High resolution mapping of QTLs for fruit color and firmness in Amrapali/Sensation mango hybrids

Abstract

IntroductionMango (Mangifera indica L.), acclaimed as the ‘king of fruits’ in the tropical world, has historical, religious, and economic values. It is grown commercially in more than 100 countries, and fresh mango world trade accounts for ~3,200 million US dollars for the year 2020. Mango is widely cultivated in sub-tropical and tropical regions of the world, with India, China, and Thailand being the top three producers. Mango fruit is adored for its taste, color, flavor, and aroma. Fruit color and firmness are important fruit quality traits for consumer acceptance, but their genetics is poorly understood.MethodsFor mapping of fruit color and firmness, mango varieties Amrapali and Sensation, having contrasting fruit quality traits, were crossed for the development of a mapping population. Ninety-two bi-parental progenies obtained from this cross were used for the construction of a high-density linkage map and identification of QTLs. Genotyping was carried out using an 80K SNP chip array.Results and discussionInitially, we constructed two high-density linkage maps based on the segregation of female and male parents. A female map with 3,213 SNPs and male map with 1,781 SNPs were distributed on 20 linkages groups covering map lengths of 2,844.39 and 2,684.22cM, respectively. Finally, the integrated map was constructed comprised of 4,361 SNP markers distributed on 20 linkage groups, which consisted of the chromosome haploid number in Mangifera indica (n =20). The integrated genetic map covered the entire genome of Mangifera indica cv. Dashehari, with a total genetic distance of 2,982.75 cM and an average distance between markers of 0.68 cM. The length of LGs varied from 85.78 to 218.28 cM, with a mean size of 149.14 cM. Phenotyping for fruit color and firmness traits was done for two consecutive seasons. We identified important consistent QTLs for 12 out of 20 traits, with integrated genetic linkages having significant LOD scores in at least one season. Important consistent QTLs for fruit peel color are located at Chr 3 and 18, and firmness on Chr 11 and 20. The QTLs mapped in this study would be useful in the marker-assisted breeding of mango for improved efficiency.

A high-density linkage map construction in guava (Psidium guajava L.) using genotyping by sequencing and identification of QTLs for leaf, peel, and pulp color in an intervarietal mapping population

“…In apple, the availability of reference genomes, genetic linkage maps and association studies facilitated the identification of QTLs associated with fruit color ( Chen et al., 2021 ). Similarly, in mango, various omics-based approaches ( Mathiazhagan et al., 2022 ) and QTL mapping identified genes linked to fruit color ( Srivastav et al., 2023 ). In our study, we crossed contrasting parents, ‘Arka Poorna’ and ‘Purple Local’ and developed a diverse mapping population that has highly variable leaf color (green and greyed purple), peel color (yellow and purple) and pulp color (white, purple and red).…”

“…Even though color is a qualitative trait, subjective scoring may not depict color variations in a population precisely. Studies have reported employing the Color reader for measuring color attributes like L*, a*, and b* for scoring and identification of QTLs for fruit peel color and pulp color in segregating mapping populations ( Oh et al., 2023 ; Srivastav et al., 2023 and Zhang et al., 2019 ). In the present study, leaf and fruit colors were scored using both methods in order to identify the QTL regions with more accuracy.…”

“…GBS is a cost-effective strategy which provides sufficient genome coverage enabling identification of large number of SNPs throughout the genome ( Elshire et al., 2011 ). Hence, SNP marker-based linkage maps in plants are highly dense, saturated, unambiguous, and informative ( Srivastav et al., 2023 ).…”

Advancing tree genomics to future proof next generation orchard production

“…These technologies and new selection methods have enabled tree breeders to accelerate genetic gain and the development of superior tree varieties with desirable trait combinations. High-throughput genotyping methods assay thousands of genetic markers simultaneously at a relatively modest cost and when analysed in segregating or reference populations have enabled the identification of key genetic variants associated with traits of interest, such as disease resistance, fruit quality, and plant architecture, among others (Peng et al, 2020;Wang L. et al, 2022;Huang M. et al, 2023;Srivastav et al, 2023). Comprehensive knowledge of the genetic basis of multiple agronomically important traits has allowed breeders to make informed decisions on the selection of parent trees for crossing in breeding programs, generating new hybrid varieties with improved trait combinations.…”

“…Consequently, GS has the potential to enable breeders to accurately estimate the performance of trees before they reach maturity, allowing for early identification of top-performing individuals. (Shen et al, 2019) Disease resistance in trifoliate orange (Peng et al, 2020) HLB tolerance in 'Argentina' and 'Flying Dragon' trifoliate orange and 'Sanford' and 'Succari' sweet orange (Huang M. et al, 2023) Male sterility and polyembryony in 'Kiyomi' and 'Murcott' mandarin (Montalt et al, 2023) Fruit weight in 'Tommy Atkins' x 'Kensington Pride' hybrids (Bally et al, 2021) Anthracnose resistance in 143 mango varieties (Felipe et al, 2022) Fruit colour and firmness in 'Amrapali'/ 'Sensation' hybrids (Srivastav et al, 2023)…”