Genetic dynamics underlying phenotypic development of biomass yield in triticale

Abstract

BackgroundThe nature of dynamic traits with their phenotypic plasticity suggests that they are under the control of a dynamic genetic regulation. We employed a precision phenotyping platform to non-invasively assess biomass yield in a large mapping population of triticale at three developmental stages.ResultsUsing multiple-line cross QTL mapping we identified QTL for each of these developmental stages which explained a considerable proportion of the genotypic variance. Some QTL were identified at each developmental stage and thus contribute to biomass yield throughout the studied developmental phases. Interestingly, we also observed QTL that were only identified for one or two of the developmental stages illustrating a temporal contribution of these QTL to the trait. In addition, epistatic QTL were detected and the epistatic interaction landscape was shown to dynamically change with developmental progression.ConclusionsIn summary, our results reveal the temporal dynamics of the genetic architecture underlying biomass accumulation in triticale and emphasize the need for a temporal assessment of dynamic traits.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-458) contains supplementary material, which is available to authorized users.

Accuracy of within‐ and among‐family genomic prediction in triticale

“…Frost tolerance was scored at one environment (Liu et al. b) and Fusarium head blight resistance at four environments as described previously (Kalih et al. ).…”

“…Plant material, field trials and phenotypic data: The plant material and the field trials have been described previously and the data used for QTL mapping of various traits (Busemeyer et al 2013a, Liu et al 2014a,b, 2015. In brief, the study is based on a mapping population with 647 doubled haploid (DH) (W€ urschum et al 2012b, 2015) triticale lines derived from four families designated DH06 (n = 131; parents Modus 9 Saka3006), DH07 (n = 120; parents Modus 9 Saka3008), EAW74 (n = 200; parents HeTi117-06 9 Pawo) and EAW78 (n = 196; parents HeTi117-06 9 TIW671) which have been described by Alheit et al (2011).…”

Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non‐invasive phenotyping

“…These and the vast majority of other QTL studies in plants assessed the expression of traits at a certain stage, frequently at final harvest or at the time point when a certain developmental stage such as flowering and kernel architecture has been reached (Buckler et al ., ; Hung et al ., ; Cook et al ., ). More recently, some studies have been reported on dynamically acting genetic factors in plants assessed via monitoring trait expression at multiple time points (Yan et al ., ; Bian et al ., ; Busemeyer et al ., ; Moore et al ., ; Liu et al ., ; Würschum et al ., ,b; Bac‐Molenaar et al ., ).…”

“…Recently, a population of 647 doubled haploid triticale lines have been evaluated in a field trial using a partially replicated design and a field phenotyping platform (“BreedVision”) that was used to derive plant biomass and height estimates at three developmental stages and to map QTL showing main and epistatic effects (Busemeyer et al ., ; Liu et al ., ; Würschum et al ., ,b). In addition to QTL with detectable effects at all three developmental stages, also QTL effective at two stages or only one stage were identified emphasizing the existence of permanently expressed QTL and stage‐specifically expressed QTL.…”

Populations of doubled haploids for genetic mapping in hexaploid winter triticale

“…Putative rearrangements involving chromosomes 2A, 2B, and 6A in triticale have already been suggested (Tyrka et al 2011 ) and may represent a form of adaptive genome rearrangements in an amphiploid. Inconsistencies in position of genetic markers may influence detection and localization of effects contributing to plant height and biomass yield in a triticale (Busemeyer et al 2013 , Alheit et al 2014 , Liu et al 2014 , Würschum et al 2014a , b , Liu et al 2017 ).…”