Author Archives:

Identification of SSR markers linked to new fertility restoration trait in sorghum (Sorghum bicolor (L.) Moench) for A4 (maldandi) male sterile cytoplasm

Posted on by

Abstract

Identification of markers associated with fertility restoration (Rf) genes is essential because they can streamline the breeding of new CMS lines and production of commercial hybrid seeds. Therefore, in the present study, F2 populations (M31-2A × DSMR 8) was utilized to identify markers linked to Rf loci on maldandi (A4) cytoplasm through bulk segregant analysis (BSA). The F2 population was analysed for seed set percentage. Chi-square (χ2) analysis showed that the fertility restoration trait followed expected digenic ratio. By BSA, simple sequence repeats (SSRs) markers, namely, Xtxp 34 and Xtxp 69 located on chromosome 3 and SB 3956 and Xtxp 312 located on chromosome 7, showed clear polymorphism between two groups of fertile and sterile bulks. The genomic region harbouring Rf locus on chromosome 3 (2.61 Mbp) predicted to encode five pentatricopeptide repeat (PPR) genes whereas, on chromosome 7, the gene SORBI_3007G047400 predicted to encode MYB (myeloblastosis) domain containing proteins. These predicted genes could be the candidate for restoring fertility on A4 cytoplasm. This finding will be fundamental in the production and rapid selection of novel restorer lines.

Multivariate analysis of the effects of weather variables on white rust epidemics and yield reduction of mustard over multiple growing seasons

Posted on by
Multivariate analysis of the effects of weather variables on white rust epidemics and yield reduction of mustard over multiple growing seasons

Present work illustrates the relevance of weather variables in predicting multiple epidemiological variables, and of multiple disease variables as predictors of actual crop yield.


Abstract

Three shrinkage regression and two machine-learning approaches were evaluated to derive models for the prediction of epidemiological characteristics of white rust of mustard, using data from 112 epidemics in the field. Four epidemiological characteristics were considered: (a) crop age at first appearance of disease, (b) crop age at highest disease severity, (c) highest disease severity in a growing season and (d) area under disease progress curve (AUDPC), along with (e) crop yield to measure the effects of disease on crop performance. We developed models using weather indices to predict these variables using five different approaches: ANN, Elastic Net, LASSO, random forest and ridge regression. One model was developed for each sowing date corresponding to each dependent variable. Two hundred different models were developed. All models performed well at the calibration stage for most of the five variables at all sowing dates. However, at the validation stage, ANN-derived models outperformed (R 2val ~ 1.00, nRMSEV ~0.00 and MBEV ~0.00 in most cases) the three shrinkage regression-derived models in predicting all five variables. Predictions by random forest- and LASSO-derived models were acceptable for AUDPC and crop yield. Evaluation metrics (including R 2val, nRMSEV and MBEV) suggested that ENET- and ridge-derived models do not perform satisfactorily, whereas ANN-derived models yielded reliable results and thus generate robust predictions. The present work constitutes a systematic effort to compare modelling methods for disease and yield prediction and illustrates the relevance of weather variables in predicting multiple epidemiological variables, and of multiple disease variables as predictors of actual crop yield.

Genomic‐wide identification and expression analysis of AP2/ERF transcription factors in Zanthoxylum armatum reveals the candidate genes for the biosynthesis of terpenoids

Posted on by

Abstract

Terpenoids are the main active components in the Zanthoxylum armatum leaves, which have extensive medicinal value. The Z. armatum leaf is the main by-product in the Z. armatum industry. However, the transcription factors involved in the biosynthesis of terpenoids are rarely reported. This study was performed to identify and classify the APETALA2/ethylene-responsive factor (AP2/ERF) gene family of Z. armatum. The chromosome distribution, gene structure, conserved motifs, and cis-acting elements of the promoter of the species were also comprehensively analyzed. A total of 214 ZaAP2/ERFs were identified. From the obtained transcriptome and terpenoid content data, four candidate ZaAP2/ERFs involved in the biosynthesis of terpenoids were selected via correlation and weighted gene co-expression network analysis. A phylogenetic tree was constructed using 13 AP2/ERFs related to the biosynthesis of terpenoids in other plants. ZaERF063 and ZaERF166 showed close evolutionary relationships with the ERFs in other plant species and shared a high AP2-domain sequence similarity with the two closest AP2/ERF proteins, namelySmERF8 from Salvia miltiorrhiza and AaERF4 from Artemisia annua. Further investigation into the effects of methyl jasmonate (MeJA) treatment on the content of terpenoids in Z. armatum leaves revealed that MeJA significantly induced the upregulation of ZaERF166 and led to a significant increase in the terpenoids content in Z. armatum leaves, indicating that ZaERF166 might be involved in the accumulation of terpenoids of Z. armatum. Results will be beneficial for the functional characterization of AP2/ERFs in Z. armatum and establishment of the theoretical foundation to increase the production of terpenoids via the manipulation of the regulatory elements and strengthen the development and utilization of Z. armatum leaves.

Impact of genotype‐calling methodologies on genome‐wide association and genomic prediction in polyploids

Posted on by

Abstract

Discovery and analysis of genetic variants underlying agriculturally important traits are key to molecular breeding of crops. Reduced representation approaches have provided cost-efficient genotyping using next-generation sequencing. However, accurate genotype calling from next-generation sequencing data is challenging, particularly in polyploid species due to their genome complexity. Recently developed Bayesian statistical methods implemented in available software packages, polyRAD, EBG, and updog, incorporate error rates and population parameters to accurately estimate allelic dosage across any ploidy. We used empirical and simulated data to evaluate the three Bayesian algorithms and demonstrated their impact on the power of genome-wide association study (GWAS) analysis and the accuracy of genomic prediction. We further incorporated uncertainty in allelic dosage estimation by testing continuous genotype calls and comparing their performance to discrete genotypes in GWAS and genomic prediction. We tested the genotype-calling methods using data from two autotetraploid species, Miscanthus sacchariflorus and Vaccinium corymbosum, and performed GWAS and genomic prediction. In the empirical study, the tested Bayesian genotype-calling algorithms differed in their downstream effects on GWAS and genomic prediction, with some showing advantages over others. Through subsequent simulation studies, we observed that at low read depth, polyRAD was advantageous in its effect on GWAS power and limit of false positives. Additionally, we found that continuous genotypes increased the accuracy of genomic prediction, by reducing genotyping error, particularly at low sequencing depth. Our results indicate that by using the Bayesian algorithm implemented in polyRAD and continuous genotypes, we can accurately and cost-efficiently implement GWAS and genomic prediction in polyploid crops.

Soybean genetics, genomics, and breeding for improving nutritional value and reducing antinutritional traits in food and feed

Posted on by

Abstract

Soybean [Glycine max (L.) Merr.] is a globally important crop due to its valuable seed composition, versatile feed, food, and industrial end-uses, and consistent genetic gain. Successful genetic gain in soybean has led to widespread adaptation and increased value for producers, processors, and consumers. Specific focus on the nutritional quality of soybean seed composition for food and feed has further elucidated genetic knowledge and bolstered breeding progress. Seed components are historical and current targets for soybean breeders seeking to improve nutritional quality of soybean. This article reviews genetic and genomic foundations for improvement of nutritionally important traits, such as protein and amino acids, oil and fatty acids, carbohydrates, and specific food-grade considerations; discusses the application of advanced breeding technology such as CRISPR/Cas9 in creating seed composition variations; and provides future directions and breeding recommendations regarding soybean seed composition traits.

A medium‐density genotyping platform for cultivated strawberry using DArTag technology

Posted on by

Abstract

Genomic prediction in breeding populations containing hundreds to thousands of parents and seedlings is prohibitively expensive with current high-density genetic marker platforms designed for strawberry. We developed mid-density panels of molecular inversion probes (MIPs) to be deployed with the “DArTag” marker platform to provide a low-cost, high-throughput genotyping solution for strawberry genomic prediction. In total, 7742 target single nucleotide polymorphism (SNP) regions were used to generate MIP assays that were tested with a screening panel of 376 octoploid Fragaria accessions. We evaluated the performance of DArTag assays based on genotype segregation, amplicon coverage, and their ability to produce subgenome-specific amplicon alignments to the FaRR1 assembly and subsequent alignment-based variant calls with strong concordance to DArT's alignment-free, count-based genotype reports. We used a combination of marker performance metrics and physical distribution in the FaRR1 assembly to select 3K and 5K production panels for genotyping of large strawberry populations. We show that the 3K and 5K DArTag panels are able to target and amplify homologous alleles within subgenomic sequences with low-amplification bias between reference and alternate alleles, supporting accurate genotype calling while producing marker genotypes that can be treated as functionally diploid for quantitative genetic analysis. The 3K and 5K target SNPs show high levels of polymorphism in diverse F. × ananassa germplasm and UC Davis cultivars, with mean pairwise diversity (π) estimates of 0.40 and 0.32 and mean heterozygous genotype frequencies of 0.35 and 0.33, respectively.

Mapping QTL for vernalization requirement identified adaptive divergence of the candidate gene Flowering Locus C in polyploid Camelina sativa

Posted on by

Abstract

Vernalization requirement is an integral component of flowering in winter-type plants. The availability of winter ecotypes among Camelina species facilitated the mapping of quantitative trait loci (QTL) for vernalization requirement in Camelina sativa. An inter and intraspecific crossing scheme between related Camelina species, where one spring and two different sources of winter-type habit were used, resulted in the development of two segregating populations. Linkage maps generated with sequence-based markers identified three QTLs associated with vernalization requirement in C. sativa; two from the interspecific (chromosomes 13 and 20) and one from the intraspecific cross (chromosome 8). Notably, the three loci were mapped to different homologous regions of the hexaploid C. sativa genome. All three QTLs were found in proximity to Flowering Locus C (FLC), variants of which have been reported to affect the vernalization requirement in plants. Temporal transcriptome analysis for winter-type Camelina alyssum demonstrated reduction in expression of FLC on chromosomes 13 and 20 during cold treatment, which would trigger flowering, since FLC would be expected to suppress floral initiation. FLC on chromosome 8 also showed reduced expression in the C. sativa ssp. pilosa winter parent upon cold treatment, but was expressed at very high levels across all time points in the spring-type C. sativa. The chromosome 8 copy carried a deletion in the spring-type line, which could impact its functionality. Contrary to previous reports, all three FLC loci can contribute to controlling the vernalization response in C. sativa and provide opportunities for manipulating this requirement in the crop.

Genomic analysis and characterization of new loci associated with seed protein and oil content in soybeans

Posted on by

Abstract

Breeding for increased protein without a reduction in oil content in soybeans [Glycine max (L.) Merr.] is a challenge for soybean breeders but an expected goal. Many efforts have been made to develop new soybean varieties with high yield in combination with desirable protein and/or oil traits. An elite line, R05-1415, was reported to be high yielding, high protein, and low oil. Several significant quantitative trait loci (QTL) for protein and oil were reported in this line, but many of them were unstable across environments or genetic backgrounds. Thus, a new study under multiple field environments using the Infinium BARCSoySNP6K BeadChips was conducted to detect and confirm stable genomic loci for these traits. Genetic analyses consistently detected a single major genomic locus conveying these two traits with remarkably high phenotypic variation explained (R 2), varying between 24.2% and 43.5%. This new genomic locus is located between 25.0 and 26.7 Mb, distant from the previously reported QTL and did not overlap with other commonly reported QTL and the recently cloned gene Glyma.20G085100. Homolog analysis indicated that this QTL did not result from the paracentric chromosome inversion with an adjacent genomic fragment that harbors the reported QTL. The pleiotropic effect of this QTL could be a challenge for improving protein and oil simultaneously; however, a further study of four candidate genes with significant expressions in the seed developmental stages coupled with haplotype analysis may be able to pinpoint causative genes. The functionality and roles of these genes can be determined and characterized, which lay a solid foundation for the improvement of protein and oil content in soybeans.

Exploring the competitive potential of Ralstonia pseudosolanacearum and Ralstonia solanacearum: Insights from a comparative adaptability study

Posted on by
Exploring the competitive potential of Ralstonia pseudosolanacearum and Ralstonia solanacearum: Insights from a comparative adaptability study

Ralstonia pseudosolanacearum exhibits greater biochemical and pathogenic adaptability than R. solanacearum. Conversely, the latter demonstrates greater ecological and physiological adaptability.


Abstract

Bacterial wilt, caused by Ralstonia pseudosolanacearum (Rpsol) and R. solanacearum (Rsol), poses a significant challenge to solanaceous plant cultivation worldwide, particularly in tropical and subtropical regions. Even though Brazil is recognized as one of the centres of origin and diversity of Rsol, in certain regions of this large country there is an emerging prevalence of Rpsol in production fields. Therefore, this study aimed to comprehensively investigate the adaptive traits of Rpsol and Rsol using a polyphasic approach. A diverse collection of isolates from both species was assessed for their physiological, biochemical, ecological and pathogenic traits. Rsol isolates demonstrated greater adaptability to a broader range of temperature, salinity and pH. They also exhibited enhanced abilities in biofilm formation and bacteriocin production. Conversely, Rpsol isolates exhibited a broader utilization of carbon sources and displayed a wider spectrum of resistance to inhibitory substances. Moreover, they demonstrated higher infectivity towards different solanaceous hosts, showing a faster invasion and colonization process in the roots and stems of tomato plants compared to Rsol isolates. Based on our findings, we concluded that Rsol exhibited greater physiological and ecological adaptability, while Rpsol showed greater pathogenic and biochemical adaptability. These results suggest that the coexistence of both species is maintained through a balance of distinct traits within each species.