Comparative Genomic Analysis of Quantitative Trait Loci Associated With Micronutrient Contents, Grain Quality, and Agronomic Traits in Wheat (Triticum aestivum L.)

Comparative genomics and meta-quantitative trait loci (MQTLs) analysis are important tools for the identification of reliable and stable QTLs and functional genes controlling quantitative traits. We conducted a meta-analysis to identify the most stable QTLs for grain yield (GY), grain quality traits, and micronutrient contents in wheat. A total of 735 QTLs retrieved from 27 independent mapping populations reported in the last 13 years were used for the meta-analysis. The results showed that 449 QTLs were successfully projected onto the genetic consensus map which condensed to 100 MQTLs distributed on wheat chromosomes. This consolidation of MQTLs resulted in a three-fold reduction in the confidence interval (CI) compared with the CI for the initial QTLs. Projection of QTLs revealed that the majority of QTLs and MQTLs were in the non-telomeric regions of chromosomes. The majority of micronutrient MQTLs were located on the A and D genomes. The QTLs of thousand kernel weight (TKW) were frequently associated with QTLs for GY and grain protein content (GPC) with co-localization occurring at 55 and 63%, respectively. The co- localization of QTLs for GY and grain Fe was found to be 52% and for QTLs of grain Fe and Zn, it was found to be 66%. The genomic collinearity within Poaceae allowed us to identify 16 orthologous MQTLs (OrMQTLs) in wheat, rice, and maize. Annotation of promising candidate genes (CGs) located in the genomic intervals of the stable MQTLs indicated that several CGs (e.g., TraesCS2A02G141400, TraesCS3B02G040900, TraesCS4D02G323700, TraesCS3B02G077100, and TraesCS4D02G290900) had effects on micronutrients contents, yield, and yield-related traits. The mapping refinements leading to the identification of these CGs provide an opportunity to understand the genetic mechanisms driving quantitative variation for these traits and apply this information for crop improvement programs.

QTL Mapping and Validation for Kernel Area and Circumference in Common Wheat via High-Density SNP-Based Genotyping

As an important component, 1,000 kernel weight (TKW) plays a significant role in the formation of yield traits of wheat. Kernel size is significantly positively correlated to TKW. Although numerous loci for kernel size in wheat have been reported, our knowledge on loci for kernel area (KA) and kernel circumference (KC) remains limited. In the present study, a recombinant inbred lines (RIL) population containing 371 lines genotyped using the Wheat55K SNP array was used to map quantitative trait loci (QTLs) controlling the KA and KC in multiple environments. A total of 54 and 44 QTLs were mapped by using the biparental population or multienvironment trial module of the inclusive composite interval mapping method, respectively. Twenty-two QTLs were considered major QTLs. BLAST analysis showed that major and stable QTLs QKc.sau-6A.1 (23.12–31.64 cM on 6A) for KC and QKa.sau-6A.2 (66.00–66.57 cM on 6A) for KA were likely novel QTLs, which explained 22.25 and 20.34% of the phenotypic variation on average in the 3 year experiments, respectively. Two Kompetitive allele-specific PCR (KASP) markers, KASP-AX-109894590 and KASP-AX-109380327, were developed and tightly linked to QKc.sau-6A.1 and QKa.sau-6A.2, respectively, and the genetic effects of the different genotypes in the RIL population were successfully confirmed. Furthermore, in the interval where QKa.sau-6A.2 was located on Chinese Spring and T. Turgidum ssp. dicoccoides reference genomes, only 11 genes were found. In addition, digenic epistatic QTLs also showed a significant influence on KC and KA. Altogether, the results revealed the genetic basis of KA and KC and will be useful for the marker-assisted selection of lines with different kernel sizes, laying the foundation for the fine mapping and cloning of the gene(s) underlying the stable QTLs detected in this study.

A consensus and saturated genetic map provides insight into genome anchoring, synteny of Solanaceae and leaf- and fruit-related QTLs in wolfberry (Lycium Linn.)

Background Lycium Linn. (Solanaceae) is a genus of economically important plants producing fruits and leaves with high nutritional value and medicinal benefits. However, genetic analysis of this plant and molecular breeding for quality improvement are limited by the lack of sufficient molecular markers. Results In this study, two parental strains, ‘Ningqi No. 1’ (Lycium barbarum L.) and ‘Yunnan Gouqi’ (Lycium yunnanense Kuang et A.M. Lu), and 200 F1 hybrid individuals were resequenced for genetic analysis. In total, 8,507 well-selected SNPs were developed, and a high-density genetic map (NY map) was constructed with a total genetic distance of 2,122.24 cM. A consensus genetic map was established by integrating the NY map and a previously published genetic map (NC map) containing 15,240 SNPs, with a total genetic distance of 3,058.19 cM and an average map distance of 0.21 cM. The 12 pseudochromosomes of the Lycium reference genome were anchored using this consensus genetic map, with an anchoring rate of 64.3%. Moreover, weak collinearities between the consensus map and the pepper, potato, and tomato genomes were observed. Twenty-five stable QTLs were identified for leaf- and fruit-related phenotypes, including fruit weight, fruit longitude, leaf length, the fruit index, and the leaf index; these stable QTLs were mapped to four different linkage groups, with LOD scores ranging from 2.51 to 19.37 and amounts of phenotypic variance explained from 6.2% to 51.9%. Finally, 82 out of 188 predicted genes underlying stable QTLs for fruit-related traits were differentially expressed according to RNA-seq analysis. Conclusions A chromosome-level assembly can provide a foundation for further functional genomics research for wolfberry. The genomic regions of these stably expressed QTLs could be used as targets for further fine mapping and development of molecular markers for marker-assisted selection (MAS). The present study provided valuable information on saturated SNP markers and reliable QTLs for map-based cloning of functional genes related to yield and morphological traits in Lycium spp.

A consensus and saturated genetic map provides insight into genome anchoring, synteny of Solanaceae and leaf- and fruit-related QTLs in wolfberry (Lycium Linn.)

Background: Lycium Linn. (Solanaceae) is a genus of economically important plants producing fruits and leaves with high nutritional value and medicinal benefits. However, genetic analysis of this plant and molecular breeding for quality improvement are limited by the lack of sufficient molecular markers. Results: In this study, two parental strains, ‘Ningqi No. 1’ (Lycium barbarum L.) and ‘Yunnan Gouqi’ (Lycium yunnanense Kuang et A.M. Lu), and 200 F1 hybrid individuals were resequenced for genetic analysis. In total, 8,507 well-selected SNPs were developed, and a high-density genetic map (NY map) was constructed with a total genetic distance of 2,122.24 cM. A consensus genetic map was established by integrating the NY map and a previously published genetic map (NC map) containing 15,240 SNPs, with a total genetic distance of 3,058.19 cM and an average map distance of 0.21 cM. The 12 pseudochromosomes of the Lycium reference genome were anchored using this consensus genetic map, with an anchoring rate of 64.3%. Moreover, weak collinearities between the consensus map and the pepper, potato, and tomato genomes were observed. Twenty-five stable QTLs were identified for leaf- and fruit-related phenotypes, including fruit weight, fruit longitude, leaf length, the fruit index, and the leaf index; these stable QTLs were mapped to four different linkage groups, with LOD scores ranging from 2.51 to 19.37 and amounts of phenotypic variance explained from 6.2% to 51.9%. Finally, 82 out of 188 predicted genes underlying stable QTLs for fruit-related traits were differentially expressed according to RNA-seq analysis. Conclusions: A chromosome-level assembly can provide a foundation for further functional genomics research for wolfberry. The genomic regions of these stably expressed QTLs could be used as targets for further fine mapping and development of molecular markers for marker-assisted selection (MAS). The present study provided valuable information on saturated SNP markers and reliable QTLs for map-based cloning of functional genes related to yield and morphological traits in Lycium spp.

Meta-Analysis of Quantitative Traits Loci (QTL) Identified in Drought Response in Rice (Oryza sativa L.)

Rice is an important grain that is the staple food for most of the world’s population. Drought is one of the major stresses that negatively affects rice yield. The nature of drought tolerance in rice is complex as it is determined by various components and has low heritability. Therefore, to ensure success in breeding programs for drought tolerant rice, QTLs (quantitative trait loci) of interest must be stable in a variety of plant genotypes and environments. This study identified stable QTLs in rice chromosomes in a variety of backgrounds and environments and conducted a meta-QTL analysis of stable QTLs that have been reported by previous research for use in breeding programs. A total of 653 QTLs for drought tolerance in rice from 27 genetic maps were recorded for analysis. The QTLs recorded were related to 13 traits in rice that respond to drought. Through the use of BioMercartor V4.2, a consensus map containing QTLs and molecular markers were generated using 27 genetic maps that were extracted from the previous 20 studies and meta-QTL analysis was conducted on the consensus map. A total of 70 MQTLs were identified and a total of 453 QTLs were mapped into the meta-QTL areas. Five meta-QTLs from chromosome 1 (MQTL 1.5 and MQTL 1.6), chromosome 2 (MQTL2.1 and MQTL 2.2) and chromosome 3 (MQTL 3.1) were selected for functional annotation as these regions have high number of QTLs and include many traits in rice that respond to drought. A number of genes in MQTL1.5 (268 genes), MQTL1.6 (640 genes), MQTL 2.1 (319 genes), MQTL 2.2 (19 genes) and MQTL 3.1 (787 genes) were annotated through Blast2GO. Few major proteins that respond to drought stress were identified in the meta-QTL areas which are Abscisic Acid-Insensitive Protein 5 (ABI5), the G-box binding factor 4 (GBF4), protein kinase PINOID (PID), histidine kinase 2 (AHK2), protein related to autophagy 18A (ATG18A), mitochondrial transcription termination factor (MTERF), aquaporin PIP 1-2, protein detoxification 48 (DTX48) and inositol-tetrakisphosphate 1-kinase 2 (ITPK2). These proteins are regulatory proteins involved in the regulation of signal transduction and gene expression that respond to drought stress. The meta-QTLs derived from this study and the genes that have been identified can be used effectively in molecular breeding and in genetic engineering for drought resistance/tolerance in rice.

Meta-QTL and ortho-MQTL analyses identified genomic regions controlling rice yield, yield-related traits and root architecture under water deficit conditions

Meta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits. Rice varieties adapted to non-flooded cultivation are highly desirable in breeding programs due to the water deficit global problem. In order to identify stable QTLs for major agronomic traits under water deficit conditions, we performed a comprehensive MQTL analysis on 563 QTLs from 67 rice populations published from 2001 to 2019. Yield and yield-related traits including grain weight, heading date, plant height, tiller number as well as root architecture-related traits including root dry weight, root length, root number, root thickness, the ratio of deep rooting and plant water content under water deficit condition were investigated. A total of 61 stable MQTLs over different genetic backgrounds and environments were identified. The average confidence interval of MQTLs was considerably refined compared to the initial QTLs, resulted in the identification of some well-known functionally characterized genes and several putative novel CGs for investigated traits. Ortho-MQTL mining based on genomic collinearity between rice and maize allowed identification of five ortho-MQTLs between these two cereals. The results can help breeders to improve yield under water deficit conditions.

QTL mapping of PEG-induced drought tolerance at the early seedling stage in sesame using whole genome re-sequencing

Improvement in sesame drought tolerance at seedling stage is important for yield stability. Genetic approaches combing with conventional breeding is the most effective way to develop drought-tolerant cultivars. In this study, three traits and their relative values, including seedling weight (SW), shoot length (SL) and root length (RL), were evaluated under control and osmotic conditions in a recombinant inbred line (RIL) population derived from cross of Zhushanbai and Jinhuangma. Significant variation and high broad sense heritability were observed for all traits except SW under stress condition in the population. With this population, a high-density linkage map with 1354 bin markers was constructed through whole genome re-sequencing (WGS) strategy. Quantitative trait loci (QTL) mapping was performed for all the traits. A total of 34 QTLs were detected on 10 chromosomes. Among them, 13 stable QTLs were revealed in two independent experiments, eight of them were associated with traits under water stress condition. One region on chromosome 12 related to RL under osmotic condition and relative RL had the highest LOD value and explained the largest phenotypic variation among all the QTLs detected under water stress condition. These findings will provide new genetic resources for molecular improvement of drought tolerance and candidate gene identification in sesame.

Rapid Excavating a FLOWERING LOCUS T-Regulator NF-YA Using Genotyping-by-Sequencing

Soybean [Glycine max (L.) Merrill] is one of the most important crop plants in the world as an important source of protein for both human consumption and livestock fodder. Soybean flowering time is beneficial to the improvement of soybean yield. Therefore, finding new QTLs and further identifying candidate genes associated with various flowering time are fundamental approaches in enhancing the yield of soybean. In this study, a set of 120 recombinant inbred lines (RILs) which developed from a cross of two soybean cultivars, Suinong4 (SN4) and ZK168, were genotyped by genotyping-by-sequencing (GBS) approach and phenotyped to expand the cognitive of flowering time (R1) by Quantitative Trait Loci (QTL) analysis. Eventually, we detected three stable QTLs related to R1 separately located on chromosome 14, 18, and 19 under long-day conditions. The candidate genes of the three QTLs were predicted, and association analysis of the candidate genes related to flowering time was carried out. Moreover, a transient transfection assay was performed and showed that a candidate gene of the QTL on chromosome 19, GmNF-YA21 (Nuclear factor YA21), might affect flowering by suppressing the expression of GmFTs. QTLs detected in this study will provide fundamental resources for finding candidate genes and clarify the mechanisms of flowering which would be helpful for breeding novel high-yield soybean cultivars.

QTL Analysis and Fine Mapping of a Major QTL Conferring Kernel Size in Maize (Zea mays)

Kernel size is an important agronomic trait for grain yield in maize. The purpose of this study is to map QTLs and predict candidate genes for kernel size in maize. A total of 199 F2 and its F2:3 lines from the cross between SG5/SG7 were developed. A composite interval mapping (CIM) method was used to detect QTLs in three environments of F2 and F2:3 populations. The result showed that a total of 10 QTLs for kernel size were detected, among which were five QTLs for kernel length (KL) and five QTLs for kernel width (KW). Two stable QTLs, qKW-1, and qKL-2, were mapped in all three environments. Three QTLs, qKL-1, qKW-1, and qKW-2, were overlapped with the QTLs identified from previous studies. In order to validate and fine map qKL-2, near-isogenic lines (NILs) were developed by continuous backcrossing between SG5 as the donor parent and SG7 as the recurrent parent. Marker-assisted selection was conducted from BC2F1 generation with molecular markers near qKL-2. A secondary linkage map with six markers around the qKL-2 region was developed and used for fine mapping of qKL-2. Finally, qKL-2 was confirmed in a 1.95 Mb physical interval with selected overlapping recombinant chromosomes on maize chromosome 9 by blasting with the Zea_Mays_B73 v4 genome. Transcriptome analysis showed that a total of 11 out of 40 protein-coding genes differently expressed between the two parents were detected in the identified qKL-2 interval. GRMZM2G006080 encoding a receptor-like protein kinase FERONIA, was predicted as a candidate gene to control kernel size. The work will not only help to understand the genetic mechanisms of kernel size of maize but also lay a foundation for further fine mapping and even cloning of the promising loci.