Welcome To Website IAS

Hot news
Achievement

Independence Award

- First Rank - Second Rank - Third Rank

Labour Award

- First Rank - Second Rank -Third Rank

National Award

 - Study on food stuff for animal(2005)

 - Study on rice breeding for export and domestic consumption(2005)

VIFOTEC Award

- Hybrid Maize by Single Cross V2002 (2003)

- Tomato Grafting to Manage Ralstonia Disease(2005)

- Cassava variety KM140(2010)

Centres
Website links
Vietnamese calendar
Library
Visitors summary
 Curently online :  2
 Total visitors :  4781318

Genome-based trait prediction in multi- environment breeding trials in groundnut
Thursday, 2020/10/29 | 08:21:27

Manish K. PandeySunil ChaudhariDiego JarquinPasupuleti JanilaJose CrossaSudam C. PatilSubramaniam SundravadanaDhirendra KhareRamesh S. BhatThankappan RadhakrishnanJohn M. Hickey & Rajeev K. Varshney

Theoretical and Applied Genetics November 2020; vol. 133:3101–3117.

Key message

Comparative assessment identified naïve interaction model, and naïve and informed interaction GS models suitable for achieving higher prediction accuracy in groundnut keeping in mind the high genotype × environment interaction for complex traits.

Abstract

Genomic selection (GS) can be an efficient and cost-effective breeding approach which captures both small- and large-effect genetic factors and therefore promises to achieve higher genetic gains for complex traits such as yield and oil content in groundnut. A training population was constituted with 340 elite lines followed by genotyping with 58 K ‘Axiom_Arachis’ SNP array and phenotyping for key agronomic traits at three locations in India. Four GS models were tested using three different random cross-validation schemes (CV0, CV1 and CV2). These models are: (1) model 1 (M1 = E + L) which includes the main effects of environment (E) and line (L); (2) model 2 (M2 = E + L + G) which includes the main effects of markers (G) in addition to E and L; (3) model 3 (M3 = E + L + G + GE), a naïve interaction model; and (4) model 4 (E + L + G + LE + GE), a naïve and informed interaction model. Prediction accuracy estimated for four models indicated clear advantage of the inclusion of marker information which was reflected in better prediction accuracy achieved with models M2, M3 and M4 as compared to M1 model. High prediction accuracies (> 0.600) were observed for days to 50% flowering, days to maturity, hundred seed weight, oleic acid, rust@90 days, rust@105 days and late leaf spot@90 days, while medium prediction accuracies (0.400–0.600) were obtained for pods/plant, shelling  %, and total yield/plant. Assessment of comparative prediction accuracy for different GS models to perform selection for untested genotypes, and unobserved and unevaluated environments provided greater insights on potential application of GS breeding in groundnut.

 

See https://link.springer.com/article/10.1007/s00122-020-03658-1

Figure 1: Cross-validation between the predicted and the observed values for a unobserved environment (CV0); b untested genotypes (CV1); and unevaluated environment (CV2) for different agronomic, quality and disease resistance traits of groundnut

Back      Print      View: 30

[ Other News ]___________________________________________________
  • Genome-wide analysis of autophagy-associated genes in foxtail millet (Setaria italica L.) and characterization of the function of SiATG8a in conferring tolerance to nitrogen starvation in rice.
  • Arabidopsis small nucleolar RNA monitors the efficient pre-rRNA processing during ribosome biogenesis
  • XA21-specific induction of stress-related genes following Xanthomonas infection of detached rice leaves.
  • Reducing the Use of Pesticides with Site-Specific Application: The Chemical Control of Rhizoctonia solani as a Case of Study for the Management of Soil-Borne Diseases
  • OsJRL, a rice jacalin-related mannose-binding lectin gene, enhances Escherichia coli viability under high-salinity stress and improves salinity tolerance of rice.
  • Production of lipopeptide biosurfactants by Bacillus atrophaeus 5-2a and their potential use in microbial enhanced oil recovery.
  • GhABF2, a bZIP transcription factor, confers drought and salinity tolerance in cotton (Gossypium hirsutum L.).
  • Resilience of cassava (Manihot esculenta Crantz) to salinity: implications for food security in low-lying regions.
  • Cellulose synthase complexes act in a concerted fashion to synthesize highly aggregated cellulose in secondary cell walls of plants
  • No adverse effects of transgenic maize on population dynamics of endophytic Bacillus subtilis strain B916-gfp
  • Identification and expression analysis of OsLPR family revealed the potential roles of OsLPR3 and 5 in maintaining phosphate homeostasis in rice
  • Functional analysis of molecular interactions in synthetic auxin response circuits
  • Titanium dioxide nanoparticles strongly impact soil microbial function by affecting archaeal nitrifiers.
  • Inducible Expression of the De-Novo Designed Antimicrobial Peptide SP1-1 in Tomato Confers Resistance to Xanthomonas campestris pv. vesicatoria.
  • Toward combined delignification and saccharification of wheat straw by a laccase-containing designer cellulosome
  • SNP-based discovery of salinity-tolerant QTLs in a bi-parental population of rice (Oryza sativa)
  • Pinpointing genes underlying the quantitative trait loci for root-knot nematode resistance in palaeopolyploid soybean by whole genome resequencing.
  • Transcriptome- Assisted Label-Free Quantitative Proteomics Analysis Reveals Novel Insights into Piper nigrum -Phytophthora capsici Phytopathosystem.
  • Brassinosteroids participate in the control of basal and acquired freezing tolerance of plants
  • Rapid hyperosmotic-induced Ca2+ responses in Arabidopsis thaliana exhibit sensory potentiation and involvement of plastidial KEA transporters

 

Designed & Powered by WEBSO CO.,LTD