Continuous progress in genome sequencing and assembly, coupled with the growing availability of massive resources of long-read genomic sequences and high-quality molecular markers, based on single nucleotide polymorphisms (SNPs) and insertions-deletions (indels), demands accurate methods to easily, accurately and readily determine marker positions across genome versions. This is particularly important for applications such as development and updating of genotyping array. However, existing tools often require an associated reference genome for the molecular markers and additional adaptations are needed to map the short context sequences of these markers when no such reference genome is available. To overcome these limitations, our aim was to develop an original pipeline.
AlignMarkers is a robust bioinformatics pipeline designed to accurately place molecular markers on genome assemblies without requiring information on initial positions on a reference genome, using sequence alignment. It can also operate on coordinate-based files to perform liftover-like analyses, providing an alternative when genome-to-genome alignments could not be generated. It accepts multiple input file formats (VCF, BED, FASTA, CSV) and is optimized for sequences of ≥ 100 base pairs. Context sequences are retrieved, when only coordinates are provided, and then aligned to target genomes using Minimap2, followed by a stringent filtering process ensuring alignment uniqueness, high sequence identity, and verification of the expected nucleotide. AlignMarkers is built with Nextflow and Python and integrates established tools such as Minimap2, Samtools, and Bedtools. It generates comprehensive reports and visualizations to facilitate result interpretation. We evaluated AlignMarkers using 80,000 randomly selected positions across the version 2
Pisum sativum
genome assembly of cultivar Cameor, showing that increasing flanking sequence length improves placement accuracy and reduces multimapping, especially in repeat-rich regions. We further benchmarked AlignMarkers on 100,000
Solanum lycopersicum
SNPs and indels against CrossMap and bcftools/liftover, showing high concordance in the outputs of all tools. These results demonstrate the robustness and reliability of the pipeline when used with different marker resources.
AlignMarkers is a reliable and user-friendly solution for transferring marker positions. It supports multiple applications and facilitates the management of large sets of molecular markers for various purposes, including the construction of genotyping platforms.
Faba bean is a globally adapted legume protein crop with a high yield potential. Currently, yield variation across environments limits more widespread cultivation, and the underlying genetics remain poorly understood. Here, we identify major QTL for faba bean yield and yield stability. We genotype the ProFaba diversity panel with high resolution and carry out coordinated multi-year/location trials across Europe. Based on these data, we identify more than one hundred loci associated with mean performance and stability for 14 complex traits, including yield. Experimental validation supports the involvement of the candidate gene Vfaba.Hedin2.R2.1g002122 in plant architecture, with gene expression significantly associated with first pod position and plant height. Furthermore, we introduce a method for integrating environmental data in the analysis of trait stability based on a random regression mixed model, which enables prediction of performance in untested environments. Our study provides insights into the genetic architecture of yield, yield stability, and genotype-by-environment interaction in faba bean. The genomic resources, candidate loci, and weather-informed analytical framework provide practical tools for predicting performance across environments and accelerating breeding of resilient, high-yielding protein crops.
Elesandro Bornhofen, Troels W. Mouritzen, Sheila Alves et al.· Genome Biology· 0 citations