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      QTL mapping of flowering time and biomass yield in tetraploid alfalfa ( Medicago sativa L.)

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          Abstract

          Background

          The genetic and genomic basis of flowering time and biomass yield in alfalfa ( Medicago sativa L.) remains poorly understood mainly due to the autopolyploid nature of the species and the lack of adequate genomic resources. We constructed linkage maps using genotyping-by-sequencing (GBS) based single dose allele (SDA) SNP and mapped alfalfa timing of flowering (TOF), spring yield (SY), and cumulative summer biomass (CSB) in a pseudo-testcross F1 population derived from a fall dormant (3010) and a non-dormant (CW 1010) cultivars. We analyzed the quantitative trait loci (QTL) to identify conserved genomic regions and detected molecular markers and potential candidate genes associated with the traits to improve alfalfa and provide genomic resources for the future studies.

          Results

          This study showed that both fall dormant and non-dormant alfalfa cultivars harbored QTL for early and late flowering, suggesting that flowering time in alfalfa is not an indicator of its fall dormancy (FD) levels. A weak phenotypic correlation between the flowering time and fall dormancy (FD) in F1 and checks also corroborated that alfalfa FD and TOF are not the predictors of one another. The relationship between flowering time and alfalfa biomass yield was not strong, but the non-dormant had relatively more SY than dormant. Therefore, selecting superior alfalfa cultivars that are non-dormant, winter-hardy, and early flowering would allow for an early spring harvest with enhanced biomass. In this study, we found 25 QTL for TOF, 17 for SY and six QTL for CSB. Three TOF related QTL were stable and four TOF QTL were detected in the corresponding genomic locations of the flowering QTL of M. truncatula, an indication of possible evolutionarily conserved regions. The potential candidate genes for the SNP sequences of QTL regions were identified for all three traits and these genes would be potential targets for further molecular studies.

          Conclusions

          This research showed that variation in alfalfa flowering time after spring green up has no association with dormancy levels. Here we reported QTL, markers, and potential candidate genes associated with spring flowering time and biomass yield of alfalfa, which constitute valuable genomic resources for improving these traits via marker-assisted selection (MAS).

          Electronic supplementary material

          The online version of this article (10.1186/s12870-019-1946-0) contains supplementary material, which is available to authorized users.

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          Most cited references32

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          Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome.

          Genetic architecture of flowering time in maize was addressed by synthesizing a total of 313 quantitative trait loci (QTL) available for this trait. These were analyzed first with an overview statistic that highlighted regions of key importance and then with a meta-analysis method that yielded a synthetic genetic model with 62 consensus QTL. Six of these displayed a major effect. Meta-analysis led in this case to a twofold increase in the precision in QTL position estimation, when compared to the most precise initial QTL position within the corresponding region. The 62 consensus QTL were compared first to the positions of the few flowering-time candidate genes that have been mapped in maize. We then projected rice candidate genes onto the maize genome using a synteny conservation approach based on comparative mapping between the maize genetic map and japonica rice physical map. This yielded 19 associations between maize QTL and genes involved in flowering time in rice and in Arabidopsis. Results suggest that the combination of meta-analysis within a species of interest and synteny-based projections from a related model plant can be an efficient strategy for identifying new candidate genes for trait variation.
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            Genomic plant DNA preparation from fresh tissue-CTAB method. -

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              Genetic control of flowering time in legumes

              The timing of flowering, and in particular the degree to which it is responsive to the environment, is a key factor in the adaptation of a given species to various eco-geographic locations and agricultural practices. Flowering time variation has been documented in many crop legumes, and selection for specific variants has permitted significant expansion and improvement in cultivation, from prehistoric times to the present day. Recent advances in legume genomics have accelerated the process of gene identification and functional analysis, and opened up new prospects for a molecular understanding of flowering time adaptation in this important crop group. Within the legumes, two species have been prominent in flowering time studies; the vernalization-responsive long-day species pea (Pisum sativum) and the warm-season short-day plant soybean (Glycine max). Analysis of flowering in these species is now being complemented by reverse genetics capabilities in the model legumes Medicago truncatula and Lotus japonicus, and the emergence of genome-scale resources in a range of other legumes. This review will outline the insights gained from detailed forward genetic analysis of flowering time in pea and soybean, highlighting the importance of light perception, the circadian clock and the FT family of flowering integrators. It discusses the current state of knowledge on genetic mechanisms for photoperiod and vernalization response, and concludes with a broader discussion of flowering time adaptation across legumes generally.
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                Author and article information

                Contributors
                cssamm@uga.edu
                Journal
                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                1471-2229
                16 August 2019
                16 August 2019
                2019
                : 19
                : 359
                Affiliations
                ISNI 0000 0004 1936 738X, GRID grid.213876.9, Institute of Plant Breeding, Genetics and Genomics and Department of Crop and Soil Sciences, , The University of Georgia, ; Athens, GA USA
                Author information
                http://orcid.org/0000-0003-1710-1142
                Article
                1946
                10.1186/s12870-019-1946-0
                6697951
                00e46e14-8758-4988-b518-3a05a8243621
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 12 February 2019
                : 26 July 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100005825, National Institute of Food and Agriculture;
                Award ID: 1008718
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Plant science & Botany
                alfalfa,medicago truncatula,gbs,single dose allele,flowering qtl,biomass
                Plant science & Botany
                alfalfa, medicago truncatula, gbs, single dose allele, flowering qtl, biomass

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