MVQTLCIM: composite interval mapping of multivariate traits in a hybrid F1 population of outbred species

Identify of Fast-Growing Related Genes Especially in Height Growth by Combining QTL Analysis and Transcriptome in Salix matsudana (Koidz)

The study on the fast-growing traits of trees, mainly valued by tree height (TH) and diameter at breast height (DBH), is of great significance to promote the development of the forest industry. Quantitative trait locus (QTL) mapping based on high-density genetic maps is an efficient approach to identify genetic regions for fast-growing traits. In our study, a high-density genetic map for the F₁ population was constructed. The genetic map had a total size of 5,484.07 centimorgan (cM), containing 5,956 single nucleotide polymorphisms (SNPs) based on Specific Length Amplified Fragment sequencing. Six fast-growing related stable QTL were identified on six chromosomes, and five stable QTL were identified by a principal component analysis (PCA). By combining the RNA-seq analysis for the two parents and two progenies with the qRT-PCR analysis, four candidate genes, annotated as DnaJ, 1-aminocyclopropane-1-carboxylate oxidase 1 (ACO1), Caffeic acid 3-O-methyltransferase 1 (COMT1), and Dirigent protein 6 (DIR6), that may regulate height growth were identified. Several lignin biosynthesis-related genes that may take part in height growth were detected. In addition, 21 hotspots in this population were found. The results of this study will provide an important foundation for further studies on the molecular and genetic regulation of TH and DBH.

Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design

With the advances in high-throughput sequencing technologies, it is not difficult to extract tens of thousands of single-nucleotide polymorphisms (SNPs) across many individuals in a fast and cheap way, making it possible to perform genome-wide association studies (GWAS) of quantitative traits in outbred forest trees. It is very valuable to apply traditional breeding experiments in GWAS for identifying genome variants associated with ecologically and economically important traits in Populus. Here, we reported a GWAS of tree height measured at multiple time points from a randomized complete block design (RCBD), which was established with clones from an F₁ hybrid population of Populus deltoides and Populus simonii. A total of 22,670 SNPs across 172 clones in the RCBD were obtained with restriction site-associated DNA sequencing (RADseq) technology. The multivariate mixed linear model was applied by incorporating the pedigree relationship matrix of individuals to test the association of each SNP to the tree heights over 8 time points. Consequently, 41 SNPs were identified significantly associated with the tree height under the P-value threshold determined by Bonferroni correction at the significant level of 0.01. These SNPs were distributed on all but two chromosomes (Chr02 and Chr18) and explained the phenotypic variance ranged from 0.26% to 2.64%, amounting to 63.68% in total. Comparison with previous mapping studies for poplar height as well as the candidate genes of these detected SNPs were also investigated. We therefore showed that the application of multivariate linear mixed model to the longitudinal phenotypic data from the traditional breeding experimental design facilitated to identify far more genome-wide variants for tree height in poplar. The significant SNPs identified in this study would enhance understanding of molecular mechanism for growth traits and would accelerate marker-assisted breeding programs in Populus.

High-Quality SNP Linkage Maps Improved QTL Mapping and Genome Assembly in Populus

With the advances in high-throughput sequencing technologies and the development of new software for extracting single nucleotide polymorphisms (SNPs) across a mapping population, it is possible to construct high-quality genetic maps with thousands of SNPs in outbred forest trees. Two parent-specific linkage maps were constructed with restriction site-associated DNA sequencing data from an F₁ hybrid population derived from Populus deltoides and Populus simonii, and applied in QTL mapping and genome assembly. The female P. deltoides map contained 4018 SNPs, which were divided into 19 linkage groups under a wide range of LOD thresholds from 7 to 55. The male P. simonii map showed similar characteristics, consisting of 2097 SNPs, which also belonged to 19 linkage groups under LOD thresholds of 7 to 29. The SNP order of each linkage group was optimal among different ordering results from several available software. Moreover, the linkage maps allowed the detection of 39 QTLs underlying tree height and 47 for diameter at breast height. In addition, the linkage maps improved the anchoring of 689 contigs of P. simonii to chromosomes. The 2 parental genetic maps of Populus are of high quality, especially in terms of SNP data quality, the SNP order within linkage groups, and the perfect match between the number of linkage groups and the karyotype of Populus, as well as the excellent performances in QTL mapping and genome assembly. Both approaches for extracting and ordering SNPs could be applied to other species for constructing high-quality genetic maps.

gmRAD: an integrated SNP calling pipeline for genetic mapping with RADseq across a hybrid population

Restriction site-associated DNA sequencing (RADseq) is a powerful technology that has been extensively applied in population genetics, phylogenetics and genetic mapping. Although many software packages are available for ecological and evolutionary studies, a few effective tools are available for extracting genotype data with RADseq for genetic mapping, a prerequisite for quantitative trait locus mapping, comparative genomics and genome scaffold assembly. Here, we present an integrated pipeline called gmRAD for generating single nucleotide polymorphism (SNP) genotypes from RADseq data, de novo, across a genetic mapping population derived by crossing two parents. As an analytical strategy, the software takes five steps to implement the whole algorithms, including clustering the first (forward) reads of each parent, building two parental references, generating parental SNP catalogs, calling SNP genotypes across all individuals and filtering the genotype data for genetic linkage mapping. All the steps can be completed with a simple command line, but they can be also performed optionally if prerequisite files are available. To validate its application, we also performed a real data analysis with RADseq data from an F1 hybrid population derived by crossing Populus deltoides and Populus simonii. The software gmRAD is freely available at https://github.com/tongchf/gmRAD.