Weighted gene co-expression network analysis unveils gene networks regulating folate biosynthesis in maize endosperm

Bioinformatics and meta-analysis of expression data to investigate transcriptomic response of wheat root to abiotic stresses

Abiotic stresses are predominant and main causes of the losses in the crop yield. A complexity of systems biology and involvement of numerous genes in the response to abiotic factors have challenged efforts to create tolerant cultivars with sustainable production. The root is the main organ of the plant and determines a plant tolerance under stressful conditions. In this study, we carried out a meta-analysis of expression datasets from wheat root to identify differentially expressed genes, followed by the weighted gene co-expression network analysis (WGCNA) to construct the weighted gene co-expression network. The aim was to identify consensus differentially expressed genes with regulatory functions, gene networks, and biological pathways involved in response of wheat root to a set of abiotic stresses. The meta-analysis using Fisher method (FDR<0.05) identified consensus 526 DEGs from 55,367 probe sets. Although the annotated expression data are limited for wheat, the functional analysis based on the data from model plants could identify the up-regulated seven regulatory genes involved in chromosome organization and response to oxygen-containing compounds. WGCNA identified four gene modules that were mostly associated with the ribosome biogenesis and polypeptide synthesis. This study's findings enhance our understanding of key players and gene networks related to wheat root response to multiple abiotic stresses.

Identification of novel loci associated with starch content in maize kernels by a genome-wide association study using an enlarged SNP panel

Starch is a major component of cereals, comprising over 70% of dry weight. It serves as a primary carbon source for humans and animals. In addition, starch is an indispensable industrial raw material. While maize (Zea mays) is a key crop and the primary source of starch, the genetic basis for starch content in maize kernels remains poorly understood. In this study, using an enlarged panel, we conducted a genome-wide association study (GWAS) based on best linear unbiased prediction (BLUP) value for starch content of 261 inbred lines across three environments. Compared with previous study, we identified 14 additional significant quantitative trait loci (QTL), encompassed a total of 42 genes, and indicated that increased marker density contributes to improved statistical power. By integrating gene expression profiling, Gene Ontology (GO) enrichment and haplotype analysis, several potential target genes that may play a role in regulating starch content in maize kernels have been identified. Notably, we found that ZmAPC4, associated with the significant SNP chr4.S_175584318, which encodes a WD40 repeat-like superfamily protein and is highly expressed in maize endosperm, might be a crucial regulator of maize kernel starch synthesis. Out of the 261 inbred lines analyzed, they were categorized into four haplotypes. Remarkably, it was observed that the inbred lines harboring hap4 demonstrated the highest starch content compared to the other haplotypes. Additionally, as a significant achievement, we have developed molecular markers that effectively differentiate maize inbred lines based on their starch content. Overall, our study provides valuable insights into the genetic basis of starch content and the molecular markers can be useful in breeding programs aimed at developing maize varieties with high starch content, thereby improving breeding efficiency.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01437-6.

Identification of quantitative trait loci and candidate genes for seed folate content in soybean

KEY MESSAGE

From 61 QTL mapped, a stable QTL cluster of 992 kb was discovered on chromosome 5 for folate content and a putative candidate gene, Glyma.05G237500, was identified. Folate (vitamin B9) is one of the most essential micronutrients whose deficiencies lead to various health defects in humans. Herein, we mapped the quantitative trait loci (QTL) underlying seed folate content in soybean using recombinant inbred lines developed from cultivars, ZH35 and ZH13, across four environments. We identified 61 QTL on 12 chromosomes through composite interval mapping, with phenotypic variance values ranging from 1.68 to 24.68%. A major-effect QTL cluster (qFo-05) was found on chromosome 5, spanning 992 kb and containing 134 genes. Through gene annotation and single-locus haplotyping analysis of qFo-05 in a natural soybean population, we identified seven candidate genes significantly associated with 5MTHF and total folate content in multiple environments. RNA-seq analysis showed a unique expression pattern of a hemerythrin RING zinc finger gene, Glyma.05G237500, between both parental cultivars during seed development, which suggest the gene might regulate folate content in soybean. This is the first study to investigate QTL underlying folate content in soybean and provides new insight for molecular breeding to improve folate content in soybean.