Identification of Quantitative Trait Locus and Candidate Genes for Drought Tolerance in a Soybean Recombinant Inbred Line Population

With global warming and regional decreases in precipitation, drought has become a problem worldwide. As the number of arid regions in the world is increasing, drought has become a major factor leading to significant crop yield reductions and food crises. Soybean is a crop that is relatively sensitive to drought. It is also a crop that requires more water during growth and development. The aim of this study was to identify the quantitative trait locus (QTL) that affects drought tolerance in soybean by using a recombinant inbred line (RIL) population from a cross between the drought-tolerant cultivar ‘Jindou21’ and the drought-sensitive cultivar ‘Zhongdou33’. Nine agronomic and physiological traits were identified under drought and well-watered conditions. Genetic maps were constructed with 923,420 polymorphic single nucleotide polymorphism (SNP) markers distributed on 20 chromosomes at an average genetic distance of 0.57 centimorgan (cM) between markers. A total of five QTLs with a logarithm of odds (LOD) value of 4.035–8.681 were identified on five chromosomes. Under well-watered conditions and drought-stress conditions, one QTL related to the main stem node number was located on chromosome 16, accounting for 17.177% of the phenotypic variation. Nine candidate genes for drought resistance were screened from this QTL, namely Glyma.16G036700, Glyma.16G036400, Glyma.16G036600, Glyma.16G036800, Glyma.13G312700, Glyma.13G312800, Glyma.16G042900, Glyma.16G043200, and Glyma.15G100700. These genes were annotated as NAC transport factor, GATA transport factor, and BTB/POZ-MATH proteins. This result can be used for molecular marker-assisted selection and provide a reference for breeding for drought tolerance in soybean.     

Genome-Wide Association Study on Root System Architecture and Identification of Candidate Genes in Wheat (Triticum aestivum L.)

The root tissues play important roles in water and nutrient acquisition, environmental adaptation, and plant development. In this study, a diversity panel of 388 wheat accessions was collected to investigate nine root system architecture (RSA) traits at the three-leaf stage under two growing environments: outdoor pot culture (OPC) and indoor pot culture (IPC). Phenotypic analysis revealed that root development was faster under OPC than that under IPC and a significant correlation was observed between the nine RSA traits. The 660K single-nucleotide polymorphism (SNP) chip was used for a genome-wide association study (GWAS). Significant SNPs with a threshold of −log₁₀ (p-value) ≥ 4 were considered. Thus, 36 quantitative trait loci (QTLs), including 13 QTL clusters that were associated with more than one trait, were detected, and 31 QTLs were first identified. The QTL clusters on chromosomes 3D and 5B were associated with four and five RSA traits, respectively. Two candidate genes, TraesCS2A01G516200 and TraesCS7B01G036900, were found to be associated with more than one RSA trait using haplotype analysis, and preferentially expressed in the root tissues. These favourable alleles for RSA traits identified in this study may be useful to optimise the root system in wheat.     

Genetic Dissection of Seedling Root System Architectural Traits in a Diverse Panel of Hexaploid Wheat through Multi-Locus Genome-Wide Association Mapping for Improving Drought Tolerance

Cultivars with efficient root systems play a major role in enhancing resource use efficiency, particularly water absorption, and thus in drought tolerance. In this study, a diverse wheat association panel of 136 wheat accessions including mini core subset was genotyped using Axiom 35k Breeders’ Array to identify genomic regions associated with seedling stage root architecture and shoot traits using multi-locus genome-wide association studies (ML-GWAS). The association panel revealed a wide variation of 1.5- to 50-fold and were grouped into six clusters based on 15 traits. Six different ML-GWAS models revealed 456 significant quantitative trait nucleotides (QTNs) for various traits with phenotypic variance in the range of 0.12–38.60%. Of these, 87 QTNs were repeatedly detected by two or more models and were considered reliable genomic regions for the respective traits. Among these QTNs, eleven were associated with average diameter and nine each for second order lateral root number (SOLRN), root volume (RV) and root length density (RLD). A total of eleven genomic regions were pleiotropic and each controlled two or three traits. Some important candidate genes such as Formin homology 1, Ubiquitin-like domain superfamily and ATP-dependent 6-phosphofructokinase were identified from the associated genomic regions. The genomic regions/genes identified in this study could potentially be targeted for improving root traits and drought tolerance in wheat.     

Combined QTL Mapping across Multiple Environments and Co-Expression Network Analysis Identified Key Genes for Embryogenic Callus Induction from Immature Maize Embryos

The ability of immature embryos to induce embryogenic callus (EC) is crucial for genetic transformation in maize, which is highly genotype-dependent. To dissect the genetic basis of maize EC induction, we conducted QTL mapping for four EC induction-related traits, the rate of embryogenic callus induction (REC), rate of shoot formation (RSF), length of shoot (LS), and diameter of callus (DC) under three environments by using an IBM Syn10 DH population derived from a cross of B73 and Mo17. These EC induction traits showed high broad-sense heritability (>80%), and significantly negative correlations were observed between REC and each of the other traits across multiple environments. A total of 41 QTLs for EC induction were identified, among which 13, 12, 10, and 6 QTLs were responsible for DC, RSF, LS, and REC, respectively. Among them, three major QTLs accounted for >10% of the phenotypic variation, including qLS1-1 (11.54%), qLS1-3 (10.68%), and qREC4-1 (11.45%). Based on the expression data of the 215 candidate genes located in these QTL intervals, we performed a weighted gene co-expression network analysis (WGCNA). A combined use of KEGG pathway enrichment and eigengene-based connectivity (KME) values identified the EC induction-associated module and four hub genes (Zm00001d028477, Zm00001d047896, Zm00001d034388, and Zm00001d022542). Gene-based association analyses validated that the variations in Zm00001d028477 and Zm00001d034388, which were involved in tryptophan biosynthesis and metabolism, respectively, significantly affected EC induction ability among different inbred lines. Our study brings novel insights into the genetic and molecular mechanisms of EC induction and helps to promote marker-assisted selection of high-REC varieties in maize.     

QTL Mapping and Diurnal Transcriptome Analysis Identify Candidate Genes Regulating Brassica napus Flowering Time

Timely flowering is important for seed formation and maximization of rapeseed (Brassica napus) yield. Here, we performed flowering-time quantitative trait loci (QTL) mapping using a double haploid (DH) population grown in three environments to study the genetic architecture. Brassica 60 K Illumina Infinium™ single nucleotide polymorphism (SNP) array and simple sequence repeat (SSR) markers were used for genotyping of the DH population, and a high-density genetic linkage map was constructed. QTL analysis of flowering time from the three environments revealed five consensus QTLs, including two major QTLs. A major QTL located on chromosome A03 was detected specifically in the semi-winter rapeseed growing region, and the one on chromosome C08 was detected in all environments. Ribonucleic acid sequencing (RNA-seq) was performed on the parents’ leaves at seven time-points in a day to determine differentially expressed genes (DEGs). The biological processes and pathways with significant enrichment of DEGs were obtained. The DEGs in the QTL intervals were analyzed, and four flowering time-related candidate genes were found. These results lay a foundation for the genetic regulation of rapeseed flowering time and create a rapeseed gene expression library for seven time-points in a day.     

Proofing Direct-Seeded Rice with Better Root Plasticity and Architecture

The underground reserve (root) has been an uncharted research territory with its untapped genetic variation yet to be exploited. Identifying ideal traits and breeding new rice varieties with efficient root system architecture (RSA) has great potential to increase resource-use efficiency and grain yield, especially under direct-seeded rice, by adapting to aerobic soil conditions. In this review, we tried to mine the available research information on the direct-seeded rice (DSR) root system to highlight the requirements of different root traits such as root architecture, length, number, density, thickness, diameter, and angle that play a pivotal role in determining the uptake of nutrients and moisture at different stages of plant growth. RSA also faces several stresses, due to excess or deficiency of moisture and nutrients, low or high temperature, or saline conditions. To counteract these hindrances, adaptation in response to stress becomes essential. Candidate genes such as early root growth enhancer PSTOL1, surface rooting QTL qSOR1, deep rooting gene DRO1, and numerous transporters for their respective nutrients and stress-responsive factors have been identified and validated under different circumstances. Identifying the desired QTLs and transporters underlying these traits and then designing an ideal root architecture can help in developing a suitable DSR cultivar and aid in further advancement in this direction.     

Deciphering the Genetic Basis of Root and Biomass Traits in Rapeseed (Brassica napus L.) through the Integration of GWAS and RNA-Seq under Nitrogen Stress

An excellent root system is responsible for crops with high nitrogen-use efficiency (NUE). The current study evaluated the natural variations in 13 root- and biomass-related traits under a low nitrogen (LN) treatment in a rapeseed association panel. The studied traits exhibited significant phenotypic differences with heritabilities ranging from 0.53 to 0.66, and most of the traits showed significant correlations with each other. The genome-wide association study (GWAS) found 51 significant and 30 suggestive trait–SNP associations that integrated into 14 valid quantitative trait loci (QTL) clusters and explained 5.7–21.2% phenotypic variance. In addition, RNA sequencing was performed at two time points to examine the differential expression of genes (DEGs) between high and low NUE lines. In total, 245, 540, and 399 DEGs were identified as LN stress-specific, high nitrogen (HN) condition-specific, and HNLN common DEGs, respectively. An integrated analysis of GWAS, weighted gene co-expression network, and DEGs revealed 16 genes involved in rapeseed root development under LN stress. Previous studies have reported that the homologs of seven out of sixteen potential genes control root growth and NUE. These findings revealed the genetic basis underlying nitrogen stress and provided worthwhile SNPs/genes information for the genetic improvement of NUE in rapeseed.     

Genomic regions governing soybean seed nitrogen accumulation

Nitrogen accumulation in the form of seed protein takes place in soybean [Glycine max (L.) Merr.] during the reproductive stages of development. The purpose of this study was to relate genotypic differences in seed nitrogen accumulation with genomic regions controlling nitrogen accumulation in soybean during R₅, R₆, and R₇ growth stages. A population of 101 F_6∶8 recombinant inbred lines (RIL) developed from a cross of N87-984-16×TN93-99 was utilized. The RIL were grown at the University of Tennessee, Knoxville Experiment Station, in a randomized complete block design with three replications in 2002. Seed nitrogen was determined from pod samples harvested at the R₅, R₆, and R₇ growth stages. A significant (P<0.05) difference among genotypes was found for nitrogen accumulation at all three growth stages. Single-factor ANOVA revealed that quantitative trait loci (QTL) governing nitrogen accumulation in soybean seed were distributed in the linkage groups A2, B2, D1a, D1b, E, G, and M. Phenotypic variation explained by an individual QTL ranged from 5 to 11.6%. These QTL may provide useful marker-assisted selection opportunities for soybean protein improvement.     

Identification and Validation of Quantitative Trait Loci Mapping for Spike-Layer Uniformity in Wheat

Spike-layer uniformity (SLU), the consistency of the spike distribution in the vertical space, is an important trait. It directly affects the yield potential and appearance. Revealing the genetic basis of SLU will provide new insights into wheat improvement. To map the SLU-related quantitative trait loci (QTL), 300 recombinant inbred lines (RILs) that were derived from a cross between H461 and Chinese Spring were used in this study. The RILs and parents were tested in fields from two continuous years from two different pilots. Phenotypic analysis showed that H461 was more consistent in the vertical spatial distribution of the spike layer than in Chinese Spring. Based on inclusive composite interval mapping, four QTL were identified for SLU. There were two major QTL on chromosomes 2BL and 2DL and two minor QTL on chromosomes 1BS and 2BL that were identified. The additive effects of QSlu.sicau-1B, Qslu.sicau-2B-2, and QSlu.sicau-2D were all from the parent, H461. The major QTL, QSlu.sicau-2B-2 and QSlu.sicau-2D, were detected in each of the conducted trials. Based on the best linear unbiased prediction values, the two loci explained 23.97% and 15.98% of the phenotypic variation, respectively. Compared with previous studies, the two major loci were potentially novel and the two minor loci were overlapped. Based on the kompetitive allele-specific PCR (KASP) marker, the genetic effects for QSlu.sicau-2B-2 were validated in an additional RIL population. The genetic effects ranged from 26.65% to 32.56%, with an average value of 30.40%. In addition, QSlu.sicau-2B-2 showed a significant (p < 0.01) and positive influence on the spike length, spikelet number, and thousand kernel weight. The identified QTL and the developed KASP marker will be helpful for fine-mapping these loci, finally contributing to wheat breeding programs in a marker-assisted selection way.     

Genetic Evidence for a Causal Relationship between Hyperlipidemia and Type 2 Diabetes in Mice

Dyslipidemia is considered a risk factor for type 2 diabetes (T2D), yet studies with statins and candidate genes suggest that circulating lipids may protect against T2D development. Apoe-null (Apoe^-/-) mouse strains develop spontaneous dyslipidemia and exhibit a wide variation in susceptibility to diet-induced T2D. We thus used Apoe^-/- mice to elucidate phenotypic and genetic relationships of circulating lipids with T2D. A male F2 cohort was generated from an intercross between LP/J and BALB/cJ Apoe^-/- mice and fed 12 weeks of a Western diet. Fasting, non-fasting plasma glucose, and lipid levels were measured and genotyping was performed using miniMUGA arrays. We uncovered a major QTL near 60 Mb on chromosome 15, Nhdlq18, which affected non-HDL cholesterol and triglyceride levels under both fasting and non-fasting states. This QTL was coincident with Bglu20, a QTL that modulates fasting and non-fasting glucose levels. The plasma levels of non-HDL cholesterol and triglycerides were closely correlated with the plasma glucose levels in F2 mice. Bglu20 disappeared after adjustment for non-HDL cholesterol or triglycerides. These results demonstrate a causative role for dyslipidemia in T2D development in mice.     

Quantitative Trait Locus Mapping of Marsh Spot Disease Resistance in Cranberry Common Bean (Phaseolus vulgaris L.)

Common bean (Phaseolus vulgaris L.) is a food crop that is an important source of dietary proteins and carbohydrates. Marsh spot is a physiological disorder that diminishes seed quality in beans. Prior research suggested that this disease is likely caused by manganese (Mn) deficiency during seed development and that marsh spot resistance is controlled by at least four genes. In this study, genetic mapping was performed to identify quantitative trait loci (QTL) and the potential candidate genes associated with marsh spot resistance. All 138 recombinant inbred lines (RILs) from a bi-parental population were evaluated for marsh spot resistance during five years from 2015 to 2019 in sandy and heavy clay soils in Morden, Manitoba, Canada. The RILs were sequenced using a genotyping by sequencing approach. A total of 52,676 single nucleotide polymorphisms (SNPs) were identified and filtered to generate a high-quality set of 2066 SNPs for QTL mapping. A genetic map based on 1273 SNP markers distributed on 11 chromosomes and covering 1599 cm was constructed. A total of 12 stable and 4 environment-specific QTL were identified using additive effect models, and an additional two epistatic QTL interacting with two of the 16 QTL were identified using an epistasis model. Genome-wide scans of the candidate genes identified 13 metal transport-related candidate genes co-locating within six QTL regions. In particular, two QTL (QTL.3.1 and QTL.3.2) with the highest R² values (21.8% and 24.5%, respectively) harbored several metal transport genes Phvul.003G086300, Phvul.003G092500, Phvul.003G104900, Phvul.003G099700, and Phvul.003G108900 in a large genomic region of 16.8–27.5 Mb on chromosome 3. These results advance the current understanding of the genetic mechanisms of marsh spot resistance in cranberry common bean and provide new genomic resources for use in genomics-assisted breeding and for candidate gene isolation and functional characterization.     

Molecular Identification of the G-Protein Genes and Their Expression Profiles in Response to Nitrogen Deprivation in Brassica napus

Heterotrimeric guanine nucleotide binding protein (G-protein) consisting of Gα, Gβ, and Gγ subunits is one of the key signal transducers in plants. Recent studies indicated that G-protein has been proposed as an important mediator of nitrogen responses in rice, wheat, and Arabidopsis. However, little is known about these G-proteins in Brassica napus (B. napus), except for three identified G-proteins, BnGA1, BnGB1, and BnGG2. Therefore, the aim of the present study is to characterize the members of the G-protein gene family in allotetraploid B. napus and to analyze their expression profiles in response to nitrogen deprivation. In total, 21 G-protein family members were identified in B. napus, encoding two Gα, six Gβ, and 13 Gγ. Sequence and phylogenetic analyses showed that although genome-wide triploid events increased the number of genes encoding Gα, Gβ, and Gγ subunits, the gene structure and protein properties of the genes encoding each G-protein subunit were extremely conserved. Collinearity analysis showed that most G-protein genes in B. napus had syntenic relationships with G-protein members of Arabidopsis, Brassica rape (B. rapa), and Brassica oleracea (B. oleracea). Expression profile analysis indicated that Gα and C-type Gγ genes (except BnGG10 and BnGG12 were highly expressed in flower and ovule) were barely expressed in most organs, whereas most Gβ and A-type Gγ genes tended to be highly expressed in most organs. G-protein genes also showed various expression patterns in response to nitrogen-deficient conditions. Under nitrogen deficiency, Gα and five C-type Gγ genes were upregulated initially in roots, while in leaves, Gα was downregulated initially and five C-type Gγ genes were highly expressed in different times. These results provide a complex genetic dissection of G-protein genes in B. napus, and insight into the biological functions of G-protein genes in response to nitrogen deficiency.     

Validation of a QTL on Chromosome 1DS Showing a Major Effect on Salt Tolerance in Winter Wheat

Salt stress is one the most destructive abiotic stressors, causing yield losses in wheat worldwide. A prerequisite for improving salt tolerance is the identification of traits for screening genotypes and uncovering causative genes. Two populations of F₃ lines developed from crosses between sensitive and tolerant parents were tested for salt tolerance at the seedling stage. Based on their response, the offspring were classified as salt sensitive and tolerant. Under saline conditions, tolerant genotypes showed lower Na⁺ and proline content but higher K⁺, higher chlorophyll content, higher K⁺/Na⁺ ratio, higher PSII activity levels, and higher photochemical efficiency, and were selected for further molecular analysis. Five stress responsive QTL identified in a previous study were validated in the populations. A QTL on the short arm of chromosome 1D showed large allelic effects in several salt tolerant related traits. An expression analysis of associated candidate genes showed that TraesCS1D02G052200 and TraesCS5B02G368800 had the highest expression in most tissues. Furthermore, qRT-PCR expression analysis revealed that ZIP-7 had higher differential expressions under saline conditions compared to KefC, AtABC8 and 6-SFT. This study provides information on the genetic and molecular basis of salt tolerance that could be useful in development of salt-tolerant wheat varieties.     

The Integration of Genome-Wide Association Study and Homology Analysis to Explore the Genomic Regions and Candidate Genes for Panicle-Related Traits in Foxtail Millet

Panicle traits are important factors affecting yield, and their improvement has long been a critical goal in foxtail millet breeding. In order to understand the genetic basis of panicle formation, a large-scale genome-wide association study (GWAS) was performed in this study for six panicle-related traits based on 706,646 high-polymorphism SNP loci in 407 accessions. As a result, 87 quantitative trait loci (QTL) regions with a physical distance of less than 100 kb were detected to be associated with these traits in three environments. Among them, 27 core regions were stably detected in at least two environments. Based on rice–foxtail millet homologous comparison, expression, and haplotype analysis, 27 high-confidence candidate genes in the QTL regions, such as Si3g11200 (OsDER1), Si1g27910 (OsMADS6), Si7g27560 (GS5), etc., affected panicle-related traits by involving multiple plant growth regulator pathways, a photoperiod response, as well as panicle and grain development. Most of these genes showed multiple effects on different panicle-related traits, such as Si3g11200 affecting all six traits. In summary, this study clarified a strategy based on the integration of GWAS, a homologous comparison, and haplotype analysis to discover the genomic regions and candidate genes for important traits in foxtail millet. The detected QTL regions and candidate genes could be further used for gene clone and marker-assisted selection in foxtail millet breeding.     

Identification of Novel Genes Associated with Partial Resistance to Aphanomyces Root Rot in Field Pea by BSR-Seq Analysis

Aphanomyces root rot, caused by Aphanomyces euteiches, causes severe yield loss in field pea (Pisum sativum). The identification of a pea germplasm resistant to this disease is an important breeding objective. Polygenetic resistance has been reported in the field pea cultivar ‘00-2067’. To facilitate marker-assisted selection (MAS), bulked segregant RNA-seq (BSR-seq) analysis was conducted using an F₈ RIL population derived from the cross of ‘Carman’ × ‘00-2067’. Root rot development was assessed under controlled conditions in replicated experiments. Resistant (R) and susceptible (S) bulks were constructed based on the root rot severity in a greenhouse study. The BSR-seq analysis of the R bulks generated 44,595,510~51,658,688 reads, of which the aligned sequences were linked to 44,757 genes in a reference genome. In total, 2356 differentially expressed genes were identified, of which 44 were used for gene annotation, including defense-related pathways (jasmonate, ethylene and salicylate) and the GO biological process. A total of 344.1 K SNPs were identified between the R and S bulks, of which 395 variants were located in 31 candidate genes. The identification of novel genes associated with partial resistance to Aphanomyces root rot in field pea by BSR-seq may facilitate efforts to improve management of this important disease.     

Genome-Wide Identification and Characterization of the RCI2 Gene Family in Allotetraploid Brassica napus Compared with Its Diploid Progenitors

Brassica napus and its diploid progenitors (B. rapa and B. oleracea) are suitable for studying the problems associated with polyploidization. As an important anti-stress protein, RCI2 proteins widely exist in various tissues of plants, and are crucial to plant growth, development, and stress response. In this study, the RCI2 gene family was comprehensively identified and analyzed, and 9, 9, and 24 RCI2 genes were identified in B. rapa, B. oleracea, and B. napus, respectively. Phylogenetic analysis showed that all of the identified RCI2 genes were divided into two groups, and further divided into three subgroups. Ka/Ks analysis showed that most of the identified RCI2 genes underwent a purifying selection after the duplication events. Moreover, gene structure analysis showed that the structure of RCI2 genes is largely conserved during polyploidization. The promoters of the RCI2 genes in B. napus contained more cis-acting elements, which were mainly involved in plant development and growth, plant hormone response, and stress responses. Thus, B. napus might have potential advantages in some biological aspects. In addition, the changes of RCI2 genes during polyploidization were also discussed from the aspects of gene number, gene structure, gene relative location, and gene expression, which can provide reference for future polyploidization analysis.