A SNP variation in the Sucrose synthase (SoSUS) gene associated with sugar-related traits in sugarcane.

Background: Sugarcane (Saccharum spp.) is an economically significant crop for both the sugar and biofuel industries. Breeding sugarcane cultivars with high-performance agronomic traits is the most effective approach for meeting the rising demand for sugar and biofuels. Molecular markers associated with relevant agronomic traits could drastically reduce the time and resources required to develop new sugarcane varieties. Previous sugarcane candidate gene association analyses have found single nucleotide polymorphism (SNP) markers associated with sugar-related traits. This study aims to validate these associated SNP markers of six genes, including Lesion simulating disease 1 (LSD), Calreticulin (CALR), Sucrose synthase 1 (SUS1), DEAD-box ATP-dependent RNA helicase (RH), KANADI1 (KAN1), and Sodium/hydrogen exchanger 7 (NHX7), in a diverse population in 2-year and two-location evaluations. Methods: After genotyping of seven targeted SNP markers was performed by PCR Allelic Competitive Extension (PACE) SNP genotyping, the association with sugar-related traits and important cane yield component traits was determined on a set of 159 sugarcane genotypes. The marker-trait relationships were validated and identified by both t-test analysis and an association analysis based on the general linear model. Results: The mSoSUS1_SNPCh10.T/C and mSoKAN1_SNPCh7.T/C markers that were designed from the SUS1 and KAN1 genes, respectively, showed significant associations with different amounts of sugar-related traits and yield components. The mSoSUS1_SNPCh10.T/C marker was found to have more significant association with sugar-related traits, including pol, CCS, brix, fiber and sugar yield, with p values of 6.08 × 10-6 to 4.35 × 10-2, as well as some cane yield component traits with p values of 1.61 × 10-4 to 3.35 × 10-2. The significant association is consistent across four environments. Conclusion: Sucrose synthase (SUS) is considered a crucial enzyme involved in sucrose metabolism. This marker is a high potential functional marker that may be used in sugarcane breeding programs to select superior sugarcane with good fiber and high sugar contents.

Assessment of the Genetic Diversity and Population Structure of Rhizophora mucronata along Coastal Areas in Thailand.

Unique and biodiverse, mangrove ecosystems provide humans with benefits and contribute to coastal protection. Rhizophora mucronata, a member of the Rhizophoraceae family, is prevalent in the mangrove forests of Thailand. R. mucronata's population structure and genetic diversity have received scant attention. Here, we sequenced the entire genome of R. mucronata using 10× Genomics technology and obtained an assembly size of 219 Mb with the N50 length of 542,540 bases. Using 2857 single nucleotide polymorphism (SNP) markers, this study investigated the genetic diversity and population structure of 80 R. mucronata accessions obtained from the mangrove forests in Thailand. The genetic diversity of R. mucronata was moderate (I = 0.573, Ho = 0.619, He = 0.391). Two subpopulations were observed and confirmed from both population structure and principal component analysis (PCA). Analysis of molecular variance (AMOVA) showed that there was more variation within populations than between them. Mean pairwise genetic differentiation (FST = 0.09) showed that there was not much genetic difference between populations. Intriguingly, the predominant clustering pattern in the R. mucronata population did not correspond to the Gulf of Thailand and the Andaman Sea, which are separated by the Malay Peninsula. Several factors could have influenced the R. mucronata genetic pattern, such as hybridization and anthropogenic factors. This research will provide important information for the future conservation and management of R. mucronata in Thailand.

Candidate gene association of gene expression data in sugarcane contrasting for sucrose content.

Association mapping of gene expression data, generated from transcriptome and proteome studies, provides a means of understanding the functional significance and trait association potential of candidate genes. In this study, we applied candidate gene association mapping to validate sugarcane genes, using data from the starch and sucrose metabolism pathway, transcriptome, and proteome. We performed multiplex PCR targeted amplicon sequencing of 109 candidate genes, using NGS technology. A range of statistical models, both single-locus and multi-locus, were compared for minimization of false positives in association mapping of four sugar-related traits with different heritability. The Fixed and random model Circulating Probability Unification model effectively suppressed false positives for both low- and high-heritability traits. We identified favorable alleles of the candidate genes involved in signalling and transcriptional regulation. The results will support genetic improvement of sugarcane and may help clarify the genetic architecture of sugar-related traits.