Validating a Major Quantitative Trait Locus and Predicting Candidate Genes Associated With Kernel Width Through QTL Mapping and RNA-Sequencing Technology Using Near-Isogenic Lines in Maize

Kernel size is an important agronomic trait for grain yield in maize. The purpose of this study was to validate a major quantitative trait locus (QTL), qKW-1, which was identified in the F₂ and F_2:3 populations from a cross between the maize inbred lines SG5/SG7 and to predict candidate genes for kernel width (KW) in maize. A major QTL, qKW-1, was mapped in multiple environments in our previous study. To validate and fine map qKW-1, near-isogenic lines (NILs) with 469 individuals were developed by continuous backcrossing between SG5 as the donor parent and SG7 as the recurrent parent. Marker-assisted selection was conducted from the BC₂F₁ generation with simple sequence repeat (SSR) markers near qKW-1. A secondary linkage map with four markers, PLK12, PLK13, PLK15, and PLK17, was developed and used for mapping the qKW-1 locus. Finally, qKW-1 was mapped between the PLK12 and PLK13 intervals, with a distance of 2.23 cM to PLK12 and 0.04 cM to PLK13, a confidence interval of 5.3 cM and a phenotypic contribution rate of 23.8%. The QTL mapping result obtained was further validated by using selected overlapping recombinant chromosomes on the target segment of maize chromosome 3. Transcriptome analysis showed that a total of 12 out of 45 protein-coding genes differentially expressed between the two parents were detected in the identified qKW-1 physical interval by blasting with the Zea_Mays_B73 v4 genome. GRMZM2G083176 encodes the Niemann-Pick disease type C, and GRMZM2G081719 encodes the nitrate transporter 1 (NRT1) protein. The two genes GRMZM2G083176 and GRMZM2G081719 were predicted to be candidate genes of qKW-1. Reverse transcription-polymerase chain reaction (RT-qPCR) validation was conducted, and the results provide further proof of the two candidate genes most likely responsible for qKW-1. The work will not only help to understand the genetic mechanisms of KW in maize but also lay a foundation for further cloning of promising loci.

High-LD SNP markers exhibiting pleiotropic effects on salt tolerance at germination and seedlings stages in spring wheat

Salt tolerance at germination and seedling growth stages was investigated. GWAS revealed nine genomic regions with pleiotropic effects on salt tolerance. Salt tolerant genotypes were identified for future breeding program. With 20% of the irrigated land worldwide affected by it, salinity is a serious threat to plant development and crop production. While wheat is the most stable food source worldwide, it has been classified as moderately tolerant to salinity. In several crop plants; such as barley, maize and rice, it has been shown that salinity tolerance at seed germination and seedling establishment is under polygenic control. As yield was the ultimate goal of breeders and geneticists, less attention has been paid to understanding the genetic architecture of salt tolerance at early stages. Thus, the genetic control of salt tolerance at these stages is poorly understood relative to the late stages. In the current study, 176 genotypes of spring wheat were tested for salinity tolerance at seed germination and seedling establishment. Genome-Wide Association Study (GWAS) has been used to identify the genomic regions/genes conferring salt tolerance at seed germination and seedling establishment. Salinity stress negatively impacted all germination and seedling development parameters. A set of 137 SNPs showed significant association with the traits of interest. Across the whole genome, 33 regions showed high linkage disequilibrium (LD). These high LD regions harbored 15 SNPs with pleiotropic effect (i.e. SNPs that control more than one trait). Nine genes belonging to different functional groups were found to be associated with the pleiotropic SNPs. Noteworthy, chromosome 2B harbored the gene TraesCS2B02G135900 that acts as a potassium transporter. Remarkably, one SNP marker, reported in an early study, associated with salt tolerance was validated in this study. Our findings represent potential targets of genetic manipulation to understand and improve salinity tolerance in wheat.

QTL Validation and Development of SNP-Based High Throughput Molecular Markers Targeting a Genomic Region Conferring Narrow Root Cone Angle in Aerobic Rice Production Systems

Aerobic rice production (AP) provides potential solutions to the global water crisis by consuming less water than traditional permanent water culture. Narrow root cone angle (RCA), development of deeper rooting and associated genomic regions are key for AP adaptation. However, their usefulness depends on validation across genetic backgrounds and development of linked markers. Using three F2 populations derived from IRAT109, qRCA4 was shown to be effective in multiple backgrounds, explaining 9.3-17.3% of the genotypic variation and introgression of the favourable allele resulted in 11.7-15.1° narrower RCA. Novel kompetitive allele specific PCR (KASP) markers were developed targeting narrow RCA and revealed robust quality metrics. Candidate genes related with plant response to abiotic stress and root development were identified along with 178 potential donors across rice subpopulations. This study validated qRCA4's effect in multiple genetic backgrounds further strengthening its value in rice improvement for AP adaptation. Furthermore, the development of novel KASP markers ensured the opportunity for its seamless introgression across pertinent breeding programs. This work provides the tools and opportunity to accelerate development of genotypes with narrow RCA through marker assisted selection in breeding programs targeting AP, which may ultimately contribute to more sustainable rice production where water availability is limited.

Genetic identification and characterization of chromosomal regions for kernel length and width increase from tetraploid wheat

BACKGROUND

Improvement of wheat gercTriticum aestivum L.) yield could relieve global food shortages. Kernel size, as an important component of 1000-kernel weight (TKW), is always a significant consideration to improve yield for wheat breeders. Wheat related species possesses numerous elite genes that can be introduced into wheat breeding. It is thus vital to explore, identify, and introduce new genetic resources for kernel size from wheat wild relatives to increase wheat yield.

RESULTS

In the present study, quantitative trait loci (QTL) for kernel length (KL) and width (KW) were detected in a recombinant inbred line (RIL) population derived from a cross between a wild emmer accession 'LM001' and a Sichuan endemic tetraploid wheat 'Ailanmai' using the Wheat 55 K single nucleotide polymorphism (SNP) array-based constructed linkage map and phenotype from six different environments. We identified eleven QTL for KL and KW including two major ones QKL.sicau-AM-3B and QKW.sicau-AM-4B, the positive alleles of which were from LM001 and Ailanmai, respectively. They explained 17.57 to 44.28% and 13.91 to 39.01% of the phenotypic variance, respectively. For these two major QTL, Kompetitive allele-specific PCR (KASP) markers were developed and used to successfully validate their effects in three F3 populations and two natural populations containing a panel of 272 Chinese wheat landraces and that of 300 Chinese wheat cultivars, respectively. QKL.sicau-AM-3B was located at 675.6-695.4 Mb on chromosome arm 3BL. QKW.sicau-AM-4B was located at 444.2-474.0 Mb on chromosome arm 4BL. Comparison with previous studies suggested that these two major QTL were likely new loci. Further analysis indicated that the positive alleles of QKL.sicau-AM-3B and QKW.sicau-AM-4B had a great additive effect increasing TKW by 6.01%. Correlation analysis between KL and other agronomic traits showed that KL was significantly correlated to spike length, length of uppermost internode, TKW, and flag leaf length. KW was also significantly correlated with TKW. Four genes, TRIDC3BG062390, TRIDC3BG062400, TRIDC4BG037810, and TRIDC4BG037830, associated with kernel development were predicted in physical intervals harboring these two major QTL on wild emmer and Chinese Spring reference genomes.

CONCLUSIONS

Two stable and major QTL for KL and KW across six environments were detected and verified in three biparental populations and two natural populations. Significant relationships between kernel size and yield-related traits were identified. KASP markers tightly linked the two major QTL could contribute greatly to subsequent fine mapping. These results suggested the application potential of wheat related species in wheat genetic improvement.

Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut

With an objective of identifying the genomic regions for productivity and quality traits in peanut, a recombinant inbred line (RIL) population developed from an elite variety, TMV 2 and its ethyl methane sulfonate (EMS)-derived mutant was phenotyped over six seasons and genotyped with genotyping-by-sequencing (GBS), Arachis hypogaea transposable element (AhTE) and simple sequence repeats (SSR) markers. The genetic map with 700 markers spanning 2,438.1 cM was employed for quantitative trait loci (QTL) analysis which identified a total of 47 main-effect QTLs for the productivity and oil quality traits with the phenotypic variance explained (PVE) of 10-52% over the seasons. A common QTL region (46.7-50.1 cM) on Ah02 was identified for the multiple traits, such as a number of pods per plant (NPPP), pod weight per plant (PWPP), shelling percentage (SP), and test weight (TW). Similarly, a QTL (7.1-18.0 cM) on Ah16 was identified for both SP and protein content (PC). Epistatic QTL (epiQTL) analysis revealed intra- and inter-chromosomal interactions for the main-effect QTLs and other genomic regions governing these productivity traits. The markers identified by a single marker analysis (SMA) mapped to the QTL regions for most of the traits. Among the five potential candidate genes identified for PC, SP and oil quality, two genes (Arahy.7A57YA and Arahy.CH9B83) were affected by AhMITE1 transposition, and three genes (Arahy.J5SZ1I, Arahy.MZJT69, and Arahy.X7PJ8H) involved functional single nucleotide polymorphisms (SNPs). With major and consistent effects, the genomic regions, candidate genes, and the associated markers identified in this study would provide an opportunity for gene cloning and genomics-assisted breeding for increasing the productivity and enhancing the quality of peanut.

Validation and delineation of a locus conferring Fusarium crown rot resistance on 1HL in barley by analysing transcriptomes from multiple pairs of near isogenic lines

BACKGROUND

Fusarium crown rot (FCR) is a chronic and severe disease in cereal production in semi-arid regions worldwide. A putative quantitative trait locus conferring FCR resistance, Qcrs.cpi-1H, had previously been mapped on the long arm of chromosome 1H in barley.

RESULTS

In this study, five pairs of near-isogenic lines (NILs) targeting the 1HL locus were developed. Analysing the NILs found that the resistant allele at Qcrs.cpi-1H significantly reduced FCR severity. Transcriptomic analysis was then conducted against three of the NIL pairs, which placed the Qcrs.cpi-1H locus in an interval spanning about 11 Mbp. A total of 56 expressed genes bearing single nucleotide polymorphisms (SNPs) were detected in this interval. Five of them contain non-synonymous SNPs. These results would facilitate detailed mapping as well as cloning gene(s) underlying the resistance locus.

CONCLUSION

NILs developed in this study and the transcriptomic sequences obtained from them did not only allow the validation of the resistance locus Qcrs.cpi-1H and the identification of candidate genes underlying its resistance, they also allowed the delineation of the resistance locus and the development of SNPs markers which formed a solid base for detailed mapping as well as cloning gene(s) underlying the locus.

Identification of Soybean Genes Related to Soybean Seed Protein Content Based on Quantitative Trait Loci Collinearity Analysis

Increasing the protein content of soybean seeds through a higher ratio of glycinin is important for soybean breeding and food processing; therefore, the integration of different quantitative trait loci (QTLs) is of great significance. In this study, we investigated the collinearity of seed protein QTLs. We identified 192 collinear protein QTLs that formed six hotspot regions. The two most important regions had seed protein 36-10 and seed protein 36-20 as hub nodes. We used a chromosome segment substitution line (CSSL) population for QTL validation and identified six CSSL materials with collinear QTLs. Five materials with higher protein and glycinin contents in comparison to the recurrent parent were analyzed. A total of 13 candidate genes related to seed protein from the QTL hotspot intervals were detected, 8 of which had high expression in mature soybean seeds. These results offer a new analysis method for molecular-assisted selection (MAS) and improvement of soybean product quality.

Validation of QTL mapping and transcriptome profiling for identification of candidate genes associated with nitrogen stress tolerance in sorghum

BACKGROUND

Quantitative trait loci (QTLs) detected in one mapping population may not be detected in other mapping populations at all the time. Therefore, before being used for marker assisted breeding, QTLs need to be validated in different environments and/or genetic backgrounds to rule out statistical anomalies. In this regard, we mapped the QTLs controlling various agronomic traits in a recombinant inbred line (RIL) population in response to Nitrogen (N) stress and validated these with the reported QTLs in our earlier study to find the stable and consistent QTLs across populations. Also, with Illumina RNA-sequencing we checked the differential expression of gene (DEG) transcripts between parents and pools of RILs with high and low nitrogen use efficiency (NUE) and overlaid these DEGs on to the common validated QTLs to find candidate genes associated with N-stress tolerance in sorghum.

RESULTS

An F₇ RIL population derived from a cross between CK60 (N-stress sensitive) and San Chi San (N-stress tolerant) inbred sorghum lines was used to map QTLs for 11 agronomic traits tested under different N-levels. Composite interval mapping analysis detected a total of 32 QTLs for 11 agronomic traits. Validation of these QTLs revealed that of the detected, nine QTLs from this population were consistent with the reported QTLs in earlier study using CK60/China17 RIL population. The validated QTLs were located on chromosomes 1, 6, 7, 8, and 9. In addition, root transcriptomic profiling detected 55 and 20 differentially expressed gene (DEG) transcripts between parents and pools of RILs with high and low NUE respectively. Also, overlay of these DEG transcripts on to the validated QTLs found candidate genes transcripts for NUE and also showed the expected differential expression. For example, DEG transcripts encoding Lysine histidine transporter 1 (LHT1) had abundant expression in San Chi San and the tolerant RIL pool, whereas DEG transcripts encoding seed storage albumin, transcription factor IIIC (TFIIIC) and dwarfing gene (DW2) encoding multidrug resistance-associated protein-9 homolog showed abundant expression in CK60 parent, similar to earlier study.

CONCLUSIONS

The validated QTLs among different mapping populations would be the most reliable and stable QTLs across germplasm. The DEG transcripts found in the validated QTL regions will serve as future candidate genes for enhancing NUE in sorghum using molecular approaches.

Microsomal Omega-3 Fatty Acid Desaturase Genes in Low Linolenic Acid Soybean Line RG10 and Validation of Major Linolenic Acid QTL

High levels of linolenic acid (80 g kg(-1)) are associated with the development of off-flavors and poor stability in soybean oil. The development of low linolenic acid lines such as RG10 (20 g kg(-1) linolenic acid) can reduce these problems. The level of linolenic acid in seed oil is determined by the activities of microsomal omega-3 fatty acid desaturases (FAD3). A major linolenic acid QTL (>70% of variation) on linkage group B2 (chromosome Gm14) was previously detected in a recombinant inbred line population from the RG10 × OX948 cross. The objectives of this study were to validate the major linolenic acid QTL in an independent population and characterize all the soybean FAD3 genes. Four FAD3 genes were sequenced and localized in RG10 and OX948 and compared to the genes in the reference Williams 82 genome. The FAD3A gene sequences mapped to the locus Glyma.14g194300 [on the chromosome Gm14 (B2)], which is syntenic to the FAD3B gene (locus Glyma.02g227200) on the chromosome Gm02 (D1b). The location of the FAD3A gene is the same as was previously determined for the fan allele, that conditions low linolenic acid content and several linolenic acid QTL, including Linolen 3-3, mapped previously with the RG10 × OX948 population and confirmed in the PI 361088B × OX948 population as Linolen-PO (FAD3A). The FAD3B gene-based marker, developed previously, was mapped to the chromosome Gm02 (D1b) in a region containing a newly detected linolenic acid QTL [Linolen-RO(FAD3B)] in the RG10 × OX948 genetic map and corresponds well with the in silico position of the FAD3B gene sequences. FAD3C and FAD3D gene sequences, mapped to syntenic regions on chromosomes Gm18 (locus Glyma.18g062000) and Gm11 (locus Glyma.11g227200), respectively. Association of linolenic acid QTL with the desaturase genes FAD3A and FAD3B, their validation in an independent population, and development of FAD3 gene-specific markers should simplify and accelerate breeding for low linolenic acid soybean cultivars.

Identification and Verification of QTL Associated with Frost Tolerance Using Linkage Mapping and GWAS in Winter Faba Bean

Frost stress is one of the abiotic stresses that causes a significant reduction in winter faba bean yield in Europe. The main objective of this work is to genetically improve frost tolerance in winter faba bean by identifying and validating QTL associated with frost tolerance to be used in marker-assisted selection (MAS). Two different genetic backgrounds were used: a biparental population (BPP) consisting of 101 inbred lines, and 189 genotypes from single seed descent (SSD) from the Gottingen Winter bean Population (GWBP). All experiments were conducted in a frost growth chamber under controlled conditions. Both populations were genotyped using the same set of 189 SNP markers. Visual scoring for frost stress symptoms was used to define frost tolerance in both populations. In addition, leaf fatty acid composition (FAC) and proline content were analyzed in BPP as physiological traits. QTL mapping (for BPP) and genome wide association studies (for GWBP) were performed to detect QTL associated with frost tolerance. High genetic variation between genotypes, and repeatability estimates, were found for all traits. QTL mapping and GWAS identified new putative QTL associated with promising frost tolerance and related traits. A set of 54 SNP markers common in both genetic backgrounds showed a high genetic diversity with polymorphic information content (PIC) ranging from 0.31 to 0.37 and gene diversity ranging from 0.39 to 0.50. This indicates that these markers may be polymorphic for many faba bean populations. Five SNP markers showed a significant marker-trait association with frost tolerance and related traits in both populations. Moreover, synteny analysis between Medicago truncatula (a model legume) and faba bean genomes was performed to identify candidate genes for these markers. Collinearity was evaluated between the faba bean genetic map constructed in this study and the faba bean consensus map, resulting in identifying possible genomic regions in faba bean which may control frost tolerance genes. The two genetic backgrounds were useful in detecting new variation for improving frost tolerance in winter faba bean. Of the five validated SNP markers, one (VF_Mt3g086600) was found to be associated with frost tolerance and FAC in both populations. This marker was also associated with winter hardiness and high yield in earlier studies. This marker is located in a gene of unknown function.