SRAP analysis of the genetic diversity of wild castor (Ricinus communis L.) in South China

Fine mapping and candidate gene analysis of major QTLs for number of seeds per pod in Arachis hypogaea L

BACKGROUND

Peanut (Arachis hypogaea L., 2n = 2x = 20) is an important industrial and oil crop that is widely grown in more than 100 countries. In recent years, breeders have focused on increasing the seed number per pod to improve their yield in addition to other breeding for other key components of yield, including the pod number, seeds per pod, and 100-seed weight.

RESULTS

In this study, a secondary population of 1,114 BC1F2 lines was derived from a cross between the parents R45 and JNH3. Two stable major-effect quantitative trait loci of qRMPA09.1 and qRMPA09.2 were detected simultaneously and mapped within chromosomal intervals of approximately 400 Kb and 600 Kb on chromosome A09. Additionally, combined whole-genome and RNA sequencing analyses showed the differential expression of the Arahy.04JNDX gene that belongs to a MYB transcription factor (TF) between the two parents. The AhMYB51 gene was also inferred to influence the number of seeds per pod in peanuts. An examination of the backcross lines L2/L4 showed that AhMYB51 increases the rate of multiple pods per plant (RMSP) primarily by affecting brassinosteroids in the flowers, while its overexpression promotes the length of siliques in Arabidopsis thaliana.

CONCLUSIONS

Our findings provide valuable insights for the cloning of favorable alleles for RMSP in peanuts. The qRMSPA09.1 and qRMSPA09.2 are two novel QTL associated with the RMSP trait, with AhMYB51 predicted as its candidate gene. Moreover, the closely linked polymorphic SNP markers for loci of two significant QTLs may be useful in accelerating marker-assisted breeding in peanuts.

Integrating QTL mapping with transcriptome analysis mined candidate genes of growth stages in castor (Ricinus communis L.)

BACKGROUND

The growth stages largely determine the crop yield, while little is known about their genetic mechanisms in castor. In this study, the QTL mapping and candidate gene mining of growth stages were conducted using populations F2 and BC1, combining with differential expression analysis and weighted gene co-expression network analysis (WGCNA). The traits studied included the emergence date (ED), the budding date of primary spike (PSBD), the flowering date of primary spike (PSFD), the maturation date of primary spike (PSMD), and the maturation date of primary branch spike (PBSMD).

RESULTS

A total of 20 QTLs conferring four traits (ED, PSBD, PSFD and PBSMD) were identified in the F2 population, with a phenotypic variation explained (PVE) of single QTL ranged from 0.24 to 25.46%. Five QTLs underlying PSMD and PBSMD were identified in the BC1 population, with a PVE of single QTL ranged from 4.74 to 10.82%. To our surprise, almost all the identified QTLs were clustered within two marker intervals, the RCM1769-RCM1838 on linkage group 6 and RCM950-RCM917 on linkage group 3. Subsequently, 473 open reading frames (ORFs) were searched out within these two clusters and 110 differentially expressed genes (DEGs) were screened out from these ORFs by the comparative transcriptome clean data (a total of 140.86 G) at the budding date, the initial flowering date and the full flowering date between parental racemes. With these DEGs, five distinct gene co-expression modules were generated using WGCNA. Showing significant differential expression between parents, four candidate genes (LOC8261128, LOC8278994, LOC8281165 and LOC8259049) in module MEturquoise, were recognized and were annotated as RcSYN3, RcNTT, RcGG3 and RcSAUR76 respectively. This finding implies their potential role in regulating the growth stages of castor.

CONCLUSION

In this study, numerous QTLs conferring growth stages were detected and four candidate genes were mined, which need to be functionally validated. The results provided a new insight into the genetic structure of ED, PSBD, PSFD, PSMD and PBSMD, offered the candidate genes and molecular markers for their improvement as well in castor.

QTL mapping and candidate gene mining of seed size and seed weight in castor plant (Ricinus communis L.)

BACKGROUND

Castor (Ricinus communis L., 2n = 2x = 20) is an important industrial crop, due to its oil is very important to the global special chemical industry. Seed size and seed weight are fundamentally important in determining castor yield, while little is known about it. In this study, QTL analysis and candidate gene mining of castor seed size and seed weight were conducted with composite interval mapping (CIM), inclusive composite interval mapping (ICIM) and marker enrichment strategy in 4 populations, i.e., populations F2, BC1, S1-1 and S1-2, derived from 2 accessions with significant phenotypic differences.

RESULTS

In the QTL primary mapping, 2 novel QTL clusters were detected in marker intervals RCM520-RCM76 and RCM915-RCM950. In order to verify their accuracy and to narrow their intervals, QTL remapping was carried out in populations F2 and BC1. Among them, 44 and 30 QTLs underlying seed size and seed weight were detected in F2 population using methods CIM and ICIM-ADD respectively, including 4-9 and 3-5 ones conferring each trait were identified with a phenotypic variation explained ranged from 37.92 to 115.81% and 32.86-45.98% respectively. The remapping results in BC1 population were consistent with those in F2 population. Importantly, 3 QTL clusters (i.e. QTL-cluster1, QTL-cluster2 and QTL-cluster3) were found in marker intervals RCM74-RCM76 (37.1 kb), RCM930-RCM950 (259.8 kb) and RCM918-RCM920 (172.9 kb) respectively; in addition, all of them were detected again, the former one was found in the S1-2 population, and the latter two were found simultaneously in the populations S1-1 and S1-2. Finally, 6 candidate genes (i.e. LOC8266555, LOC8281168, LOC8281151, LOC8259066, LOC8258591 and LOC8270077) were screened in the above QTL clusters, they were differentially expressed in multiple seed tissues of both parents, signifying the potential role in regulating seed size and seed weight.

CONCLUSION

The above results not only provide new insights into the genetic structure of seed size and seed weight in castor, but also lay the foundation for the functional identification of these candidate genes.

Modern day breeding approaches for improvement of castor

Castor (Ricinus communis L.) is an industrially important oil producing crop belongs to Euphorbiaceae family. Castor oil has unique chemical properties make it industrially important crop. It is a member of monotypic genus even though it has ample amount of variability. Using this variability, conventionally many varieties and hybrids have been developed. But, like other crops, the modern and unconventional methods of crop improvement has not fully explored in castor. This article discusses the use of polyploidy induction, distant/wide hybridization and mutation breeding as tools for generating variety. Modern approaches accelerate the speed of crop breeding as an alternative tool. To achieve this goal, molecular markers are employed in breeding to capture the genetic variability through molecular analysis and population structuring. Allele mining is used to trace the evolution of alleles, identify new haplotypes and produce allele specific markers for use in marker aided selection using Genome wide association studies (GWAS) and quantitative trait loci (QTL) mapping. Plant genetic transformation is a rapid and effective mode of castor improvement is also discussed here. The efforts towards developing stable regeneration protocol provide a wide range of utility like embryo rescue in distant crosses, development of somaclonal variation, haploid development using anther culture and callus development for stable genetic transformation has reviewed in this article. Omics has provided intuitions to the molecular mechanisms of (a)biotic stress management in castor along with dissected out the possible genes for improving the yield. Relating genes to traits offers additional scientific inevitability leading to enhancement and sympathetic mechanisms of yield improvement and several stress tolerance.

Molecular genetics, seed morphology and fatty acids diversity in castor (Ricinus communis L., Euphorbiaceae) Iranian populations

BACKGROUND

Castor (Ricinus communis L.) seeds contain a large amount of oil that has several biological activities. In the current research, phytogeographic distribution, seed morphological characteristics, molecular genetic diversity and structure, and fatty acid composition were investigated in nine Iranian castor populations.

METHODS AND RESULTS

The cetyltrimethylammonium bromide (CTAB) protocol was used to extract the nuclear genomes. These were later amplified using 13 SCoT molecular primers. The phytogeographic distribution was determined based on the Zohary mapping, GC apparatus determined the fatty acid composition of the seeds. GenAlex, STRUCTURE, GenoDive, PopGene, and PopART software were used for the statistical analyzes. On phytogeographic mapping, the harvested populations belonged to different districts of the Euro-Siberian and Irano-Turanian regions (Holarctic kingdom). Most of the quantitative morphological traits of the seeds differed significantly (P ≤ 0.05) between the populations. The AMOVA test demonstrated a large proportion of significant genetic diversity assigned among populations, which were approved by some estimated parameters of genetic diversity such as Nm, Ht, Hs, and Gst. Nei's genetic distance and structure analysis confirmed the existence of two main genotype groups and some intermediates. However, there was no isolation by distance between the genotypes. Unsaturated fatty acids were detected as the main component of seed oil with linoleic and ricinoleic acids. Significant correlations were detected between the main fatty acids of seed oil with seed morphological traits, geographic distance and the geographic parameters of habitats. According to the composition of the seed fatty acids, four chemotypes groups were detected.

CONCLUSIONS

The classification patterns of the populations based on molecular genetic data, fatty acid composition, and phytogeographic mapping were not identical. These findings indicated that Iranian castor populations had unusual seed fatty acid composition which strongly depended on habitat geographic factors and seed morphological traits. However, the identified chemotypes and genotypes can be used in future breeding programs.

Screening of castor germplasm for wilt reaction and morpho-molecular characterization of resistant genotypes

Castor (Ricinus communis L.) is an important industrial versatile non-edible oilseed C₃ crop belongs to spurge family. Its oil has exceptional properties which provides an industrial importance to this crop. The present investigation was aimed to evaluate the genotypes of castor for Fusarium wilt reaction in pot followed by characterization of resistant genotypes for yield related traits in field and inter-genotype genetic diversity at DNA level. The percent disease incidence (PDI) among 50 genotypes ranged from 0 to 100%. A total of 36 genotypes were found wilt resistant (28 highly resistant and 8 resistant). ANOVA revealed that the genotypes MSS was significant for each trait studied, indicating the existence of plentiful variability in the experimental material. The morphological characterization showed that DCS-109 (73.30 cm) had a dwarf stature The genotype RG-1954 was superior for oil content (50.29%) with moderate for shelling out (67.63). RG-1673 was outstanding for seed boldness as 100 seed weight for this genotype was maximum (38.98 gm). JI-403 had maximum seed yield per plant (SYPP; 354.88 gm). SYPP positively associated with all traits except oil and seed length:breadth ratio. The path analysis revealed that the direct effects of NPR (0.549), TLFP (0.916), and CPP on SYPP are quite significant. A total of 38 alleles from 18 SSR markers were amplified in 36 genotypes. The NJ tree could divide 36 genotypes into three main clusters. AMOVA revealed 15% and 85% variance among and within subpopulations, respectively. Both morphological and SSR data demonstrated to be effective tools for discerning inter-genotypes diversity and categorizing high-yielding and disesae-tolerant castor genotypes lines.