Biology subjects

Ai, Q.

Publications and source records attributed to Ai, Q..

3 recordsLinked to original sources

bioRxiv2024

Estimation of Species Abundance Based on the Number of Segregating Sites using Environmental DNA (eDNA)

The advance of environmental DNA (eDNA) has enabled rapid and non-invasive species detection in aquatic environments. Although most studies focus on species detections, some recent studies explored the potential of using eDNA concentration to quantify species abundance. However, the differential individual DNA contribution to eDNA samples could easily obscure the concentration-species abundance relationship. We propose using the number of segregating sites as a proxy for estimating species abundance. Since segregating sites reflects the genetic diversity of the population, which is less sensitive to differential individual DNA contribution than eDNA concentration. We examined the relationship between the number of segregating sites and species abundance in silico, in vitro, and in situ using two brackish goby species, Acanthogobius hasta and Tridentiger bifasciatus. Analyses of the simulated data and in vitro data with DNA mixed from a known number of individuals showed a strong correlation between the number of segregating sites and species abundance (R2 > 0.9; P < 0.01). Results from the in situ experiment further validated the correlation (R2 = 0.70, P < 0.01), and such correlation was not affected by biotic factors, including body size and feeding behavior (P > 0.05). Results of the cross-validation test also showed that the number of segregating sites predicted species abundance with less bias and variability than the eDNA concentration. Overall, the number of segregating sites correlates stronger with species abundance and also provides a better estimate than eDNA concentration. This advancement can significantly enhance the quantitative capabilities of eDNA technology.

ecology↗

bioRxiv2023

Improved Super-Resolution Ribosome Profiling Revealed Prevalent Translation of Upstream ORFs and Small ORFs in Arabidopsis

A crucial step in functional genomics is identifying actively translated open reading frames (ORFs) that link biological functions. The challenge lies in identifying short ORFs, as they are greatly impacted by data quality and depth. Here, we improved the coverage of super-resolution Ribo-seq in Arabidopsis, revealing uncharacterized translation events in nucleus-, chloroplast-, and mitochondria-encoded genes. We identified 7,751 unconventional translation events, including 6,996 upstream ORFs (uORFs) and 209 downstream ORFs on annotated protein-coding genes, as well as 546 ncORFs on presumed non-coding RNAs. Proteomics data confirmed the production of stable proteins from some of the unannotated translation events. We present evidence of active translation on primary transcripts of tasiRNAs (TAS1-4) and microRNAs (pri-miR163, pri-miR169), and periodic ribosome stalling supporting co-translational decay. Additionally, we developed a method for identifying extremely short uORFs, including 370 minimum uORF (AUG-stop), and 2,984 tiny uORFs (2-10 aa), as well as 681 uORFs that overlap with each other. Remarkably, these short uORFs exhibit strong translational repression as longer uORFs. We also systematically discovered 594 uORFs regulated by alternative splicing, suggesting widespread isoform-specific translational control. Finally, these prevalent uORFs are associated with numerous important pathways. In summary, our improved Arabidopsis translational landscape provides valuable resources to study gene expression regulation.

genomics↗

bioRxiv2023

Tip60-mediated Rheb acetylation links palmitic acid with mTORC1 activation and insulin resistance

Differences in dietary fatty acid saturation impact glucose homeostasis and insulin sensitivity in vertebrates. Excess dietary intake of saturated fatty acids (SFAs) induces glucose intolerance and metabolic disorders. In contrast, unsaturated fatty acids (UFAs) elicit beneficial effects on insulin sensitivity. However, it remains elusive how SFAs and UFAs signal differentially toward insulin signaling to influence glucose homeostasis. Here, using a croaker model, we report that dietary palmitic acid (PA), but not oleic acid or linoleic acid, leads to dysregulation of mTORC1 signaling which provokes systemic insulin resistance and glucose intolerance. Mechanistically, using croaker primary myocytes, mouse C2C12 myotubes and HEK293T cells, we show that PA-induced mTORC1 activation is dependent on mitochondrial fatty acid {beta} oxidation. Notably, PA profoundly elevates acetyl-CoA derived from mitochondrial fatty acid {beta} oxidation which intensifies Tip60-mediated Rheb acetylation. Subsequently, the induction of Rheb acetylation facilitates hyperactivation of mTORC1 which enhances serine phosphorylation of IRS1 and simultaneously inhibits transcription of IRS1 through impeding TFEB nuclear translocation, leading to impairment of insulin signaling. Furthermore, targeted abrogation of acetyl-CoA produced from fatty acid {beta} oxidation or Tip60-mediated Rheb acetylation by pharmacological inhibition and genetic knockdown rescues PA-induced insulin resistance. Collectively, this study reveals a conserved acetylation-dependent mechanistic insight for understanding the link between fatty acids and insulin resistance, which may provide a potential therapeutic avenue to intervene in the development of T2D.

cell biology↗