QTL Clusters Research Articles

QTL mapping and candidate gene mining of seed size and seed weight in castor plant (Ricinus communis L.).

Castor (Ricinus communis L., 2n = 2x = 20) is an important industrial crop, due to its oil is very important to the global special chemical industry. Seed size and seed weight are fundamentally important in determining castor yield, while little is known about it. In this study, QTL analysis and candidate gene mining of castor seed size and seed weight were conducted with composite interval mapping (CIM), inclusive composite interval mapping (ICIM) and marker enrichment strategy in 4 populations, i.e., populations F2, BC1, S1-1 and S1-2, derived from 2 accessions with significant phenotypic differences. In the QTL primary mapping, 2 novel QTL clusters were detected in marker intervals RCM520-RCM76 and RCM915-RCM950. In order to verify their accuracy and to narrow their intervals, QTL remapping was carried out in populations F2 and BC1. Among them, 44 and 30 QTLs underlying seed size and seed weight were detected in F2 population using methods CIM and ICIM-ADD respectively, including 4-9 and 3-5 ones conferring each trait were identified with a phenotypic variation explained ranged from 37.92 to 115.81% and 32.86-45.98% respectively. The remapping results in BC1 population were consistent with those in F2 population. Importantly, 3 QTL clusters (i.e. QTL-cluster1, QTL-cluster2 and QTL-cluster3) were found in marker intervals RCM74-RCM76 (37.1kb), RCM930-RCM950 (259.8kb) and RCM918-RCM920 (172.9kb) respectively; in addition, all of them were detected again, the former one was found in the S1-2 population, and the latter two were found simultaneously in the populations S1-1 and S1-2. Finally, 6 candidate genes (i.e. LOC8266555, LOC8281168, LOC8281151, LOC8259066, LOC8258591 and LOC8270077) were screened in the above QTL clusters, they were differentially expressed in multiple seed tissues of both parents, signifying the potential role in regulating seed size and seed weight. The above results not only provide new insights into the genetic structure of seed size and seed weight in castor, but also lay the foundation for the functional identification of these candidate genes.

QTL Mapping of Fiber- and Seed-Related Traits in Chromosome Segment Substitution Lines Derived from Gossypium hirsutum × Gossypium darwinii.

A narrow genetic basis limits further the improvement of modern Gossypium hirsutum cultivar. The abundant genetic diversity of wild species provides available resources to solve this dilemma. In the present study, a chromosome segment substitution line (CSSL) population including 553 individuals was established using G. darwinii accession 5-7 as the donor parent and G. hirsutum cultivar CCRI35 as the recipient parent. After constructing a high-density genetic map with the BC1 population, the genotype and phenotype of the CSSL population were investigated. A total of 235 QTLs, including 104 QTLs for fiber-related traits and 132 QTLs for seed-related traits, were identified from four environments. Among these QTLs, twenty-seven QTLs were identified in two or more environments, and twenty-five QTL clusters consisted of 114 QTLs. Moreover, we identified three candidate genes for three stable QTLs, including GH_A01G1096 (ARF5) and GH_A10G0141 (PDF2) for lint percentage, and GH_D01G0047 (KCS4) for seed index or oil content. These results pave way for understanding the molecular regulatory mechanism of fiber and seed development and would provide valuable information for marker-assisted genetic improvement in cotton.

Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review.

In this study, hotspot regions, QTL clusters, and candidate genes for eight ear-related traits of maize (ear length, ear diameter, kernel row number, kernel number per row, kernel length, kernel width, kernel thickness, and 100-kernel weight) were summarized and analyzed over the past three decades. This review aims to (1) comprehensively summarize and analyze previous studies on QTLs associated with these eight ear-related traits and identify hotspot bin regions located on maize chromosomes and key candidate genes associated with the ear-related traits and (2) compile major and stable QTLs and QTL clusters from various mapping populations and mapping methods and techniques providing valuable insights for fine mapping, gene cloning, and breeding for high-yield and high-quality maize. Previous research has demonstrated that QTLs for ear-related traits are distributed across all ten chromosomes in maize, and the phenotypic variation explained by a single QTL ranged from 0.40% to 36.76%. In total, 23 QTL hotspot bins for ear-related traits were identified across all ten chromosomes. The most prominent hotspot region is bin 4.08 on chromosome 4 with 15 QTLs related to eight ear-related traits. Additionally, this study identified 48 candidate genes associated with ear-related traits. Out of these, five have been cloned and validated, while twenty-eight candidate genes located in the QTL hotspots were defined by this study. This review offers a deeper understanding of the advancements in QTL mapping and the identification of key candidates associated with eight ear-related traits. These insights will undoubtedly assist maize breeders in formulating strategies to develop higher-yield maize varieties, contributing to global food security.

Genomic analysis of a new heterotic maize group reveals key loci for pedigree breeding.

Genome-wide analyses of maize populations have clarified the genetic basis of crop domestication and improvement. However, limited information is available on how breeding improvement reshaped the genome in the process of the formation of heterotic groups. In this study, we identified a new heterotic group (X group) based on an examination of 512 Chinese maize inbred lines. The X group was clearly distinct from the other non-H&L groups, implying that X × HIL is a new heterotic pattern. We selected the core inbred lines for an analysis of yield-related traits. Almost all yield-related traits were better in the X lines than those in the parental lines, indicating that the primary genetic improvement in the X group during breeding was yield-related traits. We generated whole-genome sequences of these lines with an average coverage of 17.35× to explore genome changes further. We analyzed the identity-by-descent (IBD) segments transferred from the two parents to the X lines and identified 29 and 28 IBD conserved regions (ICRs) from the parents PH4CV and PH6WC, respectively, accounting for 28.8% and 12.8% of the genome. We also identified 103, 89, and 131 selective sweeps (SSWs) using methods that involved the π, Tajima's D, and CLR values, respectively. Notably, 96.13% of the ICRs co-localized with SSWs, indicating that SSW signals concentrated in ICRs. We identified 171 annotated genes associated with yield-related traits in maize both in ICRs and SSWs. To identify the genetic factors associated with yield improvement, we conducted QTL mapping for 240 lines from a DH population (PH4CV × PH6WC, which are the parents of X1132X) for ten key yield-related traits and identified a total of 55 QTLs. Furthermore, we detected three QTL clusters both in ICRs and SSWs. Based on the genetic evidence, we finally identified three key genes contributing to yield improvement in breeding the X group. These findings reveal key loci and genes targeted during pedigree breeding and provide new insights for future genomic breeding.

Transcriptome analysis reveals key regulatory genes for root growth related to potassium utilization efficiency in rapeseed (Brassica napus L.).

Root system architecture (RSA) is the primary predictor of nutrient intake and significantly influences potassium utilization efficiency (KUE). Uncertainty persists regarding the genetic factors governing root growth in rapeseed. The root transcriptome analysis reveals the genetic basis driving crop root growth. In this study, RNA-seq was used to profile the overall transcriptome in the root tissue of 20 Brassica napus accessions with high and low KUE. 71,437 genes in the roots displayed variable expression profiles between the two contrasting genotype groups. The 212 genes that had varied expression levels between the high and low KUE lines were found using a pairwise comparison approach. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional classification analysis revealed that the DEGs implicated in hormone and signaling pathways, as well as glucose, lipid, and amino acid metabolism, were all differently regulated in the rapeseed root system. Additionally, we discovered 33 transcription factors (TFs) that control root development were differentially expressed. By combining differential expression analysis, weighted gene co-expression network analysis (WGCNA), and recent genome-wide association study (GWAS) results, four candidate genes were identified as essential hub genes. These potential genes were located fewer than 100 kb from the peak SNPs of QTL clusters, and it was hypothesized that they regulated the formation of the root system. Three of the four hub genes' homologs-BnaC04G0560400ZS, BnaC04G0560400ZS, and BnaA03G0073500ZS-have been shown to control root development in earlier research. The information produced by our transcriptome profiling could be useful in revealing the molecular processes involved in the growth of rapeseed roots in response to KUE.

QTL Mapping of Agronomic and Physiological Traits at the Seedling and Maturity Stages under Different Nitrogen Treatments in Barley.

Nitrogen (N) stress seriously constrains barley (Hordeum vulgare L.) production globally by influencing its growth and development. In this study, we used a recombinant inbred line (RIL) population of 121 crosses between the variety Baudin and the wild barley accession CN4027 to detect QTL for 27 traits at the seedling stage in hydroponic culture trials and 12 traits at the maturity stage in field trials both under two N treatments, aiming to uncover favorable alleles for N tolerance in wild barley. In total, eight stable QTL and seven QTL clusters were detected. Among them, the stable QTL Qtgw.sau-2H located in a 0.46 cM interval on the chromosome arm 2HL was a novel QTL specific for low N. Notably, Clusters C4 and C7 contained QTL for traits at both the seedling and maturity stages. In addition, four stable QTLs in Cluster C4 were identified. Furthermore, a gene (HORVU2Hr1G080990.1) related to grain protein in the interval of Qtgw.sau-2H was predicted. Correlation analysis and QTL mapping showed that different N treatments significantly affected agronomic and physiological traits at the seedling and maturity stages. These results provide valuable information for understanding N tolerance as well as breeding and utilizing the loci of interest in barley.

Genetic mapping of some key plant architecture traits in Brassica juncea using a doubled haploid population derived from a cross between two distinct lines: vegetable type Tumida and oleiferous Varuna.

Genetic mapping of some key plant architectural traits in a vegetable type and an oleiferous B. juncea cross revealed QTL and candidate genes for breeding more productive ideotypes. Brassica juncea (AABB, 2n = 36), commonly called mustard, is an allopolyploid crop of recent origin but contains considerable morphological and genetic variation. An F1-derived doubled haploid population developed from a cross between an Indian oleiferous line, Varuna, and a Chinese stem type vegetable mustard, Tumida showed significant variability for some key plant architectural traits-four stem strength-related traits, stem diameter (Dia), plant height (Plht), branch initiation height (Bih), number of primary branches (Pbr), and days to flowering (Df). Multi-environment QTL analysis identified twenty Stable QTL for the above-mentioned nine plant architectural traits. Though Tumida is ill-adapted to the Indian growing conditions, it was found to contribute favorable alleles in Stable QTL for five architectural traits-press force, Dia, Plht, Bih, and Pbr; these QTL could be used to breed superior ideotypes in the oleiferous mustard lines. A QTL cluster on LG A10 contained Stable QTL for seven architectural traits that included major QTL (phenotypic variance ≥ 10%) for Df and Pbr, with Tumida contributing the trait-enhancing alleles for both. Since early flowering is critical for the cultivation of mustard in the Indian subcontinent, this QTL cannot be used for the improvement of Pbr in the Indian gene pool lines. Conditional QTL analysis for Pbr, however, identified other QTL which could be used for the improvement of Pbr without affecting Df. The Stable QTL intervalswere mapped on the genome assemblies of Tumida and Varuna for the identification of candidate genes.

Identification of QTL controlling volatile terpene contents in tea plant (Camellia sinensis) using a high-aroma 'Huangdan' x 'Jinxuan' F1 population.

Aroma is an important factor affecting the character and quality of tea. The improvement of aroma trait is a crucial research direction of tea plant breeding. Volatile terpenes, as the major contributors to the floral odors of tea products, also play critical roles in the defense responses of plants to multiple stresses. However, previous studies have largely focused on the aroma formation during the manufacture of tea or the comparison of raw tea samples. The mechanisms causing different aroma profiles between tea cultivars have remained underexplored. In the current study, a high-density genetic linkage map of tea plant was constructed based on an F1 population of 'Huangdan' × 'Jinxuan' using genotyping by sequencing. This linkage map covered 1754.57 cM and contained 15 linkage groups with a low inter-marker distance of 0.47 cM. A total of 42 QTLs associated with eight monoterpene contents and 12 QTLs associated with four sesquiterpenes contents were identified with the average PVE of 12.6% and 11.7% respectively. Furthermore, six candidate genes related to volatile terpene contents were found in QTL cluster on chromosome 5 by RNA-seq analysis. This work will enrich our understanding of the molecular mechanism of volatile terpene biosynthesis and provide a theoretical basis for tea plant breeding programs for aroma quality improvement.

Molecular dissection of connected rice populations revealed important genomic regions for agronomic and biofortification traits.

Breeding staple crops with increased micronutrient concentration is a sustainable approach to address micronutrient malnutrition. We carried out Multi-Cross QTL analysis and Inclusive Composite Interval Mapping for 11 agronomic, yield and biofortification traits using four connected RILs populations of rice. Overall, MC-156 QTLs were detected for agronomic (115) and biofortification (41) traits, which were higher in number but smaller in effects compared to single population analysis. The MC-QTL analysis was able to detect important QTLs viz: qZn5.2, qFe7.1, qGY10.1, qDF7.1, qPH1.1, qNT4.1, qPT4.1, qPL1.2, qTGW5.1, qGL3.1 , and qGW6.1 , which can be used in rice genomics assisted breeding. A major QTL (qZn5.2 ) for grain Zn concentration has been detected on chromosome 5 that accounted for 13% of R2. In all, 26 QTL clusters were identified on different chromosomes. qPH6.1 epistatically interacted with qZn5.1 and qGY6.2 . Most of QTLs were co-located with functionally related candidate genes indicating the accuracy of QTL mapping. The genomic region of qZn5.2 was co-located with putative genes such as OsZIP5, OsZIP9, and LOC_OS05G40490 that are involved in Zn uptake. These genes included polymorphic functional SNPs, and their promoter regions were enriched with cis-regulatory elements involved in plant growth and development, and biotic and abiotic stress tolerance. Major effect QTL identified for biofortification and agronomic traits can be utilized in breeding for Zn biofortified rice varieties.

QTL Mapping for Important Agronomic Traits Using a Wheat55K SNP Array-Based Genetic Map in Tetraploid Wheat

Wheat yield is highly correlated with plant height, heading date, spike characteristics, and kernel traits. In this study, we used the wheat55K single nucleotide polymorphism array to genotype a recombinant inbred line population of 165 lines constructed by crossing two tetraploid wheat materials, Icaro and Y4. A genetic linkage map with a total length of 6244.51 cM was constructed, covering 14 chromosomes of tetraploid wheat. QTLs for 12 important agronomic traits, including plant height (PH), heading date (HD), awn color (AC), spike-branching (SB), and related traits of spike and kernel, were mapped in multiple environments, while combined QTL-by-environment interactions and epistatic effects were analyzed for each trait. A total of 52 major or stable QTLs were identified, among which may be some novel loci controlling PH, SB, and kernel length-width ratio (LWR), etc., with LOD values ranging from 2.51 to 54.49, thereby explaining 2.40-66.27% of the phenotypic variation. Based on the 'China Spring' and durum wheat reference genome annotations, candidate genes were predicted for four stable QTLs, QPH.nwafu-2B.2 (165.67-166.99 cM), QAC.nwafu-3A.1 (419.89-420.52 cM), QAC.nwafu-4A.1 (424.31-447.4 cM), and QLWR.nwafu-7A.1 (166.66-175.46 cM). Thirty-one QTL clusters and 44 segregation distortion regions were also detected, and 38 and 18 major or stable QTLs were included in these clusters and segregation distortion regions, respectively. These results provide QTLs with breeding application potential in tetraploid wheat that broadens the genetic basis of important agronomic traits such as PH, HD, AC, SB, etc., and benefits wheat breeding.

Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments.

The seed weight of soybean [Glycine max (L.) Merr.] is one of the major traits that determine soybean yield and is closely related to seed size. However, the genetic basis of the synergistic regulation of traits related to soybean yield is unclear. To understand the molecular genetic basis for the formation of soybean yield traits, the present study focused on QTLs mapping for seed size and weight traits in different environments and target genes mining. A total of 85 QTLs associated with seed size and weight traits were identified using a recombinant inbred line (RIL) population developed from Guizao1×B13 (GB13). We also detected 18 environmentally stable QTLs. Of these, qSL-3-1 was a novel QTL with a stable main effect associated with seed length. It was detected in all environments, three of which explained more than 10% of phenotypic variance (PV), with a maximum of 15.91%. In addition, qSW-20-3 was a novel QTL with a stable main effect associated with seed width, which was identified in four environments. And the amount of phenotypic variance explained (PVE) varied from 9.22 to 21.93%. Five QTL clusters associated with both seed size and seed weight were summarized by QTL cluster identification. Fifteen candidate genes that may be involved in regulating soybean seed size and weight were also screened based on gene function annotation and GO enrichment analysis. The results provide a biologically basic reference for understanding the formation of soybean seed size and weight traits.

Mapping and identification of QTL for agro-physiological traits in rice (Oryza sativa L.) under drought stress

Exploring novel QTLs for drought tolerance traits using a new rice genetic resource would be valuable to dissect the mechanisms underlying the complexity of the trait. Here, we used a recombinant inbred line population to detect the QTL associated with agro-physiological traits under drought stress, in particular incorporating the SNPs and 147 phenotype data, analyzed the transcript expression of genes within QTL using differential gene expression meta-analysis and qRT-PCR technique. Composite interval mapping analysis allowed the detection of 154 QTLs distributed into 66 regions, which included a large QTL cluster called ‘hotspot QTL’ that strongly associated with drought tolerance on rice chromosome 8. We found several genes within the QTL-containing regions that were highly expressed based on the meta-analysis approach. In the future, the QTL reported here may be utilized for marker-assisted breeding and the candidate drought-responsive genes could be characterized for dissecting a comprehensive molecular mechanism of drought tolerance in rice.

Traditional and Conditional QTL Analysis of Kernel Size- and Shape-Related Traits in Wheat (Triticum aestivum L.)

Optimal kernel size and shape were critical in improving the wheat yield potential and processing quality. A traditional and conditional QTL analysis for kernel-related traits was performed using 152 recombinant inbred lines derived from a cross between Zhongkemai 138 (ZKM138) and Kechengmai 2, whose kernel size showed significant differences. A total of 48 traditional QTLs (LOD: 3.69–14.20) were identified, with twenty-six QTLs distributed across five genomic regions. Each had at least one major stable QTL for kernel-related traits. We deduced from the co-location and conditional QTL analysis results that R3D and R4B.1 primarily controlled kernel shape, while R4D, R6A, and R6D2 primarily contributed to kernel size and the final thousand-kernel weight, potentially providing the genetic basis for the ZKM138’s high TKW and large-kernel performance. R4D may be involved with Rht2, and the possible regulatory effects of the other four QTL clusters are more likely to be influenced by unknown genes. The KASP markers validated their effect on kernel-related traits, and they were used to analyze the transmissibility and distribution of superior genotypes in ZKM138 derivatives and global wheat cultivars, respectively. These findings may serve as a reference for future genetic improvement of the ideal kernel morphology.

Identification of QTLs and joint QTL segments of leaflet traits at different canopy layers in an interspecific RIL population of soybean.

A leaflet trait on different canopy layers may have different QTLs; leaflet trait QTLs may cluster to form joint QTL segments; all canopy layer QTLs form a complete QTL system for a leaflet trait. As the main part of the plant canopy structure, leaf/leaflet size and shape affect the plant architecture and yield. To explore the leaflet trait QTL system, a population composed of 199 recombinant inbred lines derived from Changling (annual wild, narrow leaflet) and Yiqianli (landrace, broad leaflet) with their parents was tested for leaflet length (LL), width (LW) and length to width (LLW). The population was genotyped with specific-locus amplified fragment sequencing (SLAF-seq) and applied for linkage mapping of the leaflet traits. The results showed that the leaflet traits varied greatly even within a plant, which supported a stratified leaflet sampling strategy to evaluate these traits at top, middle and bottom canopy layers. Altogether, 13 LL, 10 LW and 9 LLW in a total of 32 plus 3 duplicated QTLs were identified, in which, 17 QTLs were new ones, and 48.6%, 28.6% and 22.8% of QTLs were from the top, middle and bottom layers, respectively, indicating the genetic importance of the top layer leaves. Since a leaflet trait may have layer-specific QTLs, all layer QTLs form a complete QTL system. Five QTL clusters each with their QTL supporting intervals overlapped were designated as joint QTL segments (JQSs). In JQS-16, with its linkage map further validated using PCR markers, two QTLs, qLW-16-1 and qLLW-16-1 of the top layer leaflet, were identified six QTL·times. Six candidate genes were predicted, with Glyma.16G127900 as the most potential one for LW and LLW. Three PCR markers, Gm16PAV0653, BARCSOYSSR_16_0796 and YC-16-3, were suggested for marker-assisted selection for LW and LLW in JQS-16.

Integration of QTL Mapping and Whole Genome Sequencing Identifies Candidate Genes for Alkalinity Tolerance in Rice (Oryza sativa).

Soil alkalinity is an important stressor that impairs crop growth and development, resulting in reduced crop productivity. Unlike salinity stress, research efforts to understand the mechanism of plant adaptation to alkaline stress is limited in rice, a major staple food for the world population. We evaluated a population of 193 recombinant inbred lines (RIL) developed from a cross between Cocodrie and N22 under alkaline stress at the seedling stage. Using a linkage map consisting of 4849 SNP markers, 42 additive QTLs were identified. There were seven genomic regions where two or more QTLs for multiple traits colocalized. Three important QTL clusters were targeted, and several candidate genes were identified based on high impact variants using whole genome sequences (WGS) of both parents and differential expression in response to alkalinity stress. These genes included two expressed protein genes, the glucan endo-1,3-beta-glucosidase precursor, F-box domain-containing proteins, double-stranded RNA-binding motif-containing protein, aquaporin protein, receptor kinase-like protein, semialdehyde hydrogenase, and NAD-binding domain-containing protein genes. Tolerance to alkaline stress in Cocodrie was most likely due to the low Na+/K+ ratio resulting from reduced accumulation of Na+ ions and higher accumulation of K+ in roots and shoots. Our study demonstrated the utility of integrating QTL mapping with WGS to identify the candidate genes in the QTL regions. The QTLs and candidate genes originating from the tolerant parent Cocodrie should be targeted for introgression to improve alkalinity tolerance in rice and to elucidate the molecular basis of alkali tolerance.

Wheat glutamine synthetase TaGSr-4B is a candidate gene for a QTL of thousand grain weight on chromosome 4B

Key messageGlutamine synthetase TaGSr-4B is a candidate gene for a QTL of thousand grain weight on 4B, and the gene marker is ready for wheat breeding.A QTL for thousand grain weight (TGW) in wheat was previously mapped on chromosome 4B in a DH population of Westonia × Kauz. For identifying the candidate genes of the QTL, wheat 90 K SNP array was used to saturate the existing linkage map, and four field trials plus one glasshouse experiment over five locations were conducted to refine the QTL. Three nitrogen levels were applied to two of those field trials, resulting in a TGW phenotype data set from nine environments. A robust TGW QTL cluster including 773 genes was detected in six environments with the highest LOD value of 13.4. Based on differentiate gene expression within the QTL cluster in an RNAseq data of Westonia and Kauz during grain filling, a glutamine synthesis gene (GS: TaGSr-4B) was selected as a potential candidate gene for the QTL. A SNP on the promoter region between Westonia and Kauz was used to develop a cleaved amplified polymorphic marker for TaGSr-4B gene mapping and QTL reanalysing. As results, TGW QTL appeared in seven environments, and in four out of seven environments, the TGW QTL were localized on the TaGSr-4B locus and showed significant contributions to the phenotype. Based on the marker, two allele groups of Westonia and Kauz formed showed significant differences on TGW in eight environments. In agreement with the roles of GS genes on nitrogen and carbon remobilizations, TaGSr-4B is likely the candidate gene of the TGW QTL on 4B and the TaGSr-4B gene marker is ready for wheat breeding.

Dissection of two QTL clusters underlying yield-related heterosis in the cabbage founder parent 01–20

Cabbage has significant heterosis and most commercial cultivars are hybrids. To explore genetic basis of cabbage heterosis and promote cabbage heterosis utilization, we constructed two populations by crossing 100 DH lines derived from a cabbage hybrid 01–20 × 96–100 with two female parents. Hybrids exhibited different extents of heterosis, the mean value of economic yield was 2.6 times bigger than parents. We identified 66 and 73 QTLs associated with mid-parent heterosis and transgressive heterosis of twelve yield-related traits, respectively. Some QTLs could be detected under the two-year experiment existed in two populations with different testers, showing relatively high phenotypic contribution rate (15.8%–20.0%). Heterosis QTLs exhibited clustered distribution in several cabbage chromosome regions. Two dominant genetic regions, mk300–316 and mk258–268, originated from the elite parent 01–20, exhibited significant genetic effects for yield-related heterosis, which were first identified. Three elite DH lines (D22, D46, D83) harboring these two dominant regions were selected as having strong heterosis in cabbage production. Candidate gene analysis revealed that some genes participating in biosynthetic processes of carbohydrates and some responses to auxin might affect cabbage yield heterosis. QTL identification and genetic dissection of yield-related traits provide new insights into the genetic effects of cabbage heterosis.

Genome-wide identification of quantitative trait loci for morpho-agronomic and yield-related traits in foxtail millet (Setaria italica) across multi-environments

Foxtail millet (Setaria italica) is an ideal model of genetic system for functional genomics of the Panicoideae crop. Identification of QTL responsible for morpho-agronomic and yield-related traits facilitates dissection of genetic control and breeding in cereal crops. Here, based on a Yugu1 × Longgu7 RIL population and genome-wide resequencing data, an updated linkage map harboring 2297 bin and 74 SSR markers was constructed, spanning 1315.1 cM with an average distance of 0.56 cM between adjacent markers. A total of 221 QTL for 17 morpho-agronomic and yield-related traits explaining 5.5 ~ 36% of phenotypic variation were identified across multi-environments. Of these, 109 QTL were detected in two to nine environments, including the most stable qLMS6.1 harboring a promising candidate gene Seita.6G250500, of which 70 were repeatedly identified in different trials in the same geographic location, suggesting that foxtail millet has more identical genetic modules under the similar ecological environment. One hundred-thirty QTL with overlapping intervals formed 22 QTL clusters. Furthermore, six superior recombinant inbred lines, RIL35, RIL48, RIL77, RIL80, RIL115 and RIL125 with transgressive inheritance and enrichment of favorable alleles in plant height, tiller, panicle morphology and yield related-traits were screened by hierarchical cluster. These identified QTL, QTL clusters and superior lines lay ground for further gene-trait association studies and breeding practice in foxtail millet.

Mapping combined with principal component analysis identifies excellent lines with increased rice quality

Quality-related traits are some of the most important traits in rice, and screening and breeding rice lines with excellent quality are common ways for breeders to improve the quality of rice. In this study, we used 151 recombinant inbred lines (RILs) obtained by crossing the northern cultivated japonica rice variety ShenNong265 (SN265) with the southern indica rice variety LuHui99 (LH99) and simplified 18 common rice quality-related traits into 8 independent principal components (PCs) by principal component analysis (PCA). These PCs included peak and hot paste viscosity, chalky grain percentage and chalkiness degree, brown and milled rice recovery, width length rate, cooked taste score, head rice recovery, milled rice width, and cooked comprehensive score factors. Based on the weight ratio of each PC score, the RILs were classified into five types from excellent to poor, and five excellent lines were identified. Compared with SN265, these 5 lines showed better performance regarding the chalky grain percentage and chalkiness degree factor. Moreover, we performed QTL localization on the RIL population and identified 94 QTLs for quality-related traits that formed 6 QTL clusters. In future research, by combining these QTL mapping results, we will be using backcrossing to aggregate excellent traits and achieve quality improvement of SN265.

QTL Mapping Low-Temperature Germination Ability in the Maize IBM Syn10 DH Population.

Chilling injury poses a serious threat to seed emergence of spring-sowing maize in China, which has become one of the main climatic limiting factors affecting maize production in China. It is of great significance to mine the key genes controlling low-temperature tolerance during seed germination and study their functions for breeding new maize varieties with strong low-temperature tolerance during germination. In this study, 176 lines of the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, which comprised 6618 bin markers, were used for QTL analysis of low-temperature germination ability. The results showed significant differences in germination related traits under optimum-temperature condition (25 °C) and low-temperature condition (10 °C) between two parental lines. In total, 13 QTLs were detected on all chromosomes, except for chromosome 5, 7, 10. Among them, seven QTLs formed five QTL clusters on chromosomes 1, 2, 3, 4, and 9 under the low-temperature condition, which suggested that there may be some genes regulating multiple germination traits at the same time. A total of 39 candidate genes were extracted from five QTL clusters based on the maize GDB under the low-temperature condition. To further screen candidate genes controlling low-temperature germination, RNA-Seq, in which RNA was extracted from the germination seeds of B73 and Mo17 at 10 °C, was conducted, and three B73 upregulated genes and five Mo17 upregulated genes were found by combined analysis of RNA-Seq and QTL located genes. Additionally, the variations of Zm00001d027976 (GLABRA2), Zm00001d007311 (bHLH transcription factor), and Zm00001d053703 (bZIP transcription factor) were found by comparison of amino sequence between B73 and Mo17. This study will provide a theoretical basis for marker-assisted breeding and lay a foundation for further revealing molecular mechanism of low-temperature germination tolerance in maize.