High-throughput plant breeding approaches: Moving along with plant-based food demands for pet food industries

In vitro simulated digestion and Caco-2 cell absorption to explore potential of soy protein isolates as whey protein substitutes in canine and feline food

Digestive properties and bioavailability of soy protein isolate and whey protein in canine and feline were evaluated using in vitro simulated digestion and cell absorption experiments. The amino acids and peptides in soybean protein isolate and whey protein after digestion were detected by high-performance liquid chromatography and liquid mass spectrometry. Gastrointestinal digestion rates of soy protein isolate and whey protein were analyzed by fitting digestive kinetics curves. The degree of absorption and utilization of amino acids and peptides from the digestive products was evaluated by establishing a Caco-2 cell model. The results demonstrated that soy protein isolate, like whey protein, could produce large amounts of free amino acids and peptides distributed 100-1500 Da. The gastrointestinal digestion speed of soy protein isolate was similar with whey protein. It is worth noting from the intestinal absorption of Caco-2 cell that more than 15 amino acids produced by soy protein isolate and whey protein could be absorbed, and a large number of peptides were also utilized by Caco-2 cell. The bioavailability of soy protein isolates and whey protein for dogs respectively reached 6.30% and 9.00%, and it reached 7.40% and 16.40% in cats, respectively. Soy isolate proteins can be digested and absorbed by pets like whey proteins. These findings may provide significant strategies and support for the application of plant-based proteins in pet foods.

Omics-Driven Strategies for Developing Saline-Smart Lentils: A Comprehensive Review

A number of consequences of climate change, notably salinity, put global food security at risk by impacting the development and production of lentils. Salinity-induced stress alters lentil genetics, resulting in severe developmental issues and eventual phenotypic damage. Lentils have evolved sophisticated signaling networks to combat salinity stress. Lentil genomics and transcriptomics have discovered key genes and pathways that play an important role in mitigating salinity stress. The development of saline-smart cultivars can be further revolutionized by implementing proteomics, metabolomics, miRNAomics, epigenomics, phenomics, ionomics, machine learning, and speed breeding approaches. All these cutting-edge approaches represent a viable path toward creating saline-tolerant lentil cultivars that can withstand climate change and meet the growing demand for high-quality food worldwide. The review emphasizes the gaps that must be filled for future food security in a changing climate while also highlighting the significant discoveries and insights made possible by omics and other state-of-the-art biotechnological techniques.

Genetic diversity and genome-wide association study of partial resistance to Sclerotinia stem rot in a Canadian soybean germplasm panel

KEY MESSAGE

Developing genetically resistant soybean cultivars is key in controlling the destructive Sclerotinia Stem Rot (SSR) disease. Here, a GWAS study in Canadian soybeans identified potential marker-trait associations and candidate genes, paving the way for more efficient breeding methods for SSR. Sclerotinia stem rot (SSR), caused by the fungal pathogen Sclerotinia sclerotiorum, is one of the most important diseases leading to significant soybean yield losses in Canada and worldwide. Developing soybean cultivars that are genetically resistant to the disease is the most inexpensive and reliable method to control the disease. However, breeding for resistance is hampered by the highly complex nature of genetic resistance to SSR in soybean. This study sought to understand the genetic basis underlying SSR resistance particularly in soybean grown in Canada. Consequently, a panel of 193 genotypes was assembled based on maturity group and genetic diversity as representative of Canadian soybean cultivars. Plants were inoculated and screened for SSR resistance in controlled environments, where variation for SSR phenotypic response was observed. The panel was also genotyped via genotyping-by-sequencing and the resulting genotypic data were imputed using BEAGLE v5 leading to a catalogue of 417 K SNPs. Through genome-wide association analyses (GWAS) using FarmCPU method with threshold of FDR-adjusted p-values < 0.1, we identified significant SNPs on chromosomes 2 and 9 with allele effects of 16.1 and 14.3, respectively. Further analysis identified three potential candidate genes linked to SSR disease resistance within a 100 Kb window surrounding each of the peak SNPs. Our results will be important in developing molecular markers that can speed up the breeding for SSR resistance in Canadian grown soybean.

Genetic study for seed germination and shattering in Euphorbia lagascae in response to different seed treatments

Euphorbia lagascae Spreng is a promising emerging oilseed crop, with its seed oil accounting for approximately 50% of the seed weight. Euphorbia oil contains a significant amount of vernolic acid, comprising two-thirds of its composition, which boasts various industrial applications, including acting as a stabilizer-plasticizer and natural dye. However, this species was known to have a high degree of seed-shattering and a low germination rate, which act as two important barriers to large-scale production and exploitation. Therefore, the objective of this study is to determine the genetic control of seed germination and seed-shattering traits in order to develop a reliable pipeline that would be applicable for industries and breeders to select superior E. lagascae lines and design a robust breeding scheme in a short time at reduced labor costs. For this objective, five different wild-type genotypes of E. lagascae that demonstrated high germination potential were crossed with an ethyl methanesulfonate (EMS) mutant genotype that produces non-shattering capsules. The F2 populations from two successful crosses (A and B) were separated into three different treated groups for seed germination evaluation and to study the segregation of 200 individuals per F2 population. The three treatments were: light, gibberellic acid (GA3), and control treatment. Consequently, plants treated with approximately 250 μmol/m2/s of light showed significant improvement in germination up to 75% in cross A and 82.4 % in cross B compared with the control plants and the group treated with 0.05% GA3. According to the chi-square test results, the inheritance pattern of seed germination in response to light treatment follows a 3:1 segregation ratio between germinated and non-germinated seeds, indicating a dominant gene action in the F2 generation. The same conclusion was followed for the shattering trait in the group treated with light, which was also simply inherited as a 3:1 ratio for shattering vs. non-shattering capsules. Our results emphasize the importance and significance of light treatment in producing uniform populations through acceptable germination and shattering resistance of the mutant genotypes of E. lagascae. This is the first report of light treatment that significantly improved seed germination of E. lagascae, which may enhance efforts in the development of this new industrial crop as a feedstock for vernolic acid production.

In vitro gastrointestinal simulated digestion of three plant proteins: determination of digestion rate, free amino acids and peptide contents

Cassava protein (CP), barley protein (BP) and yellow pea protein (YPP) are important nutrient and integral constituent of staple in pet foods. It is known that the digestion of proteins directly influences their absorption and utilisation. In the present work, we performed in vitro simulated gastrointestinal digestion of three plant proteins as a staple for dog and cat food. The digestion rate of CP, BP and YPP in dog food was 56.33 ± 0.90%, 48.53 ± 0.91%, and 66.96 ± 0.37%, respectively, whereas the digestion rate of CP, BP, and YPP in cat food was 66.25 ± 0.72%, 43.42 ± 0.83%, and 58.05 ± 0.85%, respectively. Using SDS-polyacrylamide gel electrophoresis to determine the molecular weight (MW) of each protein and the products of their digestion, it was revealed that MW of digestion samples decreased, and MW during the small intestine phase was lower than that during the gastric phase. Peptide sequences of digested products were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and it was found that the total number of peptides in the small intestine digestion samples was higher than that in the gastric phase samples. The MW of peptides obtained from CP was within the range of 1000-1500 Da, while MW of peptides derived from BP and YPP was within the range of 400-2000 Da. In addition, free amino acids were mainly produced in the small intestine phase. Furthermore, the percentage of essential amino acids in the small intestine phase (63 ~ 82%) was higher than that in the gastric phase (37 ~ 63%). Taken together, these findings contribute to the current understanding of the utilisation of plant proteins in dog and cat foods and provide important insights into the selection and application of plant proteins as a staple in dog and cat foods.

Novel genetic resources associated with sucrose and stachyose content through genome-wide association study in soybean (Glycine max (L.) Merr.)

The nutritional value of soybean [Glycine max (L.) Merr.] for animals is influenced by soluble carbohydrates, such as sucrose and stachyose. Although sucrose is nutritionally desirable, stachyose is an antinutrient causing diarrhea and flatulence in non-ruminant animals. We conducted a genome-wide association study of 220 soybean accessions using 21,317 single nucleotide polymorphisms (SNPs) from the SoySNP50K iSelect Beadchip data to identify significant SNPs associated with sucrose and stachyose content. Seven significant SNPs were identified for sucrose content across chromosomes (Chrs.) 2, 8, 12, 17, and 20, while thirteen significant SNPs were identified for stachyose content across Chrs. 2, 5, 8, 9, 10, 13, 14, and 15. Among those significant SNPs, three sucrose-related SNPs on Chrs. 8 and 17 were novel, while twelve stachyose-related SNPs on Chrs. 2, 5, 8, 9, 10, 13, 14, and 15 were novel. Based on Phytozome, STRING, and GO annotation, 17 and 24 candidate genes for sucrose and stachyose content, respectively, were highly associated with the carbohydrate metabolic pathway. Among these, the publicly available RNA-seq Atlas database highlighted four candidate genes associated with sucrose (Glyma.08g361200 and Glyma.17g258100) and stachyose (Glyma.05g025300 and Glyma.13g077900) content, which had higher gene expression levels in developing seed and multiple parts of the soybean plant. The results of this study will extend knowledge of the molecular mechanism and genetic basis underlying sucrose and stachyose content in soybean seed. Furthermore, the novel candidate genes and SNPs can be valuable genetic resources that soybean breeders may utilize to modify carbohydrate profiles for animal and human usage.

Prediction and optimization of indirect shoot regeneration of Passiflora caerulea using machine learning and optimization algorithms

BACKGROUND

Optimization of indirect shoot regeneration protocols is one of the key prerequisites for the development of Agrobacterium-mediated genetic transformation and/or genome editing in Passiflora caerulea. Comprehensive knowledge of indirect shoot regeneration and optimized protocol can be obtained by the application of a combination of machine learning (ML) and optimization algorithms.

MATERIALS AND METHODS

In the present investigation, the indirect shoot regeneration responses (i.e., de novo shoot regeneration rate, the number of de novo shoots, and length of de novo shoots) of P. caerulea were predicted based on different types and concentrations of PGRs (i.e., TDZ, BAP, PUT, KIN, and IBA) as well as callus types (i.e., callus derived from different explants including leaf, node, and internode) using generalized regression neural network (GRNN) and random forest (RF). Moreover, the developed models were integrated into the genetic algorithm (GA) to optimize the concentration of PGRs and callus types for maximizing indirect shoot regeneration responses. Moreover, sensitivity analysis was conducted to assess the importance of each input variable on the studied parameters.

RESULTS

The results showed that both algorithms (RF and GRNN) had high predictive accuracy (R² > 0.86) in both training and testing sets for modeling all studied parameters. Based on the results of optimization process, the highest de novo shoot regeneration rate (100%) would be obtained from callus derived from nodal segments cultured in the medium supplemented with 0.77 mg/L BAP plus 2.41 mg/L PUT plus 0.06 mg/L IBA. The results of the sensitivity analysis showed the explant-dependent impact of exogenous application of PGRs on indirect de novo shoot regeneration.

CONCLUSIONS

A combination of ML (GRNN and RF) and GA can display a forward-thinking aid to optimize and predict in vitro culture systems and consequentially cope with several challenges faced currently in Passiflora tissue culture.

Application of SVR-Mediated GWAS for Identification of Durable Genetic Regions Associated with Soybean Seed Quality Traits

Soybean (Glycine max L.) is an important food-grade strategic crop worldwide because of its high seed protein and oil contents. Due to the negative correlation between seed protein and oil percentage, there is a dire need to detect reliable quantitative trait loci (QTL) underlying these traits in order to be used in marker-assisted selection (MAS) programs. Genome-wide association study (GWAS) is one of the most common genetic approaches that is regularly used for detecting QTL associated with quantitative traits. However, the current approaches are mainly focused on estimating the main effects of QTL, and, therefore, a substantial statistical improvement in GWAS is required to detect associated QTL considering their interactions with other QTL as well. This study aimed to compare the support vector regression (SVR) algorithm as a common machine learning method to fixed and random model circulating probability unification (FarmCPU), a common conventional GWAS method in detecting relevant QTL associated with soybean seed quality traits such as protein, oil, and 100-seed weight using 227 soybean genotypes. The results showed a significant negative correlation between soybean seed protein and oil concentrations, with heritability values of 0.69 and 0.67, respectively. In addition, SVR-mediated GWAS was able to identify more relevant QTL underlying the target traits than the FarmCPU method. Our findings demonstrate the potential use of machine learning algorithms in GWAS to detect durable QTL associated with soybean seed quality traits suitable for genomic-based breeding approaches. This study provides new insights into improving the accuracy and efficiency of GWAS and highlights the significance of using advanced computational methods in crop breeding research.

Unveiling the Mysteries of Non-Mendelian Heredity in Plant Breeding

Mendelian heredity is the cornerstone of plant breeding and has been used to develop new varieties of plants since the 19th century. However, there are several breeding cases, such as cytoplasmic inheritance, methylation, epigenetics, hybrid vigor, and loss of heterozygosity (LOH), where Mendelian heredity is not applicable, known as non-Mendelian heredity. This type of inheritance can be influenced by several factors besides the genetic architecture of the plant and its breeding potential. Therefore, exploring various non-Mendelian heredity mechanisms, their prevalence in plants, and the implications for plant breeding is of paramount importance to accelerate the pace of crop improvement. In this review, we examine the current understanding of non-Mendelian heredity in plants, including the mechanisms, inheritance patterns, and applications in plant breeding, provide an overview of the various forms of non-Mendelian inheritance (including epigenetic inheritance, cytoplasmic inheritance, hybrid vigor, and LOH), explore insight into the implications of non-Mendelian heredity in plant breeding, and the potential it holds for future research.