Large-scale data mining pipeline for identifying novel soybean genes involved in resistance against the soybean cyst nematode

The soybean cyst nematode (SCN) [Heterodera glycines Ichinohe] is a devastating pathogen of soybean [Glycine max (L.) Merr.] that is rapidly becoming a global economic issue. Two loci conferring SCN resistance have been identified in soybean, Rhg1 and Rhg4; however, they offer declining protection. Therefore, it is imperative that we identify additional mechanisms for SCN resistance. In this paper, we develop a bioinformatics pipeline to identify protein–protein interactions related to SCN resistance by data mining massive-scale datasets. The pipeline combines two leading sequence-based protein–protein interaction predictors, the Protein–protein Interaction Prediction Engine (PIPE), PIPE4, and Scoring PRotein INTeractions (SPRINT) to predict high-confidence interactomes. First, we predicted the top soy interacting protein partners of the Rhg1 and Rhg4 proteins. Both PIPE4 and SPRINT overlap in their predictions with 58 soybean interacting partners, 19 of which had GO terms related to defense. Beginning with the top predicted interactors of Rhg1 and Rhg4, we implement a “guilt by association” in silico proteome-wide approach to identify novel soybean genes that may be involved in SCN resistance. This pipeline identified 1,082 candidate genes whose local interactomes overlap significantly with the Rhg1 and Rhg4 interactomes. Using GO enrichment tools, we highlighted many important genes including five genes with GO terms related to response to the nematode (GO:0009624), namely, Glyma.18G029000, Glyma.11G228300, Glyma.08G120500, Glyma.17G152300, and Glyma.08G265700. This study is the first of its kind to predict interacting partners of known resistance proteins Rhg1 and Rhg4, forming an analysis pipeline that enables researchers to focus their search on high-confidence targets to identify novel SCN resistance genes in soybean

Differential gene expression provides leads to environmentally regulated soybean seed protein content

Soybean is an important global source of plant-based protein. A persistent trend has been observed over the past two decades that soybeans grown in western Canada have lower seed protein content than soybeans grown in eastern Canada. In this study, 10 soybean genotypes ranging in average seed protein content were grown in an eastern location (control) and three western locations (experimental) in Canada. Seed protein and oil contents were measured for all lines in each location. RNA-sequencing and differential gene expression analysis were used to identify differentially expressed genes that may account for relatively low protein content in western-grown soybeans. Differentially expressed genes were enriched for ontologies and pathways that included amino acid biosynthesis, circadian rhythm, starch metabolism, and lipid biosynthesis. Gene ontology, pathway mapping, and quantitative trait locus (QTL) mapping collectively provide a close inspection of mechanisms influencing nitrogen assimilation and amino acid biosynthesis between soybeans grown in the East and West. It was found that western-grown soybeans had persistent upregulation of asparaginase (an asparagine hydrolase) and persistent downregulation of asparagine synthetase across 30 individual differential expression datasets. This specific difference in asparagine metabolism between growing environments is almost certainly related to the observed differences in seed protein content because of the positive correlation between seed protein content at maturity and free asparagine in the developing seed. These results provided pointed information on seed protein-related genes influenced by environment. This information is valuable for breeding programs and genetic engineering of geographically optimized soybeans

Genetic Analysis of High Protein Content in ‘AC Proteus’ Related Soybean Populations Using SSR, SNP, DArT and DArTseq Markers

Key message: Several AC Proteus derived genomic regions (QTLs, SNPs) have been identified which may prove useful for further development of high yielding high protein cultivars and allele-specific marker developments. High seed protein content is a trait which is typically difficult to introgress into soybean without an accompanying reduction in seed yield. In a previous study, ‘AC Proteus’ was used as a high protein source and was found to produce populations that did not exhibit the typical association between high protein and low yield. Five high x low protein RIL populations and a high x high protein RIL population were evaluated by either quantitative trait locus (QTL) analysis or bulk segregant analyses (BSA) following phenotyping in the field. QTL analysis in one population using SSR, DArT and DArTseq markers found two QTLs for seed protein content on chromosomes 15 and 20. The BSA analyses suggested multiple genomic regions are involved with high protein content across the five populations, including the two previously mentioned QTLs. In an alternative approach to identify high protein genes, pedigree analysis identified SNPs for which the allele associated with high protein was retained in seven high protein descendants of AC Proteus on chromosomes 2, 17 and 18. Aside from the two identified QTLs (five genomic regions in total considering the two with highly elevated test statistic, but below the statistical threshold and the one with epistatic interactions) which were some distance from Meta-QTL regions and which were also supported by our BSA analysis within five populations. These high protein regions may prove useful for further development of high yielding high protein cultivars

The sensitivity of the yeast, Saccharomyces cerevisiae, to acetic acid is influenced by DOM34 and RPL36A

The presence of acetic acid during industrial alcohol fermentation reduces the yield of fermentation by imposing additional stress on the yeast cells. The biology of cellular responses to stress has been a subject of vigorous investigations. Although much has been learned, details of some of these responses remain poorly understood. Members of heat shock chaperone HSP proteins have been linked to acetic acid and heat shock stress responses in yeast. Both acetic acid and heat shock have been identified to trigger different cellular responses including reduction of global protein synthesis and induction of programmed cell death. Yeast HSC82 and HSP82 code for two important heat shock proteins that together account for 1-2% of total cellular proteins. Both proteins have been linked to responses to acetic acid and heat shock. In contrast to the overall rate of protein synthesis which is reduced, the expression of HSC82 and HSP82 is induced in response to acetic acid stress. In the current study we identified two yeast genes DOM34 and RPL36A that are linked to acetic acid and heat shock sensitivity. We investigated the influence of these genes on the expression of HSP proteins. Our observations suggest that Dom34 and RPL36A influence translation in a CAP-independent manner.This work was funded by the Natural Sciences and Engineering Research Council of Canada, NSERC.info:eu-repo/semantics/publishedVersio

Systematic Genetic Screens Reveal the Dynamic Global Functional Organization of the Bacterial Translation Machinery

Bacterial protein synthesis is an essential, conserved, and environmentally responsive process. Yet, many of its components and dependencies remain unidentified. To address this gap, we used quantitative synthetic genetic arrays to map functional relationships among >48,000 gene pairs in Escherichia coli under four culture conditions differing in temperature and nutrient availability. The resulting data provide global functional insights into the roles and associations of genes, pathways, and processes important for efficient translation, growth, and environmental adaptation. We predict and independently verify the requirement of unannotated genes for normal translation, including a previously unappreciated role of YhbY in 30S biogenesis. Dynamic changes in the patterns of genetic dependencies across the four growth conditions and data projections onto other species reveal overarching functional and evolutionary pressures impacting the translation system and bacterial fitness, underscoring the utility of systematic screens for investigating protein synthesis, adaptation, and evolution

Can Epigenetics Guide the Production of Better Adapted Cultivars?

As the global population continues to grow, food demand will be reaching levels which current agricultural practices cannot meet. This projected demand combined with the negative impacts of climate change on crop production calls for more careful breeding efforts to develop better adapted plants more tolerant to climate fluctuations. Fortunately, the development of molecular biology techniques like genome, transcriptome and epigenome sequencing now offer new approaches to help classical breeding meet these challenges. This review focuses on the potential of epigenetic approaches, particularly the creation of epigenetic markers (epi-markers) for guiding the selection process in breeding programs. Many studies have indeed successfully linked stable epigenetic modifications to different plant traits of interest but research on the applicability of using epi-markers in breeding programs is still scarce. This review emphasises the current progress that has been made with regards to the usefulness of epi-markers in selective plant breeding programs and the gaps in knowledge that still need to be addressed. It highlights the importance of pursuing research efforts to confirm the value of epi-markers for crop development in the years to come in order to meet the agricultural challenges of the 21st century

Can Epigenetics Guide the Production of Better Adapted Cultivars?

As the global population continues to grow, food demand will be reaching levels which current agricultural practices cannot meet. This projected demand combined with the negative impacts of climate change on crop production calls for more careful breeding efforts to develop better adapted plants more tolerant to climate fluctuations. Fortunately, the development of molecular biology techniques like genome, transcriptome and epigenome sequencing now offer new approaches to help classical breeding meet these challenges. This review focuses on the potential of epigenetic approaches, particularly the creation of epigenetic markers (epi-markers) for guiding the selection process in breeding programs. Many studies have indeed successfully linked stable epigenetic modifications to different plant traits of interest but research on the applicability of using epi-markers in breeding programs is still scarce. This review emphasises the current progress that has been made with regards to the usefulness of epi-markers in selective plant breeding programs and the gaps in knowledge that still need to be addressed. It highlights the importance of pursuing research efforts to confirm the value of epi-markers for crop development in the years to come in order to meet the agricultural challenges of the 21st century

A Broad Review of Soybean Research on the Ongoing Race to Overcome Soybean Cyst Nematode

Plant pathogens greatly impact food security of the ever-growing human population. Breeding resistant crops is one of the most sustainable strategies to overcome the negative effects of these biotic stressors. In order to efficiently breed for resistant plants, the specific plant–pathogen interactions should be understood. Soybean is a short-day legume that is a staple in human food and animal feed due to its high nutritional content. Soybean cyst nematode (SCN) is a major soybean stressor infecting soybean worldwide including in China, Brazil, Argentina, USA and Canada. There are many Quantitative Trait Loci (QTLs) conferring resistance to SCN that have been identified; however, only two are widely used: rhg1 and Rhg4. Overuse of cultivars containing these QTLs/genes can lead to SCN resistance breakdown, necessitating the use of additional strategies. In this manuscript, a literature review is conducted on research related to soybean resistance to SCN. The main goal is to provide a current understanding of the mechanisms of SCN resistance and list the areas of research that could be further explored

Photoperiod Affects Node Appearance Rate and Flowering in Early Maturing Soybean

The photoperiod plays a critical role in the control of flowering timing in soybean (Glycine max (L.) Merr.) with long days increasing the time to flowering. Early flowering cultivars have been developed from breeding programs for environments with long photoperiods; however, this effect is challenging to isolate in field experiments because of other environmental influences. Our experiment examined the effect of photoperiod on the node appearance rate and time to flower for 13 early maturing soybean cultivars ranging in maturity group (MG) between 000.9 and 1.3. Growth chambers were programmed to 14, 15, 16, and 17 h photoperiods and temperature was kept at 25 °C. The date of emergence and main stem node appearance were recorded until flowering. The node appearance rate was slowest for the first node and increased thereafter. All cultivars required more time to flowering in the longer photoperiod treatments and the later rated MG had the greatest sensitivity to photoperiod. A delay in time to flower from a longer photoperiod can delay maturity and expose the crop to fall frost that can reduce seed yield and quality. Understanding and documentation of soybean photoperiod sensitivity will help plant breeders develop suitable cultivars for environments with long photoperiods