Evaluation of Inbred Maize (Zea mays L.) for Tolerance to Low Phosphorus at the Seedling Stage.

In underdeveloped nations where low-input agriculture is practiced, low phosphorus (LP) in the soil reduces the production of maize. In the present study, a total of 550 inbred maize lines were assessed for seedling traits under LP (2.5 × 10-6 mol L-1 of KH2PO4) and NP (2.5 × 10-4 mol L-1 of KH2PO4) hydroponic conditions. The purpose of this study was to quantify the amount of variation present in the measured traits, estimate the genetic involvement of these characteristics, examine the phenotypic correlation coefficients between traits, and to integrate this information to prepare a multi-trait selection index for LP tolerance in maize. A great deal of variability in the maize genotype panel was confirmed by descriptive statistics and analysis of variance (ANOVA). Estimated broad-sense heritability (h2) ranged from 0.7 to 0.91, indicating intermediate to high heritability values for the measured traits. A substantial connection between MSL and other root traits suggested that the direct selection of MSL (maximum shoot length) could be beneficial for the enhancement of other traits. The principal component analysis (PCA) of the first two main component axes explained approximately 81.27% of the variation between lines for the eight maize seedling variables. TDM (total dry matter), SDW (shoot dry weight), RDW (root dry weight), SFW (shoot fresh weight), RFW (root fresh weight), MRL (maximum root length), and MSL measurements accounted for the majority of the first principal component (59.35%). The multi-trait indices were calculated based on PCA using all the measured traits, and 30 genotypes were selected. These selected lines might be considered as the potential source for the improvement of LP tolerance in maize.

Introgression of Bacterial Blight Resistance Genes in the Rice Cultivar Ciherang: Response against Xanthomonas oryzae pv. oryzae in the F6 Generation.

Bacterial blight (BB) is caused by Xanthomonas oryzae pv. oryzae and is one of the most important diseases in rice. It results in significantly reduced productivity throughout all rice-growing regions of the world. Four BB resistance genes have been reported; however, introgression of a single gene into rice has not been able to sufficiently protect rice against BB infection. Pyramiding of effective BB resistance genes (i.e., Xa genes) into background varieties is a potential approach to controlling BB infection. In this study, combinations of four BB resistance genes, Xa4, xa5, xa13, and Xa21, were pyramided into populations. The populations were derived from crossing Ciherang (a widespread Indonesian rice variety) with IRBB60 (resistance to BB). Promising recombinants from the F6 generation were identified by scoring the phenotype against three virulent bacterial strains, C5, P6, and V, which cause widespread BB infection in most rice-growing countries. Pyramiding of genes for BB resistance in 265 recombinant introgressed lines (RILs) were confirmed through marker-assisted selection (MAS) of the F5 and F6 generations using gene-specific primers. Of these 265 RILs, 11, 34 and 45 lines had four, three, or two BB resistance genes, respectively. The RILs had pyramiding of two or three resistance genes, with the Xa4 resistance gene showing broad spectrum resistance against Xoo races with higher agronomic performance compared to their donor and recipients parents. The developed BB-resistant RILs have high yield potential to be further developed for cultivation or as sources of BB resistance donor material for varietal improvement in other rice lines.

Progressive Genomic Approaches to Explore Drought- and Salt-Induced Oxidative Stress Responses in Plants under Changing Climate.

Drought and salinity are the major environmental abiotic stresses that negatively impact crop development and yield. To improve yields under abiotic stress conditions, drought- and salinity-tolerant crops are key to support world crop production and mitigate the demand of the growing world population. Nevertheless, plant responses to abiotic stresses are highly complex and controlled by networks of genetic and ecological factors that are the main targets of crop breeding programs. Several genomics strategies are employed to improve crop productivity under abiotic stress conditions, but traditional techniques are not sufficient to prevent stress-related losses in productivity. Within the last decade, modern genomics studies have advanced our capabilities of improving crop genetics, especially those traits relevant to abiotic stress management. This review provided updated and comprehensive knowledge concerning all possible combinations of advanced genomics tools and the gene regulatory network of reactive oxygen species homeostasis for the appropriate planning of future breeding programs, which will assist sustainable crop production under salinity and drought conditions.

A Comparison on Some Interval Mapping Approaches for QTL Detection.

Quantitative trait locus (QTL) analysis is a statistical method that links two types of information such as phenotypic data (trait measurements) and genotypic data (usually molecular markers). There a number of QTL tools have been developed for gene linkage mapping. Standard Interval Mapping (SIM) or Simple Interval Mapping or Interval Mapping (IM), Haley Knott, Extended Haley Knott and Multiple Imputation (IMP) method when the single-QTL is unlinked and Composite Interval Mapping (CIM) is designed to map the genetic linkage for both linked and unlinked genes in the chromosome. Performance of these methods is measured based on calculated LOD score. The QTLs are considered significant above the threshold LOD score 3.0. For backcross-simulated data, the CIM method performs significantly in detecting QTLs compare to other SIM mapping methods. CIM detected three QTLs in chromosome 1 and 4 whereas the other methods were unable to detect any significant marker positions for simulated data. For a real rice dataset, CIM also showed performance considerably in detecting marker positions compared to other four interval mapping methods. CIM finally detected 12 QTL positions while each of the other four SIM methods detected only six positions.