Biology subjects

XU, G.

Publications and source records attributed to XU, G..

3 recordsLinked to original sources

bioRxiv2026

Natural Variation in Maize Shikimate Dehydrogenase Alters Enzyme Activity and Kernel Homoserine Accumulation.

Metabolic diversity in maize kernels determines nutritional quality and end-use value. Therefore, understanding its genetic basis is essential for crop improvement and elucidating plant metabolic regulation. Here, we integrated metabolite profiling with metabolite-based genome-wide association studies (mGWAS), structural modeling, enzyme kinetics, and genome-scale metabolic simulations to identify genetic determinants of kernel metabolite variation in 265 maize inbred lines. Profiling of 57 metabolites revealed inter-genotypic variation, with homoserine among the most variable metabolites. mGWAS identified 62 locus-trait associations implicating 788 candidate genes, including 154 encoding metabolic enzymes. A major association for homoserine mapped to the shikimate dehydrogenase gene Sad1 on chromosome 10. Four tightly linked coding-region SNPs, including three non-synonymous variants, defined two Sad1 haplotypes associated with differential homoserine accumulation, independent of gene expression variation. Structural analysis and recombinant enzyme assays showed that these substitutions occur within catalytic and cofactor-binding domains and alter catalytic efficiency. Genome-scale metabolic modeling indicated that variation in SAD1 activity influences plastidial oxaloacetate availability for aspartate and homoserine biosynthesis through redox-coupled flux via the malate-oxaloacetate shuttle. Together, our results indicate that Sad1 allelic variation alters enzyme function and amino acid accumulation, linking the shikimate pathway, redox metabolism, and amino acid biosynthesis in maize kernels.

plant biology↗

bioRxiv2022

Dissecting the genetic architecture of sunflower head diameter using genome-wide association study

Sunflower (Helianthus annuus L.) plays an essential role in meeting the edible oil demand worldwide. Sunflower seed yield can be decomposed into several yield component traits, one of which is the head diameter. In 2019, 2020, and 2022, we evaluated the head diameter phenotypic variation on a set of diverse sunflower accessions (N=342) in replicated field trials. By combining three years of field data, the broad sense heritability (H2) of the head diameter trait was estimated to be 0.88. Then, a subset of N=274 accessions was genotyped by using the tunable genotyping-by-sequencing (tGBS) method, resulting in 226,779 high-quality SNPs. With these SNPs and the head diameter phenotype, the genome-wide association study (GWAS) was conducted using two statistical approaches: 1) the mixed linear model (MLM) and 2) the fixed and random model circulating probability unification (farmCPU). The MLM and farmCPU GWAS approaches identified 106 and 8 significant SNPs that were placed close to 53 and 21 genes, respectively. Two significant peaks were identified in MLM, with a strong signal on chromosome 10 and a less strong signal on chromosome 16. The farmCPU method detected the same signals on chromosomes 10 and 16 and several additional significant signals on other chromosomes. The head diameter associated genetic loci and the underlying candidate genes can be leveraged for further functional validation and serve as a basis for sunflower oil yield improvement.

genomics↗

bioRxiv2022

Estimating the genetic parameters of yield-related traits under different nitrogen conditions in maize

Understanding the genetic basis responding to nitrogen (N) fertilization in crop production is a long-standing research topic in plant breeding and genetics. Albeit years of continuous efforts, the genetic architecture parameters, such as heritability, polygenicity, and mode of selection, underlying the N responses in maize remain largely unclear. In this study, about n = 230 maize inbred lines were phenotyped under high N (HN) and low N (LN) conditions for two consecutive years to obtain six yield-related traits. Heritability analyses suggested that traits highly responsive to N treatments were less heritable. Using publicly available SNP genotypes, the genome-wide association study (GWAS) was conducted to identify n = 231 and n = 139 trait-associated loci (TALs) under HN and LN conditions, respectively, and n = 162 TALs for N-responsive (NR) traits. Furthermore, genome-wide complex trait Bayesian (GCTB) analysis, a method complementary to GWAS, was performed to estimate genetic parameters, including genetic polygenicity and the mode of selection (S). GCTB results suggested that the NR value of a yield component trait was highly polygenic and that four NR traits exhibited negative correlations between SNP effects and their minor allele frequencies (or the S value < 0) -- a pattern consistent with negative selection to purge deleterious alleles. This study reveals the complex genetic architecture underlying N responses for yield-related traits and provides insights into the future direction for N resilient maize development.

genetics↗