bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/352286

Dissecting PCNA function with a systematically designed mutation library in yeast

Dai, J.·Jiang, Q.·Zhang, W.·Liu, C.·Lin, Y.·Wu, Q.
View original source ↗Export metadata ↓

Abstract

Proliferating cell nuclear antigen (PCNA), encoded by POL30 in Saccharomyces cerevisiae, is a key component of DNA metabolism. Here a library consisting of 308 PCNA mutants was designed and synthesized to probe the contribution of each residue to its biological function. Five regions were identified with elevated sensitivity to DNA damaging reagents using high-throughput phenotype screening. Using a series of genetic and biochemical analyses, we demonstrated that one particular mutant, K168A, which displayed severe DNA damage sensitivity, abolished the DNA damage tolerance (DDT) pathway by disrupting interactions between PCNA and Rad5p. Subsequent domain analysis showed that the PCNA/Rad5p interaction is prerequisite for the function of Rad5p in DDT. Our study not only provides a resource in the form of a library of versatile mutants to study PCNA functions, but also reveals a key regulatory function of Rad5p, which highlights the importance of the PCNA-Rad5p interaction.\n\nAuthor summaryPCNA is regarded as the maestro of DNA replication fork because of the astonishing ability to interact with lots of partner proteins that participate in various DNA metabolism processes. However, it has remained elusive as to how does PCNA orchestrate these functions in harmony. Here, we constructed a systematic mutation library of PCNA, which covers every amino acid to map the functional sites of it. This carefully designed synthetic mutant pool could be generally useful and serve as a flexible resource, such as dissecting the functional mechanism of PCNA by genetic relationship analysis with key proteins through Synthetic genetic array. We further dissected the intrinsic mechanism for damage sensitivity of PCNAK168A, the most severe DNA damage sensitive mutant in our alanine scanning mutation library, this helps us to get better understanding of how PCNA participates in DNA damage tolerance (DDT) pathways. Our findings indicate that K168 site is vital for the interaction between DDT related partner proteins and PCNA, and also highlight the importance of the PCNA-Rad5p interaction.

Source connections

Explore related subjects

geneticsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Dai, J., Jiang, Q., Zhang, W., Liu, C., Lin, Y., Wu, Q.. 2018-06-20. Dissecting PCNA function with a systematically designed mutation library in yeast. https://doi.org/10.1101/352286

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Cellular context shapes the transcriptomic impact of somatic variants

Somatic SNVs are commonly prioritized by recurrence or sequence annotation, leaving the molecular consequences of private variants unresolved. We developed PrismSNV and Ligo-Seq, a single-cell full-length transcriptome sequencing platform, to quantify transcriptomic displacement associated with within-cell SNV-state toggling. Across 26 samples from three cancer types, more than 60% of candidate SNVs showed significant cell-type-specific displacement with over 30% variation in magnitude. Sequence-based deleteriousness was poorly aligned with cellular displacement, and fewer than 3% of top-displacement SNVs across six tumor types were catalogued in ClinVar. Displacement was strongest in transcriptionally plastic, less differentiated states. Analysis of 655,349 CD4+ T-cell transcriptomes further showed that SNV-gene associations changed in magnitude and sometimes direction during activation. Lack of recurrence or clinical annotation does not imply transcriptomic inertness; variant impact is shaped by cellular context rather than sequence alone, establishing the variant-cell pair as a critical unit for interpreting somatic variation.

genetics↗
bioRxiv2026

Genetic and Epigenetic Landscape of Self-Identified Hispanics/Latino in All Of Us

Human genetic studies still underrepresent many populations, limiting discovery and interpretation of medically relevant variation. Extensive admixture in self-identified Hispanic/Latino populations increases the need for representative reference data and ancestry-aware interpretation of medically relevant variation. We used long-read sequencing to analyze genetic variation, ancestry, and DNA methylation in 1,490 self-identified Hispanic/Latino participants from the All of Us Research Program. We identified 10 million novel variants and more than 100 candidate phenotype associations, with fine-mapping prioritizing structural variants over nearby single-nucleotide variants in more than half. We linked 3,329 tandem repeats to DNA methylation, resolved widespread allele-specific methylation, and identified ancestry-linked regulation across paralogous genes. These results reveal previously inaccessible genetic and regulatory variation and show the value of long-read sequencing for diverse populations.

genetics↗
bioRxiv2026

The genetic architecture of human DNA methylome variation

Population DNA methylome analyses remain largely confined to reference-defined genomic space despite extensive human genetic diversity. A central challenge is therefore to define comparable methylation phenotypes across diverse genomes and map the genetic architecture of methylome variation. Here, using 460 haplotypes from the Human Pangenome Reference Consortium Release 2, we develop two complementary pangenome-based frameworks: one compares methylation within homologous regions while retaining haplotype-specific structural configuration and CpG content; the other represents CpG island (CGI) variation at homologous loci as sequence-resolved alleles. We identified 47,039 CGI alleles, including 8,040 absent from CHM13; 62% were attributable to structural variants and 31% to small variants. Through local genealogies, we reconstructed CGI gain, loss and turnover, revealing how present-day methylation differences align with CGI evolutionary trajectories. We found that genome-wide, methylation variability was buffered against genetic diversity across more than 90% of the genome, with exceptions at extreme nucleotide diversity and locally around structural variants. Our methylation framework enabled population-scale allele-aware methylation quantitative trait locus (mQTL) mapping into non-reference and structurally complex sequence, where mQTL-associated intervals were enriched. mQTLs linked methylation to transcriptomic phenotypes, population differentiation and complex traits, supporting 8% of population differentially methylated regions and colocalizing with more than half of genome-wide association study loci. Together, our study redefines human methylome analysis and our findings reveal a genome-wide architecture of genetic-epigenetic coupling, reshaping how methylation variation is interpreted across human development and disease.

genetics↗