- High-Throughput Genomics: Application in Plant Breeding under Abiotic Stress Conditions
- Tools for Studying Functional Genome Editing in Plants
- Potential Use of Genome Editing in Generating Abiotic Stress Tolerance
- Next-Generation Sequencing for Screening the Plant Genome
- Use of Quantitative Trait Loci (QTL) Mapping and Genomics-Assisted Breeding (GAB) in Generating Abiotic Stress Tolerance
High-Throughput Genomics: Application in Plant Breeding under Abiotic Stress Conditions
Aditya Banerjee and Aryadeep Roychoudhury
Abiotic stresses like salinity, drought, temperature, light, heavy metal toxicity, etc., are altogether major agricultural constraints across the world (Banerjee et al. 2018, 2019; Banerjee and Roychoudhury 2018a, b, c, d, e). In spite of exhaustive research in this field, a concise blueprint regarding the genetic regulation of abiotic stress signaling in plants has not yet been fully explored. Among the identified molecular components, the majority have been used to genetically engineer stress tolerance in model or crop plants. This has led to increased yield and stress adaptation in specific cases but with less precision (Banerjee and Roychoudhury 2018f; Banerjee and Roychoudhury 2019a, b). Hence the use of functional genomics is popularly advertised to ensure high-quality precision in genomic modification. The availability of genome databases of various model and crop plants along with efficient genomeediting tools has opened up the opportunity to incorporate targeted manipulations in the genome and record the functional aspects under various abiotic stresses (Jain 2015).
Tools for Studying Functional Genome Editing in Plants
The availability of genome-editing tools has facilitated targeted mutation, insertion and deletion (indel) with high precision (Voytas 2013). These tools mainly include the clustered regularly interspaced short palindromic repeat (CRISPR) - CRISPR-associated nuclease 9 (Cas9), zinc finger nucleases (ZFNs) and transcriptional activator-like effector nucleases (TALENs) (Mahfouz et al. 2014; Kumar and Jain 2015). These nucleases are engineered to be sequence-specific, and they introduce double strand breaks (DSBs) at the concerned locus. The type of mutation in the targeted locus depends on the type of repair mechanism adapted by the cell to reverse the DSB. Repair by non-homologous end joining (NHEJ) introduces indel, whereas the use of homology-directed repair (HDR) results in point mutations or the incorporation of desired sequence tags through recombination events (Jain 2015).
Potential Use of Genome Editing in Generating Abiotic Stress Tolerance
Genome-editing technology has been rarely used in developing stress-tolerant crops. In a recent instance, the novel allele open stomata 2/H*-ATPase I (Ostl/Ahal) has been created by optimized CRISPR/Cas9 approaches. The modified Arabidopsis plants exhibited altered responses to abiotic stresses (Osakabe and Osakabe 2017). In recent years, quality web- based programs have been developed to facilitate single guide RNA (sgRNA) designing for the specific targeting of genes and loci (Montague et al. 2014). The sgRNA guides the Cas9 nuclease to recognize target DNA sequences using Watson-Crick base pairing and complementarity (Kumar and Jain 2015). Different versions of Cas9 nucleases can be used to carry out variable genome editing in plants. The catalytically inactive Cas9 protein (dCas9) inhibits gene function by facilitating CRISPR interference (CRISPRi) (Qi et al. 2013). Jain (2015) proposed that the fusion of Cas9 to transcriptionally active domains of VIVIPAROUS 16 (VP16)/VP64 could lead to gain-of-function phenotypes which could then be screened for abiotic stress tolerance. Osakabe et al. (2010) designed a zinc finger nuclease fused to a heat shock promoter. This construct was used to mutate the abscisic acid (ABA)-insensitive 4 (ABI4) transcription factor, which also regulates desiccation stress responses and ABA-mediated signaling in Arabidopsis. Jain (2015) reviewed some reports where genome editing has been used to generate homozygous transgenic plants in the first generation itself. This will reduce the enormous time lag required for breeding or genetic transformation. CRISPR technology is often highlighted as an advanced plant breeding technology, since the nucleases can also be delivered within the plant nucleus via non-transgenic approaches (Marton et al. 2010). Hence, plants produced by this technology can qualify as non-genetically modified crops and thus aid in the scientific culmination of agricultural breeding and genomics.
Next-Generation Sequencing for Screening the Plant Genome
Next-generation sequencing (NGS) techniques have enabled the cost-effective sequencing of large sample numbers. This technology could overcome the limitations of Sanger-based methods which were unsuitable for sequencing large number of samples and massive parallel signature sequencing (MPSS). The presence of repetitive elements due to the frequently segmented or tandem duplicated transposable elements (TEs) increases the complexity of the plant genome (Ray and Satya 2014). NGS-based whole genome sequencing has enabled the identification of single nucleotide polymorphism (SNP) in place of fragment-based polymorphism within a short time frame. This sophisticated method involves library construction prior to sequencing. Such libraries can also be partial representations of genomes if complete sequencing data is unavailable. The partially represented libraries might be complexity-reduced representation libraries formed by the use of restriction enzymes or can be sequence capture libraries lacking restriction enzyme use (Gore et al. 2009). Ray and Satya (2014) reviewed that the first group can be used for complexity reduction of polymorphic sequences, restriction-site associated DNA sequencing (RAD-seq), sequence-based polymorphic marker technology, multiplexed shotgun genotyping and genotyping-by-sequencing (GBS). The second group can be utilized for technologies involving molecular inversion probe, solution hybrid selection, microarray-based genomic selection, exome sequencing and genome region sequencing linked to a specific trait (Porreca et al. 2007; Gnirke et al. 2009; Albert et al. 2007; Teer et al. 2010). A general outline of NGS-assisted plant breeding has been illustrated in Figure 17.1.
The availability of a genomic sequence at the online public platforms enables easy development of genic molecular or functional markers. Yang et al. (2012) and Glaubitz et al. (2014) have discussed the importance of RAD-seq and GBS for efficient next-generation plant breeding. In RAD-seq, the genomic DNA is digested with a particular restriction enzyme and then ligated with barcoded adaptors with molecular identifiers. Next, the DNA from multiple plants is pooled and
FIGURE 17.1 A generalized pipeline of NGS-assisted plant breeding [extracted from Ray and Satya (2014)].
subjected to random shear so that only a sub-set of the fragments contain the barcoded adapter. For effective PCR, another set of adapters is then ligated to the generated DNA fragments. The fragments containing both of the adapters are PCR amplified and sequenced via Illumina platforms, and the SNPs of individual plants are decoded by in silico analyses. This technology does not require any knowledge of the genomic sequence and has been utilized to identify QTLs for increasing the anthocyanin content in the fruit of eggplant (Barchi et al. 2012).
The constructed GBS map of wheat consists of 416,856 markers, thus indicating the robustness of the technology (Saintenac et al. 2013). Out of these, 20,000 are SNPs. About 34,000 SNPs have been identified in barley via this approach (Poland et al. 2012). GBS is performed following a modified RAD-seq protocol where the second adapter is not divergent in nature, thus allowing the generation of amplicons flanked by either of the adapter sequences. This highly multiplexed technique can be used for marker discovery and genotyping (Glaubitz et al. 2014). The ploidy character of the genome is also a challenge for sequencing projects. NGS has resolved these problems and can be used as a tool for allele mining during abiotic stress cues (Zhang et al. 2016). This field is rather young and needs exhaustive exploration.
Use of Quantitative Trait Loci (QTL) Mapping and Genomics-Assisted Breeding (GAB) in Generating Abiotic Stress Tolerance
Genes and QTLs related to plant tolerance to abiotic stress are valuable resources for improving crop phenotype. Wang et al. (2016) reported that a natural variant of vacuolar H*-translocating inorganic pyrophosphatase I (VPP1) was involved in generating drought tolerance in maize. In another report, it was observed that the QTL, COLD], was associated with chilling tolerance in japonica rice (Ma et al. 2015). The QTLs like grain width 2 (GW2), GW5, GW8, grain size 2 (GS2), GS3 and GS5 can be targeted for generating elite cultivars with high yield (Leng et al. 2017).
GAB uses advanced marker-assisted breeding for ensuring genome-wide genetic selection and high-density genotyping. This increases the probability of generating elite varieties with efficient stress-tackling properties (Singh et al. 2017). Marker-assisted backcrossing (MABC) and marker- assisted recurrent selection (MARS) are being currently used as strategies to introduce complex traits within the target plant genome (Singh et al. 2017).
MABC was used to introgress the identified four QTLs associated with root trait development in the upland rice cultivar Kalinga III from Azucena (Steele et al. 2007). Root size, architecture and grain yield have been found to be controlled by a major QTL in maize involved in regulating the leaf abscisic acid (ABA) concentration (Landi et al. 2007). Avoidance of leaf senescence (‘stay green’ trait) under drought or desiccation can be an effective strategy for generating tolerance. Four such ‘stay green’-related QTLs (Stgl-Stg4) have been identified in Sorghum (Harris et al. 2007). A critical analysis of the ‘stay green’ phenotype and its positional cloning remains to be reported. QTLs associated with increasing the water use efficiency (WUE) have been identified in Brassica oleracea, rice, barley and wheat (Collins et al. 2008). The anthesis-silking interval (ASI) in maize increases during desiccation stress. Five QTL alleles associated with short ASI were introduced in a drought- sensitive line from a drought-tolerant donor using MABC. The selected lines exhibited high yield under drought compared to the unselected control plants (Ribaut and Ragot 2007). Recently, Abdelraheem et al. (2017) performed QTL mapping for abiotic stress tolerance in tetra- ploid cotton based on multiple morphological and physiological traits. This led to the identification of 23 QTL clusters across 15 chromosomes. Among 28 QTL hotspots, two QTL hotspots on chromosome number 24 were found to be associated with drought and salt tolerance (Abdelraheem et al. 2017). In another recent study, Diaz et al. (2018) used 95 recombinant inbred lines (RILs) of Phaseolus vulgaris for QTL mapping under multiple abiotic stresses. The investigation revealed a stable QTL associated with yield on chromosome number 4. Tw'o more QTL hotspots were identified on chromosome numbers 1 and 8 (Diaz et al. 2018). QTL mapping in durum wheat led to the identification of two loci, Naxl and Nax2, which were related to Na+ accumulation in the shoot tissue (James et al. 2006). It was observed that Naxl induced the retention of Na+ in the leaf sheath instead of the leaf blade and promoted xylem unloading of Na+ in the leaf sheath (James et al. 2006).
MABC-dependent introgression of the QTL, Subl, has led to improved submergence and anoxia tolerance in the rice cultivar Swarna (Neeraja et al. 2007). Swarna was eventually converted to a submergence-tolerant variety in three backcross generations within a period of two to three years (Collins et al. 2008). Ismail et al. (2007) reported the incorporation of markers to identify the Subl introgressed lines for effective breeding in flood-prone areas. Subl A, Subl В and SublC were identified via positional cloning as three putative ethylene- responsive factor genes. The products of these genes controlled the Subl locus. Xu et al. (2006) established that SublA-1 was the primary determinant of submergence tolerance in rice.
QTLs controlling pollen heat tolerance involving pollen germination and pollen tube growth were identified in maize (Frova and Sari-Gorla 1994). Hong et al. (2003) identified seven ‘hot’ loci in Arabidopsis. The compromised action of these loci led to reduced thermotolerance. Introgression of a QTL allele from wild tomato (Solarium hirsutum) into S. lycopersicum led to increased cold tolerance (Goodstal et al. 2005). The C-repeat binding factor 2 (CBF2) gene was mapped to a freezing-tolerant QTL in Arabidopsis (Alonso-Bianco et al. 2005). Subsequently QTLs for cold tolerance have been mapped in Lens culinaris, Brassica napus and Lolium perenne (Collins et al.
2008). Some QTLs involved in mineral deficiency have also been mapped across plant species. These have been highlighted separately in Table 17.1.