QTL analysis for carbon assimilate translocation-related traits during maturity in rice (Oryza sativa L.).

Problems with carbon assimilate translocation from source organs to sink (grains) during ripening cause yield losses in rice (Oryza sativa L.), especially in high-sink-capacity varieties. We conducted a genetic analysis of traits related to such translocation by using recombinant inbred lines. Shoot weight (SW) of T65, a japonica parent, was retained from heading to late maturity, whereas that of DV85, an aus parent, was greater than that of T65 at 5 days after heading (DAH) and then decreased until 20 DAH. This difference was observed clearly under standard-fertilizer but not low-fertilizer conditions. Non-structural carbohydrate (NSC) contents in the parents showed a tendency similar to that for SW. QTL analysis revealed pleiotropic QTLs on chromosomes 5 and 10, probably by associations with heading date QTLs. A QTL associated with harvest index and NSC at 5 DAH was detected on chromosome 1. By considering the temporal changes of the traits, we found a QTL for decrease in SW on chromosome 11; the DV85 allele of this QTL facilitated assimilate translocation and suppressed biomass growth. A suggestive QTL for NSC decrease was located on chromosome 2. These QTLs could represent potential targets for controlling carbon assimilate translocation in breeding programs.

Genetic variation of blast (Pyricularia oryzae Cavara) resistance in rice (Oryza sativa L.) accessions widely used in Kenya.

A total of 47 rice accessions collected from Kenya were investigated the genetic variations and classified into two cluster groups, A and B, by polymorphism data of 65 simple sequence repeat (SSR) markers. Clusters A and B corresponded to Japonica and Indica Groups, respectively. The number of Japonica Group accessions was limited in comparison with those of the Indica Group. Based on their patterns of reaction to standard differential blast isolates (SDBIs), these accessions and 57 control cultivars including differential varieties and several accessions harboring partial resistance genes were classified again into three cluster groups: Ia (high resistance), Ib (intermediate resistance) and II (susceptible). The rice accessions from Kenya were classified only into groups Ia and Ib. The accessions from Kenya were finally classified into three categories, A-Ia, B-Ia and B-Ib, based on the two classifications of polymorphism of SSR markers and resistance. The Indica Group accessions had wider genetic variation for blast resistance than did the Japonica Group accessions. The three leading cultivars (Basmati 217, Basmati 370 and ITA 310) categorized into Cluster group Ia were susceptible to some SDBIs from Kenya. The genetic variation for blast resistance in Kenya was demonstrated as the first report using SDBIs.

Pathogenicities of Rice Blast (Pyricularia oryzae Cavara) Isolates From Kenya.

A total of 99 isolates of rice blast (Pyricularia oryzae Cavara) were collected from 2010 to 2015 from four regions in Kenya: Kirinyaga County and Embu County, Kisumu County, Tana River County, and Mombasa County. The pathogenicities of these isolates were clarified based on the reaction patterns of Lijiangxintuanheigu and differential varieties (DVs) targeting 23 resistance genes. The frequency of virulent isolates was high for DVs for Pib, Pia, Pii, Pi3, Pi5(t), Pik-s, Pik-m, Pi1, Pik-h, Pik, Pik-p, Pi7(t), Pi19(t), and Pi20(t); low for DVs for Pish, Pi9(t), Piz-5, and Piz-t; and intermediate for the remaining DVs for Pit, Piz, Pita-2, Pita, and Pi12(t). These blast isolates were classified into three cluster groups: Ia, Ib, and II. The frequencies of virulent isolates to DVs for Pit, Pii, Pik-m, Pi1, Pik-h, Pik, Pik-p, Pi7(t), Piz, and Pi12(t) differed markedly between clusters I and II, and those of DVs for Pib, Pit, Pia, Pi3, Pita-2, Pita, and Pi20(t) differed between Ia and Ib. The frequencies of cluster groups in the four geographical regions were different. A total of 62 races were found, with 19 blast isolates categorized into one race (U63-i7-k177-z00-ta003), whereas the other races included only some isolates in each.

Evaluation of Grain-Filling-Related Traits Using Taichung 65 x DV85 Chromosome Segment Substitution Lines (TD-CSSLs) of Rice.

Grain yield of rice consists of sink capacity and grain filling. There are some genes known to contribute to sink capacity, but few genes associated with grain filling are known. We conducted a genetic analysis on yield-related traits by using a chromosome segment substitution line population that have introgression from DV85, an aus variety of rice, in the background of T65, a japonica variety. Refined whole-genome genotypes of the 43 TD-CSSLs were obtained by genotyping-by-sequencing. The effects of previously detected quantitative trait loci (QTLs), qNSC1 and qNSC2, were confirmed by the amount of non-structural carbohydrate (NSC) at 5 days after heading (DAH). The CSSL for qSWTR11, the QTL for decrease in shoot weight during the maturity stage, showed the highest NSC at 5 DAH and lowest at 35 DAH. The brown rice yield of these lines were not stably significant. Most of the sink-related traits correlated between the 2 tested years, but most of the grain-filling traits did not show correlation between the 2 years. Correlation analysis revealed that the sink capacity is stable and primarily determines the yield, and grain filling is more affected by the environment. In addition, biomass production before heading and during the maturity stage contributes to higher yield in TD-CSSLs, and the amount of translocation of stem reserve does not affect much to the yield. We conclude that higher NSC at the heading stage and rapid decrease in shoot biomass during the maturity stage did not directly contribute to the yield formation in the japonica genetic background.

Genetic Variation of Blast (Pyricularia oryzae Cavara) Resistance in the Longistaminata Chromosome Segment Introgression Lines (LCSILs) and Potential for Breeding Use in Kenya.

In Kenya's rice-growing areas, Basmati varieties have been produced in monoculture since the late 1980s. This has resulted in the breakdown of the resistance (R) gene-mediated response of the local Basmati varieties to blast disease caused by Pyricularia oryzae. To improve blast resistance in Kenyan Basmati varieties, continuous identification of R genes and suitable breeding materials for Basmati are necessary. Longistaminata chromosome segment introgression lines (LCSILs) with the Kernel Basmati genetic background, developed using a rice line called potential low-input adaptable-1 (pLIA-1) derived from a cross between Taichung 65 (T65) (a rice variety in the Japonica Group) and O. longistaminata, are expected to contain useful blast R genes derived from O. longistaminata or T65. In this study, we investigated the genetic variation of blast R genes in LCSILs and their parents by using a new international differential system for designating blast races based on the gene-for-gene theory and molecular characterization using single nucleotide polymorphism (SNP) markers. LCSILs and their parents were classified into three groups-A, B1, and B2-based on reaction patterns to the standard differential blast isolates (SDBIs). Group A, including pLIA-1, showed the highest resistance in all groups, followed by groups B1 and B2. Kernel Basmati in group B1 was considered to possess Pik-p or Pi7(t), Pi19(t), and other unknown R genes. In addition to these R genes, LCSIL 6, 12, 27, 28, and 40, in group A, were determined to possess one of Pish, Piz-t, or both genes that confer resistance to the Kenyan blast races. These lines can be used for efficiently pyramiding blast R genes in the local Basmati varieties.

Utilization of Genotyping-by-Sequencing (GBS) for Rice Pre-Breeding and Improvement: A Review.

Molecular markers play a crucial role in the improvement of rice. To benefit from these markers, genotyping is carried out to identify the differences at a specific position in the genome of individuals. The advances in sequencing technologies have led to the development of different genotyping techniques such as genotyping-by-sequencing. Unlike PCR-fragment-based genotyping, genotyping-by-sequencing has enabled the parallel sequencing and genotyping of hundreds of samples in a single run, making it more cost-effective. Currently, GBS is being used in several pre-breeding programs of rice to identify beneficial genes and QTL from different rice genetic resources. In this review, we present the current advances in the utilization of genotyping-by-sequencing for the development of rice pre-breeding materials and the improvement of existing rice cultivars. The challenges and perspectives of using this approach are also highlighted.

Marker-Assisted Introgression and Stacking of Major QTLs Controlling Grain Number (Gn1a) and Number of Primary Branching (WFP) to NERICA Cultivars.

The era of the green revolution has significantly improved rice yield productivity. However, with the growing population and decreasing arable land, rice scientists must find new ways to improve rice productivity. Although hundreds of rice yield-related QTLs were already mapped and some of them were cloned, only a few were utilized for actual systematic introgression breeding programs. In this study, the major yield QTLs Grain Number 1a (Gn1a) and Wealthy Farmer's Panicle (WFP) were introgressed and stacked in selected NERICA cultivars by marker-assisted backcross breeding (MABB). The DNA markers RM3360, RM3452, and RM5493 were used for foreground selection. At BC3F4 and BC3F5 generation, a combination of marker-assisted selection and phenotypic evaluation were carried out to select lines with target alleles and traits. Further, genotyping-by-sequencing (GBS) was conducted to validate the introgression and determine the recurrent parent genome recovery (RPGR) of the selected lines. The Gn1a and/or WFP introgression lines showed significantly higher numbers of spikelets per panicle and primary branching compared to the recurrent parents. In addition, lines with Gn1a and/or WFP alleles were comparatively similar to the recurrent parents (RP) in most yield-related traits. This study demonstrates the success of utilizing yield QTLs and marker-assisted selection to develop and improve rice cultivars.

Investigating the impact of rice blast disease on the livelihood of the local farmers in greater Mwea region of Kenya.

Rice is the most important cereal crop in Kenya coming third after maize and wheat. It forms a very important diet for a majority of families in Kenya. The demand for rice in Kenya has seen a dramatic increase over the last few years while production has remained low. This is because rice production has been faced by serious constraints notably plant diseases of which the most devastating is rice blast. Rice blast is known to cause approximately 60% -100% yield losses. It is caused by an Ascomycete fungus called Magnaporthe Oryzae. The aim of this study was to investigate the impact of rice blast disease on the livelihood of the local farmers in Greater Mwea region and develop a rice blast disease distribution map using GIS approach. The study methodology employed a questionnaire survey which were subjected to sample population of households in the 7 sections with 70 blocks within Mwea region. The collected data was analysed using SAS Version 9.1. Descriptive statistics were used to summarize the household characteristics, the farm characteristics and the farmers' perceptions of rice blast disease. In the questionnaire, farmers' response on whether they had been affected by rice blast disease and the total production per acreage was used to develop an attribute table with GPS points. The GPS points were interpolated to create a geographical distribution map of rice blast disease. From the research findings almost all the farmers' had awareness and knowledge of rice blast disease, 98% of the farmers interviewed were aware of rice blast disease. Out of the 98% with knowledge and awareness 76% have been affected by the disease, while 24% have never been affected. Farmers attributed rice blast disease to a range of different causes, including excessive use of nitrogen fertilizer, water shortage, lack of proper drainage canal and due to climate change. Majority of the farmers interviewed (72%) did not engage themselves in any other socio-economic activity even after being affected by the rice blast disease. 15% opted to growing horticultural crops, 7% engaged in trading activities while 2% started livestock raring, wage earning and Boda boda business.