chen, L. | Search bioRxiv

bioRxiv2026

MMMAS: A Mendelian Mismatch Matrix Analysis System for Deterministic Pre-Screening of Germplasm Collections

Pedigree errors, duplicate accessions, and undocumented kinship limit the effective use of large genebank collections. Existing tools such as CERVUS and COLONY require allele-frequency estimates and return relationship-level assignments, providing no collection-wide view of Mendelian consistency. We developed the Mendelian Mismatch Matrix (MMM) framework and its open-source implementation, MMMAS (Mendelian Mismatch Matrix Analysis System). We applied MMM to apple (Malus x domestica; 1,085 accessions, 15 SSRs) and sweet cherry (Prunus avium; 383 accessions, 13 SSRs) datasets from the German Fruit Genebank. MMM converts pairwise Mendelian mismatch numbers (Mmn) into an N x N symmetric matrix, from which we derive four collection-scale indices (Mmin, the Mendelian minimum mismatch number; Mavg, the Mendelian average mismatch number; Mzmp, the Mendelian zero-mismatch partner number; Mmmd, the Mendelian mismatch-mode duplication index) and the Mendelian Exhaustive Stratification (MES) grading system. Apple showed a gradient-type structure (Mendelian Grade-gap Index, MGI = 0.125), sweet cherry a broken-type structure (MGI = 0.545). The Mmin-Mavg strategy identified 20 and 10 distinct accessions in apple and sweet cherry, including the scab-resistance donor Malus x floribunda 821 (Rvi6) and the fire-blight donor M. x robusta 5. The Mmmd index flagged one literature-confirmed pair of duplicate genotypes in sweet cherry. Of CERVUS-confirmed parent-offspring pairs, 97.31% in apple and 100% of high-confidence pairs in sweet cherry fell within Mmn <= 1. Mzmp rankings matched documented breeding history, with 'Cox Orange' (Mzmp = 57) and 'Luebecker Bunte' (Mzmp = 49) ranking first in each species. The complete end-to-end analysis of all 588,070 apple pairwise comparisons took 7.24 s on an ordinary workstation. This deterministic pre-screening framework, with a parameter-free core, supports routine quality assessment in germplasm collections.

genetics↗

bioRxiv2025

Hyper-Glycosylation as a Central Metabolic Driver of Alzheimers Disease

Alzheimers disease (AD) is a neurodegenerative disorder characterized by devastating degenerative decline. Metabolic disruptions are widely observed, yet their involvement in the molecular etiology of AD remains underexplored. Utilizing spatial metabolomics, lipidomics, and glycomics in both mouse models and human post-mortem samples, we identified a hyper-glycosylation phenotype as a hallmark of AD. To investigate the underlying mechanisms and whether the observed effect was a driver of the observed decline, we developed an advanced spatial isotopic tracing pulse-chase method to study the dynamics of N-linked glycans. Our analysis revealed enhanced glycan biosynthesis in AD mouse models. Based on these findings, we performed genetic and dietary interventions to modulate glycan biosynthesis. Genetic knockdown of glycan biosynthetic enzymes ameliorated the hyper-glycosylation and improved cognitive and behavioral outcomes in AD mice. In contrast, oral glucosamine supplementation drove hyper-glycosylation and exacerbated cognitive and behavioral deficits. To assess the clinical relevance of these findings, we conducted a retrospective analysis of a large population of patients with mild cognitive impairment (MCI), AD, and Alzheimers Disease Related Dementias (ADRD) stratified by glucosamine use, leveraging electronic health records. Consistently, glucosamine supplementation was associated with increased mortality in AD and ADRD patient cohorts, and significantly elevated progression from MCI to AD compared to age-matched controls. Collectively, our findings establish hyper-glycosylation as a pathological driver of AD and highlight glycan metabolism as an actional target in the fight against AD.

neuroscience↗