Biology subjects

Yue, J.-X.

Publications and source records attributed to Yue, J.-X..

22 records · Page 2Linked to original sources

bioRxiv2019

Intragenic repeat expansions control yeast chronological aging

Aging varies among individuals due to both genetics and environment but the underlying molecular mechanisms remain largely unknown. Using a highly recombined Saccharomyces cerevisiae population, we found 30 distinct Quantitative Trait Loci (QTLs) that control chronological life span (CLS) in calorie rich and calorie restricted environments, and under rapamycin exposure. Calorie restriction and rapamycin extended life span in virtually all genotypes, but through different genetic variants. We tracked the two major QTLs to massive expansions of intragenic tandem repeats in the cell wall glycoproteins FLO11 and HPF1, which caused a dramatic life span shortening. Life span impairment by N-terminal HPF1 repeat expansion was partially buffered by rapamycin but not by calorie restriction. The HPF1 repeat expansion shifted yeast cells from a sedentary to a buoyant state, thereby increasing their exposure to surrounding oxygen. The higher oxygenation perturbed methionine, lipid, and purine metabolism, which likely explains the life span shortening. We conclude that fast evolving intragenic repeat expansions can fundamentally change the relationship between cells and their environment with profound effects on cellular life style and longevity.

genomics↗

bioRxiv2018

simuG: a general-purpose genome simulator

SummarySimulated genomes with pre-defined and random genomic variants can be very useful for benchmarking genomic and bioinformatics analyses. Here we introduce simuG, a light-weighted tool for simulating the full-spectrum of genomic variants. The simplicity and versatility of simuG makes it a unique general purpose genome simulator for a wide-range of simulation-based applications.\n\nAvailability and implementationCode in Perl along with user manual and testing data is available at https://github.com/yjx1217/simuG. This software is free for use under the MIT license.

bioinformatics↗

bioRxiv2017

Patterns of selection reveal shared molecular targets over short and long evolutionary timescales

Standing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the dynamics of drug adaptation in yeast populations with different levels of standing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of standing variation alone boost the adaptation by 64.1% and 51.5% in hydroxyuea and rapamycin respectively. The causative standing and de novo variants were selected on shared targets of RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. The standing and de novo TOR variants map to different functional domains and act via distinct mechanisms. Interestingly, standing TOR variants from two domesticated strains exhibited opposite resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how standing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving diseases.

genetics↗

bioRxiv2017

LRSDAY: Long-read sequencing data analysis for yeasts

Long-read sequencing technologies have become increasingly popular in genome projects due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding yeast, Saccharomyces cerevisiae, has many isolates currently being sequenced with long reads. However, analyzing long-read sequencing data to produce high-quality genome assembly and annotation remains challenging. Here we present LRSDAY, the first one-stop solution to streamline this process. LRSDAY can produce chromosome-level end-to-end genome assembly and comprehensive annotations for various genomic features (including centromeres, protein-coding genes, tRNAs, transposable elements and telomere-associated elements) that are ready for downstream analysis. Although tailored for S. cerevisiae, we designed LRSDAY to be highly modular and customizable, making it adaptable for virtually any eukaryotic organisms. Applying LRSDAY to a S. cerevisiae strain takes [~]43 hrs to generate a complete and well-annotated genome from [~]100X Pacific Biosciences (PacBio) reads using four threads.

bioinformatics↗