Introduction
Plant traits are often correlated, either positively or negatively,
which has been ecologically explained to reflect the trade‐offs in
biological functions and resource allocation, and allometric scaling
(Freschet et al., 2015; Agrawal, 2020). The traits could become
correlated due to common evolutionary processes such as correlated
selection (Armbruster et al., 2014). The plant height and seed size
scaling are manifested as a positive correlation between the two traits,
and it sits within the broad allometric scaling that describes the
relative growth rates of different body parts following a positive
correlation of an individual organ versus total body size. Allometric
scaling emerges as one of a seemly universal law in biology from genomes
to ecosystems (West & Brown, 2005). Over the past century, many
morphological, ecological, and evolutionary size-correlated trends have
been observed across organisms and life forms (Kleiber, 1947, 1975;
McMahon & Bonner, 1983; Schmidt-Nielson, 1984; Niklas, 1994; Brown &
West, 2000; Moles et al., 2004; Novack-Gottshall., 2008; Vasseur et al.,
2018). Various of conceptual frameworks have been proposed when seeking
the underlying mechanisms of the broadly observed allometric scaling
(e.g. Charnov et al., 1993; Blum, 1977; West et al., 1997; Darveau et
al., 2002; Weibel, 2002, Niklas, 2004; Moles et al. 2005; Grubb et al.
2005; Rees & Veranble, 2007; Falster et al. 2008, Veranble and Rees,
2009, Westoby et al., 2009). The mechanism underlying the scaling law
and traits correlation requires genetic explanations, but that is less
explored in the current research endeavour.
Pleiotropy has been proposed as a significant mechanism leading to trait
correlation (Saltz et al., 2017). Pleiotropy is defined as the
phenomenon in which a genetic variant influences two or more phenotypic
traits. The pleiotropic genetic variant may only have a single function,
but it is involved in multiple biological processes; alternatively, the
variant could have multiple functions that are related to different
traits (Blow & Hoffmann, 2005; Hine et al., 2014; Saltz et al., 2017).
Trait correlation could also be the effect of genetic linkage, e.g. the
co-selection of gene variants closely linked to selected loci of
interest in the chromosome leading the correlation of trait expression,
as physical linkage based correlations can be stable over many
generations in species with low recombination rate (Agrawal et al.,
2010; Langridge & Fleury, 2011). The recent advancements of high
throughput genotyping and large scale phenotyping offers an opportunity
to decipher the different genetic basis of trait correlation.
Genome-wide association studies (GWAS) reveal single nucleotides
polymorphisms (SNPs) that are significantly associated with a particular
phenotype (Xiao et al., 2017), therefore allows identifying genetic
variants that influence more than one trait. Further, if the physical
position on the chromosome of the responsible genetic variants is known,
their genetic linkage can be examined. Recently, genomic structural
equation modelling (genomic SEM) emerges as a powerful method for
deciphering the joint genetic architecture of multiple traits. Genomic
SEM models shared genetic architecture across multiple phenotypes with
factors representing broad genetic liabilities through common factors
analysis (Grotzinger et al., 2019). Therefore, genomic SEM offers an
opportunity to not only directly explore pleiotropy as a genetic
explanation on trait correlation, but also to describe pleiotropic
genetic variants that may have driven the trait correlation.
Moreover, plant height and seed size (weight) are important agronomic
traits in cereal crops and pulses. The pattern and evolution of plant
height and seeds weight scaling might be affected by direct selection,
as domestication and modern breeding often target the two traits in
opposite directions. For example, shorter and stiffer stems protect
cereal crops against lodging and provide a significant yield
improvement, referred as ‘Green Revolution’ in literatures (Langridge,
2014). Larger seeds for consumption might have been one of the selection
goals in the domestication and breeding of grains and pulses (Milla et
al., 2015). However, it is still largely unknown if the artificial
selection such as domestication and intense breeding change the pattern
of size scaling. Barley (Hordeum vulgare L.) is one of the most
important cereal crops in Old World agriculture and has been
domesticated 10,000 years ago (Badr et al., 2000). Barley has been
subject to extensive genomic study with abundant genomic and phenotypic
data resources available (e.g. Mascher et al., 2017; Gonzalez et al.,
2018; He et al., 2019; Milner et al. 2019), which provides unprecedented
opportunity to explore the genomic basis of size scaling in plants. Here
we use the recently generated high-density genome-wide SNP profile for a
diverse set of barley samples, and their measurements of plant height
and seeds weight to identify the possible genetic mechanisms that may
lead to a correlation of plant height and seeds weight to explore the
genomic basis of size scaling in plants.