Background The progress in tagging/mapping of genes in crops like Arabidopsis, rice, maize etc. is far ahead when compared to the major legume crops viz. groundnut, chickpea, redgram, greengram, soyabean etc., even in the post release period of legume genome sequence databases. This can be attributed mainly to low level of available molecular genetic diversity in these crops. Methods The study of transferability of Rice yield gene tagged markers to Peanut was carried out by employing17 diverse groundnut genotypes. ANOVA revealed significant differences for six yield and seven seed quality traits studied which indicates availability of ample amount of variability among the genotypes. Molecular analysis was conducted to analyse the transferability of known rice yield, grain size and micronutrient content (Fe and Zn) controlling gene tagged markers (GTMs) to peanut by using 45 GTMsthat targets 24 known functional genes. Results Of 45 markers, 31 (76%) were transferable to peanut, denotes very high conservation at functional regions. The extent of amplification of rice GTMs at individual groundnut genotype level was observed from 79.17% for the cultivated varieties (2n = 4x) Nithya Haritha, Greeshma, Prasuna, Kalahasti, Narayani and with a wild genotype, Arachis villosa(2n = 2x) to 91.67% for Dheeraj variety. The analysis on transferable efficiency of individual rice GTM revealed that 17 markers belong to 14 rice genes showed amplification among all the 17groundnut genotypes (100%) under study. Conclusions Hence, focusing research on the available knowledge of functionally characterized genes of molecular model crops and vast list of annotated orthologous genes present in ‘Omics’ databases, widens the scope to tag the genes at molecular level and thereby to improve the cropslike groundnutthat has meager progress in gene tagging;by pyramiding of desirable genes with high veracity.
Background The progress in tagging/mapping of genes in crops like Arabidopsis, rice, maize etc. is far ahead when compared to the major legume crops viz. groundnut, chickpea, redgram, greengram, soyabean etc., even in the post release period of legume genome sequence databases. This can be attributed mainly to low level of available molecular genetic diversity in these crops. Methods The study of transferability of Rice yield gene tagged markers to Peanut was carried out by employing17 diverse groundnut genotypes. ANOVA revealed significant differences for six yield and seven seed quality traits studied which indicates availability of ample amount of variability among the genotypes. Molecular analysis was conducted to analyse the transferability of known rice yield, grain size and micronutrient content (Fe and Zn) controlling gene tagged markers (GTMs) to peanut by using 45 GTMsthat targets 24 known functional genes. Results Of 45 markers, 31 (76%) were transferable to peanut, denotes very high conservation at functional regions. The extent of amplification of rice GTMs at individual groundnut genotype level was observed from 79.17% for the cultivated varieties (2n = 4x) Nithya Haritha, Greeshma, Prasuna, Kalahasti, Narayani and with a wild genotype, Arachisvillosa(2n = 2x) to 91.67% for Dheeraj variety. The analysis on transferable efficiency of individual rice GTM revealed that 17 markers belong to 14 rice genes showed amplification among all the 17groundnut genotypes (100%) under study. Conclusions Hence, focusing research on the available knowledge of functionally characterized genes of molecular model crops and vast list of annotated orthologous genes present in ‘Omics’ databases, widens the scope to tag the genes at molecular level and thereby to improve the cropslike groundnutthat has meager progress in gene tagging;by pyramiding of desirable genes with high veracity.
Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability, the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desirable parents. The present study was carried out with six parents crossed in full diallel fashion and generated 30 F1 hybrids. These hybrids were evaluated in two replications in Randomized Block Design at Department of Cotton, TNAU for combining ability and gene action. Diallel analysis was carried out according to Griffing’s method-I (parents + F1 + reciprocals) and model-I and Hayman’s graphical approach by using INDOSTAT software. Results Analysis of variance for combining ability indicated that mean square values of GCA, SCA and reciprocals were highly significant for all the traits except for the uniformity index. RG763 and K12 showed highly positively significant GCA effects for most of the yield traits while PA838 and K12 for fibre quality traits, so they were found as best general combiners. PAIG379 × K12 and PDB29 × K12 for yield traits, and PDB29 × PA838, RG763 × PA838, and CNA1007 × RG763 cross combinations for fibre quality traits could be recommended for future breeding programms. Conclusion The results of both Griffing’s and Hayman’s approaches showed that non-additive gene action predominates as SCA variance was bigger than GCA variance, so heterosis breeding is thought to be a more fruitful option for enhancing GCA of many traits.
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