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Two interrelated aspects of the sweetpotato genome, its polyploid origin and inheritance type, remain uncertain. We recently proposed a segmental allohexaploid sweetpotato and thus sought to clarify its inheritance type by direct analyses of homoeolog segregations at selected single-copy loci. For such analyses, we developed a digital quantitative PCR genotyping method using one nondiscriminatory and three discriminatory probes for each selected locus to discriminate and quantify three homoeolog-differentiating variation types (homoeolog-types) in genomic DNA samples for genotype fitting and constructed a F2 population for segregation analyses. We confirmed inter-subgenomic distinctions of three identified homoeolog-types at each of five selected loci by their interspecific differentiations among 14 species in Ipomoea section batatas and genotyped the loci in 549 F2 lines, selected F1 progenies, and their founding parents. Segregation and genotype analyses revealed a locus-dependent mixed inheritance (disomic, polysomic, and intermediate types) of the homoeolog-types at 4 loci in the F2 population, displaying estimated disomic-inheritance frequencies of 0, 2.72%, 14.52%, and 36.92%, and probably in the F1 population too. There were also low-frequency non-hexaploid F1 and F2 genotypes that were probably derived from double-reduction recombination or partially unreduced gametes, and F2 genotypes of apparent aneuploids/dysploids with neopolyploid-like frequencies. Additional analyses of homoeolog-type genotypes at the 5 loci in 46 lines from various regions revealed locus-dependent selection biases, favoring genotypes having more of one homoeolog-type, i.e. more of di- or homogenized homoeolog-type composition, and one-direction ploidy trending among apparent aneuploids/dysploids. These inheritance features pointed to an evolving segmental allohexaploid sweetpotato impacted by selection biases.

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The tassel competes with the ear for nutrients and shields the upper leaves, thereby reducing the yield of grain. The tassel branch number (TBN) is a pivotal determinant of tassel size, wherein the reduced TBN has the potential to enhance the transmission of light and reduce the consumption of nutrients, which should ultimately result in increased yield. Consequently, the TBN has emerged as a vital target trait in contemporary breeding programs that focus on compact maize varieties. In this study, QTL-seq technology and advanced population mapping were used to rapidly identify and dissect the major effects of the TBN on QTL. Advanced mapping populations (BC4F2 and BC4F3) were derived from the inbred lines 18-599 (8-11 TBN) and 3237 (0-1 TBN) through phenotypic recurrent selection. First, 13 genomic regions associated with the TBN were detected using quantitative trait locus (QTL)-seq and were located on chromosomes 2 and 5. Subsequently, validated loci within these regions were identified by QTL-seq. Three QTLs for TBN were identified in the BC4F2 populations by traditional QTL mapping, with each QTL explaining the phenotypic variation of 6.13-18.17%. In addition, for the major QTL (qTBN2-2 and qTBN5-1), residual heterozygous lines (RHLs) were developed from the BC4F2 population. These two major QTLs were verified in the RHLs by QTL mapping, with the phenotypic variation explained (PVE) of 21.57% and 30.75%, respectively. Near-isogenic lines (NILs) of qTBN2-2 and qTBN5-1 were constructed. There were significant differences between the NILs in TBN. These results will enhance our understanding of the genetic basis of TBN and provide a solid foundation for the fine-mapping of TBN. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01431-y.

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The sorghum-sudangrass hybrid is a vital gramineous herbage.The F2 population was obtained to clarify genetic regularities among the traits of sorghum-sudangrass hybrids by bagging and selfing in the F1 generation using 'scattered ear sorghum' and 'red hull sudangrass.' This hybrid combines the characteristics of the strong resistance of parents, high yield, and good palatability and has clear heterosis. A thorough understanding of the genetic mechanisms of yield traits in sorghum-sudangrass hybrids is essential in improving their yield. Therefore, we conducted quantitative trait locus (QTL) mapping for plant height, stem diameter, tiller number, leaf number, leaf length, leaf width, and fresh weight of each plant in three different environments, using a high-density genetic linkage map based on single nucleotide polymorphism markers previously constructed by our team. A total of 55 QTLs were detected, uniformly distributed over the 10 linkage groups (LGs), with logarithm of odds values ranging between 2.5 and 7.1, which could explain the 4.9-52.44% phenotypic variation. Furthermore, 17 yield-related relatively high-frequency QTL (RHF-QTL) loci were repeatedly detected in at least two environments, with an explanatory phenotypic variation of 4.9-30.97%. No RHF-QTLs were associated with the tiller number. The genes within the confidence interval of RHF-QTL were annotated, and seven candidate genes related to yield traits were screened. Three QTL sites overlapping or adjacent to previous studies were detected by comparative analysis. We also found that QTL was enriched and that qLL-10-1 and qFW-10-4 were located at the same location of 25.81 cM on LG10. The results of this study provide a foundation for QTL fine mapping, candidate gene cloning, and molecular marker-assisted breeding of sorghum-sudangrass hybrids.

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Maize lethal necrosis (MLN) is a viral disease with a devastating effect on maize production. Developing and deploying improved varieties with resistance to the disease is important to effectively control MLN; however, little is known about the causal genes and molecular mechanism(s) underlying MLN resistance. Screening thousands of maize inbred lines revealed KS23-5 and KS23-6 as two of the most promising donors of MLN resistance alleles. KS23-5 and KS23-6 lines were earlier developed at the University of Hawaii, United States, on the basis of a source population constituted using germplasm from Kasetsart University, Thailand. Both linkage mapping and association mapping approaches were used to discover and validate genomic regions associated with MLN resistance. Selective genotyping of resistant and susceptible individuals within large F2 populations coupled with genome-wide association study identified a major-effect QTL (qMLN06_157) on chromosome 6 for MLN disease severity score and area under the disease progress curve values in all three F2 populations involving one of the KS23 lines as a parent. The major-effect QTL (qMLN06_157) is recessively inherited and explained 55%-70% of the phenotypic variation with an approximately 6 Mb confidence interval. Linkage mapping in three F3 populations and three F2 populations involving KS23-5 or KS23-6 as one of the parents confirmed the presence of this major-effect QTL on chromosome 6, demonstrating the efficacy of the KS23 allele at qMLN06.157 in varying populations. This QTL could not be identified in population that was not derived using KS23 lines. Validation of this QTL in six F2 populations with 20 SNPs closely linked with qMLN06.157 was further confirmed its consistent expression across populations and its recessive nature of inheritance. On the basis of the consistent and effective resistance afforded by the KS23 allele at qMLN06.157, the QTL can be used in both marker-assisted forward breeding and marker-assisted backcrossing schemes to improve MLN resistance of breeding populations and key lines for eastern Africa.

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Dissecting the genetic mechanisms underlying agronomic traits is of great importance for crop breeding. Agronomic traits are usually controlled by multiple quantitative trait loci (QTLs) and genetic interactions, and mapping the underlying causal genes is still labor-intensive and time-consuming. Here, we present a genetic tool for directly targeting the specific causal genes by using a single-gene resolution linkage map that was constructed from 3756 F2 rice plants via targeted sequencing technology and Tukey-Kramer multiple comparisons test. Three large- and moderate-effect QTLs, qHD6-2, qGL3-1, and qGW5-2, were successfully mapped to their specific causal genes, Hd1, GS3, and GW5, respectively. A complex genetic interaction network containing 30 QTL-QTL interactions was constructed, revealing that the alternative allele of hub QTL, qHD6-2, can hide or release the genetic contributions of the alleles at interacting loci. Moreover, arranging genetic interactions in the models lead to more accurate phenotypic predictions. These results provide a community resource and new feasible strategy for deciphering the genetic mechanisms of complex agronomic traits and accelerating crop breeding.

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Genomic imprinting is an epigenetic phenomenon, which plays important roles in the growth and development of animals and plants. Immortalized F2 (imF2) populations generated by random cross between recombinant inbred (RI) or doubled haploid (DH) lines have been proved to have significant advantages for mapping imprinted quantitative trait loci (iQTLs), and statistical methods for this purpose have been proposed. In this paper, we propose a special type of imF2 population (R-imF2) for iQTL mapping, which is developed by random reciprocal cross between RI/DH lines. We also propose two modified iQTL mapping methods: two-step point mapping (PM-2) and two-step composite point mapping (CPM-2). Simulation studies indicated that: (i) R-imF2 cannot improve the results of iQTL mapping, but the experimental design can probably reduce the workload of population construction; (ii) PM-2 can increase the precision of estimating the position and effects of a single iQTL; and (iii) CPM-2 can precisely map not only iQTLs, but also non-imprinted QTLs. The modified experimental design and statistical methods will facilitate and promote the study of iQTL mapping.

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Spontaneous mutants are mainly obtained from tissue culture or natural occurrences in plants. The traditional strategy for identifying spontaneously mutated genes is to continuously backcross these mutants to another variety and develop a near-isogenic F2 population for map-based cloning or bulked segregant analysis. However, this strategy is time-consuming. Here, we have developed a new method to efficiently accelerate the identification process. The chemical mutagen ethyl methanesulfonate was first used to treat the wild type of the spontaneous mutants to induce thousands of neutral mutations. An induced individual without any statistically significant phenotypic changes which was compared with the wild type was chosen as the neutral mutant. The spontaneous mutant was then crossed with the neutral mutant to develop a pseudo-near-isogenic F2 population in which only the induced neutral mutations and the causal mutation were segregated in the genome. This population ensures that the variation of the mutated trait is controlled only by the spontaneously mutated gene. Finally, after sequencing the neutral mutant and the mutant-type DNA pool of the F2 population the spontaneous mutation will be identified quickly by bioinformatics analysis. Using this method, two spontaneously mutated genes were identified successfully. Therefore, the neutral mutant-bridging method efficiently identifies spontaneously mutated genes in rice, and its value in other plants is discussed.

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BACKGROUND: Grapevine is a crop of major economic importance, yet little is known about the regulation of shoot development in grapevine or other perennial fruits crops. Here we combine genetic and genomic tools to identify candidate genes regulating shoot development in Vitis spp. RESULTS: An F2 population from an interspecific cross between V. vinifera and V. riparia was phenotyped for shoot development traits, and three Quantitative Trait Loci (QTLs) were identified on linkage groups (LGs) 7, 14 and 18. Around 17% of the individuals exhibited a dwarfed phenotype. A transcriptomic study identified four candidate genes that were not expressed in dwarfed individuals and located within the confidence interval of the QTL on LG7. A deletion of 84,482 bp was identified in the genome of dwarfed plants, which included these four not expressed genes. One of these genes was VviCURLY LEAF (VviCLF), an orthologue of CLF, a regulator of shoot development in Arabidopsis thaliana. CONCLUSIONS: The phenotype of the dwarfed grapevine plants was similar to that of clf mutants of A. thaliana and orthologues of the known targets of CLF in A. thaliana were differentially expressed in the dwarfed plants. This suggests that CLF, a major developmental regulator in A. thaliana, also controls shoot development in grapevine.

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BACKGROUND: Utilization of heterosis in maize could be critical in maize breeding for boosting grain yield. However, the genetic architecture of heterosis is not fully understood. To dissect the genetic basis of yield-related traits and heterosis in maize, 301 recombinant inbred lines derived from 08 to 641 × YE478 and 298 hybrids from the immortalized F2 (IF2) population were used to map quantitative trait loci (QTLs) for nine yield-related traits and mid-parent heterosis. RESULTS: We observed 156 QTLs, 28 pairs of loci with epistatic interaction, and 10 significant QTL × environment interactions in the inbred and hybrid mapping populations. The high heterosis in F1 and IF2 populations for kernel weight per ear (KWPE), ear weight per ear (EWPE), and kernel number per row (KNPR) matched the high percentages of QTLs (over 50%) for those traits exhibiting overdominance, whereas a notable predominance of loci with dominance effects (more than 70%) was observed for traits that show low heterosis such as cob weight per ear (CWPE), rate of kernel production (RKP), ear length (EL), ear diameter (ED), cob diameter, and row number (RN). The environmentally stable QTL qRKP3-2 was identified across two mapping populations, while qKWPE9, affecting the trait mean and the mid-parent heterosis (MPH) level, explained over 18% of phenotypic variations. Nine QTLs, qEWPE9-1, qEWPE10-1, qCWPE6, qEL8, qED2-2, qRN10-1, qKWPE9, qKWPE10-1, and qRKP4-3, accounted for over 10% of phenotypic variation. In addition, QTL mapping identified 95 QTLs that were gathered together and integrated into 33 QTL clusters on 10 chromosomes. CONCLUSIONS: The results revealed that (1) the inheritance of yield-related traits and MPH in the heterotic pattern improved Reid (PA) × Tem-tropic I (PB) is trait-dependent; (2) a large proportion of loci showed dominance effects, whereas overdominance also contributed to MPH for KNPR, EWPE, and KWPE; (3) marker-assisted selection for markers at genomic regions 1.09-1.11, 2.04, 3.08-3.09, and 10.04-10.05 contributed to hybrid performance per se and heterosis and were repeatedly reported in previous studies using different heterotic patterns is recommended.

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Plasma cholinesterase (PCHE) activity is an important auxiliary test in human clinical medicine. It can distinguish liver diseases from non-liver diseases and help detect organophosphorus poisoning. Animal experiments have confirmed that PCHE activity is associated with obesity and hypertension and changes with physiological changes in an animal's body. The objective of this study was to locate the genetic loci responsible for PCHE activity variation in ducks. PCHE activity of Pekin duck × mallard F2 ducks at 3 and 8 weeks of age were analyzed, and genome-wide association studies were conducted. A region of about 1.5 Mb (21.8-23.3 Mb) on duck chromosome 9 was found to be associated with PCHE activity at both 3 and 8 weeks of age. The top SNP, g.22643979C>T in the butyrylcholinesterase (BCHE) gene, was most highly associated with PCHE activity at 3 weeks (-logP = 21.45) and 8 weeks (-logP = 27.60) of age. For the top SNP, the strong associations of CC and CT genotypes with low PCHE activity and the TT genotype with high PCHE activity indicates the dominant inheritance of low PCHE activity. Problems with block inheritance or linkage exist in this region. This study supports that BCHE is a functional gene for determining PCHE levels in ducks and that the genetic variations around this gene can cause phenotypic variations of PCHE activity.

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BACKGROUND: Quantitative trait loci (QTL) mapping provides a powerful tool to unravel the genetic bases of cotton yield and its components, as well as their heterosis. In the present study, the genetic basis underlying inbreeding depression and heterosis for yield and yield components of upland cotton was investigated in recombinant inbred line (RIL), immortalized F2 (IF2), and two backcross (BCF1) populations based on a high-density SNP linkage map across four environments. RESULTS: Significant inbreeding depression of fruit branches per plant (FB), boll numbers per plant (BN), seed cotton yield (SY), and lint yield (LY) in RIL population and high levels of heterosis for SY, LY, and boll weight (BW) in IF2 and two BCF1 populations were observed. A total of 285 QTLs were identified in the four related populations using a composite interval mapping approach. In the IF2 population, 26.60% partially dominant (PD) QTLs and 71.28% over-dominant (OD) QTLs were identified. In two BCF1 populations, 42.41% additive QTLs, 4.19% PD QTLs, and 53.40% OD QTLs were detected. For multi-environment analysis, phenotypic variances (PV) explained by e-QTLs were higher than those by m-QTLs in each of the populations, and the average PV of m-QTLs and e-QTLs explained by QTL × environment interactions occupied a considerable proportion of total PV in all seven datasets. CONCLUSIONS: At the single-locus level, the genetic bases of heterosis varied in different populations. Partial dominance and over-dominance were the main cause of heterosis in the IF2 population, while additive effects and over-dominance were the main genetic bases of heterosis in two BCF1 populations. In addition, the various genetic components to heterosis presented trait specificity. In the multi-environment model analysis, epistasis was a common feature of most loci associated with inbreeding depression and heterosis. Furthermore, the environment was a critical factor in the expression of these m-QTLs and e-QTLs. Altogether, additive effects, over-dominance, epistasis and environmental interactions all contributed to the heterosis of yield and its components in upland cotton, with over-dominance and epistasis more important than the others.

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1. In order to identify loci associated with metabolic traits, a genome-wide association study was carried out in a chicken F2 population derived from a reciprocal cross between Iranian Urmia indigenous chickens and Arian broiler line using Illumina 60K Chicken single nucleotide polymorphism (SNP) BeadChip. 2. Six traits including plasma level of triglycerides (TGs), cholesterol (Chol), glucose (Glu), total protein, albumin (Alb) and globulin (Glo) were recorded. The association between the identified SNPs and metabolic traits was estimated by general linear model (GLM) and compressed mixed linear model (CMLM). 3. A total of 38 SNPs were identified at the genome-wide significant and suggestive levels, of which 5 SNPs reached a 5% Bonferroni genome-wide significance (P < 2.58E-6) for TG, Alb and Glo through CMLM, and 21 SNPs were significantly associated with TG, Chol, Glu, Alb and Glo through GLM. 4. Gene ontology showed that these SNPs were located within or near the candidate genes responsible for metabolic traits. 5. In conclusion, the identified candidate genes provided novel information for molecular mechanisms underlying metabolic traits. These findings are important in marker-assisted selection in the chicken breeding scheme.

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Untargeted LCMS profiling of semi-polar metabolites followed by metabolite quantitative trait locus (mQTL) analysis was performed in ripe pepper fruits of 113 F2 plants derived from a cross between Capsicum annuum AC1979 (no. 19) and Capsicum chinense No. 4661 Selection (no. 18). The parental accessions were selected based on their variation in fruit morphological characteristics and fruit content of some target phytonutrients. Clear segregation of fruit colour and fruit metabolite profiles was observed in the F2 population. The F2 plants formed three clusters based on their metabolite profiles. Of the total of 542 metabolites, 52 could be annotated, including a range of flavonoids, such as flavone C-glycosides, flavonol O-glycosides and naringenin chalcone, as well as several phenylpropanoids, a capsaicin analogue, fatty acid derivatives and amino acid derivatives. Interval mapping revealed 279 mQTLs in total. Two mQTL hotspots were found on chromosome 9. These two chromosomal regions regulated the relative levels of 35 and 103 metabolites, respectively. Analysis also revealed an mQTL for a capsaicin analogue, located on chromosome 7. Confirmation of flavonoid mQTLs using a set of six flavonoid candidate gene markers and their corresponding expression data (expression QTLs) indicated the Ca-MYB12 transcription factor gene on chromosome 1 and the gene encoding flavone synthase (FS-2) on chromosome 6 as likely causative genes determining the variation in naringenin chalcone and flavone C-glycosides, respectively, in this population. The combination of large-scale metabolite profiling and QTL analysis provided valuable insight into the genomic regions and genes important for the production of (secondary) metabolites in pepper fruit. This will impact breeding strategies aimed at optimising the content of specific metabolites in pepper fruit.

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High-density genetic map provides an essential framework for accurate and efficient genome assembly and QTL fine mapping. Construction of high-density genetic maps appears more feasible since the advent of next-generation sequencing (NGS), which eases SNP discovery and high-throughput genotyping of large population. In this research, a high-density genetic map of cucumber (Cucumis sativus L.) was successfully constructed across an F2 population by a recently developed Specific Length Amplified Fragment sequencing (SLAF-seq) method. In total, 18.69 GB of data containing 93,460,000 paired-end reads were obtained after preprocessing. The average sequencing depth was 44.92 in the D8 (female parent), 42.16 in the Jin5-508 (male parent), and 5.01 in each progeny. 79,092 high-quality SLAFs were detected, of which 6784 SLAFs were polymorphic, and 1892 of the polymorphic markers met the requirements for constructing genetic map. The genetic map spanned 845.87 cm with an average genetic distance of 0.45 cm. It is a reliable linkage map for fine mapping and molecular breeding of cucumber for its high marker density and well-ordered markers.

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In order to identify quantitative trait loci (QTL) for the eating quality of waxy corn and sweet corn (Zea mays L.), QTL analysis was conducted on an F2 population derived from a cross between a waxy corn inbred line and a sweet corn inbred line. Ten QTLs for pericarp thickness (PER), amylose content (AMY), dextrose content (DEX) and sucrose content (SUC) were found in the 158 F2 families. Among them, four QTLs, qAMY4 (10.43%), qAMY9 (19.33%), qDEX4 (21.31%) and qSUC4 (30.71%), may be considered as major QTLs. Three of these, qAMY4, qDEX4 and qSUC4, were found to be located within a region flanked by two adjacent SSR markers on chromosome 4 (umc1088 and bnlg1265), making this SSR marker pair a useful selection tool for screening the eating quality traits of AMY, DEX and SUC. The QTL for amylose content was found to be located between markers phi027 and umc1634, raising the possibility of its identity being the Wx1 gene, which encodes a granule-bound amylose synthase. The new QTLs identified by the present study could serve as useful molecular markers for selecting important eating quality traits in subsequent waxy corn breeding studies.