- https://doi.org/10.1111/mec.12998
Recipient of the 2014 molecular ecology prize: Johanna Schmitt.
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Johanna Schmitt It is a great pleasure to help honour the 2014 recipient of the Molecular Ecology Prize: Johanna Schmitt, Professor of Evolution and Ecology and of Population Biology at the University of California, Davis. Johanna, or Annie as she is known by friends and colleagues, has had tremendous influence on the field of ecological genetics throughout her career, and her recent work on the genetic basis of adaptation in Arabidopsis thaliana is some of the most ambitious applications of genomic methods to test hypotheses of ecological and evolutionary dynamics. Entering the field of evolutionary genetics and genomics from the field of ecology, she has infused genetic studies of adaptation with a rich and nuanced view of the ecological environment as seen from the perspective of her study organisms. Anyone who has walked in the woods with her will recognize her plants' eye view in her research. As her former postdoc John Stinchcombe observed, ‘one of the things I find remarkable about Annie (among many) is that as the field has transitioned from a few genes or anonymous markers to whole genome level variation, she's never lost her “feel for the organism” or sight of the larger ecological or evolutionary questions that motivated her to go down this path’. Annie majored in Biology at Swarthmore College and continued her PhD in Biology at Stanford University, with Ward Watt as her advisor. There, she wrote her dissertation on the pollination biology of Scenecio and Linanthus, cultivating interests in the population genetic consequences of density-dependent pollination dynamics (e.g. Schmitt 1983a,b). It was during her postdoctoral work at Duke University, with Janis Antonovics (whom she admired as a great female role model, until she met him in person), that she developed her signature methodology of applying genetic designs to clever and complex field experiments. This approach had two important consequences for her own research and for the field of ecological genetics: first, it illustrated how ecological manipulations can be combined with genetic analysis to test evolutionary hypotheses. For example, her work at Duke tested how genetic diversity within local neighbourhoods can influence competitive interactions and adverse effects of herbivores, relating these dynamics to the evolution of sexual reproduction (Schmitt & Antonovics 1986b; Schmitt & Ehrhardt 1987; Kelley et al. 1988). The focus on sexual reproduction also motivated her to distinguish maternal vs. paternal effects on progeny phenotypes, bringing into focus the phenomenon of maternal effects or cross-generational phenotypic plasticity (Antonovics & Schmitt 1986; Schmitt & Antonovics 1986a). Second, this approach illustrated the strong environmental context of the expression of genetically based traits. Her subsequent work, which she continued at her first faculty appointment at Brown University, engaged the evolutionary and ecological consequences of this environment-dependent genetic expression or genotype–environment interaction. She made phenotypic plasticity a central focus of her research programme (Schmitt et al. 1992; Schmitt 1993, 1995). It was this work that pioneered methods for testing the adaptive significance of phenotypic plasticity, both within and across generations (Schmitt 1993, 1997; Wulff et al. 1994, Schmitt et al. 1999). Her combination of environmental manipulations, phenotypic and genetic manipulations, and measurements of environment-dependent natural selection became the gold standard of tests for adaptive plasticity. Her work on shade avoidance responses in Impatiens capensis unambiguously demonstrated adaptive plasticity and documented that not only did phenotypes change in response to environmental conditions, but genetic variances and covariances did as well (Dudley & Schmitt 1996; Schmitt & Dudley 1996; Donohue et al. 2000a,b). That is, the genetic basis of traits under selection, and the genetic relationships among them, depended strongly on the ecological environment they experienced. Annie's work on shade avoidance responses engaged not only the quantitative genetic basis of this complex trait, but the molecular genetic pathways associated with it as well. Shade avoidance—the ability of plants to elongate in response to vegetation shade—was long known to be mediated by the plant photoreceptors, phytochromes (Schmitt & Wulff 1993). During a sabbatical at the University of Leicester, she collaborated with Alex McCormac and Harry Smith to test how the genetic disruption of phytochrome function would alter shade avoidance and fitness. Using transgenic lines of tobacco whose shade avoidance ability had been blocked, and constitutively shade-avoiding mutants of Brassica, they demonstrated a significant fitness disadvantage of inappropriate shade avoidance responses (Schmitt et al. 1995). This was her first work that employed tools of molecular genetics to test ecological hypotheses. While continuing to investigate the quantitative genetic basis of diverse plastic responses to vegetation shade, Annie began to explore other genetic methods to evaluate their genetic architecture. Like other evolutionary geneticists at the time, she discovered the utility of employing natural genetic variation in ecologically important traits to investigate their genetic basis through quantitative trait locus (QTL) mapping. At the time when QTL analysis was just beginning to be broadly applied to identify loci associated with ecologically significant phenotypes, Annie and her associates implemented a highly ambitious QTL study using Arabidopsis thaliana under field conditions to map not only well-defined phenological and morphological phenotypes, but fitness itself. This intense collaborative effort, initially supported by an NSF FIBR grant, was among the very first to map loci associated with fitness under natural conditions in contrasting geographical sites (Weinig et al. 2002, 2003a,b,c). By demonstrating that some genetic loci were associated with fitness only in one location but neutral in another, while other genetic loci were associated with fitness in both locations, but in opposite directions, this study illustrated how QTL analysis could be employed to resolve long-standing issues of trade-offs in adaptation across geographical locations—specifically revealing instances of conditional neutrality and evidence of antagonistic pleiotropy. The success of this research programme spawned a monster, according to the numerous participants of the next major research effort. Encouraged by the success of the two-site field study with numerous recombinant inbred lines, the team, with some new recruits, initiated a study using four sites across the native range of A. thaliana, from Oulu, Finland to Valencia, Spain, in which hundreds of natural ecotypes combined with a strategic array of mutants, were planted for continuous monitoring. Simultaneously with this ambitious field experiment, creative modelling efforts were being developed to predict the flowering time of specific genotypes under diverse climatic scenarios using agronomic models. This synthesis of genetics, ecology, agronomy and mathematical modelling was unique, and it provided unique insight into the genetic basis of adaptation. Their synthetic approach revealed, for example, that even well-known flowering time genes are expected to exhibit (and did exhibit) effects on flowering time only under certain ecological circumstances and life history backgrounds (Wilczek et al. 2009; Chew et al. 2012). The feat of bringing evolutionary ecologists (Cynthia Weinig, Tonia Korves, Amity Wilczek) in dialogue with population geneticists (Michael Purugganan), molecular geneticists (George Coupland, Rick Amasino, Caroline Dean) and modellers (Steve Welch), while engaging international collaborators (Outi Savolainen, Matthias Hoffmann) in fieldwork, was a Herculean accomplishment. A series of articles from this work was published in Science, PNAS, Molecular Ecology and a number of other prominent journals. Among the most notable findings of this programme were that A. thaliana shows evidence of climate adaptation, with geographic clines in adaptively significant life history traits as well as the loci associated with those traits (Caicedo et al. 2004; Stinchcombe et al. 2004, 2005; Korves et al. 2007; Wilczek et al. 2010). Moreover, genome-wide association studies revealed associations of loci with climate factors across the genome (Fournier-Level et al. 2011, 2013). Most recently (Wilczek et al. 2014), the team found evidence that climate change has caused banked seeds to no longer be optimally adapted to their locations of collection, but that that ecotypes from historically warmer locations performed better under current (warmer) conditions than banked seeds in their native location. As such, immigration of more warm-adapted genotypes into areas with climate change, not emergence from the seed bank or introduction of local banked seeds, is expected to be more effective at maintaining populations in the face of climate change. These empirical data, combined with predictive modelling, establishes a new standard for predictions of how organisms can respond to climate change. Annie was involved at the beginning stages of developing model genetic organisms into model ecological organisms. She helped shape the sorts of questions that could be addressed with this sort of collaboration and made ecological genetics a collaborative endeavour between ecologists, population geneticists and molecular geneticists. Always promoting collaboration over competition, she brokered many matches between PIs studying related phenomena and proposed opportunities to combine efforts in synergistic directions. The field has her to thank for the open and collaborative spirit she has infused it with. In addition to shaping the collaborative nature of the field of ecological genetics, Annie has been a valuable mentor to people at all stages. At Brown, she worked closely with her undergraduate students to involve them with every step of their research projects, from helping to design experiments to data collection, and analysis and presentation. Many of us are grateful for this effort, which has produced so many excellent students who have joined our laboratories as graduate students or technicians. It was here, too, that so many of her postdocs learned the craft of designing undergraduate projects that were self-contained, challenging and rewarding, providing a model for tapping the unique resources of undergraduates in research. Her numerous postdocs also benefitted from being members of such a cohesive laboratory, in which laboratory members could count on each other for technical help and conceptual exchange. Annie's generosity of time, creativity and opportunity were critical to the professional development of many of us. Personally, I will never take for granted the extreme generosity she extended to me when, after a very ill-timed postdoc in Yemen during what turned into its civil war, I found myself evacuated back stateside with no backup plan. I basically knocked on her door to ask for a short-term landing pad, and she opened it up in a manner I could never have expected. At that critical, awkward and very tricky time in my career, she welcomed me into her laboratory, involved me in the ongoing research and gave me new skills, intellectual companionship and a model for how to run a laboratory that was collegial, engaging and effective. I am certain that anyone who spent time in her laboratory benefitted in the same way, and several of her former postdocs (including Susan Dudley, Massimo Pigliucci, Cynthia Weinig, John Stinchcombe, Amity Wilczek and others) have expressed the same appreciation over the years. Annie has amassed several honours as a result of her creative contributions, including election to the National Academy of Sciences, the American Academy of Arts and Sciences, the American Association for the Advancement of Sciences and an Alexander von Humboldt Award, among others. She has been the President of the major professional societies in her field: the Society for the Study of Evolution and the American Society of Naturalists. While at Brown University, she was Stephen T. Olney Professor of Natural History, and she was also the director of the Environmental Change Initiative there, where she exercised her remarkable ability to communicate and synthesize across scientific subfields. UC Davis is now the beneficiary of Annie's energy and expertise, after she moved there in 2012. This Molecular Ecology Prize serves to honour her past accomplishments and inspire curiosity for what is to come.
- Research Article
134 - 10.1371/journal.pgen.1001100
- Sep 9, 2010
- PLoS Genetics
Quantitative Trait Loci (QTL) analyses in immortal populations are a powerful method for exploring the genetic mechanisms that control interactions of organisms with their environment. However, QTL analyses frequently do not culminate in the identification of a causal gene due to the large chromosomal regions often underlying QTLs. A reasonable approach to inform the process of causal gene identification is to incorporate additional genome-wide information, which is becoming increasingly accessible. In this work, we perform QTL analysis of the shade avoidance response in the Bayreuth-0 (Bay-0, CS954) x Shahdara (Sha, CS929) recombinant inbred line population of Arabidopsis. We take advantage of the complex pleiotropic nature of this trait to perform network analysis using co-expression, eQTL and functional classification from publicly available datasets to help us find good candidate genes for our strongest QTL, SAR2. This novel network analysis detected EARLY FLOWERING 3 (ELF3; AT2G25930) as the most likely candidate gene affecting the shade avoidance response in our population. Further genetic and transgenic experiments confirmed ELF3 as the causative gene for SAR2. The Bay-0 and Sha alleles of ELF3 differentially regulate developmental time and circadian clock period length in Arabidopsis, and the extent of this regulation is dependent on the light environment. This is the first time that ELF3 has been implicated in the shade avoidance response and that different natural alleles of this gene are shown to have phenotypic effects. In summary, we show that development of networks to inform candidate gene identification for QTLs is a promising technique that can significantly accelerate the process of QTL cloning.
- Research Article
- 799
- 10.1016/j.cub.2009.01.046
- Feb 26, 2009
- Current biology : CB
High Temperature-Mediated Adaptations in Plant Architecture Require the bHLH Transcription Factor PIF4
- Research Article
- 69
- 10.1007/s001220050598
- Sep 1, 1997
- Theoretical and Applied Genetics
We have mapped QTLs (quantitative trait loci) for an adaptive trait, flowering time, in a selfing annual, Arabidopsis thaliana. To obtain a mapping population we made a cross between an early-summer, annual strain, Li-5, and an individual from a late over-wintering natural population, Naantali. From the backcross to Li-5 298 progeny were grown, of which 93 of the most extreme individuals were genotyped. The data were analysed with both interval mapping and composite interval mapping methods to reveal one major and six minor QTLs, with at least one QTL on each of the five chromosomes. The QTL on chromosome 4 was a major one with an effect of 17.3 days on flowering time and explaining 53.4% of the total variance. The others had effects of at most 6.5 days, and they accounted for only small portions of the variance. Epistasis was indicated between one pair of the QTLs. The result of finding one major QTL and little epistasis agrees with previous studies on flowering time in Arabidopsis thaliana and other species. That several QTLs were found was expected considering the large number of possible candidate loci. In the light of the suggested genetic models of gene action at the candidate loci, epistasis was to be expected. The data showed that major QTLs for adaptive traits can be detected in non-domesticated species.
- Research Article
- 23
- 10.1007/s10681-014-1140-2
- May 22, 2014
- Euphytica
The inheritance of flowering time trait in spring-type rapeseed (Brassica napus L.) is poorly understood, and the investigations on mapping of quantitative trait loci (QTL) for the trait are only few. We identified QTL underlying variation for flowering time in a doubled haploid (DH) mapping population of nonvernalization-responsive canola (B. napus L.) cultivar 465 and line 86 containing introgressions from Houyou11, a Chinese early-flowering cultivar in Brassica rapa L. Significant genetic variation in flowering time and response to photoperiod were observed among the DH lines from 465/86. A molecular linkage map was generated comprising three types of markers loci. QTL analysis indicated that flowering time is a complex trait and is controlled by at least 4 major loci, localized on four different linkage groups A6, A7, C8 and C9. These loci each accounted for between 9.2 and 12.56 % of the total genotypic variation for first flowering. The published high-density maps for flowering time mapping used different marker systems, and the parents of our crosses have different genetic origins, with either spring-type B. napus or B. rapa. So we cannot determine whether the QTL on the same linkage groups were in the same region or not. There was evidence of additive × additive epistatic effects for flowering time in the DH population. Epistasis existed not only between main-effect QTLs, but also between QTLs with minor effects. Four pair of epistasis effects between minor QTLs explained about 20 % of the genetic variance observed in the DH population. The results indicated that minor QTLs for flowering time should not be ignored. Significant genotypes × environment interactions were also found for the quantitative traits, and with significant change in the ranking of the DH lines in different environments. The results implied that FQ3 was a non-environment-specific QTL and may control flowering time by autonomous pathway. FQ4 were winter-environment-specific QTL and may control flowering time by photoperiod-pathway. Identification of the chromosomal location and effect of the genes influencing flowering time may hasten the development of canola varieties having an optimal time for flowering in target environments such as for high altitude areas, via marker-assisted selection.
- Research Article
- 216
- 10.1093/icb/43.3.459
- Jul 1, 2003
- Integrative and Comparative Biology
Many plants display a characteristic suite of developmental "shade avoidance" responses, such as stem elongation and accelerated reproduction, to the low ratio of red to far-red wavelengths (R:FR) reflected or transmitted from green vegetation. This R:FR cue of crowding and vegetation shade is perceived by the phytochrome family of photoreceptors. Phytochrome-mediated responses provide an ideal system for investigating the adaptive evolution of phenotypic plasticity in natural environments. The molecular and developmental mechanisms underlying shade avoidance responses are well studied, and testable ecological hypotheses exist for their adaptive significance. Experimental manipulation of phenotypes demonstrates that shade avoidance responses may be adaptive, resulting in phenotypes with high relative fitness in the environments that induce those phenotypes. The adaptive value of shade avoidance depends upon the competitive environment, resource availability, and the reliability of the R:FR cue for predicting the selective environment experienced by an induced phenotype. Comparative studies and a reciprocal transplant experiment with Impatiens capensis provide evidence of adaptive divergence in shade avoidance responses between woodland and clearing habitats, which may result from population differences in the frequency of selection on shade avoidance traits, as well as differences in the reliability of the R:FR cue. Recent rapid progress in elucidating phytochrome signaling pathways in the genetic model Arabidopsis thaliana and other species now provides the opportunity for studying how selection on shade avoidance traits in natural environments acts upon the molecular mechanisms underlying natural phenotypic variation.
- Research Article
- 31
- 10.1007/s10681-015-1501-5
- Jul 7, 2015
- Euphytica
Flowering represents the transition from the vegetative to reproductive phase and plays an important role in many agronomic traits. For soybean, a short day (SD) induced and photoperiod-sensitive plant, delaying flowering time under SD environments is very important and has been used by breeders to increase yields and enhance plant adaptabilities at lower latitudes. The purpose of this study was to identify quantitative trait loci (QTLs) associated with flowering time, especially QTLs underlying the long juvenile (LJ) trait which delays flowering time under SD environments. A population of 91 recombinant inbred lines derived from a cross between AGS292 and K3 was used for map construction and QTL analysis. The map covered 2546.7 cM and included 52 new promoter-specific indel and 9 new exon-specific indel markers. The phenotypic days-to-flowering data were examined in nine environments, including four short-day (SD, low latitude) and five long-day photoperiod (LD, high latitude) environments. For the SD environments, six QTLs were detected. Five of them were associated with the LJ trait. Among the five LJ QTLs, four QTLs may be attributed to the known flowering time genes, including qFT-J-1 for FT5a locus, qFT-J-2 for the FT2a locus, qFT-O for the E2 locus and qFT-L for the E3 locus. This is the first report that the E2, E3, FT2a and FT5a loci may be associated with the LJ trait. Under the five LD environments, as expected, qFT-O for the E2 locus and qFT-L for the E3 locus were identified, suggesting that E2 and E3 loci are very important for soybean adaptation in LD photoperiod. Conjoint analysis of multiple environments identified nine additive QTLs and nine pairs of epistatic QTLs, among which most were involved in interactions with the environments. In total, five QTLs (qFT-B2-1, qFT-C1-1, qFT-K, qFT-D2 and qFT-F) were identified that may represent novel flowering time genes. This provides a fundamental foundation for future studies of flowering time in soybean using fine mapping, map-based cloning, and molecular-assisted breeding.
- Research Article
- 10
- 10.2307/2463584
- Jan 1, 1999
- The American Naturalist
Exploring Cost Constraints on Stem Elongation in Plants Using Phenotypic Manipulation
- Research Article
- 44
- 10.1186/s12915-019-0642-8
- Mar 12, 2019
- BMC Biology
BackgroundThe nematode Caenorhabditis elegans has been extensively used to explore the relationships between complex traits, genotypes, and environments. Complex traits can vary across different genotypes of a species, and the genetic regulators of trait variation can be mapped on the genome using quantitative trait locus (QTL) analysis of recombinant inbred lines (RILs) derived from genetically and phenotypically divergent parents. Most RILs have been derived from crossing two parents from globally distant locations. However, the genetic diversity between local C. elegans populations can be as diverse as between global populations and could thus provide means of identifying genetic variation associated with complex traits relevant on a broader scale.ResultsTo investigate the effect of local genetic variation on heritable traits, we developed a new RIL population derived from 4 parental wild isolates collected from 2 closely located sites in France: Orsay and Santeuil. We crossed these 4 genetically diverse parental isolates to generate a population of 200 multi-parental RILs and used RNA-seq to obtain sequence polymorphisms identifying almost 9000 SNPs variable between the 4 genotypes with an average spacing of 11 kb, doubling the mapping resolution relative to currently available RIL panels for many loci. The SNPs were used to construct a genetic map to facilitate QTL analysis. We measured life history traits such as lifespan, stress resistance, developmental speed, and population growth in different environments, and found substantial variation for most traits. We detected multiple QTLs for most traits, including novel QTLs not found in previous QTL analysis, including those for lifespan and pathogen responses. This shows that recombining genetic variation across C. elegans populations that are in geographical close proximity provides ample variation for QTL mapping.ConclusionTaken together, we show that using more parents than the classical two parental genotypes to construct a RIL population facilitates the detection of QTLs and that the use of wild isolates facilitates the detection of QTLs. The use of multi-parent RIL populations can further enhance our understanding of local adaptation and life history trade-offs.
- Research Article
- 9
- 10.1007/s11295-018-1280-y
- Aug 27, 2018
- Tree Genetics & Genomes
Blush skin and flowering time are agronomic traits of interest to the Agricultural Research Council (ARC) Infruitec-Nietvoorbij pear breeding programme. The genetic control of these traits was investigated in the pear progeny derived from ‘Flamingo’ (blush cultivar) × ‘Abate Fetel’ (slightly blush) made up of 121 seedlings. Blush skin was scored phenotypically over three seasons and flowering time was scored over two seasons. A total of 160 loci from 137 simple sequence repeat (SSR) markers were scored in the progeny and used to construct parental genetic linkage maps. Quantitative trait loci (QTL) analysis revealed two QTLs for blush skin, a major QTL on linkage group (LG) 5 in ‘Flamingo’, and a major QTL on LG9 in ‘Abate Fetel’. Two SSR markers, NB101a and SAmsCO865954, were closely linked with the major QTL on LG5 in ‘Flamingo’, with alleles 139 bp and 462 bp in coupling, respectively. These markers were present in approximately 90% of the seedlings scored as good blush (class 4) based on the average data set. These two markers were used to genotype other pear accessions to validate the QTL on LG5 with the view of marker-assisted selection. Two candidate genes, MYB86 and UDP-glucosyl transferase, were associated with the QTL on LG5 and MYB21 and MYB39 were associated with the QTL on LG9. QTL analysis for flowering time revealed a major QTL located on LG9 in both parents. Marker GD142 with allele 161 bp from ‘Flamingo’ was present in approximately 88% of the seedlings that flowered earlier than either parent, based on the average data set. The QTLs and linked markers will facilitate marker-assisted selection for the improvement of these complex traits.
- Research Article
- 32
- 10.1094/pdis-08-14-0825-re
- Dec 15, 2015
- Plant Disease
A tropical gray leaf spot (GLS)-resistant line, YML 32, was crossed to a temperate GLS-susceptible line, Ye 478, to produce an F2:3 population for the identification of quantitative trait loci (QTL) associated with resistance to GLS. The population was evaluated for GLS disease resistance and flowering time at two locations in Yunnan province. Seven QTL using GLS disease scores and six QTL using flowering time were identified on chromosomes 2, 3, 4, 5, and 8 in the YML 32 × Ye 478 maize population. All QTL, except one identified on chromosome 2 using flowering time, were overlapped with the QTL for GLS disease scores. The results indicated that QTL for flowering time in this population strongly corresponded to QTL for GLS resistance. Among the QTL, qRgls.yaas-8-1/qFt.yaas-8 with the largest genetic effect accounted for 17.9 to 18.1 and 11.0 to 21.42% of variations for GLS disease scores and flowering time, respectively, and these should be very useful for improving resistance to GLS, especially in subtropical maize breeding programs. The QTL effects for resistance to GLS were predominantly additive in nature, with a dominance effect having been found for two QTL on the basis of joint segregation genetic analysis and QTL analysis.
- Research Article
- 48
- 10.1371/journal.pone.0090587
- Mar 4, 2014
- PLoS ONE
Plants are highly attuned to translating environmental changes to appropriate modifications in growth. Such phenotypic plasticity is observed in dense vegetations, where shading by neighboring plants, triggers rapid unidirectional shoot growth (shade avoidance), such as petiole elongation, which is partly under the control of auxin. This growth is fuelled by cellular expansion requiring cell-wall modification by proteins such as xyloglucan endotransglucosylase/hydrolases (XTHs). Cortical microtubules (cMTs) are highly dynamic cytoskeletal structures that are also implicated in growth regulation. The objective of this study was to investigate the tripartite interaction between auxin, cMTs and XTHs in shade avoidance. Our results indicate a role for cMTs to control rapid petiole elongation in Arabidopsis during shade avoidance. Genetic and pharmacological perturbation of cMTs obliterated shade-induced growth and led to a reduction in XTH activity as well. Furthermore, the cMT disruption repressed the shade-induced expression of a specific set of XTHs. These XTHs were also regulated by the hormone auxin, an important regulator of plant developmental plasticity and also of several shade avoidance responses. Accordingly, the effect of cMT disruption on the shade enhanced XTH expression could be rescued by auxin application. Based on the results we hypothesize that cMTs can mediate petiole elongation during shade avoidance by regulating the expression of cell wall modifying proteins via control of auxin distribution.
- Book Chapter
- 6
- 10.1007/978-3-642-37045-8_4
- Jan 1, 2013
Through selection by humans, crop plants are adapted to produce optimal yield in the areas where they are cultivated. Climate changes may cause stress to plants, disturb plant growth, and decrease plant yield. Food shortages due to crop failure may cause hunger particularly in poor countries. Therefore, it is important to develop new crop cultivars that can adapt to climate changes. This chapter summarizes quantitative trait loci (QTL) analysis and findings for candidate genes of traits related to tolerance to drought, heat, salinity, macronutrient and micronutrient deficiency, flooding, frost, particularly in major cereal crops. In addition, QTL studies on flowering time of cereal crops are also deliberated. Flowering time is a critical plant phase that determines the transition from the vegetative to the reproductive phase. The optimal time of flowering largely affects the overall yield. Information obtained from QTL analysis has been utilized in the development of stress-tolerant cultivars. Indeed, several stress-tolerant cultivars have been released in stress-prone areas. However, QTLs for most of the traits have not been elucidated. Fortunately, development in sequencing technologies has accelerated elucidation of the genomic regions conferring stress tolerance. This chapter also provides information regarding several recent technologies and approaches in QTL/gene mapping and also in plant breeding.
- Research Article
- 124
- 10.1007/s11295-011-0448-5
- Nov 30, 2011
- Tree Genetics & Genomes
The chilling and heat requirements and flowering time were studied, for 2 years, in an almond progeny from the cross between the late-flowering French selection “R1000” and the early-flowering Spanish “Desmayo Largueta”. These three temperature-dependent traits showed quantitative inheritance, although for chilling requirements and flowering time a major gene could be involved, modified by other minor genes. The results indicate that flowering time is mainly a consequence of the chilling requirements; heat requirements having a smaller effect. In agreement with the genetic findings, a significant Quantitative Trait Loci (QTL) for chilling requirements was found in G4 together with other minor QTLs in G1, G3, and G7. For heat requirements, two QTLs in G2 and G7 were identified. The results also show the high influence of temperature in the expression of the three traits and their QTL analyses. In addition, QTL analysis for flowering time allowed the identification of one significant QTL in linkage group 4 (G4) that explained most of the phenotypic variation together with other minor QTLs located in G1, G6, and G7.
- Book Chapter
- 5
- 10.1007/978-3-319-31703-8_3
- Jan 1, 2016
Quantitative traits exhibit continuous variation, indicating their control through multiple genes. Segregating populations are used to mine out associations between phenotypic and genotypic variations. Phenotyping performed for a specific trait and its variation in the population is justified with genotypic variation obtained through genetic markers application. A snapshot of genotypic variation is strictly dependent on the number and density of the markers applied. Parental and marker information is required to correlate genetic and phenotypic data for quantitative trait loci (QTL) analysis. For many years (now becoming obsolete), it has been of core importance to identify QTL with such methodology. Failure had to be faced by the researcher because the DNA region identified for phenotypic variation was much wider, and needed to be narrowed down by further dense marker application in that area to obtain required and accurate results. Nowadays the focus is on high-throughput technologies to obtain genome-wide resolution: high-throughput sequencing (HTS) is one of them. A comprehensive map of genomic variations can be produced with resequencing or reference genome sequences. Along with expression profiling, new molecular markers can be searched out with QTL analysis. Genomic-assisted breeding by studying the evolutionary variations in crops has many applied aspects as well. As compared to the conventional biparental population, presently the focus is on raising multiparent advanced generation inter-cross (MAGIC) populations to explore the genetic basis of quantitative traits. Probabilities of alleles of interest across the whole genome are calculated through the Hidden Markov Model (HMM). Different software packages (such as R-package, Qgene) are used for the estimates. Such whole-genome approaches in QTL analysis are a powerful and recently used technique. In this chapter, all these recent and modified modern techniques are reviewed with the most recent upcoming details. Traditional and modern QTL analyses have clearly been differentiated on applicable grounds.
- Research Article
- 96
- 10.1007/s00122-007-0610-5
- Jul 24, 2007
- Theoretical and Applied Genetics
Quantitative trait loci (QTL) analysis of yield influencing traits was carried out in Brassica juncea (AABB) using a doubled haploid (DH) mapping population of 123 lines derived from a cross between Varuna (a line representing the Indian gene pool) and Heera (representing the east European gene pool) to identify potentially useful alleles from both the parents. The existing AFLP based map of B. juncea was further saturated with RFLP and SSR markers which led to the identification of the linkage groups belonging to the A (B. rapa) and B (B. nigra) genome components of B. juncea. For QTL dissection, the DH lines were evaluated at three different environments and phenotyped for 12 quantitative traits. A total of 65 QTL spread over 13 linkage groups (LG) were identified from the three environments. QTL analysis showed that the A genome has contributed more than the B genome to productivity (68% of the total QTL detected) suggesting a more prominent role of the A genome towards domestication of this crop. The east European line, Heera, carried favorable alleles for 42% of the detected QTL and the remaining 58% were in the Indian gene pool line, Varuna. We observed clustering of major QTL in a few linkage groups, particularly in J7 and J10 of the A genome, with QTL of different traits having agronomically antagonistic allelic effects co-mapping to the same genetic interval. QTL analysis also identified some well-separated QTL which could be readily transferred between the two pools. Based on the QTL analysis, we propose that improvement in yield could be achieved more readily by heterosis breeding rather than by pure line breeding.
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