Dissecting Key Adaptation Traits in the Polyploid Perennial Medicago sativa Using GBS-SNP Mapping

Abstract

Understanding key adaptation traits is crucial to developing new cultivars with broad adaptations. The main objective of this research is to understand the genetic basis of winter hardiness (WH) and fall dormancy (FD) in alfalfa and the association between the two traits. QTL analysis was conducted in a pseudo-testcross F1 population developed from two cultivars contrasting in FD (3010 with FD = 2 and CW 1010 with FD = 10). The mapping population was evaluated in three replications at two locations (Watkinsville and Blairsville, GA). FD levels showed low to moderate correlations with WH (0.22–0.57). Assessing dormancy in winter is more reliable than in the fall in southern regions with warm winters. The mapping population was genotyped using Genotyping-by-sequencing (GBS). Single dose allele SNPs (SDA) were used for constructing linkage maps. The parental map (CW 1010) consisted of 32 linkage groups spanning 2127.5 cM with 1377 markers and an average marker density of 1.5 cM/SNP. The maternal map (3010) had 32 linkage groups spanning 2788.4 cM with 1837 SDA SNPs with an average marker density of 1.5 cM/SNP. Forty-five significant (P < 0.05) QTLs for FD and 35 QTLs for WH were detected on both male and female linkage maps. More than 75% (22/28) of the dormancy QTL detected from the 3010 parent did not share genomic regions with WH QTLs and more than 70% (12/17) dormancy QTLs detected from CW 1010 parent were localized in different genomic regions than WH QTLs. These results suggest that the two traits have independent inheritance and therefore can be improved separately in breeding programs.

Detection of Quantitative Trait Loci (QTL) associated with the spring regrowth vigor trait in alfalfa (Medicago sativa L.)

“…The QTL analysis performed in this study revealed that some of the QTL associated with spring vigor were located at a similar region as those associated with fall dormancy and winter injury in previous studies [16,17]. Adhikari et al (2018) mapped four QTL associated with winter injury on chromosome Unfortunately, there was no QTL located in the same or similar interval to the QTL associated with fall dormancy in their study [17]. identified six QTL associated with fall dormancy on chromosomes 4, 6 and 7, and five QTL associated with winter injury on chromosomes 3 and 7 [16].…”

“…This notion indicates that QTL mapping analysis of complex quantitative traits in alfalfa could be challenging and that large populations will be needed [33]. Compared with other QTL mapping populations in alfalfa [12,17] and other species [34,35], the population in our study was sufficiently large for the QTL mapping of spring regrowth vigor traits.…”

“…Major QTL related to yield [12,13], flowing time [14], water use efficiency [15], fall dormancy and winter-hardiness [16,17] and leaf rust resistance [18] have been mapped in tetraploid alfalfa. Mccord et al (2014) identified QTL and markers associated with forage yield, resistance to lodging, and spring vigor in alfalfa [19].…”

Evaluation of Different Fall Dormancy-Rating Alfalfa Cultivars for Forage Yield in a Semiarid Environment

“…Brummer et al [10] and Lauriault et al [11] described other fall dormancy-rating as fall dormant (FD 1-3), semi-fall dormant (FD 4-6), non-fall dormant (FD 7-9), and extremely non-fall dormant (FD 10-11). Photoperiodism and air temperature in fall and throughout winter determine alfalfa fall dormancy which is related to plant growth, biomass accumulation and abiotic stresses tolerance of the alfalfa plant [7,[12][13][14][15]. Fall dormant alfalfa cultivars go dormant the earliest, have reduced shoot elongation in the fall and survive better throughout winter, whereas extremely non-fall dormant cultivars continue to grow, have the tallest plant height in the fall, and generally do not have good survival over the winter [16,17].Alfalfa forage productivity is impacted by its fall dormancy-rating that has correlation with forage nutritive value, plant survival, root characteristics, and persistence [8,[18][19][20][21][22][23][24].…”

QTL Mapping for Growth-Related Traits by Constructing the First Genetic Linkage Map in Simao pine

“…In other words, the multi-environment QTL analysis is more accurate than singleenvironment experiment for the heterozygous perennial woody tree growth-related traits QTL mapping (El-Soda et al, 2014). Thus, to eliminate interference brought by environment and improve QTLs accuracy, the multi-environment QTL test in other environments using different backgrounds for Simao pine must be carried out in future Adhikari et al, 2018). Table 6 Quantitative trait loci (QTLs) for growth-related traits during 3 years in the mapping population The high-density linkage map of Simao pine A black bar indicates a SLAF marker.…”