scholarly journals Molecular Markers, Genetic Maps and QTLs for Molecular Breeding in Peanut

2014 ◽  
pp. 103-137
Keyword(s):  
Molecular Markers ◽  
Molecular Breeding ◽  
Genetic Maps

scholarly journals Genetic mapping studies in Coffea sp using molecular marker methods Studi peta genetik pada Coffea sp. menggunakan metode penanda molekuler

2016 ◽  
Vol 83 (2) ◽  
Author(s):  
. PRIYONO ◽  
Riza Arief PUTRANTO
Keyword(s):  
Molecular Markers ◽  
Genetic Mapping ◽  
Genetic Map ◽  
Crop Improvement ◽  
Average Density ◽  
Genetic Maps ◽  
Gene Characterization ◽  
Robusta Coffee ◽  
Dna And Rna ◽  
Genomic Comparative Analysis

AbstrakAnalisis genetik telah  menjadi alat yang penting  dalam  pemuliaan  tanaman untuk perbaikan sifat penting tanaman. Salah satu potensi terbesar dari analisis tersebut adalah identifikasi penanda molekuler yang berguna untuk pemetaan genetik. Pemetaan genetik  merupakan  salah satu langkah penting dari analisis  genetik.  Intisari  dari   semua pemetaan genetik adalah  menempatkan  koleksi  pe- nanda molekuler pada posisi tertentu dalam genom. Hal tersebut dapat kemudian digunakan untuk meng- identifikasi lokus sifat kuantitatif (QTLs) dengan memanfaatan keragaman genetik alami yang tersedia dan meningkatkan sifat-sifat penting serta berharga. Sampai saat ini, tiga belas peta genetik telah dipublikasi dan tersedia pada Coffea sp. yang menciptakan database besar untuk kerangka genetik. Sebuah peta genetik terbaru dengan akses terbuka dan berfungsi sebagai referensi telah dibangun oleh International Coffee Genomics Network (ICGN). Peta tersebut tediri dari 3230 lokus, dengan panjang peta 1471 cM (1cm ~ 500 Kb) serta kepadatan satu penanda setiap 220 Kb. Peta-peta genetik pada tanaman kopi telah digunakan dari karakterisasi gen hingga analisis komparatif genom dengan spesies tanaman yang berbeda. Saat ini, pesatnya kemajuan teknologi New Genome Sequencing (NGS) untuk sekuensing DNA dan RNA memungkinkan validasi dari peta-peta genetik untuk prediksi QTLs serta gen-gen yang membawa sifat penting Coffea sp.AbstractGenetic analysis has become an important tool in plant breeding for crop improvement. One of their greatest potential appears to be the identification of molecular markers useful for genetic mapping. Genetic mapping is one of important steps in genetic analysis. The essence of all genetic mapping is to place a collection of molecular markers onto their respective positions on the genome. Thus, it leads to identification of new quantitative trait loci (QTLs) by making benefits of natural available genetic diversity.and to improve important and valuable traits. Until present, thirteen genetic maps were published and available in Coffea sp. creating a huge database for genetic framework. One most recent and open reference genetic map for robusta coffee has been generated by the International Coffee Genomics Network (ICGN) comprising 3230 loci, genetic size 1471 cM (1cM ~500 Kb), with an average density close to one marker every 220 Kb. The Coffea genetic maps have been utilized from gene characterization to genomic comparative analysis with different plant species. Nowadays, the feasibility of NGS for DNA and RNA sequencing allow the validation of genetic map related to the prediction of QTLs and adjacent genes related to important traits for Coffea sp. 

scholarly journals Unlocking Genetic Diversity in Selected Chickpea Genotypes Using Morphological and Molecular Markers

2017 ◽  
Vol 5 (1) ◽  
pp. 50-57
Author(s):  
Rupsanatan Mandal ◽  
Suprakash Pal ◽  
Nonigopal Shit
Keyword(s):  
Genetic Diversity ◽  
Molecular Markers ◽  
Coefficient Of Variation ◽  
Block Design ◽  
Crop Improvement ◽  
Research Work ◽  
Genetic Maps ◽  
Quantitative Character ◽  
Moderate Degree ◽  
Improvement Program

Proficiency and organization of the genetic variability in cultivated and wild relatives are pivotal for a particular crop improvement program. In the present scenario there has been noteworthy improvement in the development of novel genetic tools such as DNA or molecular markers and genetic maps profiling techniques. In this study, seven chickpea (Cicer arietinum L.) genotypes including some cultivars were considered (Collection Id of the seven genotypes are TZCP-1, TZCP-2, TZCP-3, TZCP-4, TZCP-5, TZCP-6 and TZCP-7). The experiment was conducted out in Random Complete Block Design (RCBD) having three replications. All the quantitative characters were collected for assessing the diversity and to find key characters in chickpea cultivars. The statistical analysis was done for all the quantitative character (viz. plant height, number of branches per plant, number of pod per plant, number of seeds per pod, test weight, seed length, seed width, days to 50% flowering, days to 50% maturity and grain yield). Analysis of variance divulged significant differences among the genotypes for all the 10 characters. An extensive range of diversity was displayed by most of the characters under study. The magnitude of phenotypic coefficient of variation (1.23% - 33.71%) in the present study was slightly wider than genotypic coefficient of variation (1.13% - 33.02%) suggesting that environmental factors have high contribution to the observed variation among chickpea accessions. The first four PC axes from the principal component analysis accounted for 91.63% of the multivariate variation among entries indicating a moderate degree of correlation among characters for these entries. The genotypic data generated through RAPD profiling of seven chickpea genotypes were used to study genetic diversity or interrelationship. The pair wise Jaccard’s similarity coefficient ranged from 0.47 (TZCP-3 and TZCP-5) to 0.87 (TZCP-2 and TZCP-4). Finally, this research work helped with the analysis of genetic diversity in chickpea by using different approaches such as morphological and molecular marker system.

Collection, characterization, and utilization of germ plasm of Lentinula edodes

1995 ◽  
Vol 73 (S1) ◽  
pp. 955-961 ◽  
Author(s):  
S. T. Chang ◽  
H. S. Kwan ◽  
Y. N. Kang
Keyword(s):  
Molecular Markers ◽  
Mycelial Growth ◽  
Germ Plasm ◽  
Lentinula Edodes ◽  
Molecular Genetic ◽  
Genetic Maps ◽  
Mating Types ◽  
Genomic Fingerprinting ◽  
Polymerase Chain ◽  
Selection Of

Wild and cultivated strains of Lentinula edodes have been collected to form a germ-plasm bank of the mushroom. In addition to the ecological, morphological, and physical properties, the strains were characterized to determine their mating types (alleles of A and B incompatibility factors), substrate degradation abilities, mycelial growth rates, and fruiting abilities. The strains were used to establish molecular genetic methods of strain authentification. The genomic fingerprinting method of arbitrarily primed polymerase chain reaction was found to be a better method than the rDNA internal transcribed spacer regions sequence comparison for L. edodes strain typing. The utilization of the characterized germ-plasm bank for the selection of desirable germ plasm for breeding and cultivation is described. The value and use of molecular markers and genetic maps is also discussed. Key words: mating types, mycelial growth rate, molecular markers.

scholarly journals Development of New Candidate Gene and EST-Based Molecular Markers for Gossypium Species

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Ramesh Buyyarapu ◽  
Ramesh V. Kantety ◽  
John Z. Yu ◽  
Sukumar Saha ◽  
Govind C. Sharma
Keyword(s):  
Molecular Markers ◽  
Candidate Gene ◽  
Candidate Genes ◽  
Genetic Maps ◽  
Physical Maps ◽  
Polymorphism Detection ◽  
A Genome ◽  
Species Cluster ◽  
Gene Based Markers ◽  
Integrated Genetic Maps

New source of molecular markers accelerate the efforts in improving cotton fiber traits and aid in developing high-density integrated genetic maps. We developed new markers based on candidate genes and G. arboreum EST sequences that were used for polymorphism detection followed by genetic and physical mapping. Nineteen gene-based markers were surveyed for polymorphism detection in 26 Gossypium species. Cluster analysis generated a phylogenetic tree with four major sub-clusters for 23 species while three species branched out individually. CAP method enhanced the rate of polymorphism of candidate gene-based markers between G. hirsutum and G. barbadense. Two hundred A-genome based SSR markers were designed after datamining of G. arboreum EST sequences (Mississippi Gossypium arboreum  EST-SSR: MGAES). Over 70% of MGAES markers successfully produced amplicons while 65 of them demonstrated polymorphism between the parents of G. hirsutum and G. barbadense RIL population and formed 14 linkage groups. Chromosomal localization of both candidate gene-based and MGAES markers was assisted by euploid and hypoaneuploid CS-B analysis. Gene-based and MGAES markers were highly informative as they were designed from candidate genes and fiber transcriptome with a potential to be integrated into the existing cotton genetic and physical maps.

scholarly journals Genetic mapping studies in Coffea sp using molecular marker methods Studi peta genetik pada Coffea sp. menggunakan metode penanda molekuler

2016 ◽  
Vol 83 (2) ◽  
Author(s):  
. PRIYONO ◽  
Riza Arief PUTRANTO
Keyword(s):  
Molecular Markers ◽  
Genetic Mapping ◽  
Genetic Map ◽  
Crop Improvement ◽  
Average Density ◽  
Genetic Maps ◽  
Gene Characterization ◽  
Robusta Coffee ◽  
Dna And Rna ◽  
Genomic Comparative Analysis

AbstrakAnalisis genetik telah  menjadi alat yang penting  dalam  pemuliaan  tanaman untuk perbaikan sifat penting tanaman. Salah satu potensi terbesar dari analisis tersebut adalah identifikasi penanda molekuler yang berguna untuk pemetaan genetik. Pemetaan genetik  merupakan  salah satu langkah penting dari analisis  genetik.  Intisari  dari   semua pemetaan genetik adalah  menempatkan  koleksi  pe- nanda molekuler pada posisi tertentu dalam genom. Hal tersebut dapat kemudian digunakan untuk meng- identifikasi lokus sifat kuantitatif (QTLs) dengan memanfaatan keragaman genetik alami yang tersedia dan meningkatkan sifat-sifat penting serta berharga. Sampai saat ini, tiga belas peta genetik telah dipublikasi dan tersedia pada Coffea sp. yang menciptakan database besar untuk kerangka genetik. Sebuah peta genetik terbaru dengan akses terbuka dan berfungsi sebagai referensi telah dibangun oleh International Coffee Genomics Network (ICGN). Peta tersebut tediri dari 3230 lokus, dengan panjang peta 1471 cM (1cm ~ 500 Kb) serta kepadatan satu penanda setiap 220 Kb. Peta-peta genetik pada tanaman kopi telah digunakan dari karakterisasi gen hingga analisis komparatif genom dengan spesies tanaman yang berbeda. Saat ini, pesatnya kemajuan teknologi New Genome Sequencing (NGS) untuk sekuensing DNA dan RNA memungkinkan validasi dari peta-peta genetik untuk prediksi QTLs serta gen-gen yang membawa sifat penting Coffea sp.AbstractGenetic analysis has become an important tool in plant breeding for crop improvement. One of their greatest potential appears to be the identification of molecular markers useful for genetic mapping. Genetic mapping is one of important steps in genetic analysis. The essence of all genetic mapping is to place a collection of molecular markers onto their respective positions on the genome. Thus, it leads to identification of new quantitative trait loci (QTLs) by making benefits of natural available genetic diversity.and to improve important and valuable traits. Until present, thirteen genetic maps were published and available in Coffea sp. creating a huge database for genetic framework. One most recent and open reference genetic map for robusta coffee has been generated by the International Coffee Genomics Network (ICGN) comprising 3230 loci, genetic size 1471 cM (1cM ~500 Kb), with an average density close to one marker every 220 Kb. The Coffea genetic maps have been utilized from gene characterization to genomic comparative analysis with different plant species. Nowadays, the feasibility of NGS for DNA and RNA sequencing allow the validation of genetic map related to the prediction of QTLs and adjacent genes related to important traits for Coffea sp. 

scholarly journals Current Status of Mapping Quantitative Trait Loci (QTL) for Different Traits and Marker Assisted Breeding in Chickpea (Cicer arietinum L.) – A Review

2020 ◽  
pp. 1-14
Author(s):  
Aswini Nunavath ◽  
Venkatraman Hegde ◽  
K. Gopala Krishna Murthy ◽  
V. Venkanna
Keyword(s):  
Molecular Markers ◽  
Fusarium Wilt ◽  
Abiotic Stresses ◽  
Ascochyta Blight ◽  
Molecular Techniques ◽  
Genetic Maps ◽  
Current Status ◽  
Yield Reduction ◽  
Biotic And Abiotic Stresses ◽  
Advanced Backcross

Chickpea is one of the most important pulse crops having estimated genome size of 738 Mb. The crop is affected by various biotic and abiotic stresses causing significant yield reduction. During the recent past, some biotic stresses like fusarium wilt, ascochyta blight, botrytis grey mould and abiotic stresses like drought, heat and salinity were found to reduce the productivity, thereafter, these demands for development of high yielding early maturing chickpea varieties with resistance to various biotic and abiotic stresses. Due to the advent of molecular techniques and availability of highly polymorphic and co-dominant microsatellite and other molecular markers, development of genetic maps for chickpea has progressed significantly. Molecular markers are now considered better than morphological and physiological characters for being stable, unaffected by environmental influences and easily detectable irrespective of their growth and development stages. The mapping of genes / QTLs for various traits like flowering time, yield and yield related traits, resistance to fusarium wilt, ascochyta blight, BGM, drought, salinity, heat may be useful in developing improved varieties of chickpea besides deeper understanding of genetics underlying the inheritance of the characters. The knowledge on mapped genes / QTLs for various traits of interest could help in integration of genomics-assisted breeding through various approaches like Marker Assisted Back Crossing, introgression of superior alleles from wild species through Advanced Backcross QTL, Marker Assisted Recurrent Selection and Genome Wide Selection for improving chickpea.

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