Subtopic Deep Dive

Marker-Assisted Selection in Peanut
Research Guide

What is Marker-Assisted Selection in Peanut?

Marker-Assisted Selection (MAS) in peanut uses molecular markers like SSRs and SNPs to indirectly select desirable traits in breeding programs.

MAS applies SSR markers for diversity assessment (Luu Minh Cuc et al., 2008, 249 citations) and SNPs via KASP assays for genotyping (Pawan Khera et al., 2013, 226 citations). Researchers identify marker-trait associations, including QTLs for drought tolerance (K Ravi et al., 2010, 218 citations) and disease resistance (Manish K. Pandey et al., 2016, 202 citations). Over 10 key papers since 2003 detail genomic tools for peanut improvement.

Curated Papers

Key Challenges

Why It Matters

MAS shortens breeding cycles for traits like drought tolerance and rust resistance, boosting peanut yield in semi-arid regions (K Ravi et al., 2010; Manish K. Pandey et al., 2016). It leverages diploid ancestor genomes to overcome tetraploid challenges (David J. Bertioli et al., 2016; Manish K. Pandey et al., 2011). Applications include developing high-oil, disease-resistant cultivars using SSRs and SNPs (Pasupuleti Janila et al., 2013; Pawan Khera et al., 2013).

Key Research Challenges

Tetraploid Genome Complexity

Cultivated peanut's allotetraploid nature blocks gene flow from diploids and complicates marker development (Manish K. Pandey et al., 2011). Recent polyploidization hinders precise MAS (David J. Bertioli et al., 2016). Self-pollination narrows genetic diversity.

Limited Marker-Trait Associations

Few validated QTLs exist for key traits like drought and disease resistance (K Ravi et al., 2010). Epistatic interactions reduce MAS reliability (Manish K. Pandey et al., 2016). High-throughput SNP assays are needed for efficiency (Pawan Khera et al., 2013).

SSR and SNP Assay Costs

Developing cost-effective KASP SNP markers requires large reference sets (Pawan Khera et al., 2013). Microsatellite isolation demands extensive sequencing (Guohao He et al., 2003; Luu Minh Cuc et al., 2008). Scaling for breeding programs challenges resource-limited labs.

Essential Papers

The genome sequences of Arachis duranensis and Arachis ipaensis, the diploid ancestors of cultivated peanut

David J. Bertioli, Steven B. Cannon, Lutz Froenicke et al. · 2016 · Nature Genetics · 1.0K citations

Advances in Arachis genomics for peanut improvement

Manish K. Pandey, E. S. Monyo, Peggy Ozias‐Akins et al. · 2011 · Biotechnology Advances · 305 citations

Peanut genomics is very challenging due to its inherent problem of genetic architecture. Blockage of gene flow from diploid wild relatives to the tetraploid; cultivated peanut, recent polyploidizat...

Draft genome of the peanut A-genome progenitor (<i>Arachis duranensis</i>) provides insights into geocarpy, oil biosynthesis, and allergens

Xiaoping Chen, Hongjie Li, Manish K. Pandey et al. · 2016 · Proceedings of the National Academy of Sciences · 291 citations

Significance We present a draft genome of the peanut A-genome progenitor, Arachis duranensis , providing details on total genes present in the genome. Genome analysis suggests that the peanut linea...

Isolation and characterization of novel microsatellite markers and their application for diversity assessment in cultivated groundnut (Arachis hypogaea)

Luu Minh Cuc, Emma Mace, Jonathan H. Crouch et al. · 2008 · BMC Plant Biology · 249 citations

Groundnut improvement: use of genetic and genomic tools

Pasupuleti Janila, S. N. Nigam, Manish K. Pandey et al. · 2013 · Frontiers in Plant Science · 240 citations

Groundnut (Arachis hypogaea L.), a self-pollinated legume is an important crop cultivated in 24 million ha world over for extraction of edible oil and food uses. The kernels are rich in oil (48-50%...

Single Nucleotide Polymorphism–based Genetic Diversity in the Reference Set of Peanut ( <i>Arachis</i> spp.) by Developing and Applying Cost‐Effective Kompetitive Allele Specific Polymerase Chain Reaction Genotyping Assays

Pawan Khera, Hari D. Upadhyaya, Manish K. Pandey et al. · 2013 · The Plant Genome · 226 citations

Kompetitive allele‐specific polymerase chain reaction (KASP) assays have emerged as cost‐effective marker assays especially for molecular breeding applications. Therefore, a set of 96 informative s...

Microsatellites as DNA markers in cultivated peanut (Arachis hypogaea L.)

Guohao He, Ronghua Meng, M. Newman et al. · 2003 · BMC Plant Biology · 221 citations

Reading Guide

Foundational Papers

Start with Pandey et al. (2011, 305 citations) for genomics challenges, He et al. (2003, 221 citations) for SSR markers, and Janila et al. (2013, 240 citations) for genetic tools in breeding.

Recent Advances

Study Bertioli et al. (2016, 1027 citations) for diploid genomes, Pandey et al. (2016, 202 citations) for QTL-seq in disease resistance, and Varshney et al. (2018, 209 citations) for sequence-based breeding.

Core Methods

Core techniques include SSR isolation (Guohao He et al., 2003), KASP SNP genotyping (Pawan Khera et al., 2013), and QTL-seq for marker-trait mapping (Manish K. Pandey et al., 2016).

How PapersFlow Helps You Research Marker-Assisted Selection in Peanut

Discover & Search

Research Agent uses searchPapers and exaSearch to find MAS papers like 'QTL-seq approach... in groundnut' (Manish K. Pandey et al., 2016), then citationGraph reveals connections to Bertioli et al. (2016) diploid genomes, and findSimilarPapers uncovers SNP studies (Pawan Khera et al., 2013).

Analyze & Verify

Analysis Agent applies readPaperContent to extract QTL regions from Pandey et al. (2016), verifies marker associations with verifyResponse (CoVe), and runs PythonAnalysis on citation data for statistical validation of drought QTL effects (K Ravi et al., 2010) using GRADE for evidence strength.

Synthesize & Write

Synthesis Agent detects gaps in tetraploid MAS via contradiction flagging across Pandey et al. (2011) and Bertioli et al. (2016); Writing Agent uses latexEditText, latexSyncCitations for breeding schemes, and latexCompile to generate reports with exportMermaid for QTL linkage diagrams.

Use Cases

"Analyze SNP diversity data from Khera et al. 2013 for peanut MAS correlations"

Research Agent → searchPapers → Analysis Agent → readPaperContent + runPythonAnalysis (pandas correlation on KASP SNP data) → CSV export of trait associations.

"Draft LaTeX review on QTLs for rust resistance in peanut from Pandey 2016"

Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations (Pandey et al. 2016) + latexCompile → PDF with integrated QTL diagrams.

"Find code for SSR marker analysis in peanut diversity studies"

Research Agent → paperExtractUrls (Luu Minh Cuc et al. 2008) → Code Discovery → paperFindGithubRepo → githubRepoInspect → Python scripts for microsatellite genotyping.

Automated Workflows

Deep Research workflow scans 50+ peanut MAS papers via searchPapers → citationGraph, producing structured reports on SNP/SSR progress (Khera 2013, Cuc 2008). DeepScan applies 7-step CoVe analysis to verify QTL claims (Pandey 2016; Ravi 2010) with GRADE checkpoints. Theorizer generates hypotheses linking diploid genomes (Bertioli 2016) to tetraploid MAS gaps.

Try Doxa for Marker-Assisted Selection in Peanut Research

Frequently Asked Questions

What is Marker-Assisted Selection in peanut?

MAS uses SSRs and SNPs to select traits like disease resistance without phenotyping every plant (Pasupuleti Janila et al., 2013).

What molecular markers are used in peanut MAS?

SSR markers assess diversity (Luu Minh Cuc et al., 2008; Guohao He et al., 2003) and SNPs via KASP enable high-throughput genotyping (Pawan Khera et al., 2013).

What are key papers on peanut MAS?

Pandey et al. (2016, 202 citations) map QTLs for rust/LLS; K Ravi et al. (2010, 218 citations) identify drought QTLs; Bertioli et al. (2016, 1027 citations) provide ancestor genomes.

What are open problems in peanut MAS?

Validating epistatic QTLs across environments and scaling cost-effective SNPs for breeding remain challenges (Manish K. Pandey et al., 2011; Pawan Khera et al., 2013).