences derived from 461 small protein domains and designs, and can accommodate deletions, insertions, and multiple-point mutations. We show that a protein language model can be fine-tuned to predict folding stability. The fine-tuned protein language model, named ESMtherm, performs reasonably on small protein domains and generalizes to sequences distal from the training set. Lastly, we discuss its limitations when compared to other state-of-the-art methods in generalizing to larger protein scaffolds and highlight the need of large-scale stability measurement on a diverse dataset that represents the distribution of sequence lengths commonly observed in nature.

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Section: Resultsmentioning

confidence: 99%

Protein Stability Prediction by Fine-tuning a Protein Language Model on a Mega-scale Dataset

Chu,

Siegel

2023

Preprint

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“…Our findings from mammalian data strongly point to longer insertion lengths than deletion lengths. Further, given the higher prevalence of deletions and the remarkable uniformity of protein length distribution across the tree of life (Nevers et al, 2023), it is conceivable that the two distributions differ, with deletions lengths having a smaller mode than insertions. Recent work from Tal Pupko’s lab is a notable step in the direction of inferring indel length distributions based on event reconstruction (Wygoda et al, 2024).…”

Section: Discussionmentioning

confidence: 99%

Single-character insertion-deletion model preserves long indels in ancestral sequence reconstruction

Jowkar,

Pěcerska,

Gil

et al. 2024

Preprint

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Insertions and deletions (indels) play a significant role in mammalian genomic evolution. Sensible modelling of the evolutionary process of indels is challenging and still an open research question. Several attempts have been made to explicitly model multi-character (long) indels, such as TKF92, by violating the site independence assumption and introducing fragments. However, these methods are computationally expensive. On the other hand, among the Markov-based models, the Poisson Indel Process (PIP) allows us to infer single-character indels on the phylogenetic tree, assuming site independence and distinguishing insertions from deletions. PIP's marginal likelihood computation has linear time complexity, enabling ancestral sequence reconstruction (ASR) with indels in linear time. Recently, we developed ARPIP, an ASR method using PIP, capable of inferring indel events with explicit evolutionary interpretations. Here, we investigated the effect of the single-character indel model on reconstructed ancestral sequences on both eutherian mammal orthologous sequences and simulated data. We show that our single-character indel method preserves the gap length distribution from the input alignment in the ancestral estimates. Furthermore, we confirm the well-established deletion bias. To date, ARPIP is the only ancestral reconstruction method that explicitly models insertion and deletion events over time. In conjunction with a long indel alignment, it can capture ancestral long indel events on the phylogeny.

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“…Once these regions were identified for the F ST and ZH p analyses, we extracted all protein‐coding genes located within the genomic segment encompassing these regions plus 50 kb upstream and downstream from the mid‐position marker (where a region comprised a single marker) or from the flanking markers of the region (where a region comprised multiple markers). The selection of 50 kb was based on the known distribution of gene lengths in the O. niloticus genome, shown to be <50 kb for over 90% of genes (Nevers et al, 2021 ). There was no justification for extending the candidate regions beyond this size to account for linkage disequilibrium (LD), as often done for terrestrial domesticated species, as LD has been shown to be very low in Nile tilapia (Peñaloza et al, 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Genetic differentiation following recent domestication events: A study of farmed Nile tilapia (Oreochromis niloticus) populations

Barría

Peñaloza

Papadopoulou

et al. 2023

Evolutionary Applications

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Nile tilapia (Oreochromis niloticus) is among the most farmed finfish worldwide, distributed across different environmental conditions. Its wide distribution has mainly been facilitated by several breeding programs and widespread dissemination of genetically improved strains. In the first Nile tilapia study exploiting a whole‐genome pooled sequencing (Poolseq) approach, we identified the genetic structure and signatures of selection in diverse, farmed Nile tilapia populations, with a particular focus on the GIFT strain, developed in the 1980s, and currently managed by WorldFish (GIFTw). We also investigated important farmed strains from The Philippines and Africa. Using both SNP array data and Poolseq SNPs, we characterized the population structure of these samples. We observed the greatest separation between the Asian and African populations and greater admixture in the Asian populations than in the African ones. We also established that the SNP array data were able to successfully resolve relationships between these diverse Nile tilapia populations. The Poolseq data identified genomic regions with high levels of differentiation (FST) between GIFTw and the other populations. Gene ontology terms associated with mesoderm development were significantly enriched in the genes located in these regions. A region on chromosome Oni06 was genetically differentiated in pairwise comparisons between GIFTw and all other populations. This region contains genes associated with muscle‐related traits and overlaps with a previously published QTL for fillet yield, suggesting that these traits may have been direct targets for selection on GIFT. A nearby region was also identified using XP‐EHH to detect genomic differentiation using the SNP array data. Genomic regions with high or extended homozygosity within each population were also identified. This study provides putative genomic landmarks associated with the recent domestication process in several Nile tilapia populations, which could help to inform their genetic management and improvement.

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Protein length distribution is remarkably consistent across Life

Cited by 8 publications

References 60 publications

Protein Stability Prediction by Fine-tuning a Protein Language Model on a Mega-scale Dataset

Protein Stability Prediction by Fine-tuning a Protein Language Model on a Mega-scale Dataset

Single-character insertion-deletion model preserves long indels in ancestral sequence reconstruction

Genetic differentiation following recent domestication events: A study of farmed Nile tilapia (Oreochromis niloticus) populations

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