Abstract
BackgroundThe 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.ResultsThis 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.ConclusionsThis 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).
Highlights
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
Segregation of F1 for timing of flowering (TOF) This study explored the analysis of quantitative trait loci (QTL) for flowering time and biomass yield using a pseudo-testcross mapping population derived from two alfalfa cultivars, CW 1010 (♂) and 3010 (♀) with contrasting fall dormancy (FD) and Winter hardiness (WH)
The results indicate that flowering time manipulation in both dormant and non-dormant alfalfa is possible without affecting their dormancy levels, which is considered important for alfalfa adaptation to specific latitudes
Summary
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. Alfalfa TOF serves as a guideline for harvesting time as farmers often cut alfalfa at the early bloom stage Harvesting at the proper stage helps to balance forage quality, yield, and maintaining healthy stubbles for the future stand (https://crops.extension.iastate.edu/cropnews/2010/05/ when-make-first-spring-cut-alfalfa-and-mixed-alfalfagrass.). On the other hand, delayed flowering can be a desirable trait to minimize damage from abiotic stresses as well as to enhance biomass yield via longer vegetative growth [3]. Delayed flowering in alfalfa could be desirable for protecting the plants from late winter and early spring frost in addition to enhanced biomass yield. Photoperiod and temperature have great impacts on alfalfa flowering time and the underlying genetic factors are important to manipulate this trait (https://www.alfalfa.org/pdf/HowAnAlfalfaPlantDevelops.pdf.)
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