Genetic architecture and population structure of Oat Landraces (Avena sativa L.) using molecular and morphological descriptors

439-450Oat is grown as winter forage in India. It is a self-pollinated crop with less variability. However, the variation for different morphological traits in oat germplasm may be available at genotypic level. The present study was conducted to find out the genetic diversity among 24 oat landraces using 9 morphological traits and 24 SSR primers. Morphological data observed across the 24 landraces showed wide variation and grouped various landraces into two clusters. GFY and DMY were positively and significantly correlated with most of the traits studied. The molecular analysis using 24 SSR primers resulted amplification of 62 polymorphic alleles with an average of 2.58 alleles per primer. Size of amplified alleles ranged from 70 to 480 bp. Mean polymorphic information content was 0.42 showing moderate level of SSR polymorphism. Cluster analysis based on SSR data differentiated 24 oat landraces into three major clusters. Bayesian model-based STRUCTURE analysis assigned landraces into two clusters and showed the extent of admixture within individuals. Clustering pattern of oat landraces based on SSR marker profiles were different from that of morphometric traits. So, based on the pooled analysis at morphological and molecular level, the landraces IG-02-121, IG-02-129 and IG-02-113 were found superior for morphological traits as well as most distant among all the landraces under study. Hence, these landraces could be used in for future breeding programmes for genetic improvement in oats

Genetic architecture and population structure of Oat Landraces (Avena sativa L.) using molecular and morphological descriptors

Oat is grown as winter forage in India. It is a self-pollinated crop with less variability. However, the variation fordifferent morphological traits in oat germplasm may be available at genotypic level. The present study was conducted tofind out the genetic diversity among 24 oat landraces using 9 morphological traits and 24 SSR primers. Morphological dataobserved across the 24 landraces showed wide variation and grouped various landraces into two clusters. GFY and DMYwere positively and significantly correlated with most of the traits studied. The molecular analysis using 24 SSR primersresulted amplification of 62 polymorphic alleles with an average of 2.58 alleles per primer. Size of amplified alleles rangedfrom 70 to 480 bp. Mean polymorphic information content was 0.42 showing moderate level of SSR polymorphism. Clusteranalysis based on SSR data differentiated 24 oat landraces into three major clusters. Bayesian model-based STRUCTUREanalysis assigned landraces into two clusters and showed the extent of admixture within individuals. Clustering pattern ofoat landraces based on SSR marker profiles were different from that of morphometric traits. So, based on the pooledanalysis at morphological and molecular level, the landraces IG-02-121, IG-02-129 and IG-02-113 were found superior formorphological traits as well as most distant among all the landraces under study. Hence, these landraces could be used in forfuture breeding programmes for genetic improvement in oats

Molecular Mapping of Biofortification Traits in Bread Wheat (<i>Triticum aestivum</i> L.) Using a High-Density SNP Based Linkage Map

A set of 188 recombinant inbred lines (RILs) derived from a cross between a high-yielding Indian bread wheat cultivar HD2932 and a synthetic hexaploid wheat (SHW) Synthetic 46 derived from tetraploid Triticum turgidum (AA, BB 2n = 28) and diploid Triticum tauschii (DD, 2n = 14) was used to identify novel genomic regions associated in the expression of grain iron concentration (GFeC), grain zinc concentration (GZnC), grain protein content (GPC) and thousand kernel weight (TKW). The RIL population was genotyped using SNPs from 35K Axiom® Wheat Breeder’s Array and 34 SSRs and phenotyped in two environments. A total of nine QTLs including five for GPC (QGpc.iari_1B, QGpc.iari_4A, QGpc.iari_4B, QGpc.iari_5D, and QGpc.iari_6B), two for GFeC (QGfec.iari_5B and QGfec.iari_6B), and one each for GZnC (QGznc.iari_7A) and TKW (QTkw.iari_4B) were identified. A total of two stable and co-localized QTLs (QGpc.iari_4B and QTkw.iari_4B) were identified on the 4B chromosome between the flanking region of Xgwm149–AX-94559916. In silico analysis revealed that the key putative candidate genes such as P-loop containing nucleoside triphosphatehydrolase, Nodulin-like protein, NAC domain, Purine permease, Zinc-binding ribosomal protein, Cytochrome P450, Protein phosphatase 2A, Zinc finger CCCH-type, and Kinesin motor domain were located within the identified QTL regions and these putative genes are involved in the regulation of iron homeostasis, zinc transportation, Fe, Zn, and protein remobilization to the developing grain, regulation of grain size and shape, and increased nitrogen use efficiency. The identified novel QTLs, particularly stable and co-localized QTLs are useful for subsequent use in marker-assisted selection (MAS)

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Not AvailableHeat stress is one of the most limiting factors for the production of wheat. Global warming and consequent changes in climate adversely affect wheat plant growth and yield. To elucidate genetic basis and map heat tolerance traits, a set of 134 backcross inbred lines (BILs) derived from the cross between WH730/*2 HD2733 was used. The population was evaluated under late sown (LS) and very late sown (VLS) conditions, by exposing to heat stress during rabi season. Positive association of normalized difference vegetation index (NDVI), thousand grain weight (TGW), grain weight per spike (GWS), biomass and grain yield (GY) under both production conditions was observed. However, canopy temperature (CT) and days to heading (DH) showed negative correlation with GY under heat stress. A total of 9 Quantitative trait loci (QTL) were discovered on 7 chromosomes, which includes 4 QTLs in LS and 5 QTLs under VLS condition. Combining the results of these QTLs revealed a major stable QTL for DH (qDH_iari_5A) on chromosome 5A with 23% and 26% explaining phenotypic variance under both sowing conditions. QTL for NDVI was detected on chromosome 1B while QTL for SL and GY on chromosome 2A. The identified QTLs in the genomic regions could be targeted for genetic improvement and marker assisted selection for heat tolerance in wheat.Not Availabl