QTL mapping in eggplant reveals clusters of yield-related loci and orthology with the tomato genome.
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ABSTRACT:
SUBMITTER: Portis E
PROVIDER: S-EPMC3931786 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Improving yield is one of the most important targets of sesame breeding. Identifying quantitative trait loci (QTLs) of yield-related traits is a prerequisite for marker-assisted selection (MAS) and QTL/gene cloning. In this study, a BC1 population was developed and genotyped with the specific-locus amplified fragment (SLAF) sequencing technology, and a high-density genetic map was constructed. The map consisted of 13 linkage groups, contained 3528 SLAF markers, and covered a total of 1312.52 cM genetic distance, with an average distance of 0.37 cM between adjacent markers. Based on the map, 46 significant QTLs were identified for seven yield-related traits across three environments. These QTLs distributed on 11 linkage groups, each explaining 2.34-71.41% of the phenotypic variation. Of the QTLs, 23 were stable QTLs that were detected in more than one environment, and 20 were major QTLs that explained more than 10% of the corresponding phenotypic variation in at least one environment. Favorable alleles of 38 QTLs originated from the locally adapted variety, Yuzhi 4; the exotic germplasm line, BS, contributed favorable alleles to only 8 QTLs. The results should provide useful information for future molecular breeding and functional gene cloning.Supplementary informationThe online version contains supplementary material available at 10.1007/s11032-021-01236-x.
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Project description:Eggplant, pepper, and tomato are the most exploited berry-producing vegetables within the Solanaceae family. Their genomes differ in size, but each has 12 chromosomes which have undergone rearrangements causing a redistribution of loci. The genome sequences of all three species are available but differ in coverage, assembly quality and percentage of anchorage. Determining their syntenic relationship and QTL orthology will contribute to exploit genomic resources and genetic data for key agronomic traits. The syntenic analysis between tomato and pepper based on the alignment of 34,727 tomato CDS to the pepper genome sequence, identified 19,734 unique hits. The resulting synteny map confirmed the 14 inversions and 10 translocations previously documented, but also highlighted 3 new translocations and 4 major new inversions. Furthermore, each of the 12 chromosomes exhibited a number of rearrangements involving small regions of 0.5-0.7 Mbp. Due to high fragmentation of the publicly available eggplant genome sequence, physical localization of most eggplant QTL was not possible, thus, we compared the organization of the eggplant genetic map with the genome sequence of both tomato and pepper. The eggplant/tomato syntenic map confirmed all the 10 translocations but only 9 of the 14 known inversions; on the other hand, a newly detected inversion was recognized while another one was not confirmed. The eggplant/pepper syntenic map confirmed 10 translocations and 8 inversions already detected and suggested a putative new translocation. In order to perform the assessment of eggplant and pepper QTL orthology, the eggplant and pepper sequence-based markers located in their respective genetic map were aligned onto the pepper genome. GBrowse in pepper was used as reference platform for QTL positioning. A set of 151 pepper QTL were located as well as 212 eggplant QTL, including 76 major QTL (PVE ? 10%) affecting key agronomic traits. Most were confirmed to cluster in orthologous chromosomal regions. Our results highlight that the availability of genome sequences for an increasing number of crop species and the development of "ultra-dense" physical maps provide new and key tools for detailed syntenic and orthology studies between related plant species.
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Project description:Key messageBlossom-End Rot is Quantitatively Inherited and Maps to Four Loci in Tomato. Blossom-end rot (BER) is a devastating physiological disorder that affects tomato and other vegetables, resulting in significant crop losses. To date, most studies on BER have focused on the environmental factors that affect calcium translocation to the fruit; however, the genetic basis of this disorder remains unknown. To investigate the genetic basis of BER, two F2 and F3:4 populations along with a BC1 population that segregated for BER occurrence were evaluated in the greenhouse. Using the QTL-seq approach, quantitative trait loci (QTL) associated with BER Incidence were identified at the bottom of chromosome (ch) 3 and ch11. Additionally, linkage-based QTL mapping detected another QTL, BER3.1, on ch3 and BER4.1 on ch4. To fine map the QTLs identified by QTL-seq, recombinant screening was performed. BER3.2, the major BER QTL on ch3, was narrowed down from 5.68 to 1.58 Mbp with a 1.5-LOD support interval (SI) corresponding to 209 candidate genes. BER3.2 colocalizes with the fruit weight gene FW3.2/SlKLUH, an ortholog of cytochrome P450 KLUH in Arabidopsis. Further, BER11.1, the major BER QTL on ch11, was narrowed down from 3.99 to 1.13 Mbp with a 1.5-LOD SI interval comprising of 141 candidate genes. Taken together, our results identified and fine mapped the first loci for BER resistance in tomato that will facilitate marker-assistant breeding not only in tomato but also in many other vegetables suffering for BER.
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Project description:In the present study, four large-scale field trials using two doubled haploid wheat populations were conducted in different environments for two years. Grain protein content (GPC) and 21 other yield-related traits were investigated. A total of 227 QTL were mapped on 18 chromosomes, which formed 35 QTL clusters. The potential candidate genes underlying the QTL clusters were suggested. Furthermore, adding to the significant correlations between yield and its related traits, correlation variations were clearly shown within the QTL clusters. The QTL clusters with consistently positive correlations were suggested to be directly utilized in wheat breeding, including 1B.2, 2A.2, 2B (4.9-16.5 Mb), 2B.3, 3B (68.9-214.5 Mb), 4A.2, 4B.2, 4D, 5A.1, 5A.2, 5B.1, and 5D. The QTL clusters with negative alignments between traits may also have potential value for yield or GPC improvement in specific environments, including 1A.1, 2B.1, 1B.3, 5A.3, 5B.2 (612.1-613.6 Mb), 7A.1, 7A.2, 7B.1, and 7B.2. One GPC QTL (5B.2: 671.3-672.9 Mb) contributed by cultivar Spitfire was positively associated with nitrogen use efficiency or grain protein yield and is highly recommended for breeding use. Another GPC QTL without negatively pleiotropic effects on 2A (50.0-56.3 Mb), 2D, 4D, and 6B is suggested for quality wheat breeding.
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Project description:BackgroundDeleterious recessive conditions have been primarily studied in the context of Mendelian diseases. Recently, several deleterious recessive mutations with large effects were discovered via non-additive genome-wide association studies (GWAS) of quantitative growth and developmental traits in cattle, which showed that quantitative traits can be used as proxies of genetic disorders when such traits are indicative of whole-animal health status. We reasoned that lactation traits in cattle might also reflect genetic disorders, given the increased energy demands of lactation and the substantial stresses imposed on the animal. In this study, we screened more than 124,000 cows for recessive effects based on lactation traits.ResultsWe discovered five novel quantitative trait loci (QTL) that are associated with large recessive impacts on three milk yield traits, with these loci presenting missense variants in the DOCK8, IL4R, KIAA0556, and SLC25A4 genes or premature stop variants in the ITGAL, LRCH4, and RBM34 genes, as candidate causal mutations. For two milk composition traits, we identified several previously reported additive QTL that display small dominance effects. By contrasting results from milk yield and milk composition phenotypes, we note differing genetic architectures. Compared to milk composition phenotypes, milk yield phenotypes had lower heritabilities and were associated with fewer additive QTL but had a higher non-additive genetic variance and were associated with a higher proportion of loci exhibiting dominance.ConclusionsWe identified large-effect recessive QTL which are segregating at surprisingly high frequencies in cattle. We speculate that the differences in genetic architecture between milk yield and milk composition phenotypes derive from underlying dissimilarities in the cellular and molecular representation of these traits, with yield phenotypes acting as a better proxy of underlying biological disorders through presentation of a larger number of major recessive impacts.
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Project description:Genetic control of grain yield and phenology was examined in the Excalibur/Kukri doubled haploid mapping population grown in 32 field experiments across the climatic zones of southern Australia, India and north-western Mexico where the wheat crop experiences drought and heat stress. A total of 128 QTL were identified for four traits: grain yield, thousand grain weight (TGW), days to heading and grain filling duration. These QTL included 24 QTL for yield and 27 for TGW, showing significant interactions with the environment (Q * E). We also identified 14 QTL with a significant, small main effects on yield across environments. The study focussed on a region of chromosome 1B where two main effect QTL were found for yield and TGW without the confounding effect of phenology. Excalibur was the source of favourable alleles: QYld.aww-1B.2 with a peak at 149.5-150.1 cM and QTgw.aww-1B at 168.5-171.4 cM. We developed near isogenic lines (NIL) for the interval including QYld.aww-1B.2 and QTgw.aww-1B and evaluated them under semi-controlled conditions. Significant differences in four pairs of NIL were observed for grain yield but not for TGW, confirming a positive effect of the Excalibur allele for QYld.aww-1B.2. The interval containing QYld.aww-1B.2 was narrowed down to 2.9 cM which corresponded to a 2.2 Mbp genomic region on the chromosome 1B genomic reference sequence of cv. Chinese Spring and contained 39 predicted genes.
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Project description:Molecular markers allowed breeders to mendelize quantitative trait loci (QTL) providing another demonstration that quantitative traits are governed by the same principles as single qualitative genes. This research extends the QTL analysis to two and three QTL and tests our ability to mendelize an oligogenic trait. In tomato, agricultural yield is determined by the weight of the fruits harvested per unit area and the total soluble solids (% Brix)-sugars and acids. The current study explores the segregation of multiple independent yield-related QTL that were identified and mapped using introgression lines (IL) of Solanum pennellii in cultivated processing tomato (S. lycopersicum). We screened 45 different double and triple IL-QTL combinations for agricultural yield, to identify QTL pyramids that behaved in an additive manner and were suitable substrate for mendelizing an oligogenic trait. A pyramid of three independent QTL that significantly improved Brix(∗)Yield (BXY - the soluble solids output per unit area) compared to M82 was selected. In the progenies of the tri-hybrid we bred using markers a nearly isogenic 'immortalized F2.' While the common mode of QTL-QTL interactions across the 45 IL-QTLs combinations was less than additive, the three QTLs in the selected triple-stack performed in an additive manner which made it an exceptional material for breeding. This study demonstrates that using the phenotypic effect of all 27 possible QTL-alleles combinations it is possible to make reliable predictions about the genotypes that will maximize the yield.
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Project description:Worldwide consumption of oil is increasing with the growing population in need for edible oil and the expansion of industry using biofuels. Then, demand for high yielding varieties of oil crops is always increasing. Brassica napus (rapeseed) is one of the most important oil crop in the world, therefore, increasing rapeseed yield through breeding is inevitable in order to cater for the high demand of vegetable oil and high-quality protein for live stocks. Quantitative trait loci (QTL) analysis is a powerful tool to identify important loci and which is also valuable for molecular marker assisted breeding. Seed-yield (SY) is a complex trait that is controlled by multiple loci and is affected directly by seed weight, seeds per silique and silique number. Some yield-related traits, such as plant height, biomass yield, flowering time, and so on, also affect the SY indirectly. This study reports the assembly of QTLs identified for seed-yield and yield-related traits in rapeseed, in one unique map. A total of 972 QTLs for seed-yield and yield-related were aligned into the physical map of B. napus Darmor-bzh and 92 regions where 198 QTLs overlapped, could be discovered on 16 chromosomes. Also, 147 potential candidate genes were discovered in 65 regions where 131 QTLs overlapped, and might affect nine different traits. At the end, interaction network of candidate genes was studied, and showed nine genes that could highly interact with the other genes, and might have more influence on them. The present results would be helpful to develop molecular markers for yield associated traits and could be used for breeding improvement in B. napus.
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Project description:Peanut (Arachishypogaea L.) is one of the most important oil crops worldwide, and its yet increasing market demand may be met by genetic improvement of yield related traits, which may be facilitated by a good understanding of the underlying genetic base of these traits. Here, we have carried out a genome-wide association study (GWAS) with the aim to identify genomic regions and the candidate genes within these regions that may be involved in determining the phenotypic variation at seven yield-related traits in peanut. For the GWAS analyses, 195 peanut accessions were phenotyped and/or genotyped; the latter was done using a genotyping-by-sequencing approach, which produced a total of 13,435 high-quality single nucleotide polymorphisms (SNPs). Analyses of these SNPs show that the analyzed peanut accessions can be approximately grouped into two big groups that, to some extent, agree with the botanical classification of peanut at the subspecies level. By taking this genetic structure as well as the relationships between the analyzed accessions into consideration, our GWAS analyses have identified 93 non-overlapping peak SNPs that are significantly associated with four of the studied traits. Gene annotation of the genome regions surrounding these peak SNPs have found a total of 311 unique candidate genes. Among the 93 yield-related-trait-associated SNP peaks, 12 are found to be co-localized with the quantitative trait loci (QTLs) that were identified by earlier related QTL mapping studies, and these 12 SNP peaks are only related to three traits and are almost all located on chromosomes Arahy.05 and Arahy.16. Gene annotation of these 12 co-localized SNP peaks have found 36 candidates genes, and a close examination of these candidate genes found one very interesting gene (arahy.RI9HIF), the rice homolog of which produces a protein that has been shown to improve rice yield when over-expressed. Further tests of the arahy.RI9HIF gene, as well as other candidate genes especially those within the more confident co-localized genomic regions, may hold the potential for significantly improving peanut yield.
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