Biology subjects

Na, C.

Publications and source records attributed to Na, C..

3 recordsLinked to original sources

bioRxiv2026

Loss of Mitochondrial FMT Restores Chloroplast Proteostasis via Inter-organelle Compensation

Chloroplast proteostasis is vital for plant development, yet whether cells can actively reprogram organelle communication to restore plastid function when essential protease components fail remains unclear. Using a forward genetic suppressor screen in Arabidopsis, we identify loss of the mitochondria-associated protein FRIENDLY MITOCHONDRIA (FMT) as a strong suppressor of the virescent and growth-retarded clpc1 mutant, which lacks the major chloroplast Clp chaperone ClpC1. Suppression is highly specific and occurs independently of GUN1-mediated retrograde signaling. Integrated multi-omics analyses reveal that clpc1 and fmtclpc1 represent two distinct organelle signaling states. In clpc1, loss of ClpC1 triggers a plastid stress state characterized by repression of photosynthesis-associated transcription factors, induction of plastid metabolic stress markers, and impaired proteolytic activity. By contrast, loss of FMT shifts the system into a recovery state despite persistent mitochondrial clustering. Mechanistically, FMT negatively regulates CLPC2, a ClpC1 paralog, and fmt-mediated rescue results from CLPC2 derepression. Moderately elevated ClpC2 restores in vivo proteolysis, as evidenced by recovery of PAA2 substrate turnover, normalization of chloroplast ultrastructure, and reactivation of photosynthesis-related gene expression. Transcriptomic and proteomic profiling further reveal coordinated remodeling of nuclear gene expression and chloroplast protein investment in the recovery state, including reduced cytosolic folding stress and selective induction of jasmonic acid- and salicylic acid-associated signaling networks. Genetic analyses establish that REC1 and REC2 are required for full CLPC2 induction and phenotypic recovery. Together, our findings uncover a latent inter-organelle compensatory mechanism in which mitochondrial perturbation reprograms nuclear gene expression to restore chloroplast proteostasis when ClpC1 function is compromised.

plant biology↗

bioRxiv2018

DISTMIX2: robust imputation of summary statistics for cosmopolitan cohorts using a large and diverse reference panel

Genotype imputation across populations of mixed ancestry is critical for optimal discovery in large-scale genome-wide association studies (GWAS). Methods for direct imputation of GWAS summary statistics were previously shown to be practically as accurate as summary statistics produced after raw genotype imputation, while incurring orders of magnitude lower computational burden. Given that direct imputation needs a precise estimation of linkage-disequilibrium (LD) and that most of the methods using a small reference panel e.g., ~2,500 subject coming from the 1000 Genome Project, there is a great need for much larger and more diverse reference panels. To accurately estimate the LD needed for an exhaustive analysis of any cosmopolitan cohort, we developed DISTMIX2. DISTMIX2: i) uses a much larger and more diverse reference panel and ii) estimates weights of ethnic mixture based solely on Z-scores (when AFs are not available). We applied DISTMIX2 to GWAS summary statistics from the Psychiatric Genetic Consortium (PGC). DISTMIX2 uncovered signals in numerous new regions, with most of these findings coming from the rarer variants. Rarer variants provide much sharper location for the signals compared with common variants, as the LD for rare variants extends over a lower distance than for common ones. For example, while the original PGC post-traumatic stress disorder (PTSD) study found only 3 marginal signals for common variants, we now uncover a very strong signal for a rare variant in PKN2, a gene associated with neuronal and hippocampal development. Thus, DISTMIX2 provides a robust and fast (re)imputation approach for most Psychiatric GWAS studies.

bioinformatics↗

bioRxiv2018

JEPEGMIX2-P: Novel pathway transcriptomic method greatly increases detection of molecular pathways in cosmopolitan cohorts

Genetic signal detection in genome-wide association studies (GWAS) is enhanced by pooling small signals from multiple Single Nucleotide Polymorphism (SNP), e.g. across genes and pathways. Because genes are believed to influence traits via gene expression, it is of interest to combine information from expression Quantitative Trait Loci (eQTLs) in a gene or genes in the same pathway. Such methods, widely referred as transcriptomic wide association analysis (TWAS), already exist for gene analysis. Due to the possibility of eliminating most of the confounding effect of linkage disequilibrium (LD) from TWAS gene statistics, pathway TWAS methods would be very useful in uncovering the true molecular bases of psychiatric disorders. However, such methods are not yet available for arbitrarily large pathways/gene sets. This is possibly due to it quadratic (in the number of SNPs) computational burden for computing LD across large regions. To overcome this obstacle, we propose JEPEGMIX2-P, a novel TWAS pathway method that i) has a linear computational burden, ii) uses a large and diverse reference panel (33K subjects), iii) is competitive (adjusts for background enrichment in gene TWAS statistics) and iv) is applicable as-is to ethnically mixed cohorts. To underline its potential for increasing the power to uncover genetic signals over the state-of-the-art and commonly used non-transcriptomics methods, e.g. MAGMA, we applied JEPEGMIX2-P to summary statistics of most large meta-analyses from Psychiatric Genetics Consortium (PGC). While our work is just the very first step toward clinical translation of psychiatric disorders, PGC anorexia results suggest a possible avenue for treatment.

bioinformatics↗