S. Annepu, Happy Sharma, Anupam Barh, R. Dogra, Vipin Sharma, S. Thakur, Vinay Verma, K. Sharma
{"title":"Performance prediction of F1 crosses in eggplant (Solanum melongena L.) based on morphological and molecular divergence","authors":"S. Annepu, Happy Sharma, Anupam Barh, R. Dogra, Vipin Sharma, S. Thakur, Vinay Verma, K. Sharma","doi":"10.2298/gensr2301045a","DOIUrl":null,"url":null,"abstract":"Identifying potential F1 hybrid combinations based on the parental diversity can increase the breeding efficiency and saves the opportunity cost of time. In this work, the genetic diversity between eggplant genotypes was measured by Mahalanobis D2 statistics and Sequence Related Amplified Polymorphism (SRAP) molecular markers. The genetic distances (GD) were correlated with heterosis and trait wise mean performance of F1 crosses generated in a line ? tester mating design for prediction of F1 performance for agronomically important traits. The cluster analysis performed based on the Mahalanobis D2 distance grouped all the eleven genotypes into two clusters and three clusters were formed based on the SRAP marker data. The polymorphic information content value generated by the 30 SRAP marker combinations ranged from 0.09 to 0.77 with a mean value of 0.38. For yield, the F1 combinations exhibited the mid parent heterosis ranged from 3.99% to 83.34% and the heterobeltiosis from -35.67% to 57.19%. GD based on both phenotypic values and molecular marker data successfully predicted the heterotic patterns in the number of fruits per plant and other fruit morphological traits such as fruit length and fruit breadth which is a significant outcome of the study. A multiple linear regression model that included GD, GCA and SCA was more significantly correlated with heterosis for fruit yield than any genetic parameter alone.","PeriodicalId":50423,"journal":{"name":"Genetika-Belgrade","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genetika-Belgrade","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.2298/gensr2301045a","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 1
Abstract
Identifying potential F1 hybrid combinations based on the parental diversity can increase the breeding efficiency and saves the opportunity cost of time. In this work, the genetic diversity between eggplant genotypes was measured by Mahalanobis D2 statistics and Sequence Related Amplified Polymorphism (SRAP) molecular markers. The genetic distances (GD) were correlated with heterosis and trait wise mean performance of F1 crosses generated in a line ? tester mating design for prediction of F1 performance for agronomically important traits. The cluster analysis performed based on the Mahalanobis D2 distance grouped all the eleven genotypes into two clusters and three clusters were formed based on the SRAP marker data. The polymorphic information content value generated by the 30 SRAP marker combinations ranged from 0.09 to 0.77 with a mean value of 0.38. For yield, the F1 combinations exhibited the mid parent heterosis ranged from 3.99% to 83.34% and the heterobeltiosis from -35.67% to 57.19%. GD based on both phenotypic values and molecular marker data successfully predicted the heterotic patterns in the number of fruits per plant and other fruit morphological traits such as fruit length and fruit breadth which is a significant outcome of the study. A multiple linear regression model that included GD, GCA and SCA was more significantly correlated with heterosis for fruit yield than any genetic parameter alone.
期刊介绍:
The GENETIKA is dedicated to genetic studies of all organisms including genetics of microorganisms, plant genetics, animal genetics, human genetics, molecular genetics, genomics, functional genomics, plant and animal breeding, population and evolutionary genetics, mutagenesis and genotoxicology and biotechnology.