QTL For Traits Research Articles

Parallel evolution of integrated craniofacial traits in trophic specialist pupfishes.

Populations may adapt to similar environments via parallel or non-parallel genetic changes, but the frequency of these alternative mechanisms and underlying contributing factors are still poorly understood outside model systems. We used QTL mapping to investigate the genetic basis of highly divergent craniofacial traits between the scale-eater (Cyprinodon desquamator) and molluscivore (C. brontotheroides) pupfish adapting to two different hypersaline lake environments on San Salvador Island, Bahamas. We lab-reared F2 scale-eater x molluscivore intercrosses from two different lake populations, estimated linkage maps, scanned for significant QTL for 29 skeletal and craniofacial traits, female mate preference, and sex. We compared the location of QTL between lakes to quantify parallel and non-parallel genetic changes. We detected significant QTL for six craniofacial traits in at least one lake. However, nearly all shared QTL loci were associated with a different craniofacial trait within each lake. Therefore, our estimate of parallel evolution of craniofacial genetic architecture could range from one out of six identical trait QTL (low parallelism) to five out of six integrated trait QTL (high parallelism). We suggest that pleiotropy and trait integration can affect estimates of parallel evolution, particularly within rapid radiations. We also observed increased adaptive introgression in shared QTL regions, suggesting that gene flow contributed to parallel evolution. Overall, our results suggest that the same genomic regions may contribute to parallel adaptation across integrated suites of craniofacial traits, rather than specific traits, and highlight the need for a more expansive definition of parallel evolution.

Construction of a high-density linkage map and QTL detection for growth traits in South African abalone (Haliotis midae).

Haliotis midae is one of the most important molluscs in South African commercial aquaculture. In this study, a high-resolution integrated linkage map was constructed, and QTL identified using 2b-RADseq for genotyping SNPs in three families. The final integrated linkage map was composed by merging the individual family maps, resulting in 3290 informative SNPs mapping to 18 linkage groups, conforming to the known haploid chromosome number for H. midae. The total map spanned 1798.25 cM with an average marker interval of 0.55 cM, representing a genome coverage of 98.76%. QTL analysis, across all three families, resulted in a total of five QTL identified for growth-related traits, shell width, shell length, and total body weight. For shell width and total body weight, one QTL was identified for each trait respectively, whilst three QTL were identified for shell length. The identified QTL respectively explained between 7.20% and 11.40% of the observed phenotypic variance. All three traits were significantly correlated (r = 0.862-0.970; p < 0.01) and shared overlapping QTL. The QTL for growth traits were mapped back to the H. midae draft genome and BLAST searches revealed the identity of candidate genes, such as egf-1, megf10, megf6, tnx, sevp1, kcp, notch1, and scube2 with possible functional roles in H. midae growth. The constructed high-density linkage map and mapped QTL have given valuable insights regarding the genetic architecture of growth-related traits and will be important genetic resources for marker-assisted selection. It remains, however, important to validate causal variants through linkage disequilibrium fine mapping in future.

Detection of CRISPR/Cas9-Mediated Fetal Hemoglobin Reactivation in Erythroblasts Derived from Cord Blood-Hematopoietic Stem Cells.

Reactivation of the fetal hemoglobin (HbF) in adult erythroid cells via genome editing is a strategy for the treatment of β-thalassemia and sickle cell disease. In related reports, the reactivation of HbF is regularly examined in erythroblasts which are generated from the adult CD34+ hematopoietic stem and progenitor cells (HSPCs). However, the procurement of adult HSPCs, either from the bone-marrow (BM) or from mobilized peripheral-blood (mPB), is difficult. Cord-blood (CB) is a readily available source of HSPCs. CB-HSPCs, however, produce high quantities of HbF following differentiation into the erythroid lineage-a potential drawback in such studies. Here, we have edited the BCL11A enhancer (a well-characterized HbF-quantitative trait loci or QTL) via CRISPR/Cas9 in order to determine whether HbF reactivation could be detected in CB-HSPC-derived erythroblasts. In the edited erythroblasts, insertion/deletion (indel) frequencies of 74.0-80.4% and BCL11A RNA reduction levels of 92.6 ± 5.1% (P < 0.0001) were obtained. In turn, the γ/β-globin transcript ratios were increased from 11.3 ± 1.1-fold to 77.1 ± 2.0-fold, i.e., by 6.8-fold (P < 0.0001)-and the HbF% levels increased from 34.3% in the control population to 43.5% in the BCL11A edited erythroblasts. Our results suggest that γ-globin/HbF reactivation via genome editing can be detected in CB-HSPCs generated erythroblasts-rendering CB-HSPCs a useful model for similar studies.

Identification of Novel QTL for Seedling Root Architectural Traits in the D Genome of Natural and Resynthetic Allohexaploid Wheat

Root architectural traits at the seedling stage have been demonstrated to be crucial for the efficient uptake of nutrients and drought tolerance in wheat. To dissect the genetic basis of these traits from the D genome, 182 recombinant inbred lines (RILs) derived from the common wheat TAA10 crossed with resynthesized allohexaploid wheat XX329 possessed similar AABB genomes were used for QTL mapping of five root traits in hydroponic-cultured seedlings, including lateral root number (LRN), seminal root number (SRN), root hair length (RHL), root diameter (RD), and total root volume (TRV). A total of seven QTLs were identified for the five root traits, with six possible novel QTLs for LRN, RHL, RD and TRV, accounting for 4.98–12.17% of phenotypic variation. One QTL (QLrn.qau-5D.2), controlling lateral root number, was fine mapped an approximate 5.0-Mb interval harboring 80 annotated genes, including five auxin-related genes. We further validated that QLrn.qau-5D.2 in NILTAA10 significantly enhanced yield-related traits, such as plant height, spike length, spike compactness, tiller number per plant and grain yield per plant, as comparison with NILXX329. Collectively, these results provide vital insights for fine-mapping QTLs associated with LRN, SRN, RHL, RD and TRV and facilitate the root morphologic designs for enhancing yield performance.

The effect of marker types and density on genomic prediction and GWAS of key performance traits in tetraploid potato.

Genomic prediction and genome-wide association studies are becoming widely employed in potato key performance trait QTL identifications and to support potato breeding using genomic selection. Elite cultivars are tetraploid and highly heterozygous but also share many common ancestors and generation-spanning inbreeding events, resulting from the clonal propagation of potatoes through seed potatoes. Consequentially, many SNP markers are not in a 1:1 relationship with a single allele variant but shared over several alleles that might exert varying effects on a given trait. The impact of such redundant "diluted" predictors on the statistical models underpinning genome-wide association studies (GWAS) and genomic prediction has scarcely been evaluated despite the potential impact on model accuracy and performance. We evaluated the impact of marker location, marker type, and marker density on the genomic prediction and GWAS of five key performance traits in tetraploid potato (chipping quality, dry matter content, length/width ratio, senescence, and yield). A 762-offspring panel of a diallel cross of 18 elite cultivars was genotyped by sequencing, and markers were annotated according to a reference genome. Genomic prediction models (GBLUP) were trained on four marker subsets [non-synonymous (29,553 SNPs), synonymous (31,229), non-coding (32,388), and a combination], and robustness to marker reduction was investigated. Single-marker regression GWAS was performed for each trait and marker subset. The best cross-validated prediction correlation coefficients of 0.54, 0.75, 0.49, 0.35, and 0.28 were obtained for chipping quality, dry matter content, length/width ratio, senescence, and yield, respectively. The trait prediction abilities were similar across all marker types, with only non-synonymous variants improving yield predictive ability by 16%. Marker reduction response did not depend on marker type but rather on trait. Traits with high predictive abilities, e.g., dry matter content, reached a plateau using fewer markers than traits with intermediate-low correlations, such as yield. The predictions were unbiased across all traits, marker types, and all marker densities >100 SNPs. Our results suggest that using non-synonymous variants does not enhance the performance of genomic prediction of most traits. The major known QTLs were identified by GWAS and were reproducible across exonic and whole-genome variant sets for dry matter content, length/width ratio, and senescence. In contrast, minor QTL detection was marker type dependent.

A genomic toolkit for winged bean Psophocarpus tetragonolobus

A sustainable supply of plant protein is critical for future generations and needs to be achieved while reducing green house gas emissions from agriculture and increasing agricultural resilience in the face of climate volatility. Agricultural diversification with more nutrient-rich and stress tolerant crops could provide the solution. However, this is often hampered by the limited availability of genomic resources and the lack of understanding of the genetic structure of breeding germplasm and the inheritance of important traits. One such crop with potential is winged bean (Psophocarpus tetragonolobus), a high seed protein tropical legume which has been termed ‘the soybean for the tropics’. Here, we present a chromosome level winged bean genome assembly, an investigation of the genetic diversity of 130 worldwide accessions, together with two linked genetic maps and a trait QTL analysis (and expression studies) for regions of the genome with desirable ideotype traits for breeding, namely architecture, protein content and phytonutrients.

Genetic dissection of root architecture in Ethiopian sorghum landraces.

This study quantified genetic variation in root system architecture (root number, angle, length and dry mass) within a diversity panel of 1771 Ethiopian sorghum landraces and identified 22 genomic regions associated with the root variations. The root system architecture (RSA) of crop plants influences adaptation to water-limited conditions and determines the capacity of a plant to access soil water and nutrients. Four key root traits (number, angle, length and dry mass) were evaluated in a diversity panel of 1771 Ethiopian sorghum landraces using purpose-built root chambers. Significant genetic variation was observed in all studied root traits, with nodal root angle ranging from 16.4° to 26.6°, with a high repeatability of 78.9%. Genome wide association studies identified a total of 22 genomic regions associated with root traits which were distributed on all chromosomes except chromosome SBI-10. Among the 22 root genomic regions, 15 co-located with RSA trait QTL previously identified in sorghum, with the remaining seven representing novel RSA QTL. The majority (85.7%) of identified root angle QTL also co-localized with QTL previously identified for stay-green in sorghum. This suggests that the stay-green phenotype might be associated with root architecture that enhances water extraction during water stress conditions. The results open avenues for manipulating root phenotypes to improve productivity in abiotic stress environments via marker-assisted selection.

Introgression of Stay Green Quantitative Trait Locus (QTLS) into Elite Sorghum Variety by MABC

Sorghum is a major staple food crop for the people in semi-arid areas of Asia. Post-flowering drought is a global constraint of sorghum production. The study aimed to improve stay-green characteristics of GS-23 sorghum variety by transferring stg3A and stg3B QTL`s respectively from donor genotypes K260 and K359w of ICRISAT by using marker assisted backcrossing. The experimental material comprised of six basic generations P1, P2, F1, F2, BC1 and BC2 developed from crossing GS-23 × K260 and GS-23 × K359 were genotyped using a set of 133 SNPs and 79 SSR markers. Whereas, 53 polymorphic SNPs among parents and backcross F1s for stay green trait at maturity were used to track introgression of stay green trait. Similarly,10 SSR markers were found to be polymorphic were used to track introgression of stay green trait i.e., stay green trait QTL`s stg3A and stg3B from donor parent K260 and K359w respectively in GS-23 background across backcross population and to identify plants that were homozygous for the desired allele. In which 02 SNPs SnpSB0039 and SnpSB0093 were identified as polymorphic for both K260 and K359w. Whereas 17 SNPs identified polymorphic for K260 and 34 SNPs for K359w. These SNPs were validated in both F1 and BC1F1 populations of both the crosses. Similarly, out of 10 SSR markers utilized, 02 SSRs were identified polymorphic to K260 and 02 SSRs were identified for K359w. Whereas 06 SSRs were polymorphic to both the parents K260 and K359w. Prominent 02 SSRs viz., Xtxp 141_Fam and Xgap84_Vic found to be more reliable and polymorphic to both the parents. These SSRs were validated in both F1 and BC1F1 populations of both the crosses. The genotypic analysis revealed the presence of favorable alleles in homozygous conditions at markers loci associated with stg3A and stg3B QTL`s in BC populations, suggesting successful introgression of stay green QTLs from the donor parents to the recurrent parent. Therefore, our study demonstrated the utility of marker-assisted backcrossing for drought tolerance improvement of locally adapted sorghum variety.

Haplotype-Based Genome-Wide Association Analysis Using Exome Capture Assay and Digital Phenotyping Identifies Genetic Loci Underlying Salt Tolerance Mechanisms in Wheat.

Soil salinity can impose substantial stress on plant growth and cause significant yield losses. Crop varieties tolerant to salinity stress are needed to sustain yields in saline soils. This requires effective genotyping and phenotyping of germplasm pools to identify novel genes and QTL conferring salt tolerance that can be utilised in crop breeding schemes. We investigated a globally diverse collection of 580 wheat accessions for their growth response to salinity using automated digital phenotyping performed under controlled environmental conditions. The results show that digitally collected plant traits, including digital shoot growth rate and digital senescence rate, can be used as proxy traits for selecting salinity-tolerant accessions. A haplotype-based genome-wide association study was conducted using 58,502 linkage disequilibrium-based haplotype blocks derived from 883,300 genome-wide SNPs and identified 95 QTL for salinity tolerance component traits, of which 54 were novel and 41 overlapped with previously reported QTL. Gene ontology analysis identified a suite of candidate genes for salinity tolerance, some of which are already known to play a role in stress tolerance in other plant species. This study identified wheat accessions that utilise different tolerance mechanisms and which can be used in future studies to investigate the genetic and genic basis of salinity tolerance. Our results suggest salinity tolerance has not arisen from or been bred into accessions from specific regions or groups. Rather, they suggest salinity tolerance is widespread, with small-effect genetic variants contributing to different levels of tolerance in diverse, locally adapted germplasm.

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.

Genome-wide association study in a rat model of temperament identifies multiple loci for exploratory locomotion and anxiety-like traits.

Common genetic factors likely contribute to multiple psychiatric diseases including mood and substance use disorders. Certain stable, heritable traits reflecting temperament, termed externalizing or internalizing, play a large role in modulating vulnerability to these disorders. To model these heritable tendencies, we selectively bred rats for high and low exploration in a novel environment [bred High Responders (bHR) vs. Low Responders (bLR)]. To identify genes underlying the response to selection, we phenotyped and genotyped 538 rats from an F2 cross between bHR and bLR. Several behavioral traits show high heritability, including the selection trait: exploratory locomotion (EL) in a novel environment. There were significant phenotypic and genetic correlations between tests that capture facets of EL and anxiety. There were also correlations with Pavlovian conditioned approach (PavCA) behavior despite the lower heritability of that trait. Ten significant and conditionally independent loci for six behavioral traits were identified. Five of the six traits reflect different facets of EL that were captured by three behavioral tests. Distance traveled measures from the open field and the elevated plus maze map onto different loci, thus may represent different aspects of novelty-induced locomotor activity. The sixth behavioral trait, number of fecal boli, is the only anxiety-related trait mapping to a significant locus on chromosome 18 within which the Pik3c3 gene is located. There were no significant loci for PavCA. We identified a missense variant in the Plekhf1 gene on the chromosome 1:95Mb QTL and Fancf and Gas2 as potential candidate genes that may drive the chromosome 1:107Mb QTL for EL traits. The identification of a locomotor activity-related QTL on chromosome 7 encompassing the Pkhd1l1 and Trhr genes is consistent with our previous finding of these genes being differentially expressed in the hippocampus of bHR vs. bLR rats. The strong heritability coupled with identification of several loci associated with exploratory locomotion and emotionality provide compelling support for this selectively bred rat model in discovering relatively large effect causal variants tied to elements of internalizing and externalizing behaviors inherent to psychiatric and substance use disorders.

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.

QTL and genomic prediction accuracy for grain yield and secondary traits in a maize population under heat and heat-drought stresses

ABSTRACT Heat and drought stresses negatively affect maize (Zea mays L.) productivity. We aimed to identify the genetic basis of tolerance to heat stress (HS) and combined heat and drought stress (HS+DS) and compare how QTL and whole genome selection (GS) could be leveraged to improve tolerance to both stresses. A set of 97 testcross hybrids derived from a maize bi-parental doubled-haploid population was evaluated during the summer seasons of 2014, 2015, and 2016 in Ciudad Obregon, Sonora, Mexico, under HS and HS+DS. Grain yield (GY) reached 5.7 t ha−1 under HS and 3.0 t ha−1 under HS+DS. Twenty-six QTL were detected across six environments, with LOD scores ranging from 2.03 to 3.86; the QTL explained 8.6% to 18.6% of the observed phenotypic variation. Hyperspectral biomass and structural index (HBSI) had higher genetic correlation with GY for HS (r = 0.97) and HS+DS (r = 0.74), relative to the correlation with crop water mass or greenness indices. Genetic correlations between GY and canopy temperature for HS (r = −0.89) and HS+DS (r = −0.75) or vegetation indices, along with clusters of QTL in bins 1.02, 1.05, and 2.05, underline the importance of these genomic areas for secondary traits associated with general vigor and greenness. Prediction accuracy of the model used for GS had values below those found in previous studies. We found a high-yielding hybrid that was tolerant to HS and HS+DS.

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.

EEF1A1 transcription cofactor gene polymorphism is associated with muscle gene expression and residual feed intake in Nelore cattle.

Cis-acting effects of noncoding variants on gene expression and regulatory molecules constitute a significant factor for phenotypic variation in complex traits. To provide new insights into the impacts of single-nucleotide polymorphisms (SNPs) on transcription factors (TFs) and transcription cofactors (TcoF) coding genes, we carried out a multi-omic analysis to identify cis-regulatory effects of SNPs on these genes' expression in muscle and describe their association with feed efficiency-related traits in Nelore cattle. As a result, we identified one SNP, the rs137256008C &gt; T, predicted to impact the EEF1A1 gene expression (β = 3.02; P-value = 3.51E-03) and the residual feed intake trait (β = -3.47; P-value = 0.02). This SNP was predicted to modify transcription factor sites and overlaps with several QTL for feed efficiency traits. In addition, co-expression network analyses showed that animals containing the T allele of the rs137256008 SNP may be triggering changes in the gene network. Therefore, our analyses reinforce and contribute to a better understanding of the biological mechanisms underlying gene expression control of feed efficiency traits in bovines. The cis-regulatory SNP can be used as biomarker for feed efficiency in Nelore cattle.

Identification, pyramid, and candidate gene of QTL for yield-related traits based on rice CSSLs in indica Xihui18 background.

The online version contains supplementary material available at 10.1007/s11032-022-01284-x.

Multi-donor × elite-based populations reveal QTL for low-lodging wheat

Key messageLow-lodging high-yielding wheat germplasm and SNP-tagged novel alleles for lodging were identified in a process that involved selecting donors through functional phenotyping for underlying traits with a designed phenotypic screen, and a crossing strategy involving multiple-donor × elite populations.Lodging is a barrier to achieving high yield in wheat. As part of a study investigating the potential to breed low-lodging high-yielding wheat, populations were developed crossing four low-lodging high-yielding donors selected based on lodging related traits, with three cultivars. Lodging was evaluated in single rows in an early generation and subsequently in plots in 2 years with contrasting lodging environment. A large number of lines lodged less than their recurrent parents, and some were also higher yielding. Heritability for lodging was high, but the genetic correlation between contrasting environments was intermediate-low. Lodging genotypic rankings in single rows did not correlate well with plots. Populations from the highest lodging background were genotyped (90 K iSelect BeadChip array). Fourteen markers on nine chromosomes were associated with lodging, differing under high- versus low-lodging conditions. Of the fourteen markers, ten were found to co-locate with previously identified QTL for lodging-related traits or at homoeologous locations for previously identified lodging-related QTL, while the remaining four markers (in chromosomes 2D, 4D, 7B and 7D) appear to map to novel QTL for lodging. Lines with more favourable markers lodged less, suggesting value in these markers as a selection tool. This study demonstrates that the combination of donor functional phenotyping, screen design and crossing strategy can help identify novel alleles in germplasm without requiring extensive bi-parental populations.

Maize plant architecture trait QTL mapping and candidate gene identification based on multiple environments and double populations

BackgroundThe plant architecture traits of maize determine the yield. Plant height, ear position, leaf angle above the primary ear and internode length above the primary ear together determine the canopy structure and photosynthetic efficiency of maize and at the same time affect lodging and disease resistance. A flat and tall plant architecture confers an obvious advantage in the yield of a single plant but is not conducive to dense planting and results in high rates of lodging; thus, it has been gradually eliminated in production. Although using plants that are too compact, short and density tolerant can increase the yield per unit area to a certain extent, the photosynthetic efficiency of such plants is low, ultimately limiting yield increases. Genetic mapping is an effective method for the improvement of plant architecture to identify candidate genes for regulating plant architecture traits.ResultsTo find the best balance between the yield per plant and the yield per unit area of maize, in this study, the F2:3 pedigree population and a RIL population with the same male parent were used to identify QTL for plant height (PH), ear height (EH), leaf angle and internode length above the primary ear (LAE and ILE) in Changchun and Gongzhuling for 5 consecutive years (2016–2020). A total of 11, 13, 23 and 13 QTL were identified for PH, EH, LAE, and ILE, respectively. A pleiotropic consistent QTL for PH overlapped with that for EH on chromosome 3, with a phenotypic variation explanation rate from 6.809% to 21.96%. In addition, there were major consistent QTL for LAE and ILE, and the maximum phenotypic contribution rates were 24.226% and 30.748%, respectively. Three candidate genes were mined from the three consistent QTL regions and were involved in the gibberellin-activated signal pathway, brassinolide signal transduction pathway and auxin-activated signal pathway, respectively. Analysis of the expression levels of the three genes showed that they were actively expressed during the jointing stage of vigorous maize growth.ConclusionsIn this study, three consistent major QTL related to plant type traits were identified and three candidate genes were screened. These results lay a foundation for the cloning of related functional genes and marker-assisted breeding of related functional genes.

Genome resequencing-based high-density genetic map and QTL detection for yield and fiber quality traits in diploid Asiatic cotton (Gossypium arboreum)

Cotton is the most important fiber crop in the world. Asiatic cotton (Gossypium arboreum, genome A2) is a diploid cotton species producing spinnable fibers and important germplasm for cotton breeding and a significant model for fiber biology. However, the genetic map of Asiatic cotton has been lagging behind tetraploid cottons, as well as other stable crops. This study aimed to construct a high-density SNP genetic map and to map QTLs for important yield and fiber quality traits. Using a recombinant inbred line (RIL) population and genome resequencing technology, we constructed a high-density genetic map that covered 1980.17cM with an average distance of 0.61cM between adjacent markers. QTL analysis revealed a total of 297 QTLs for 13 yield and fiber quality traits in three environments, explaining 5.0-37.4% of the phenotypic variance, among which 75 were stably detected in two or three environments. Besides, 47 QTL clusters, comprising 131 QTLs for representative traits, were identified. Our works laid solid foundation for fine mapping and cloning of QTL for yield and fiber quality traits in Asiatic cotton.