Identification of Salt-Sensitive and Salt-Tolerant Genes through Weighted Gene Co-Expression Networks across Multiple Datasets: A Centralization and Differential Correlation Analysis.

Salt stress is a significant challenge that severely hampers rice growth, resulting in decreased yield and productivity. Over the years, researchers have identified biomarkers associated with salt stress to enhance rice tolerance. However, the understanding of the mechanism underlying salt tolerance in rice remains incomplete due to the involvement of multiple genes. Given the vast amount of genomics and transcriptomics data available today, it is crucial to integrate diverse datasets to identify key genes that play essential roles during salt stress in rice. In this study, we propose an integration of multiple datasets to identify potential key transcription factors. This involves utilizing network analysis based on weighted co-expression networks, focusing on gene-centric measurement and differential co-expression relationships among genes. Consequently, our analysis reveals 86 genes located in markers from previous meta-QTL analysis. Moreover, six transcription factors, namely LOC_Os03g45410 (OsTBP2), LOC_Os07g42400 (OsGATA23), LOC_Os01g13030 (OsIAA3), LOC_Os05g34050 (OsbZIP39), LOC_Os09g29930 (OsBIM1), and LOC_Os10g10990 (transcription initiation factor IIF), exhibited significantly altered co-expression relationships between salt-sensitive and salt-tolerant rice networks. These identified genes hold potential as crucial references for further investigation into the functions of salt stress response in rice plants and could be utilized in the development of salt-resistant rice cultivars. Overall, our findings shed light on the complex genetic regulation underlying salt tolerance in rice and contribute to the broader understanding of rice's response to salt stress.

A k-mer-based bulked segregant analysis approach to map seed traits in unphased heterozygous potato genomes.

High-throughput sequencing-based methods for bulked segregant analysis (BSA) allow for the rapid identification of genetic markers associated with traits of interest. BSA studies have successfully identified qualitative (binary) and quantitative trait loci (QTLs) using QTL mapping. However, most require population structures that fit the models available and a reference genome. Instead, high-throughput short-read sequencing can be combined with BSA of k-mers (BSA-k-mer) to map traits that appear refractory to standard approaches. This method can be applied to any organism and is particularly useful for species with genomes diverged from the closest sequenced genome. It is also instrumental when dealing with highly heterozygous and potentially polyploid genomes without phased haplotype assemblies and for which a single haplotype can control a trait. Finally, it is flexible in terms of population structure. Here, we apply the BSA-k-mer method for the rapid identification of candidate regions related to seed spot and seed size in diploid potato. Using a mixture of F1 and F2 individuals from a cross between 2 highly heterozygous parents, candidate sequences were identified for each trait using the BSA-k-mer approach. Using parental reads, we were able to determine the parental origin of the loci. Finally, we mapped the identified k-mers to a closely related potato genome to validate the method and determine the genomic loci underlying these sequences. The location identified for the seed spot matches with previously identified loci associated with pigmentation in potato. The loci associated with seed size are novel. Both loci are relevant in future breeding toward true seeds in potato.

Identification of Key Genes in 'Luang Pratahn', Thai Salt-Tolerant Rice, Based on Time-Course Data and Weighted Co-expression Networks.

Salinity is an important environmental factor causing a negative effect on rice production. To prevent salinity effects on rice yields, genetic diversity concerning salt tolerance must be evaluated. In this study, we investigated the salinity responses of rice (Oryza sativa) to determine the critical genes. The transcriptomes of 'Luang Pratahn' rice, a local Thai rice variety with high salt tolerance, were used as a model for analyzing and identifying the key genes responsible for salt-stress tolerance. Based on 3' Tag-Seq data from the time course of salt-stress treatment, weighted gene co-expression network analysis was used to identify key genes in gene modules. We obtained 1,386 significantly differentially expressed genes in eight modules. Among them, six modules indicated a significant correlation within 6, 12, or 48h after salt stress. Functional and pathway enrichment analysis was performed on the co-expressed genes of interesting modules to reveal which genes were mainly enriched within important functions for salt-stress responses. To identify the key genes in salt-stress responses, we considered the two-state co-expression networks, normal growth conditions, and salt stress to investigate which genes were less important in a normal situation but gained more impact under stress. We identified key genes for the response to biotic and abiotic stimuli and tolerance to salt stress. Thus, these novel genes may play important roles in salinity tolerance and serve as potential biomarkers to improve salt tolerance cultivars.