**5. Conclusion**

**Year Plant material Platform,** 

236 Applications of RNA-Seq and Omics Strategies - From Microorganisms to Human Health

2013 Parafield, Yarrum, Kaspa, 96–286 454 Roche,

2014 *Six spring sown*: Lumina, Hardy, Panache,

*P. sativum* ssp. *abyssinicum*: PI 358610

2017 SGE = JI3023 Illumina

Sequences (CAPS) markers for the particular transcript.

was used for pea salinity tolerance QTLs search [60].

Rocket, Kayanne, Terese

*P. fulvum*: P651

Frisson = JI2491 NGB1238 = JI0073 Sparkle = JI0427 Sprint‐2 = JI2612

*One winter sown*: Cherokee *One fodder*: Champagne 2014 *Pisum sativum*: CDC Bronco, Alfetta, Cooper, CDC Striker, Nitouche, Orb. **technique**

GS‐FLX

Roche 454, GS‐FLX

Roche 454, Titanium

HiSeq 2000, MACE

al. [59] Finale = JI2678

**Table 1.** Studies aimed at gene polymorphism detection in pea (*Pisum sativum* L.) using transcriptome NGS‐sequencing.

reduction is achievable by limiting sequenced mRNA regions. Since UTRs are generally more polymorphic than ORFs using sequences from the 3' and 5' mRNA, ends in SNV analysis should yield comparable results to those obtained with RNA‐seq. 3'MACE protocol for cDNA‐libraries preparation was used by Zhernakov et al. [59] to discover SNVs distinguish‐ ing six pea lines. Mapping MACE reads to the reference nodule transcriptome assembly of the pea line SGE [36] resulted in characterisation of over 34,000 polymorphic sites in more than 9700 contigs. Several of these SNVs were located within recognition sites of restriction endonucleases which allowed the design of co‐dominant Cleaved Amplified Polymorphic

SNVs are markers of choice now due to their abundance and the availability of high‐through‐ put screening techniques. SNV genotyping systems are now available, varying in the number of samples and markers to be genotyped, such as GoldenGate® and Infinium from Illumina Inc., SNPStream from Beckman Coulter and GeneChip from Affymetrix [61]. Illumina GoldenGate® oligonucleotide pool assay (OPA) designed for transcriptome‐discovered SNVs

As the pea genome is not sequenced yet, the genetic linkage maps are still relevant, since determination of loci responsible for target traits requires their fine mapping and subsequent

**Number of putative discovered SNVs**

**Number of putative discovered SSR‐sites**

**Number of created and mapped markers**

36,188 2932 705 Leonforte et

35,455 2397 1340 Duarte et al.

over 20,000 406 1536 Sindhu et al.

34,711 ‐ ‐ Zhernakov et

**References**

al. [60]

[33]

[35]

Next‐generation sequencing techniques make the analysis of differential gene expression and molecular marker development by transcriptome sequencing possible even in species lacking genomic information. Further development of sequencing and bioinformatics should substantially promote the investigation into genetics of non‐model plants. It is worth noting that numerous traits like effectiveness of symbioses development [62] or specific resistance to pathogens can only be studied in each particular cultivated plant species, most having limited genomic data available. In addition, the decline in biodiversity makes the investiga‐ tion of unique secondary metabolites inherent to non‐model medicinal plants a pressing matter.

Leguminous plants capable of improving the soil quality due to the formation of the mutual‐ istic symbioses with nodule bacteria and arbuscular mycorrhizal fungi are an integral part of agricultural systems. The genetics of most crop legumes lags behind that of model plants, and some are even considered 'orphan' crops, separated from the intense genomic studies due to a number of factors. Fortunately, the similarity of genome organisation, or 'genome synteny', characteristic for most related species, can help 'translate' the genomic data from the model legumes to their pulse crop relatives [63].

Using RNA‐seq technologies for de novo transcriptome assembly provides opportunities for finding novel genes and isoforms in non‐model species and investigation of their differential expression. Comparison to genomes and transcriptomes of closely related species can help determine the level of evolutionary distance between the two species and discover possible evolutionary pressures shaping contemporary species. Technologies for determining gene expression levels using transcript ends (like 3' and 5' MACE) can be used to conduct large‐ scale gene expression studies on a smaller budget. 5' MACE, a technology for simultane‐ ous analysis of prokaryotic and eukaryotic transcript abundancies, is particularly useful for studying plant‐bacteria interactions. Using transcriptome‐sequencing data in genetic marker development streamlines the construction of high‐quality genomic maps, crucial for routine gene identification tasks as well as potentially for refining genome assemblies for non‐model organisms. All the methods are useful in investigation of the unique phenotypes not present in the model plants, for example, *M. lupulina* MlS‐1 genetic line, uniquely dependent on the AM formation. Adaptation of standardised RNA‐seq approaches and data analysis devel‐ oped for model plants to an important crop culture *P. sativum* should facilitate the breeding of new cultivars that meet the requirements of the present‐day agriculture and possess the complex of beneficial traits, including increased efficiency of interactions with nodule bacteria and arbuscular‐mycorrhizal fungi.
