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Integrated Consensus Map of Cultivated Peanut and Wild Relatives Reveals Structures of the A and B Genomes of Arachis and Divergence of the Legume Genomes

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The complex, tetraploid genome structure of peanut (Arachis hypogaea) has obstructed advances in genetics and genomics in the species. The aim of this study is to understand the genome structure of Arachis by developing a high-density integrated consensus map. Three recombinant inbred line populations derived from crosses between the A genome diploid species, Arachis duranensis and Arachis stenosperma; the B genome diploid species, Arachis ipaënsis and Arachis magna; and between the AB genome tetraploids, A. hypogaea and an artificial amphidiploid (A. ipaënsis × A. duranensis)(4×), were used to construct genetic linkage maps: 10 linkage groups (LGs) of 544 cM with 597 loci for the A genome; 10 LGs of 461 cM with 798 loci for the B genome; and 20 LGs of 1442 cM with 1469 loci for the AB genome. The resultant maps plus 13 published maps were integrated into a consensus map covering 2651 cM with 3693 marker loci which was anchored to 20 consensus LGs corresponding to the A and B genomes. The comparative genomics with genome sequences of Cajanus cajan, Glycine max, Lotus japonicus, and Medicago truncatula revealed that the Arachis genome has segmented synteny relationship to the other legumes. The comparative maps in legumes, integrated tetraploid consensus maps, and genome-specific diploid maps will increase the genetic and genomic understanding of Arachis and should facilitate molecular breeding.
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... Such markers are especially helpful in the mapping of stress-related genes' QTLs (quantitative trait loci) (Younis et al. 2020). When dealing with quantitative features like HT, molecular markers that allow for the exact and time-saving recovery of desired genotypes become essential (Shirasawa et al. 2013). ...
... The grain quality of the NILs was much better than the susceptible parent 'Tohoku 168'. The chromosomal region in question had a strong QTL that influenced more than 20% of the PV and was responsible for higher grain quality under HS (Shirasawa et al. 2013). Table 2.1 contains a non-exhaustive list of DNA markers related to various HT/component features found in various crops. ...
... SNPs qREC-1-1,qREC-1-2, qREC-1-3,qREC-2-1, qREC-3-1,qREC-9-1, qREC-12-1,qCC-1-4, qCC-1-5,qCC-2-2, qFv/Fm ─ 5-1, andqFv/Fm 12-2 Singh et al. (2017) The near isogenic lines (NILs) developed by introgressing desirable alleles into the heat-sensitive lines showed a considerable reduction in the heat-induced injuries (Kobayashi et al. 2013). Recently, a major QTL controlling better grain quality under heat stress has been transferred from "Kokoromachi" to "Tohoku 168" using marker-assisted backcrossing (Shirasawa et al. 2013). The developed NILs had better grain quality with better heat tolerance over the susceptible parent. ...
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This chapter addresses the adverse effect of heat stress on plant growth, genes associated with heat stress tolerance and adaptive strategies that can be used to create heat-tolerant plants. CRISPR/Cas9 seems a promising approach regarding stress tolerance. The modified versions of CRISPR/Cas9 like CRISPRi, CRISPRa, base editing and CRISPR multiplexing offers more and more specificity and advanced editing options and minimizes the off-target effect. The versatility of CRISPR/Cas9 brings a new revolution in the field of plant science to alleviate abiotic stress like heat stress.KeywordsHeat stressCRISPR/Cas 9CRISPRiCRISPRaBase editingCRISPR multiplexing
... This low level of diversity has been a major impediment for mining a large number of polymorphic markers for constructing high-density genetic maps and QTL analyses (Pandey et al. 2017;Qin et al. 2012;Varshney et al. 2014). To date, only a few genetic maps containing more than 1,000 SSR markers have been reported (Huang et al. 2016;Shirasawa et al. 2013). ...
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Key message We identified two stable and homologous major QTLs for sucrose content in peanut, and developed breeder-friendly molecular markers for marker-assisted selection breeding. Abstract Sucrose content is a crucial quality trait for edible peanuts, and increasing sucrose content is a key breeding objective. However, the genetic basis of sucrose content in peanut remains unclear, and major quantitative trait loci (QTLs) for sucrose content have yet to be identified. In this study, a high-density genetic map was constructed based on whole-genome re-sequencing data from a peanut RIL population. This map consisted of 2,042 bins and 24,142 SNP markers, making it one of the most comprehensive maps to date in terms of marker density. Two major QTLs (qSCA06.2 and qSCB06.2) were identified, explaining 31.41% and 24.13% of the phenotypic variance, respectively. Notably, these two QTLs were located in homologous genomic regions between the A and B subgenomes. The elite allele of qSCA06.2 was exclusive to Valencia-type, while the elite allele of qSCB06.2 existed in other peanut types. Importantly, the distribution of alleles from two homologous QTLs in the RIL population and diverse germplasm accessions consistently demonstrated that only the combination of elite allelic genotypes from both QTLs/genes resulted in a significantly dominant phenotype, accompanied by a substantial increase in sucrose content. The newly developed diagnostic markers for these QTLs were confirmed to be reliable and could facilitate future breeding efforts to enhance sucrose content using marker-assisted selection techniques. Overall, this study highlights the co-regulation of sucrose content by two major homologous QTLs/genes and provides valuable insights into the genetic basis of sucrose in peanuts.
... SSR markers were concluded to be useful for peanut germplasm analysis, diversity studies, linkage mapping, and phylogenetic relationships (Cuc et al. 2008, Hong et al. 2021. Two integrated consensus genetic maps with markers, such as EST-SSRs, transcriptome-SSRs, and g-SSRs, were constructed for cultivated peanut and wild relatives (Shirasawa et al. 2013, Lu et al. 2018). Additionally, a highly informative set of SSR markers was used to screen parental accessions of peanut mapping populations for molecular breeding (Pandey et al. 2012) and SSR markers and intron sequences were used to study phylogenetic relationships of cultivated peanut and wild species of Arachis . ...
... This helps to identify true QTLs with their genetic effects and mining a large number of candidate genes located in that QTL (Shinozuka et al. 2012;Zhang et al. 2014). The basic requirements for the execution of QTL meta-analysis are: a consensus map with high-density markers (Lu et al. 2018;Hong et al. 2010;Shirasawa et al. 2013) and many QTLs controlling single trait identified under different genetic and environment backgrounds (Goffinet and Gerber 2000). For efficient introgression of MQTLs in MAS, it should have smallest CIs with consistent and large effect for the trait. ...
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A large number of QTLs controlling important traits in different crops have been mapped but their deployment in the marker assisted selection (MAS) is highly limited. The possible reason is lack of availability of stable QTLs over diverse genetic background and environment. QTL meta-analysis provides an opportunity to compile QTLs from different studies and identify consistent QTLs across genetic background and environments. These meta-QTLs can be targeted for further fine mapping and used for MAS after validation. QTL meta-analysis involve library search for reported QTL studies for a particular trait in a crop and subsequently a consensus linkage map is constructed projecting QTLs from different studies using simple scaling rule. The Confidence Interval (CI) of QTL is estimated on the consensus map using the formula as CI (95): ¼ 530/(Nλ), where CI (95) is the confidence interval at 95 percent probability level, N is the size of mapping population and λ is the proportion of phenotypic variance explained by the concerned QTL. Finally, detected QTLs are projected for cluster analysis to determine the exact number and positions of true QTLs. The utility of this approach will help to detect the stable meta-QTLs that will be further helpful to identify candidate genes and their application in MAS program.
... LGs. Later, with 897 marker loci (895 SSRs and 2 CAPS) mapped on 20 linkage groups spanning a total map distance of 3607.97 cM, followed by 3693 marker loci mapped on 20 LG with total map distance spanning 2651 cM (Gautami et al., 2012b;Shirasawa et al., 2013). ...
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Groundnut is an oilseed crop with global importance to food and nutritional security. It is a source of livelihood for millions of smallholder growers of the Asia and Sub-Saharan Africa. However, present climate change accompanied with rising CO2 levels, erratic rainfall, and rising and fluctuating atmospheric temperature accompanied with various biotic constraints limits yield potential and quality of produce. In addition, genetic architecture and tetraploid nature of the cultivated peanut have resulted in low genetic diversity for several economically important traits. Despite, significant achievement in yield, quality improvement and tolerance against biotic and abiotic factors have been made by conventional approaches but the process is time-consuming, laborious, and have other limitations. Recent advances in genomics coupled with genetic resources have raised the status of peanut to “genomic resource-rich oilseed crop.” So, future use of a holistic approach including the use of genomics information and tools in crop improvement programs is very much essential for further achieving advancement in peanut yield. Among all the genomic tools, molecular markers are the most valuable in characterizing and harnessing available genetic variability. Moreover, even molecular breeding in peanuts is in the nascent stage, and identification of some major quantitative trait locus (QTLs) for only a few traits has been reported. Nevertheless, availability of reference genome of diploid progenitors and allotetraploid cultivar, a high-density genotyping array with 58K single nucleotide polymorphisms (SNPs) has greatly facilitated high-resolution mapping in peanuts. Affordability of sequencing also encouraged initiation of sequence-based trait mapping such as QTL-seq for dissecting economically important traits. Few successful examples are available in peanuts regarding the development of diagnostic markers and their deployment in crop breeding programs. The availability of different cost-effective genomic tools (SNPs, whole genome sequencing, KASPar, GBS, etc.) and more powerful multi-parent mapping populations are expected to speed up the mapping of complex traits of groundnut in the coming years. This chapter provides an overview of the current developments and future prospects of molecular marker development and their applications in groundnut crops.
... 14 Genomics-Enabled Breeding for Heat and Drought Stress Tolerance in Crop Plants 309 The near isogenic lines (NILs) developed by introgressing desirable alleles into the heat-sensitive lines showed a considerable reduction in the heat-induced injuries (Kobayashi et al. 2013). Recently, a major QTL controlling better grain quality under heat stress has been transferred from "Kokoromachi" to "Tohoku 168" using marker-assisted backcrossing (Shirasawa et al. 2013). The developed NILs had better grain quality with better heat tolerance over the susceptible parent. ...
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