Flax
(Linum usitatissimum L., 2n = 30),
also known as flax or linseed, is an annual and self-pollinated species. It has
been propagated for its seed oil or stem fibres and for dual purpose since several
1,000 years (Dillman1953; Zohary1999). It is a versatile crop cultivated in diverse environments for fibre,
food, industrial, feed and possibly pharmaceutical uses. Flax was a potential
commercial crop before the discovery of petroleum and vast use of cotton
(McHughen1990).The bast or phloem fibres have remarkable mechanical properties
(Ferna´ndez2016) with flexibility and strength. Because of the multipurpose uses
and sustainability, there is revived interest in its breeding and cultivation. Further
information on the genetic basis of variation is needed to enable modern
breeding manipulating the biodiversity in the species and its wild relatives (McKenzie
et al. 2008; Kurt and Evans 1998). Utilization
and characterization of flax genetic resources and analysing of flax genetic diversity
are piovital for flax germplasm management and breeding. Molecular
or DNA markers have been used since almost half a century, and more than 20
types of DNA markers systems have since been established (Agarwal et al.2008).
Among the different kinds of markers accessible, Simple Sequence Repeats (SSRs)
are designated as the best preferred for different research because of their
high variability and ubiquitous occurrence (Powell et al. 1996).
The high variability of these microsatellites is mainly due to the differing
numbers of repeats in the region of the repeated motif, and also due to short
insertion/deletion events (Kalia et al. 2011). Presently,
SSR markers have been used for the analysis of genetic diversity, the
construction of linkage maps, and for QTL mapping in many plant species
(Dettoriet al. 2015; Qin et al. 2015; Bohra et al. 2017;
Luo et al.2017; Mohamed et al. 2019). Most recently, some SSR
markers have also been developed in flax (Cloutier et al. 2009, 2011, 2012;Soto-Cerda
et al. 2011; Wu et al. 2017). Researchers have developed a cost-effective method to identify
SSRs using bioinformatics to mine sequences in public databases. For example,
Cloutier et al. (2009) identified 851 putative SSRs and designed 662 primer pairsbased
on a set of 146,611 expressed sequence tags generated from 10 flax cDNA
libraries, and Soto-Cerda et al. (2011) evaluated
a total of 3242 flax genomic sequences to identify SSRs. Further, Wuet al. (2017)
screened 1574 microsatellites using reduced representation genome sequencing
(RRGS) to systematically
identify SSR markers and evaluate marker sensitivity and specificity based on
48 flax isolate samples. Nonetheless, in connection with the density of SSR
markers in rice, wheat, and other crops (Collard et
al. 2008;
Bracci et al. 2011; Waqas et al.2014), the number of SSR markers in flax is meager, and
information on these SSR markers is still a lacuna, making it cumbersome to
meet the needs of molecular analyses. Furthermore, no earlier studies have
characterized SSRs throughout the flax genome. The possibility of the flax
genome sequence (Wang et al. 2012; You et al. 2018) has permitted the scanning of the whole genome heading to
the identification of microsatellites that can be used for molecular analysis.
With contemporary improvements in the sequencing of the flax genome (You et al.
2018), SSR markers
can now be precisely assigned to particular locations on flax chromosomes, this
further improves the accuracy of molecular analyses. Starting with strategic
crop improvement programs, knowledge and concept about the extent of genetic variability
and population structure of the crop concern laid an important mile stone. Knowledge
on population structure has important significance because population structure
is the main source of spurious associations (Chaoet al. 2010; Flint-Garcia et al. 2003). As L. usitatissimum has a long and complex domestication,
divergent breeding history, and considering its limited gene flow, it is assumed
that flax seed populations display complex population structures. Association Mapping
(AM) takes the favour of a large range
of germplasm including natural populations and collections of varieties and breeding
lines to map traits by linkage disequilibrium (LD), that is the non-random association
of alleles at different loci (Myles et al. 2009). The main recognition of AM is its high resolution in determining
the correlation between polymorphisms and QTL based on thousands of meiotic
events aggregated during the shared history of the individuals in a population.
Hence, population structure must be inspected to determine the ability for
association analyses (Song et al.2009). Crop species studied till date do not fit the demographic
supposition of the standard equilibrium neutral model, and thus despair from neutral
expectation is relatively common, providing proof of the existence of stratification, specifically
in self pollinated species (Maccaferri et al. 2005; Song et al.2009). Further, assessing the genetic similarity among the
accessions of the targeted population is an important necessity for the
identification of nonredundant core collections suitable for optimizing LD estimation
and association studies (Maccaferri et al.2005). Novel advances in DNA sequencing have facilitated the
rapid development of genomic SSR (gSSR; Deng et al. 2010; Roose-Amsaleg et al.2006; Soto-Cerda et al. 2011a) and expressed sequence tag SSR markers in flax
(EST-SSR; Cloutier et al. 2009; Soto-Cerda et al. 2011b). Seeing that SSR markers are dispersed throughout the
genome, occur in both protein-coding and non-coding regions, show co-dominant
inheritance and high information content, they have become the marker of choice
for population genetic studies (Ellis and Burke 2007) and to investigate patterns of LD (Flint-Garcia et al. 2003). Quantitative
trait loci (QTL) and association mapping (AM) are integral approaches for the
identification of marker-trait association studies (MTA). Association Mapping
can accomplish higher mapping resolution through high numbers of historical recombination
events in germplasm collections. An quintessential association panel should dock
the broadest genetic diversity because this is often correlated with a rapid LD
decay essential to resolve complex trait variation(s) to single gene or
nucleotide []. Null or weak population structure and a low level of relatedness
among individuals of the germplasm collection are also alluring. Thus, genetic
diversity, population structure, familial relatedness and LD patterns are
pivotal features to be assessed prior to AM analyses to fully escapade their
advantages for flax genetic improvement. In this study we genotyped 264 flax
accessions using 28 microsatellite loci. The overall
goal of the study was to evaluate the usefulness of this flax world collection
for AM studies. Our specific goals were:
(1) to investigate the genetic diversity; (2) to estimate the levels of
population structure and assess familial relatedness; (3) to detect the patterns
of LD; and (4) to identify non-neutral genomic regions potentially underlying
divergent selection between fiber and linseed types. Our study will provide a useful tool for the molecular
analysis of flax in the future.
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