Candidate Quantitative Trait Loci Research Articles

Fine mapping and causal gene identification of a novel QTL for early flowering by QTL-seq, Target-seq and RNA-seq in spring oilseed rape

A novel quantitative trait locus for early flowering in spring oilseed rape, BnaC08cqDTF, was mapped to an 86-kb region on chromosome C08, and its causal gene, CRY2, was uncovered. Days to flowering is a very important agronomic and adaptive trait of Brassica napus oilseed rape (AACC, 2n = 38). We previously identified BnaC08cqDTF as a novel candidate quantitative trait locus (QTL) for early flowering in spring oilseed rape. Here, we present fine mapping of the locus and a study of its causal gene. Initial mapping was performed by QTL sequencing of DNA pools of BC3F2 plants with extreme flowering times derived from crosses between the spring-type cv. No. 4512 (early flowering) and cv. No. 5246 (late flowering), along with fine mapping by target sequencing of the BC3F2 and BC4F2populations.Fine mapping narrowed down BnaC08cqDTF to an 86-kb region on chromosome C08. The region harbored fifteen genes. After comparative analyses of the DNA sequences for mutation between A and C syntenic regions and detected by RNA-seq and qRT-PCR between the two parents, we found that BnaC08G0010400ZS harbors an A/G nonsynonymous mutation in exon 3. This single nucleotide polymorphism (SNP) haplotypewas alsocorrelated with early flowering ina 256 accession panel. BnaC08G0010400ZS is a homolog of the AT1G04400 gene (CRY2) in Arabidopsis. The analyses of transgenic Arabidopsis verified that BnaC08G0010400ZS is responsible for early flowering. Our results contribute to a better understanding of the genetic control mechanism of early flowering in spring Brassica napus and will promote the breeding for early mature varieties.

Chromosome groups 5, 6 and 7 harbor major quantitative trait loci controlling root traits in bread wheat (Triticum aestivum L.).

Identifying genomic regions for root traits in bread wheat can help breeders develop climate-resilient and high-yielding wheat varieties with desirable root traits. This study used the recombinant inbred line (RIL) population of Synthetic W7984 × Opata M85 to identify quantitative trait loci (QTL) for different root traits such as rooting depth (RD), root dry mass (RM), total root length (RL), root diameter (Rdia) and root surface areas (RSA1 for coarse roots and RSA2 for fine roots) under controlled conditions in a semi-hydroponic system. We detected 14 QTL for eight root traits on nine wheat chromosomes; we discovered three QTL each for RD and RSA1, two QTL each for RM and RSA2, and one QTL each for RL, Rdia, specific root length and nodal root number per plant. The detected QTL were concentrated on chromosome groups 5, 6 and 7. The QTL for shallow RD (Q.rd.uwa.7BL: Xbarc50) and high RM (Q.rm.uwa.6AS: Xgwm334) were validated in two independent F2 populations of Synthetic W7984 × Chara and Opata M85 × Cascade, respectively. Genotypes containing negative alleles for Q.rd.uwa.7BL had 52% shallower RD than other Synthetic W7984 × Chara population lines. Genotypes with the positive alleles for Q.rm.uwa.6AS had 31.58% higher RM than other Opata M85 × Cascade population lines. Further, we identified 21 putative candidate genes for RD (Q.rd.uwa.7BL) and 13 for RM (Q.rm.uwa.6AS); TraesCS6A01G020400, TraesCS6A01G024400 and TraesCS6A01G021000 identified from Q.rm.uwa.6AS, and TraesCS7B01G404000, TraesCS7B01G254900 and TraesCS7B01G446200 identified from Q.rd.uwa.7BL encoded important proteins for root traits. We found germin-like protein encoding genes in both Q.rd.uwa.7BL and Q.rm.uwa.6AS regions. These genes may play an important role in RM and RD improvement. The identified QTL, especially the validated QTL and putative candidate genes are valuable genetic resources for future root trait improvement in wheat.

Single-step genome-wide association analyses of claw horn lesions in Holstein cattle using linear and threshold models

BackgroundLameness in dairy cattle is primarily caused by foot lesions including the claw horn lesions (CHL) of sole haemorrhage (SH), sole ulcers (SU), and white line disease (WL). This study investigated the genetic architecture of the three CHL based on detailed animal phenotypes of CHL susceptibility and severity. Estimation of genetic parameters and breeding values, single-step genome-wide association analyses, and functional enrichment analyses were performed.ResultsThe studied traits were under genetic control with a low to moderate heritability. Heritability estimates of SH and SU susceptibility on the liability scale were 0.29 and 0.35, respectively. Heritability of SH and SU severity were 0.12 and 0.07, respectively. Heritability of WL was relatively lower, indicating stronger environmental influence on the presence and development of WL than the other two CHL. Genetic correlations between SH and SU were high (0.98 for lesion susceptibility and 0.59 for lesion severity), whereas genetic correlations of SH and SU with WL also tended to be positive. Candidate quantitative trait loci (QTL) were identified for all CHL, including some on Bos taurus chromosome (BTA) 3 and 18 with potential pleiotropic effects associated with multiple foot lesion traits. A genomic window of 0.65 Mb on BTA3 explained 0.41, 0.50, 0.38, and 0.49% of the genetic variance for SH susceptibility, SH severity, WL susceptibility, and WL severity, respectively. Another window on BTA18 explained 0.66, 0.41, and 0.70% of the genetic variance for SH susceptibility, SU susceptibility, and SU severity, respectively. The candidate genomic regions associated with CHL harbour annotated genes that are linked to immune system function and inflammation responses, lipid metabolism, calcium ion activities, and neuronal excitability.ConclusionsThe studied CHL are complex traits with a polygenic mode of inheritance. Most traits exhibited genetic variation suggesting that animal resistance to CHL can be improved with breeding. The CHL traits were positively correlated, which will facilitate genetic improvement for resistance to CHL as a whole. Candidate genomic regions associated with lesion susceptibility and severity of SH, SU, and WL provide insights into a global profile of the genetic background underlying CHL and inform genetic improvement programmes aiming at enhancing foot health in dairy cattle.

A brain-wide genome-wide association study of candidate quantitative trait loci associated with structural and functional phenotypes of pain sensitivity.

Individual pain sensitivity is modulated by the brain's structural and functional features, but its heritability remains unclear. This paper conducted a brain-wide genome-wide association study (GWAS) to explore the genetic bases of neuroimage phenotypes of pain sensitivity. In total, 432 normal participants were divided into high and low pain sensitivity groups according to the laser quantitative test threshold. Then, the brain's gray matter density (GMD) features correlated with pain sensitivity were identified. Next, GWAS was performed on each GMD phenotype using quality-controlled genotypes. Based on the heatmap and hierarchical clustering results, the right insula was identified for further refined analysis in terms of subregions GMD and resting-state functional connectivity (rs-FC) phenotypes. The results indicate that the right insula GMD in the high sensitivity group is significantly lower than that in the low sensitivity group. Also, the TT/TC group at locus rs187974 has lower right insula GMD than the CC group. Further, loci at gene CYP2D6 may lead to a variation of rs-FC between the right insula and left putamen. In conclusion, our study suggests that the right insula and multiple candidate loci may be importantly involved in pain sensitivity modulation, which may guide the future development of precision pain therapeutics.

SLAF marker based QTL mapping of fruit-related traits reveals a major-effect candidate locus ff2.1 for flesh firmness in melon

Flesh firmness (FF) is an important and complex trait for melon breeders and consumers. However, the genetic mechanism underlying FF is unclear. Here, a soft fruit melon (P5) and a hard fruit melon (P10) were crossed to generate F2, and the FF and fruit-related traits were recorded for two years. By performing quantitative trait locus (QTL) specific-locus amplified fragment (SLAF) (QTL-SLAF) sequencing and molecular marker-linkage analysis, 112 844 SLAF markers were identified, and 5 919 SNPs were used to construct a genetic linkage map with a total genetic distance of 1 356.49 cM. Ten FF- and fruit-related QTLs were identified. Consistent QTLs were detected for fruit length (FL) and fruit diameter (FD) in both years, and QTLs for single fruit weight (SFW) were detected on two separate chromosomes in both years. For FF, the consistent major locus (ff2.1) was located in a 0.17-Mb candidate region on chromosome 2. Using 429 F2 individuals derived from a cross between P5 and P10, we refined the ff2.1 locus to a 28.3-kb region harboring three functional genes. These results provide not only a new candidate QTL for melon FF breeding but also a theoretical foundation for research on the mechanism underlying melon gene function.

QTL mapping and candidate gene analysis for yield and grain weight/size in Tartary buckwheat

BackgroundGrain weight/size influences not only grain yield (GY) but also nutritional and appearance quality and consumer preference in Tartary buckwheat. The identification of quantitative trait loci (QTLs)/genes for grain weight/size is an important objective of Tartary buckwheat genetic research and breeding programs.ResultsHerein, we mapped the QTLs for GY, 1000-grain weight (TGW), grain length (GL), grain width (GW) and grain length–width ratio (L/W) in four environments using 221 recombinant inbred lines (XJ-RILs) derived from a cross of 'Xiaomiqiao × Jinqiaomai 2'. In total, 32 QTLs, including 7 for GY, 5 for TGW, 6 for GL, 11 for GW and 3 for L/W, were detected and distributed in 24 genomic regions. Two QTL clusters, qClu-1-3 and qClu-1-5, located on chromosome Ft1, were revealed to harbour 7 stable major QTLs for GY (qGY1.2), TGW (qTGW1.2), GL (qGL1.1 and qGL1.4), GW (qGW1.7 and qGW1.10) and L/W (qL/W1.2) repeatedly detected in three and above environments. A total of 59 homologues of 27 known plant grain weight/size genes were found within the physical intervals of qClu-1-3 and qClu-1-5. Six homologues, FtBRI1, FtAGB1, FtTGW6, FtMADS1, FtMKK4 and FtANT, were identified with both non-synonymous SNP/InDel variations and significantly differential expression levels between the two parents, which may play important roles in Tatary buckwheat grain weight/size control and were chosen as core candidate genes for further investigation.ConclusionsTwo stable major QTL clusters related to grain weight/size and six potential key candidate genes were identified by homology comparison, SNP/InDel variations and qRT‒qPCR analysis between the two parents. Our research provides valuable information for improving grain weight/size and yield in Tartary buckwheat breeding.

Mutant Tof11 alleles are highly accumulated in early planting-adaptable Japanese summer type soybeans.

To avoid crop failure because of climate change, soybean (Glycine max (L.) Merrill) cultivars adaptable to early planting are required in western Japan. Because current Japanese cultivars may not be adaptable, genetic resources with high early-planting adaptability, and their genetic information must be developed. In the present study, summer type (ST) soybeans developed for early planting were used as plant materials. We examined their phenological characteristics and short reproductive period as an indicator of early planting adaptability and performed genetic studies. Biparental quantitative trait loci (QTL) analysis of a representative ST cultivar revealed a principal QTL for the reproductive period duration on chromosome 11. The results of resequencing analysis suggested that circadian clock-related Tof11 (soybean orthologue of PRR3) is a candidate QTL. Additionally, all 25 early planting-adaptable germplasms evaluated in this study possessed mutant alleles in Tof11, whereas 15 conventional cultivars only had wild-type alleles. These results suggest that mutant alleles in Tof11 are important genetic factors in the high adaptability to early planting of these soybeans, and thus, these alleles were acquired and accumulated in the ST soybean population.

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

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

Genome-wide association study reveals novel QTLs and candidate genes for seed vigor in rice.

Highly seed vigor (SV) is essential for rice direct seeding (DS). Understanding the genetic mechanism of SV-related traits could contribute to increasing the efficiency of DS. However, only a few genes responsible for SV have been determined in rice, and the regulatory network of SV remains obscure. In this study, the seed germination rate (GR), seedling shoot length (SL), and shoot fresh weight (FW) related to SV traits were measured, and a genome-wide association study (GWAS) was conducted to detect high-quality loci responsible for SV using a panel of 346 diverse accessions. A total of 51 significant SNPs were identified and arranged into six quantitative trait locus (QTL) regions, including one (qGR1-1), two (qSL1-1, qSL1-2), and three (qFW1-1, qFW4-1, and qFW7-1) QTLs associated with GR, SL, and FW respectively, which were further validated using chromosome segment substitution lines (CSSLs). Integrating gene expression, gene annotation, and haplotype analysis, we found 21 strong candidate genes significantly associated with SV. In addition, the SV-related functions of LOC_Os01g11270 and LOC_Os01g55240 were further verified by corresponding CRISPR/Cas9 gene-edited mutants. Thus, these results provide clues for elucidating the genetic basis of SV control. The candidate genes or QTLs would be helpful for improving DS by molecular marker-assisted selection (MAS) breeding in rice.

Integrated genetic analysis of leaf blast resistance in upland rice: QTL mapping, bulked segregant analysis and transcriptome sequencing.

Elite upland rice cultivars have the advantages of less water requirement along with high yield but are usually susceptible to various diseases. Rice blast caused by Magnaporthe oryzae is the most devastating disease in rice. Identification of new sources of resistance and the introgression of major resistance genes into elite cultivars are required for sustainable rice production. In this study, an upland rice genotype UR0803 was considered an emerging source of blast resistance. An F2 mapping population was developed from a cross between UR0803 and a local susceptible cultivar Lijiang Xintuan Heigu. The individuals from the F2 population were evaluated for leaf blast resistance in three trials 7 days after inoculation. Bulked segregant analysis (BSA) by high-throughput sequencing and SNP-index algorithm was performed to map the candidate region related to disease resistance trait. A major quantitative trait locus (QTL) for leaf blast resistance was identified on chromosome 11 in an interval of 1.61-Mb genomic region. The candidate region was further shortened to a 108.9-kb genomic region by genotyping the 955 individuals with 14 SNP markers. Transcriptome analysis was further performed between the resistant and susceptible parents, yielding a total of 5044 differentially expressed genes (DEGs). There were four DEGs in the candidate QTL region, of which, two (Os11g0700900 and Os11g0704000) were upregulated and the remaining (Os11g0702400 and Os11g0703600) were downregulated in the susceptible parent after inoculation. These novel candidate genes were functionally annotated to catalytic response against disease stimulus in cellular membranes. The results were further validated by a quantitative real-time PCR analysis. The fine-mapping of a novel QTL for blast resistance by integrative BSA mapping and transcriptome sequencing enhanced the genetic understanding of the mechanism of blast resistance in upland rice. The most suitable genotypes with resistance alleles would be useful genetic resources in rice blast resistance breeding.

DeepBSA: A deep-learning algorithm improves bulked segregant analysis for dissecting complex traits

Bulked segregant analysis (BSA) is a rapid, cost-effective method for mapping mutations and quantitative trait loci (QTLs) in animals and plants based on high-throughput sequencing. However, the algorithms currently used for BSA have not been systematically evaluated and are complex and fallible to operate. We developed a BSA method driven by deep learning, DeepBSA, for QTL mapping and functional gene cloning. DeepBSA is compatible with a variable number of bulked pools and performed well with various simulated and real datasets in both animals and plants. DeepBSA outperformed all other algorithms when comparing absolute bias and signal-to-noise ratio. Moreover, we applied DeepBSA to an F2 segregating maize population of 7160 individuals and uncovered five candidate QTLs, including three well-known plant-height genes. Finally, we developed a user-friendly graphical user interface for DeepBSA, by integrating five widely used BSA algorithms and our two newly developed algorithms, that is easy to operate and can quickly map QTLs and functional genes. The DeepBSA software is freely available to non-commercial users at http://zeasystemsbio.hzau.edu.cn/tools.html and https://github.com/lizhao007/DeepBSA.

Fine mapping of candidate quantitative trait loci for plant and ear height in a maize nested-association mapping population.

Plant height (PH) and ear height (EH) are two important traits in maize (Zea mays L.), as they are closely related to lodging resistance and planting density. Our objectives were to (1) investigate single-nucleotide polymorphisms (SNPs) that are associated with PH and EH for detecting quantitative trait loci (QTL) and new gene that determines PH and EH, (2) explore the value of the QTL in maize breeding, and (3) investigate whether the “triangle heterotic group” theory is applicable for lowering PH and EH to increase yield. Seven inbred female parents were crossed with a common founder male parent Ye 107 to create a nested association mapping (NAM) population. The analysis of phenotypic data on PH and EH revealed wide variation among the parents of the NAM population. Genome-wide association study (GWAS) and high-resolution linkage mapping were conducted using the NAM population, which generated 264,694 SNPs by genotyping-by-sequencing. A total of 105 SNPs and 22 QTL were identified by GWAS and found to be significantly associated with PH and EH. A high-confidence QTL for PH, Qtl-chr1-EP, was identified on chromosome 1 via GWAS and confirmed by linkage analysis in two recombinant inbred line (RIL) populations. Results revealed that the SNP variation in the promoter region of the candidate gene Zm00001d031938, located at Qtl-chr1-EP, which encoded UDP-N-acetylglucosamine-peptide N-acetyl-glucosaminyl-transferase, might decrease PH and EH. Furthermore, the triangle heterotic pattern adopted in maize breeding programs by our team is practicable in selecting high-yield crosses based on the low ratio of EH/PH (EP).

Genome-Wide Association Studies of Root-Related Traits in Brassica napus L. under Low-Potassium Conditions.

Roots are essential organs for a plant’s ability to absorb water and obtain mineral nutrients, hence they are critical to its development. Plants use root architectural alterations to improve their chances of absorbing nutrients when their supply is low. Nine root traits of a Brassica napus association panel were explored in hydroponic-system studies under low potassium (K) stress to unravel the genetic basis of root growth in rapeseed. The quantitative trait loci (QTL) and candidate genes for root development were discovered using a multilocus genome-wide association study (ML-GWAS). For the nine traits, a total of 453 significant associated single-nucleotide polymorphism (SNP) loci were discovered, which were then integrated into 206 QTL clusters. There were 45 pleiotropic clusters, and qRTA04-4 and qRTC04-7 were linked to TRL, TSA, and TRV at the same time, contributing 5.25–11.48% of the phenotypic variance explained (PVE) to the root traits. Additionally, 1360 annotated genes were discovered by examining genomic regions within 100 kb upstream and downstream of lead SNPs within the 45 loci. Thirty-five genes were identified as possibly regulating root-system development. As per protein–protein interaction analyses, homologs of three genes (BnaC08g29120D, BnaA07g10150D, and BnaC04g45700D) have been shown to influence root growth in earlier investigations. The QTL clusters and candidate genes identified in this work will help us better understand the genetics of root growth traits and could be employed in marker-assisted breeding for rapeseed adaptable to various conditions with low K levels.

QTL Mapping and Candidate Gene Analysis for Seed Germination Response to Low Temperature in Rice.

Low temperature is a serious threat to the seed emergence of rice, which has become one of the main limiting factors affecting rice production in the world. It is of great significance to find the candidate genes controlling low-temperature tolerance during seed germination and study their functions for breeding new rice cultivars with immense low-temperature tolerance during seed germination. In the current experiment, 120 lines of the Cheongcheong Nagdong Double Haploid (CNDH) population were used for quantitative trait locus (QTL) analysis of low-temperature germinability. The results showed a significant difference in germination under low different temperature (LDT) (15 °C, 20 °C) conditions. In total, four QTLs were detected on chromosome 3, 6, and 8. A total of 41 genes were identified from all the four QTLs, among them, 25 genes were selected by gene function annotation and further screened through quantitative real-time polymerase chain reaction (qRT-PCR). Based on gene function annotation and level of expression under low-temperature, our study suggested the OsGPq3 gene as a candidate gene controlling viviparous germination, ABA and GA signaling under low-temperature. This study will provide a theoretical basis for marker-assisted breeding and lay the basis for further mining molecular mechanisms of low-temperature germination tolerance in rice.

Genome analysis in Avena sativa reveals hidden breeding barriers and opportunities for oat improvement

Oat (Avena sativa L.) is an important and nutritious cereal crop, and there is a growing need to identify genes that contribute to improved oat varieties. Here we utilize a newly sequenced and annotated oat reference genome to locate and characterize quantitative trait loci (QTLs) affecting agronomic and grain-quality traits in five oat populations. We find strong and significant associations between the positions of candidate genes and QTL that affect heading date, as well as those that influence the concentrations of oil and β-glucan in the grain. We examine genome-wide recombination profiles to confirm the presence of a large, unbalanced translocation from chromosome 1 C to 1 A, and a possible inversion on chromosome 7D. Such chromosome rearrangements appear to be common in oat, where they cause pseudo-linkage and recombination suppression, affecting the segregation, localization, and deployment of QTLs in breeding programs.

Genomic evaluation and genome-wide association studies for total number of teats in a combined American and Danish Yorkshire pig populations selected in China.

Joint genomic evaluation by combining data recordings and genomic information from different pig herds and populations is of interest for pig breeding companies because the efficiency of genomic selection (GS) could be further improved. In this work, an efficient strategy of joint genomic evaluation combining data from multiple pig populations is investigated. Total teat number (TTN), a trait that is equally recorded on 13,060 American Yorkshire (AY) populations (~14.68 teats) and 10,060 Danish Yorkshire (DY) pigs (~14.29 teats), was used to explore the feasibility and accuracy of GS combining datasets from different populations. We first estimated the genetic correlation (rg) of TTN between AY and DY pig populations (rg = 0.79, se = 0.23). Then we employed the genome-wide association study to identify quantitative trait locus (QTL) regions that are significantly associated with TTN and investigate the genetic architecture of TTN in different populations. Our results suggested that the genomic regions controlling TTN are slightly different in the two Yorkshire populations, where the candidate QTL regions were on SSC 7 and SSC 8 for the AY population and on SSC 7 for the DY population. Finally, we explored an optimal way of genomic prediction for TTN via three different genomic best linear unbiased prediction models and we concluded that when TTN across populations are regarded as different, but correlated, traits in a multitrait model, predictive abilities for both Yorkshire populations improve. As a conclusion, joint genomic evaluation for target traits in multiple pig populations is feasible in practice and more accurate, provided a proper model is used.

QTL mapping and candidate gene analysis of low temperature germination in rice (Oryza sativa L.) using a genome wide association study.

Low temperature germination (LTG) is a key agronomic trait in rice (Oryza sativa L.). However, the genetic basis of natural variation for LTG is largely unknown. Here, a genome-wide association study (GWAS) was performed using 276 accessions from the 3,000 Rice Genomes (3K-RG) project with 497 k single nucleotide polymorphisms (SNPs) to uncover potential genes for LTG in rice. In total, 37 quantitative trait loci (QTLs) from the 6th day (D6) to the 10th day (D10) were detected in the full population, overlapping with 12 previously reported QTLs for LTG. One novel QTL, namely qLTG1-2, was found stably on D7 in both 2019 and 2020. Based on two germination-specific transcriptome datasets, 13 seed-expressed genes were isolated within a 200 kb interval of qLTG1-2. Combining with haplotype analysis, a functional uncharacterized gene, LOC_Os01g23580, and a seed germination-associated gene, LOC_Os01g23620 (OsSar1a), as promising candidate genes, both of which were significantly differentially expressed between high and low LTG accessions. Collectively, the candidate genes with favorable alleles may be useful for the future characterization of the LTG mechanism and the improvement of the LTG trait in rice breeding.

Identification of candidate genes involved in salt stress response at germination and seedling stages by QTL mapping in upland cotton.

Salinity is a major abiotic stress at critical stages of seed germination and seedling establishment. Germination rate (GR) and field emergence rate (FER) are the key traits that determine the basic number of plants stand under field conditions. To explore molecular mechanisms in upland cotton under salt stress, a population of 177 recombinant inbred lines, and their parents were evaluated for seed germination traits (GP, germination potential; GR; FW, fresh weight; DW, dry weight; GL, germinal length) and seedling traits (FER; SH, seedling height; NL, number of main stem leaves) in 2016–2018. Based on the linkage map contained 2,859 single nucleotide polymorphism and simple sequence repeat markers, traits under salt stress (E1) and normal conditions (E2), and in the converted relative index (R-value) dataset of 3 years’ trials were used to map quantitative trait loci (QTL). A total of 3 QTL and 2 clusters were detected as salt-tolerant QTL. Three QTL (qGR-Chr4-3, qFER-Chr12-3, and qFER-Chr15-1) were detected under salt stress conditions and R-value dataset, which explained variance of phenotype 9.62–13.67%, and 4.2–4.72%, 4.75–8.96%, respectively. Two clusters (Loci-Chr4-2 and Loci-Chr5-4) harboring the QTL for 4 germination traits (GR, FER, GL, and NL) and 6 seedling traits (GR, FER, DW, FW, SH, and NL) were detected related under salt stress. A total of 691 genes were found in the candidate QTL or clusters. Among them, 4 genes (Gh_A04G1106, Gh_A05G3246, Gh_A05G3177, and Gh_A05G3266) showed expression differences between salt-sensitive and -tolerant lines under salt stress conditions, and were assigned as candidate genes in response to salt stress. The consistent salt-tolerance QTL identified in both germination and seedling stages will facilitate novel insights into effective utilization of cotton genetic resources.

Identifying QTLs for Grain Size in a Colossal Grain Rice (Oryza sativa L.) Line, and Analysis of Additive Effects of QTLs.

Grain size is an important component of quality and harvest traits in the field of rice breeding. Although numerous quantitative trait loci (QTLs) of grain size in rice have been reported, the molecular mechanisms of these QTLs remain poorly understood, and further research on QTL observation and candidate gene identification is warranted. In our research, we developed a suite of F2 intercross populations from a cross of 9311 and CG. These primary populations were used to map QTLs conferring grain size, evaluated across three environments, and then subjected to bulked-segregant analysis-seq (BSA-seq). In total, 4, 11, 12 and 14 QTLs for grain length (GL), grain width (GW), 1000-grain weight (TGW), and length/width ratio (LWR), respectively, were detected on the basis of a single-environment analysis. In particular, over 200 splicing-related sites were identified by whole-genome sequencing, including one splicing-site mutation with G>A at the beginning of intron 4 on Os03g0841800 (qGL3.3), producing a smaller open reading frame, without the third and fourth exons. A previous study revealed that the loss-of-function allele caused by this splicing site can negatively regulate rice grain length. Furthermore, qTGW2.1 and qGW2.3 were new QTLs for grain width. We used the near-isogenic lines (NILs) of these GW QTLs to study their genetic effects on individuals and pyramiding, and found that they have additive effects on GW. In summary, these discoveries provide a valuable genetic resource, which will facilitate further study of the genetic polymorphism of new rice varieties in rice breeding.

Mapping of genetic loci controlling fruit linked morphological traits of melon using developed CAPS markers.

Fruit morphology traits are important commercial traits that directly affect the market value. However, studying the genetic basis of these traits in un-explored botanical groups is a fundamental objective for crop genetic improvement through marker-assisted breeding. In this study, a quantitative trait loci (QTLs) mapping strategy was used for dissecting the genomic regions of fruit linked morphological traits by single nucleotide polymorphism (SNP) based cleaved amplified polymorphism sequence (CAPS) molecular markers. Next-generation sequencing was done for the genomic sequencing of two contrasted melon lines (climacteric and non-climacteric), which revealed 97% and 96% of average coverage over the reference melon genome database, respectively. A total of 57.51% non-synonymous SNPs and 42.49% synonymous SNPs were found, which produced 149 sets of codominant markers with a 24% polymorphism rate. Total 138-F2 derived plant populations were genotyped for linkage mapping and composite interval mapping based QTL mapping exposed 6 genetic loci, positioned over distinct chromosomes (02, 04, 08, 09, and 12) between the flanking intervals of CAPS markers, whichexplained an unlinked polygenic architecture in genome. Three minor QTLs of fruit weight(FWt2.1, FWt4.1, FWt9.1), one major QTL of fruit firmness(FrFir8.1), one major QTL of fruit length(FL12.1), and one major QTL of fruit shape (FS12.1)were determined and collectively explained the phenotypic variance from 5.64 to 15.64%. Fruit phenotypic correlation exhibited the significant relationship and principal component analysis also identified the potential variability. Multiple sequence alignments also indicated the significant base-mutations in the detected genetic loci, respectively. In short, our illustrated genetic loci are expected to provide the reference insights for fine QTL mapping and candidate gene(s) mining through molecular genetic breeding approaches aimed at developing the new varieties.