AUTHOR=Maan Sukhjinder Singh , Brar Jaswinder Singh , Mittal Amandeep , Gill Manav Indra Singh , Arora Naresh Kumar , Sohi Harjot Singh , Chhuneja Parveen , Dhillon Guriqbal Singh , Singh Navdeep , Thakur Sujata 

TITLE=Construction of a genetic linkage map and QTL mapping of fruit quality traits in guava (Psidium guajava L.)

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2023.1123274

DOI=10.3389/fpls.2023.1123274

ISSN=1664-462X

ABSTRACT=Guava (Psidium guajava L.) is an important fruit crop of Indian sub-continent having a potential for improved quality and yield characters. The goal of present study was to construct a genetic linkage map in an intraspecific cross between an elite cultivar ‘Allahabad Safeda’ and landrace ‘Purple Guava’ to identify the genomic regions responsible for important fruit quality traits viz., total soluble solids, titratable acidity, Vitamin-C and sugars. This population was phenotyped under field trials (winter-seasoned-crop) for three consecutive years, and depicts the moderate-to-high values of heterogeneity coefficients along with higher heritability (60.0-97.0%) and genetic advance over mean values (13.23-31.17%), suggestive of a minimal environmental influence on the expression of fruit quality traits indicating that these traits can be improved by phenotypic selection methods. Significant correlations and strong associations were also detected among fruit physico-chemical traits in segregating progeny. The constructed linkage map consisted of 195 markers distributed on eleven chromosomes spanning a length of 1604.47 cM (average inter-loci distance of 8.80 markers) with 88.00% coverage of the guava genome. Fifty-eight QTLs were detected in three environments with best linear unbiased prediction values using composite interval mapping algorithm of BIP module. The QTLs were distributed on seven different chromosomes explaining 10.95-17.77% of phenotypic variance with 5.96 being the highest LOD score for qTSS.AS.pau-6.2. Thirteen QTLs detected across multiple environments with BLUPs indicate their stability and utility in futuristic breeding program of guava. Furthermore, 7 QTL clusters with stable or common individual QTLs affecting two or more different traits were located on six LGs explaining correlation among fruit quality traits. Thus, multiple environmental evaluations conducted here increases our understanding the molecular basis of phenotypic variation, provide the basis for future high resolution fine-mapping and will pave the path for marker assisted breeding of fruit quality traits.