Genetic Mapping and Diversity in Plants and Animals

This study presents a T2T genome and graph-based pan-genome of longan, identifying structural variants and QTLs associated with maturity period and providing resources for genetic improvement.

QTLIT is a Shiny app that simplifies QTL analysis by integrating SNP identification and visualization tools for plant breeders using DNA sequence data.

This study maps genome-wide associations for grain and forage quality traits in a subtropical oat germplasm collection, identifying SNPs and candidate genes linked to yield and resilience.

The paper identifies a novel Sh1 allele in corn that synergizes with waxy1 to alter carbohydrate metabolism, resulting in a waxy-sweet texture in maize kernels.

The paper investigates how hybridization affects gene expression in brain tissues by identifying cell type-specific regulatory variation in interspecies fish hybrids.

The paper investigates how trans-eQTL hotspots contribute to phenotypic heterosis in maize by regulating non-additive gene expression through transcription factors.

This study identifies population-specific genetic strategies for agronomic traits in Coffea canephora using genomic analysis and machine learning, revealing distinct biological pathways in two populations.

This study integrates multi-omics data to identify genes influencing yield in maize, showing improved resolution and predictive power compared to GWAS.

The paper uses a multiparent yeast population to identify QTL for growth rates across environments, revealing context-dependent genetic architectures and allelic heterogeneity.

This paper establishes the first NAM population in Italian ryegrass to identify candidate genes for seed shattering and related traits using ddRAD and whole genome sequencing.

This paper uses composite interval mapping and genomic prediction to identify QTL and improve prediction accuracy for nut quality traits in American and interspecific hybrid hazelnuts.

This study integrates metabolomics and genomics in sorghum to uncover the genetic basis of metabolic diversity, identifying millions of SNP-metabolite associations and gene clusters.

The paper identifies trans-regulatory variants associated with chromatin accessibility in maize hybrids, revealing their role in heterosis and gene expression.

The paper develops and validates a 30K SNP genotyping tool for flax breeding, showing high polymorphism and genotyping accuracy.

The paper develops an in silico method to predict restriction enzyme performance for complexity-reduced genome sequencing, finding that MspI and PstI are highly informative for plant genomes.

This study identifies a genomic region on chromosome 10 associated with photosensitivity in eggplants and suggests SmNAC1-like gene involvement in anthocyanin biosynthesis.

The paper presents a genomic breeding strategy using large-scale recombinant populations and prediction models to rapidly develop rice cultivars with desired traits.

This paper estimates heritability and identifies QTL for aerial root traits and yield components in maize, finding genetic overlap with introgression from wild mexicana.

This study investigates the domestication history and genetic diversity of teff using genomic analyses, identifying key loci associated with seed color and panicle architecture.

The paper compares PCA-based QTL mapping with individual trait hotspots in metabolomic and transcriptomic data from a recombinant inbred line, finding they identify different genomic regions and genetic architectures.

The paper develops and validates a high-density SNP array for potato, demonstrating its utility in genetic diversity analysis, GWAS, and genomic prediction.

This study identifies genetic loci for MetS-like traits in Drosophila and finds that main genetic effects are distinct from diet-dependent plastic loci.

This paper constructs a sorghum pangenome and identifies trait-associated variants to inform climate-aware genome-enabled breeding strategies.

PlantVarFilter is a Python pipeline for variant filtering and GWAS in plants, supporting multiple formats and providing statistical analysis and visualization tools.

The paper conducts GWAS on Lactuca species to identify genetic loci associated with phenotypic traits, finding novel QTLs in wild species not detected in domesticated lettuce.

This study identifies genetic factors influencing aerial root traits in maize that support biological nitrogen fixation, finding heritable traits and QTLs from landrace and elite inbred varieties.

This study identifies genetic loci and subgroups in DO mice linked to anxiety-like behavior and ethanol consumption using behavioral assays and QTL analysis.

This study identifies 21 QTNs and 750 candidate genes associated with nitrogen use efficiency in potato through GWAS, contributing to understanding its genetic basis.

The paper develops a SNP array panel for Salix suchowensis to improve genotyping and identifies SNPs associated with growth traits.

This study introduces hQTL-ODS, a one-dimensional scan method for detecting heterotic QTLs, showing improved computational efficiency and reduced false positives in wheat hybrids.