Peanut is an important and nutritious agricultural commodity and a livelihood of many small-holder farmers in the semi-arid tropics (SAT) of world which are facing serious production threats. Integration of genomics tools with on-going genetic improvement approaches is expected to facilitate accelerated development of improved cultivars. Therefore, high-resolution genotyping and multiple season phenotyping data for 50 important agronomic, disease and quality traits were generated on the ‘reference set’ of peanut. This study reports comprehensive analyses of allelic diversity, population structure, linkage disequilibrium (LD) decay and marker-trait association (MTA) in peanut. Distinctness of all the genotypes can be established by using either an unique allele detected by a single SSR or a combination of unique alleles by two or more than two SSR markers. As expected, DArT features (2.0 alleles/locus, 0.125 PIC) showed lower allele frequency and polymorphic information content (PIC) than SSRs (22.21 alleles /locus, 0.715 PIC). Both marker types clearly differentiated the genotypes of diploids from tetraploids. Multi-allelic SSRs identified three sub-groups (K = 3) while the LD simulation trend line based on squared-allele frequency correlations (r2) predicted LD decay of 15–20 cM in peanut genome. Detailed analysis identified a total of 524 highly significant MTAs (pvalue >2.1×10–6) with wide phenotypic variance (PV) range (5.81–90.09%) for 36 traits. These MTAs after validation may be deployed in improving biotic resistance, oil/ seed/ nutritional quality, drought tolerance related traits, and yield/ yield components.
The nufritional quality of peanut {Arachis hypogaea L.) products depends on fhe protein content, oil content, and composition of oil. Low genefic variabllify has been a major bottleneck in genefic enhancement of these nufritional fraifs in commercial culfivars. The present sfudy was conducted fo identify stable genotypes with beffer nufrifional fraifs and good agronomic performance for use in future breeding programs. The 184 mini core accessions and four conf rol cultivars were evaluated for nufrifional traifs for fwo seasons af fwo locations and for agronomic fraifs af one location. Significanf genotypic and genofype x environmenf inferacfions were observed for all fhe nufrifional and agronomic fraifs in fhe enfire mini core collection and wifhin each A. hypogaea subspecies of fastigiata Waldron and hypogaea. Eighteen accessions wifh higher nufrifional fraifs such as profein confenf, oil confenf, oleic acid, and oleic fo linoleic acid rafio wifh superior agronomic fraifs were idenfified and fheir sfabilify analysis resulted in idenfificafion of a high oleic acid confenf (>73%) accession (ICG 2381). On fhe basis of higher nufritional and agronomic fraifs 11 subsp. fastigiata and 10 subsp. hypogaea diverse accessions were idenfified wifh more fhan fwo fraif combinations for use in peanuf breeding programs for genefic enhancement of nufrifional fraifs.
With 2 figures and 3 tables Abstract High oleic acid (O) and low linoleic acid (L) make peanut oil ideal for longer storage and better human health. Among the ICRISAT mini core collection accessions, oleic acid ranged from 33.60% to 73.54%. Accessions belonging to ssp. hypogaea had higher oleic acid (54.16%) compared with those of ssp. fastigiata (45.70%). An O : L ratio up to 6.93 was found among ssp. hypogaea. Additional varieties, mutants, germplasm lines and breeding lines had oleic acid within the range of mini core accessions. Mutations in ahFAD2A, which along with its homologous gene, ahFAD2B code for delta‐12‐desaturase, resulted in higher oleic acid and O : L ratio. ahFAD2A mutant allele was found in 49.5% of the accessions, and its frequency was higher in ssp. hypogaea (84.52%) than in ssp. fastigiata (19.39%). ahFAD2A mutation had a maximum contribution of 18.82, 12.98 and 10.52 towards the phenotypic variance of O, L and O : L ratio, respectively. Genotypes with high oleic acid levels could not reveal ‘A’ insertion mutation in ahFAD2B. Accessions with high oleic acid could be employed for improving peanut oil quality.
An effort was made in the present study to identify the main effect and epistatic quantitative trait locus (QTL) for the morphological and yield-related traits in peanut. A recombinant inbred line (RIL) population derived from TAG 24 × GPBD 4 was phenotyped in seven environments at two locations. QTL analysis with available genetic map identified 62 main-effect QTLs (M-QTLs) for ten morphological and yieldrelated traits with the phenotypic variance explained (PVE) of 3.84-15.06%. Six major QTLs (PVE > 10%) were detected for PLHT, PPP, YPP, and SLNG. Stable M-QTLs appearing in at least two environments were detected for PLHT, LLN, YPP, YKGH, and HSW. Five M-QTLs governed two traits each, and 16 genomic regions showed co-localization of two to four M-QTLs. Intriguingly, a major QTL reported to be linked to rust resistance showed pleiotropic effect for yield-attributing traits like YPP (15.06%, PVE) and SLNG (13.40%, PVE). Of the 24 epistatic interactions identified across the traits, five interactions involved six M-QTLs. Three interactions were additive × additive and remaining two involved QTL × environment (QE) interactions. Only one major M-QTL governing PLHT showed epistatic interaction. Overall, this study identified the major M-QTLs for the important productivity traits and also described the lack of epistatic interactions for majority of them so that they can be conveniently employed in peanut breeding.
Breeding science has immensely contributed to the global food security. Several varieties and hybrids in different food crops including maize have been released through conventional breeding. The ever growing population, decreasing agricultural land, lowering water table, changing climate, and other variables pose tremendous challenge to the researchers to improve the production and productivity of food crops. Drought is one of the major problems to sustain and improve the productivity of food crops including maize in tropical and subtropical production systems. With advent of novel genomics and breeding tools, the way of doing breeding has been tremendously changed in the last two decades. Drought tolerance is a combination of several component traits with a quantitative mode of inheritance. Rapid DNA and RNA sequencing tools and high-throughput SNP genotyping techniques, trait mapping, functional characterization, genomic selection, rapid generation advancement, and other tools are now available to understand the genetics of drought tolerance and to accelerate the breeding cycle. Informatics play complementary role by managing the big-data generated from the large-scale genomics and breeding experiments. Genome editing is the latest technique to alter specific genes to improve the trait expression. Integration of novel genomics, next-generation breeding, and informatics tools will accelerate the stress breeding process and increase the genetic gain under different production systems.
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