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1.
Katharina V. Alheit Lucas Busemeyer Wenxin Liu Hans Peter Maurer Manje Gowda Volker Hahn Sigrid Weissmann Arno Ruckelshausen Jochen C. Reif Tobias Würschum 《TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik》2014,127(1):251-260
Key message
QTL mapping in multiple families identifies trait-specific and pleiotropic QTL for biomass yield and plant height in triticale.Abstract
Triticale shows a broad genetic variation for biomass yield which is of interest for a range of purposes, including bioenergy. Plant height is a major contributor to biomass yield and in this study, we investigated the genetic architecture underlying biomass yield and plant height by multiple-line cross QTL mapping. We employed 647 doubled haploid lines from four mapping populations that have been evaluated in four environments and genotyped with 1710 DArT markers. Twelve QTL were identified for plant height and nine for biomass yield which cross-validated explained 59.6 and 38.2 % of the genotypic variance, respectively. A major QTL for both traits was identified on chromosome 5R which likely corresponds to the dominant dwarfing gene Ddw1. In addition, we detected epistatic QTL for plant height and biomass yield which, however, contributed only little to the genetic architecture of the traits. In conclusion, our results demonstrate the potential of genomic approaches for a knowledge-based improvement of biomass yield in triticale. 相似文献2.
Background
Drought and salinity are two major abiotic stresses that severely limit barley production worldwide. Physiological and genetic complexity of these tolerance traits has significantly slowed the progress of developing stress-tolerant cultivars. Marker-assisted selection (MAS) may potentially overcome this problem. In the current research, seventy two double haploid (DH) lines from a cross between TX9425 (a Chinese landrace variety with superior drought and salinity tolerance) and a sensitive variety, Franklin were used to identify quantitative trait loci (QTL) for drought and salinity tolerance, based on a range of developmental and physiological traits.Results
Two QTL for drought tolerance (leaf wilting under drought stress) and one QTL for salinity tolerance (plant survival under salt stress) were identified from this population. The QTL on 2H for drought tolerance determined 42% of phenotypic variation, based on three independent experiments. This QTL was closely linked with a gene controlling ear emergency. The QTL on 5H for drought tolerance was less affected by agronomic traits and can be effectively used in breeding programs. A candidate gene for this QTL on 5H was identified based on the draft barley genome sequence. The QTL for proline accumulation, under both drought and salinity stresses, were located on different positions to those for drought and salinity tolerance, indicating no relationship with plant tolerance to either of these stresses.Conclusions
Using QTL mapping, the relationships between QTL for agronomic and physiological traits and plant drought and salinity tolerance were studied. A new QTL for drought tolerance which was not linked to any of the studied traits was identified. This QTL can be effectively used in breeding programs. It was also shown that proline accumulation under stresses was not necessarily linked with drought or salinity tolerance based on methods of phenotyping used in this experiment. The use of proline content in breeding programs can also be limited by the accuracy of phenotyping.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1243-8) contains supplementary material, which is available to authorized users. 相似文献3.
Christine Gro?e-Brinkhaus Elisabeth Jonas Heiko Buschbell Chirawath Phatsara Dawit Tesfaye Heinz Jüngst Christian Looft Karl Schellander Ernst Tholen 《遗传、选种与进化》2010,42(1):39
Background
Quantitative trait loci (QTL) analyses in pig have revealed numerous individual QTL affecting growth, carcass composition, reproduction and meat quality, indicating a complex genetic architecture. In general, statistical QTL models consider only additive and dominance effects and identification of epistatic effects in livestock is not yet widespread. The aim of this study was to identify and characterize epistatic effects between common and novel QTL regions for carcass composition and meat quality traits in pig.Methods
Five hundred and eighty five F2 pigs from a Duroc × Pietrain resource population were genotyped using 131 genetic markers (microsatellites and SNP) spread over the 18 pig autosomes. Phenotypic information for 26 carcass composition and meat quality traits was available for all F2 animals. Linkage analysis was performed in a two-step procedure using a maximum likelihood approach implemented in the QxPak program.Results
A number of interacting QTL was observed for different traits, leading to the identification of a variety of networks among chromosomal regions throughout the porcine genome. We distinguished 17 epistatic QTL pairs for carcass composition and 39 for meat quality traits. These interacting QTL pairs explained up to 8% of the phenotypic variance.Conclusions
Our findings demonstrate the significance of epistasis in pigs. We have revealed evidence for epistatic relationships between different chromosomal regions, confirmed known QTL loci and connected regions reported in other studies. Considering interactions between loci allowed us to identify several novel QTL and trait-specific relationships of loci within and across chromosomes. 相似文献4.
5.
Sophie Rothammer Prisca V Kremer Maren Bernau Ignacio Fernandez-Figares Jennifer Pfister-Sch?r Ivica Medugorac Armin M Scholz 《遗传、选种与进化》2014,46(1)
Background
Since the pig is one of the most important livestock animals worldwide, mapping loci that are associated with economically important traits and/or traits that influence animal welfare is extremely relevant for efficient future pig breeding. Therefore, the purpose of this study was a genome-wide mapping of quantitative trait loci (QTL) associated with nine body composition and bone mineral traits: absolute (Fat, Lean) and percentage (FatPC, LeanPC) fat and lean mass, live weight (Weight), soft tissue X-ray attenuation coefficient (R), absolute (BMC) and percentage (BMCPC) bone mineral content and bone mineral density (BMD).Methods
Data on the nine traits investigated were obtained by Dual-energy X-ray absorptiometry for 551 pigs that were between 160 and 200 days old. In addition, all pigs were genotyped using Illumina’s PorcineSNP60 Genotyping BeadChip. Based on these data, a genome-wide combined linkage and linkage disequilibrium analysis was conducted. Thus, we used 44 611 sliding windows that each consisted of 20 adjacent single nucleotide polymorphisms (SNPs). For the middle of each sliding window a variance component analysis was carried out using ASReml. The underlying mixed linear model included random QTL and polygenic effects, with fixed effects of sex, housing, season and age.Results
Using a Bonferroni-corrected genome-wide significance threshold of P < 0.001, significant peaks were identified for all traits except BMCPC. Overall, we identified 72 QTL on 16 chromosomes, of which 24 were significantly associated with one trait only and the remaining with more than one trait. For example, a QTL on chromosome 2 included the highest peak across the genome for four traits (Fat, FatPC, LeanPC and R). The nearby gene, ZNF608, is known to be associated with body mass index in humans and involved in starvation in Drosophila, which makes it an extremely good candidate gene for this QTL.Conclusions
Our QTL mapping approach identified 72 QTL, some of which confirmed results of previous studies in pigs. However, we also detected significant associations that have not been published before and were able to identify a number of new and promising candidate genes, such as ZNF608.Electronic supplementary material
The online version of this article (doi:10.1186/s12711-014-0068-2) contains supplementary material, which is available to authorized users. 相似文献6.
Lei Shi Taoxiong Shi Martin R. Broadley Philip J. White Yan Long Jinling Meng Fangsen Xu John P. Hammond 《Annals of botany》2013,112(2):381-389
Background and Aims
Phosphate (Pi) deficiency in soils is a major limiting factor for crop growth worldwide. Plant growth under low Pi conditions correlates with root architectural traits and it may therefore be possible to select these traits for crop improvement. The aim of this study was to characterize root architectural traits, and to test quantitative trait loci (QTL) associated with these traits, under low Pi (LP) and high Pi (HP) availability in Brassica napus.Methods
Root architectural traits were characterized in seedlings of a double haploid (DH) mapping population (n = 190) of B. napus [‘Tapidor’ × ‘Ningyou 7’ (TNDH)] using high-throughput phenotyping methods. Primary root length (PRL), lateral root length (LRL), lateral root number (LRN), lateral root density (LRD) and biomass traits were measured 12 d post-germination in agar at LP and HP.Key Results
In general, root and biomass traits were highly correlated under LP and HP conditions. ‘Ningyou 7’ had greater LRL, LRN and LRD than ‘Tapidor’, at both LP and HP availability, but smaller PRL. A cluster of highly significant QTL for LRN, LRD and biomass traits at LP availability were identified on chromosome A03; QTL for PRL were identified on chromosomes A07 and C06.Conclusions
High-throughput phenotyping of Brassica can be used to identify root architectural traits which correlate with shoot biomass. It is feasible that these traits could be used in crop improvement strategies. The identification of QTL linked to root traits under LP and HP conditions provides further insights on the genetic basis of plant tolerance to P deficiency, and these QTL warrant further dissection. 相似文献7.
8.
Wellington Muchero Jianjun Guo Stephen P DiFazio Jin-Gui Chen Priya Ranjan Gancho T Slavov Lee E Gunter Sara Jawdy Anthony C Bryan Robert Sykes Angela Ziebell Jaroslav Kláp?tě Ilga Porth Oleksandr Skyba Faride Unda Yousry A El-Kassaby Carl J Douglas Shawn D Mansfield Joel Martin Wendy Schackwitz Luke M Evans Olaf Czarnecki Gerald A Tuskan 《BMC genomics》2015,16(1)
9.
In-Cheol Cho Chae-Kyoung Yoo Jae-Bong Lee Eun-Ji Jung Sang-Hyun Han Sung-Soo Lee Moon-Suck Ko Hyun-Tae Lim Hee-Bok Park 《遗传、选种与进化》2015,47(1)
Background
We conducted a genome-wide linkage analysis to identify quantitative trait loci (QTL) that influence meat quality-related traits in a large F2 intercross between Landrace and Korean native pigs. Thirteen meat quality-related traits of the m. longissimus lumborum et thoracis were measured in more than 830 F2 progeny. All these animals were genotyped with 173 microsatellite markers located throughout the pig genome, and the GridQTL program based on the least squares regression model was used to perform the QTL analysis.Results
We identified 23 genome-wide significant QTL in eight chromosome regions (SSC1, 2, 6, 7, 9, 12, 13, and 16) (SSC for Sus Scrofa) and detected 51 suggestive QTL in the 17 chromosome regions. QTL that affect 10 meat quality traits were detected on SSC12 and were highly significant at the genome-wide level. In particular, the QTL with the largest effect affected crude fat percentage and explained 22.5% of the phenotypic variance (F-ratio = 278.0 under the additive model, nominal P = 5.5 × 10−55). Interestingly, the QTL on SSC12 that influenced meat quality traits showed an obvious trend for co-localization.Conclusions
Our results confirm several previously reported QTL. In addition, we identified novel QTL for meat quality traits, which together with the associated positional candidate genes improve the knowledge on the genetic structure that underlies genetic variation for meat quality traits in pigs.Electronic supplementary material
The online version of this article (doi:10.1186/s12711-014-0080-6) contains supplementary material, which is available to authorized users. 相似文献10.
Flavie Tortereau Hélène Gilbert Henri CM Heuven Jean-Pierre Bidanel Martien AM Groenen Juliette Riquet 《遗传、选种与进化》2010,42(1):42
Background
In pig, a number of experiments have been set up to identify QTL and a multitude of chromosomal regions harbouring genes influencing traits of interest have been identified. However, the mapping resolution remains limited in most cases and the detected QTL are rather inaccurately located. Mapping accuracy can be improved by increasing the number of phenotyped and genotyped individuals and/or the number of informative markers. An alternative approach to overcome the limited power of individual studies is to combine data from two or more independent designs.Methods
In the present study we report a combined analysis of two independent design (a French and a Dutch F2 experimental designs), with 2000 F2 individuals. The purpose was to further map QTL for growth and fatness on pig chromosomes 2, 4 and 6. Using QTL-map software, uni- and multiple-QTL detection analyses were applied separately on the two pedigrees and then on the combination of the two pedigrees.Results
Joint analyses of the combined pedigree provided (1) greater significance of shared QTL, (2) exclusion of false suggestive QTL and (3) greater mapping precision for shared QTL.Conclusions
Combining two Meishan x European breeds F2 pedigrees improved the mapping of QTL compared to analysing pedigrees separately. Our work was facilitated by the access to raw phenotypic data and DNA of animals from both pedigrees and the combination of the two designs with the addition of new markers allowed us to fine map QTL without phenotyping additional animals. 相似文献11.
Vilson Mirdita Guozheng Liu Yusheng Zhao Thomas Miedaner C. Friedrich H. Longin Manje Gowda Michael Florian Mette Jochen C. Reif 《BMC genomics》2015,16(1)
Background
Fusarium head blight (FHB) and Septoria tritici blotch (STB) severely impair wheat production. With the aim to further elucidate the genetic architecture underlying FHB and STB resistance, we phenotyped 1604 European wheat hybrids and their 135 parental lines for FHB and STB disease severities and determined genotypes at 17,372 single-nucleotide polymorphic loci.Results
Cross-validated association mapping revealed the absence of large effect QTL for both traits. Genomic selection showed a three times higher prediction accuracy for FHB than STB disease severity for test sets largely unrelated to the training sets.Conclusions
Our findings suggest that the genetic architecture is less complex and, hence, can be more properly tackled to perform accurate prediction for FHB than STB disease severity. Consequently, FHB disease severity is an interesting model trait to fine-tune genomic selection models exploiting beyond relatedness also knowledge of the genetic architecture.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1628-8) contains supplementary material, which is available to authorized users. 相似文献12.
Rodrigo Gularte-Mérida Charles R Farber Ricardo A Verdugo Alma Islas–Trejo Thomas R Famula Craig H Warden Juan F Medrano 《BMC genomics》2015,16(1)
Background
Mouse chromosome 2 is linked to growth and body fat phenotypes in many mouse crosses. With the goal to identify the underlying genes regulating growth and body fat on mouse chromosome 2, we developed five overlapping subcongenic strains that contained CAST/EiJ donor regions in a C57BL/6Jhg/hg background (hg is a spontaneous deletion of 500 Kb on mouse chromosome 10). To fine map QTL on distal mouse chromosome 2 a total of 1,712 F2 mice from the five subcongenic strains, plus 278 F2 mice from the HG2D founder congenic strain were phenotyped and analyzed. Interval mapping (IM) and composite IM (CIM) were performed on body weight and body fat traits on a combination of SNP and microsatellite markers, which generated a high-density genotyping panel.Results
Phenotypic analysis and interval mapping of total fat mass identified two QTL on distal mouse chromosome 2. One QTL between 150 and 161 Mb, Fatq2a, and the second between 173.3 and 175.6 Mb, Fatq2b. The two QTL reside in different congenic strains with significant total fat differences between homozygous cast/cast and b6/b6 littermates. Both of these QTL were previously identified only as a single QTL affecting body fat, Fatq2. Furthermore, through a novel approach referred here as replicated CIM, Fatq2b was mapped to the Gnas imprinted locus.Conclusions
The integration of subcongenic strains, high-density genotyping, and CIM succesfully partitioned two previously linked QTL 20 Mb apart, and the strongest QTL, Fatq2b, was fine mapped to a ~2.3 Mb region interval encompassing the Gnas imprinted locus.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-014-1191-8) contains supplementary material, which is available to authorized users. 相似文献13.
Xianxian Liu Xinwei Xiong Jie Yang Lisheng Zhou Bin Yang Huashui Ai Huanban Ma Xianhua Xie Yixuan Huang Shaoming Fang Shijun Xiao Jun Ren Junwu Ma Lusheng Huang 《遗传、选种与进化》2015,47(1)
Background
Understanding the genetic mechanisms that underlie meat quality traits is essential to improve pork quality. To date, most quantitative trait loci (QTL) analyses have been performed on F2 crosses between outbred pig strains and have led to the identification of numerous QTL. However, because linkage disequilibrium is high in such crosses, QTL mapping precision is unsatisfactory and only a few QTL have been found to segregate within outbred strains, which limits their use to improve animal performance. To detect QTL in outbred pig populations of Chinese and Western origins, we performed genome-wide association studies (GWAS) for meat quality traits in Chinese purebred Erhualian pigs and a Western Duroc × (Landrace × Yorkshire) (DLY) commercial population.Methods
Three hundred and thirty six Chinese Erhualian and 610 DLY pigs were genotyped using the Illumina PorcineSNP60K Beadchip and evaluated for 20 meat quality traits. After quality control, 35 985 and 56 216 single nucleotide polymorphisms (SNPs) were available for the Chinese Erhualian and DLY datasets, respectively, and were used to perform two separate GWAS. We also performed a meta-analysis that combined P-values and effects of 29 516 SNPs that were common to Erhualian, DLY, F2 and Sutai pig populations.Results
We detected 28 and nine suggestive SNPs that surpassed the significance level for meat quality in Erhualian and DLY pigs, respectively. Among these SNPs, ss131261254 on pig chromosome 4 (SSC4) was the most significant (P = 7.97E-09) and was associated with drip loss in Erhualian pigs. Our results suggested that at least two QTL on SSC12 and on SSC15 may have pleiotropic effects on several related traits. All the QTL that were detected by GWAS were population-specific, including 12 novel regions. However, the meta-analysis revealed seven novel QTL for meat characteristics, which suggests the existence of common underlying variants that may differ in frequency across populations. These QTL regions contain several relevant candidate genes.Conclusions
These findings provide valuable insights into the molecular basis of convergent evolution of meat quality traits in Chinese and Western breeds that show divergent phenotypes. They may contribute to genetic improvement of purebreds for crossbred performance.Electronic supplementary material
The online version of this article (doi:10.1186/s12711-015-0120-x) contains supplementary material, which is available to authorized users. 相似文献14.
15.
A Single Locus Is Responsible for Salinity Tolerance in a Chinese Landrace Barley (Hordeum vulgare L.) 总被引:1,自引:0,他引:1
Introduction
Salinity and waterlogging are two major abiotic stresses severely limiting barley production. The lack of a reliable screening method makes it very hard to improve the tolerance through breeding programs.Methods
This work used 188 DH lines from a cross between a Chinese landrace variety, TX9425 (waterlogging and salinity tolerant), and a Japanese malting barley, Naso Nijo (waterlogging and salinity sensitive), to identify QTLs associated with the tolerance.Results
Four QTLs were found for waterlogging tolerance. The salinity tolerance was evaluated with both a hydroponic system and in potting mixture. In the trial with potting mixture, only one major QTL was identified to associate with salinity tolerance. This QTL explained nearly 50% of the phenotypic variation, which makes it possible for further fine mapping and cloning of the gene. This QTL was also identified in the hydroponic experiment for different salt-related traits. The position of this QTL was located at a similar position to one of the major QTLs for waterlogging tolerance, indicating the possibility of similar mechanisms controlling both waterlogging and salinity tolerance.Conclusion
The markers associated with the QTL provided a unique opportunity in breeding programs for selection of salinity and waterlogging tolerance. 相似文献16.
17.
Fabio Cericola Ezio Portis Sergio Lanteri Laura Toppino Lorenzo Barchi Nazzareno Acciarri Laura Pulcini Tea Sala Giuseppe Leonardo Rotino 《BMC genomics》2014,15(1)
Background
The genome-wide association (GWA) approach represents an alternative to biparental linkage mapping for determining the genetic basis of trait variation. Both approaches rely on recombination to re-arrange the genome, and seek to establish correlations between phenotype and genotype. The major advantages of GWA lie in being able to sample a much wider range of the phenotypic and genotypic variation present, in being able to exploit multiple rounds of historical recombination in many different lineages and to include multiple accessions of direct relevance to crop improvement.Results
A 191 accessions eggplant (Solanum melongena L.) association panel, comprising a mixture of breeding lines, old varieties and landrace selections originating from Asia and the Mediterranean Basin, was SNP genotyped and scored for anthocyanin pigmentation and fruit color at two locations over two years. The panel formed two major clusters, reflecting geographical provenance and fruit type. The global level of linkage disequilibrium was 3.4 cM. A mixed linear model appeared to be the most appropriate for GWA. A set of 56 SNP locus/phenotype associations was identified and the genomic regions harboring these loci were distributed over nine of the 12 eggplant chromosomes. The associations were compared with the location of known QTL for the same traits.Conclusion
The GWA mapping approach was effective in validating a number of established QTL and, thanks to the wide diversity captured by the panel, was able to detect a series of novel marker/trait associations.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-896) contains supplementary material, which is available to authorized users. 相似文献18.
Background
The genetic basis of postzygotic isolation is a central puzzle in evolutionary biology. Evolutionary forces causing hybrid sterility or inviability act on the responsible genes while they still are polymorphic, thus we have to study these traits as they arise, before isolation is complete.Methodology/Principal Findings
Isofemale strains of D. mojavensis vary significantly in their production of sterile F1 sons when females are crossed to D. arizonae males. We took advantage of the intraspecific polymorphism, in a novel design, to perform quantitative trait locus (QTL) mapping analyses directly on F1 hybrid male sterility itself. We found that the genetic architecture of the polymorphism for hybrid male sterility (HMS) in the F1 is complex, involving multiple QTL, epistasis, and cytoplasmic effects.Conclusions/Significance
The role of extensive intraspecific polymorphism, multiple QTL, and epistatic interactions in HMS in this young species pair shows that HMS is arising as a complex trait in this system. Directional selection alone would be unlikely to maintain polymorphism at multiple loci, thus we hypothesize that directional selection is unlikely to be the only evolutionary force influencing postzygotic isolation. 相似文献19.
Kathryn E Kemper Coralie M Reich Philip J Bowman Christy J vander Jagt Amanda J Chamberlain Brett A Mason Benjamin J Hayes Michael E Goddard 《遗传、选种与进化》2015,47(1)
Background
Genomic selection is increasingly widely practised, particularly in dairy cattle. However, the accuracy of current predictions using GBLUP (genomic best linear unbiased prediction) decays rapidly across generations, and also as selection candidates become less related to the reference population. This is likely caused by the effects of causative mutations being dispersed across many SNPs (single nucleotide polymorphisms) that span large genomic intervals. In this paper, we hypothesise that the use of a nonlinear method (BayesR), combined with a multi-breed (Holstein/Jersey) reference population will map causative mutations with more precision than GBLUP and this, in turn, will increase the accuracy of genomic predictions for selection candidates that are less related to the reference animals.Results
BayesR improved the across-breed prediction accuracy for Australian Red dairy cattle for five milk yield and composition traits by an average of 7% over the GBLUP approach (Australian Red animals were not included in the reference population). Using the multi-breed reference population with BayesR improved accuracy of prediction in Australian Red cattle by 2 – 5% compared to using BayesR with a single breed reference population. Inclusion of 8478 Holstein and 3917 Jersey cows in the reference population improved accuracy of predictions for these breeds by 4 and 5%. However, predictions for Holstein and Jersey cattle were similar using within-breed and multi-breed reference populations. We propose that the improvement in across-breed prediction achieved by BayesR with the multi-breed reference population is due to more precise mapping of quantitative trait loci (QTL), which was demonstrated for several regions. New candidate genes with functional links to milk synthesis were identified using differential gene expression in the mammary gland.Conclusions
QTL detection and genomic prediction are usually considered independently but persistence of genomic prediction accuracies across breeds requires accurate estimation of QTL effects. We show that accuracy of across-breed genomic predictions was higher with BayesR than with GBLUP and that BayesR mapped QTL more precisely. Further improvements of across-breed accuracy of genomic predictions and QTL mapping could be achieved by increasing the size of the reference population, including more breeds, and possibly by exploiting pleiotropic effects to improve mapping efficiency for QTL with small effects.Electronic supplementary material
The online version of this article (doi:10.1186/s12711-014-0074-4) contains supplementary material, which is available to authorized users. 相似文献20.
Gregório Miguel Ferreira de Camargo Laercio R Porto-Neto Matthew J Kelly Rowan J Bunch Sean M McWilliam Humberto Tonhati Sigrid A Lehnert Marina R S Fortes Stephen S Moore 《BMC genomics》2015,16(1)