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GENETIC MOLECULAR MARKERS TO ACCELERATE GENETIC GAINS IN CROPS

Rajaguru Bohar1 Center of Excellence in Genomics & Systems Biology,International
Crops Research Institute for The Semi-Arid Tropics (ICRISAT),Hyderabad,IndiaView
further author information
,
Annapurna Chitkineni1 Center of Excellence in Genomics & Systems
Biology,International Crops Research Institute for The Semi-Arid Tropics
(ICRISAT),Hyderabad,IndiaView further author information
&
Rajeev K Varshney1 Center of Excellence in Genomics & Systems
Biology,International Crops Research Institute for The Semi-Arid Tropics
(ICRISAT),Hyderabad,IndiaCorrespondencer.k.varshney@cgiar.org
https://orcid.org/0000-0002-4562-9131View further author information
Pages 158-160 | Received 07 May 2020, Accepted 13 May 2020, Published online: 27
May 2020
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 * https://doi.org/10.2144/btn-2020-0066
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The advent of molecular marker technology changed methods of plant breeding in a
positive direction. Since the boom of the genomic sequencing era, several
advancements and innovations originating in the field of molecular markers are
enhancing the pace of crop improvement. Over the decades, many reviews on
molecular markers have been published, especially pertaining to their
application in plant breeding. Here we provide an update on the evolution of
marker technologies and their applications for accelerating genetic gains in
crops.

Genetic markers can be described as genetic differences between individual
organisms or species. We have previously provided an account of the concept,
methods and applications for easy understanding by early career researchers
[Citation1]. The markers do not represent the target genes themselves
essentially but act as ‘signs’ or ‘flags’ and can be classified into three major
types: morphological, biochemical and DNA markers. Classification is based on
the allelic variation caused by phenotypic traits, isozymes and sites of
variation in DNA, respectively [Citation2]. To select an efficient marker
system, several criteria are considered. For instance, Gupta et al. suggested a
set of criteria for an efficient marker system applicable to crop improvement:
primarily the markers should be highly polymorphic, evenly distributed,
preferably codominant, distinctly allelic, single-copy, cost-efficient and
amenable to automation [Citation3].

Different types of molecular marker systems such as restriction fragment length
polymorphisms (RFLPs), random-amplified polymorphic DNAs (RAPDs), amplified
fragment length polymorphisms (AFLPs), Diversity Arrays Technology (DArT) and
simple sequence repeats (SSRs) have been utilized in plant breeding during the
last several years. Among these marker systems, SSR markers have been used
extensively, primarily due to their high polymorphism rate and the ability to be
performed on commonly available lab equipment [Citation4].

The most advanced and commonly used marker systems, however, are single
nucleotide polymorphisms (SNPs). Their abundance in the genomes of all organisms
and amenability to automation, leading to low-cost, high-throughput genotyping,
makes SNPs the most widely adopted marker system for various genomic
applications [Citation5]. Technological developments including TaqMan and KASP™
(Kompetitive Allele-Specific Polymerase chain reaction) revolutionized SNP
genotyping for individual and multiplexed SNP marker microarray platforms, such
as Infinium (Illumina, Inc.) or Affymetrix/Axiom (Thermo Fisher), respectively.
Technical optimization and development of breeding specific marker sets brought
down the cost of genotyping arrays, making them affordable for utilization in
crop improvement [Citation6,Citation7]. Medium-density SNP panels were also
developed, such as 1K-Rice Custom Amplicon (1k-RiCA), an amplicon panel of ∼1000
SNPs based on the custom sequencing improvement [Citation8]. The Illumina
BeadXpress SNP genotyping platform (Illumina, Inc.) has also been utilized for
smaller sets of SNPs for breeding applications; SNP genotyping panels have been
developed and utilized in several crops including rice, wheat, chickpea and
pigeon pea [Citation6,Citation7,Citation9]. However, in order to develop such
SNP genotyping panels, SNP discovery/ identification is a prerequisite. To save
time and costs in SNP genotyping, genotyping-by-sequencing (GBS) and its various
forms have been optimized for simultaneous SNP discovery and genotyping. A
detailed comparison of different SNP genotyping technologies has been provided
by Mir et al. [Citation10].

In the context of using markers for crop improvement, it is important to analyze
different components of ‘the breeder’s equation’ (ΔG = (σa) (i) (r) / L) that
assesses genetic gain (ΔG). It has the following components: additive genetic
variation within the population (σa), selection intensity (i), selection
accuracy (r) and number of years per cycle (L). In this direction, Cobb et al.
[Citation11] suggested that optimum contribution selection can be achieved and
ΔG can be enhanced in plant breeding by deploying molecular marker technology.
Developing a larger population and screening early generations for molecular
markers associated with ‘must-have’ traits (forward breeding) can enhance i.
Similarly, selection of lines for advancing generation through marker-assisted
selection (MAS) can enhance r. Genomics-assisted breeding (GAB) [Citation12] and
the ‘5 Gs’ breeding approach [Citation13] have also been suggested as ways to
use a range of genomics approaches and tools to enhance the precision and
efficiency of breeding to deliver higher genetic gains in farmers’ fields
[Citation14].

For successful GAB, apart from using genomic tools and approaches, efficient and
effective analytical and decision support tools (ADSTs) have been suggested as
‘must haves’ to evaluate and select plants for the next generations in crop
breeding; Varshney et al. proposed combining ADSTs with several molecular
breeding applications such as marker-assisted back crossing (MABC) or MAS,
marker-assisted recurrent selection and GS [Citation15]. If the markers for a
particular trait are available, they can be used in a MAS/MABC approach and
superior lines can be selected effectively by using ADSTs. MARS and GS are two
other molecular approaches to crop breeding that should make the best use of
ADSTs for the accumulation of superior alleles and for enhancing genetic gains,
respectively [Citation15].

Apart from GAB, markers have also been employed successfully in supporting
breeding tools such as doubled haploid (DH) technology. DH and MAS technology
have been combined in an integrated MAS-DH approach and utilized to increase
genetic gain for biotic and abiotic stress tolerance in maize breeding; Xu et
al. critically reviewed the factors for optimizing the combination of methods to
maximize the cost–effectiveness of the breeding programs [Citation16]. These
factors include logistics planning and stakeholder engagement. This integrated
MAS-DH approach has also been reported for developing superior restoration lines
for hybrid rice breeding, indicating its high impact in commercial breeding
programs.

The availability of several marker-based platforms for low- to high-throughput
genotyping mandates proper decision-making to choose the appropriate marker
system, depending on the objectives and field of application. High-density
genotyping platforms for discovery studies and linkage mapping experiments, and
medium-density genotyping platforms for GS, genetic diversity analyses and
background selection have been suggested [Citation17]. Low-density genotyping
platforms such as KASP can be well utilized for routine breeding applications
like forward breeding through MAS, MABC and quality control analysis
[Citation17].

While the integration of genomics in breeding is essential to accelerate genetic
gains in developing countries, there are several challenges, especially in terms
of generating genotyping data by establishing laboratories with high-end
equipment and running them in a cost-effective and sustainable manner. Several
articles have suggested outsourcing genotyping as a means of providing the data
for lower cost in less time [Citation14,Citation18,Citation19]. However, in this
context, it remains essential to develop capacity for data analysis and
decision-making to select superior lines. Many genotyping and sequencing
centers, for example the Center of Excellence in Genomics & Systems Biology at
ICRISAT [Citation20], are providing genotyping services as well as training the
next generation of scientists so that molecular markers can be used in breeding
applications in developing countries.

Several collaborative projects and platforms such as the High Through-Put
Genotyping (HTPG) Project [Citation21], the Genomic Open Breeding Informatics
Initiative (GOBii) [Citation22], the Integrated Breeding Platform [Citation23]
and the CGIAR Excellence in Breeding (EiB) platform [Citation24] are providing
shared genotyping services, analytical tools and decision support systems for
modernization of breeding across CGIAR centers as well as assisting several
national agricultural research systems in developing countries. For instance,
ICRISAT is leading the HTPG project in collaboration with IRRI, CIMMYT and EiB
with the financial support of the Bill & Melinda Gates Foundation. The HTPG
project facilitates low-cost, high-throughput genotyping for CGIAR, NARS and
small-medium private sector organizations by aggregating the genotyping demand,
mainly for forward breeding applications. Through a collaborative agreement,
Intertek-AgriTech [Citation25] offers the genotyping services for HTPG as an
external service provider. The HTPG platform, at present, offers SNP genotyping
services for over 100 traits in 18 crops with fully flexible pricing, with an
initial set-up cost of US$1.60–1.80 per sample and an incremental cost of
US$0.05–0.20 per SNP, including DNA isolation. HTPG services are well utilized
by breeders of 8 CGIAR centers and over 30 NARS partners, in addition to the
private sector, in 28 countries, mostly in south Asia and sub-Saharan Africa. As
a result, the HTPG project has streamlined integration of molecular markers into
breeding applications in about 28 countries around the world.

In summary, molecular markers are one among many tools available in the
breeders’ toolkit. Adopting integrated breeding approaches by carefully
selecting the right tools will help in accelerating the rate of genetic gain in
breeding programs [Citation14]. These tools should be combined with ADSTs
through open-source platforms; this approach, together with the adoption of
shared genotyping services like HTPG and data management systems, would
facilitate efficiency in GAB approaches. Proper cost analysis is crucial before
adopting modern technologies together with the addition of innovative concepts.
Careful consideration of economical, logistical and technical factors will help
to achieve the full success of integrating different molecular strategies into
plant breeding programs [Citation26]. Finally, integrated breeding approaches by
combining efficient genotyping, phenotyping and ADSTs will help to accelerate
the rate of genetic gain in staple food crops. This will address threats like
climate change through delivery of better varieties to farmers, and ensure the
security of global food and nutrition.


AUTHOR CONTRIBUTIONS

RK Varshney conceived the idea, R Bohar and A Chitkineni contributed to writing
different sections and RK Varshney together with R Bohar and A Chitkineni
finalized the manuscript.




FINANCIAL & COMPETING INTERESTS DISCLOSURE

The authors are thankful to the Bill and Melinda Gates Foundation for supporting
‘Shared Industrial-scale Low-density SNP Genotyping for CGIAR and Partner
Breeding Programs Serving SSA and SA’ (High Through-put Genotyping – HTPG)
project (OPP1130244). The authors have no other relevant affiliations or
financial involvement with any organization or entity with a financial interest
in or financial conflict with the subject matter or materials discussed in the
manuscript apart from those disclosed. No writing assistance was utilized in the
production of this manuscript.


ADDITIONAL INFORMATION


FUNDING

The authors are thankful to the Bill and Melinda Gates Foundation for supporting
‘Shared Industrial-scale Low-density SNP Genotyping for CGIAR and Partner
Breeding Programs Serving SSA and SA’ (High Through-put Genotyping – HTPG)
project (OPP1130244). The authors have no other relevant affiliations or
financial involvement with any organization or entity with a financial interest
in or financial conflict with the subject matter or materials discussed in the
manuscript apart from those disclosed. No writing assistance was utilized in the
production of this manuscript.



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