• GENOMICS
  • AGRIGENOMICS

Agrigenomics

Genetic resources in Agriculture

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Scientific Bio-Minds agriculture genomic specialists is providing powerful tools to address the need to develop crop strains that can support increased food production while resisting pests and disease and reducing the environmental footprint, in terms of toxic chemicals and carbon emissions,of traditional farming.

The use of genomics for crop improvement promises to increase quality and yield of crops while using less fertilizer, pesticides and water. DNA tests based on the genome sequences of plants are making the selective breeding process more targeted and two to three times faster. In certain cases, genetic modification is creating plant strains with new properties that improve productivity and nutritional value.

Application

  • Sequencing for SNP discovery
  • Bioinformatics to select the best SNPs for genome wide association studies
  • Identification of quantitative trait loci (QTL)
  • Build high or medium density SNP arrays to create genomic models
  • Build low density arrays and panels for marker assisted selection
  • Use diagnostic tools to identify resistant or susceptible lines

A variation in a single base (Adenine, Thymine, Cytosine or Guanine) within a sequence of DNA. SNPs do not generally cause disease directly but some SNPs may affect an individual’s susceptibility to disease or the response to the drugs and treatments.

  • Homogenous Detection
  • Microarray genotyping
  • Genome-wide selection
  • Determining genetic merit
  • Identification of QTLs
  • Comparative genetic studies
  • etc...

Quantitative trait locus (QTL) analysis is a statistical method that links two types of information—phenotypic data (trait measurements) and genotypic data (usually molecular markers)—in an attempt to explain the genetic basis of variation in complex traits. QTL analysis allows researchers in fields as diverse as agriculture, evolution, and medicine to link certain complex phenotypes to specific regions of chromosomes. The goal of this process is to identify the action, interaction, number, and precise location of these regions.

  • Singal QTL Analysis
  • Multiple QTL Analysis
  • Interval Mapping
  • Composite interval mapping
  • Family-pedigree based mapping
  • Detection of monogenic & QTL

The use of a molecular marker (e.g. DNA or RNA) linked to a trait of interest that can be used to identify the most favourable individuals to be used for breeding purposes.

  • Marker Assisted Backcross Selection
  • Genomic Wide Association Selection
  • Assessment of genetic variability and characterization of germplasm
  • Identification and fingerprinting of genotypes
  • Estimation of genetic distances between population, inbreeds, and breeding materials
  • Identification of sequences of useful candidate genes
  • Pathogen Resistant Genetic Markers

  • Virulence Variation in Pathogen Populations
  • Molecular Markers in Plant Pathogens
  • Pathogen Population Genetics and Resistance Breeding

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