scholarly journals Using Probabilistic Genotypes in Linkage Analysis of polyploids

Author(s):  
Yanlin Liao ◽  
Roeland E. Voorrips ◽  
Peter M. Bourke ◽  
Giorgio Tumino ◽  
Paul Arens ◽  
...  

Abstract Marker genotypes are generally called as discrete values: homozygous versus heterozygous in the case of diploids, or an integer allele dosage in the case of polyploids. Software for linkage map construction and/or QTL analysis usually relies on such discrete genotypes. However, it may not always be possible, or desirable, to assign definite values to genotype observations in the presence of uncertainty in the genotype calling. Here, we present an approach that uses probabilistic marker dosages for linkage map construction in polyploids. We compare our method to an approach based on discrete dosages, using simulated SNP array and sequence reads data with varying levels of data quality. We validate our approach using experimental data from a potato (Solanum tuberosum L.) SNP array applied to an F1 mapping population. In comparison to the approach based on discrete dosages, we mapped an additional 562 markers. All but three of these were mapped to the expected chromosome and marker position. For the remaining three markers, no physical position was known. The use of dosage probabilities is of particular relevance for map construction in polyploids using sequencing data, as these often result in a higher level of uncertainty regarding allele dosage.

Author(s):  
Yanlin Liao ◽  
Roeland E. Voorrips ◽  
Peter M. Bourke ◽  
Giorgio Tumino ◽  
Paul Arens ◽  
...  

Abstract Key message In polyploids, linkage mapping is carried out using genotyping with discrete dosage scores. Here, we use probabilistic genotypes and we validate it for the construction of polyploid linkage maps. Abstract Marker genotypes are generally called as discrete values: homozygous versus heterozygous in the case of diploids, or an integer allele dosage in the case of polyploids. Software for linkage map construction and/or QTL analysis usually relies on such discrete genotypes. However, it may not always be possible, or desirable, to assign definite values to genotype observations in the presence of uncertainty in the genotype calling. Here, we present an approach that uses probabilistic marker dosages for linkage map construction in polyploids. We compare our method to an approach based on discrete dosages, using simulated SNP array and sequence reads data with varying levels of data quality. We validate our approach using experimental data from a potato (Solanum tuberosum L.) SNP array applied to an F1 mapping population. In comparison to the approach based on discrete dosages, we mapped an additional 562 markers. All but three of these were mapped to the expected chromosome and marker position. For the remaining three markers, no physical position was known. The use of dosage probabilities is of particular relevance for map construction in polyploids using sequencing data, as these often result in a higher level of uncertainty regarding allele dosage.


Horticulturae ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 25
Author(s):  
Xingbo Wu ◽  
Amanda M. Hulse-Kemp ◽  
Phillip A. Wadl ◽  
Zach Smith ◽  
Keithanne Mockaitis ◽  
...  

Hydrangea (Hydrangea macrophylla) is an important ornamental crop that has been cultivated for more than 300 years. Despite the economic importance, genetic studies for hydrangea have been limited by the lack of genetic resources. Genetic linkage maps and subsequent trait mapping are essential tools to identify and make markers available for marker-assisted breeding. A transcriptomic study was performed on two important cultivars, Veitchii and Endless Summer, to discover simple sequence repeat (SSR) markers and an F1 population based on the cross ‘Veitchii’ × ‘Endless Summer’ was established for genetic linkage map construction. Genotyping by sequencing (GBS) was performed on the mapping population along with SSR genotyping. From an analysis of 42,682 putative transcripts, 8780 SSRs were identified and 1535 were validated in the mapping parents. A total of 267 polymorphic SSRs were selected for linkage map construction. The GBS yielded 3923 high quality single nucleotide polymorphisms (SNPs) in the mapping population, resulting in a total of 4190 markers that were used to generate maps for each parent and a consensus map. The consensus linkage map contained 1767 positioned markers (146 SSRs and 1621 SNPs), spanned 1383.4 centiMorgans (cM), and was comprised of 18 linkage groups, with an average mapping interval of 0.8 cM. The transcriptome information and large-scale marker development in this study greatly expanded the genetic resources that are available for hydrangea. The high-density genetic linkage maps presented here will serve as an important foundation for quantitative trait loci mapping, map-based gene cloning, and marker-assisted selection of H. macrophylla.


2020 ◽  
Vol 12 (11) ◽  
pp. 1953-1960
Author(s):  
Andrey A Yurchenko ◽  
Hans Recknagel ◽  
Kathryn R Elmer

Abstract Squamate reptiles exhibit high variation in their phenotypic traits and geographical distributions and are therefore fascinating taxa for evolutionary and ecological research. However, genomic resources are very limited for this group of species, consequently inhibiting research efforts. To address this gap, we assembled a high-quality genome of the common lizard, Zootoca vivipara (Lacertidae), using a combination of high coverage Illumina (shotgun and mate-pair) and PacBio sequencing data, coupled with RNAseq data and genetic linkage map generation. The 1.46-Gb genome assembly has a scaffold N50 of 11.52 Mb with N50 contig size of 220.4 kb and only 2.96% gaps. A BUSCO analysis indicates that 97.7% of the single-copy Tetrapoda orthologs were recovered in the assembly. In total, 19,829 gene models were annotated to the genome using a combination of ab initio and homology-based methods. To improve the chromosome-level assembly, we generated a high-density linkage map from wild-caught families and developed a novel analytical pipeline to accommodate multiple paternity and unknown father genotypes. We successfully anchored and oriented almost 90% of the genome on 19 linkage groups. This annotated and oriented chromosome-level reference genome represents a valuable resource to facilitate evolutionary studies in squamate reptiles.


Genome ◽  
2003 ◽  
Vol 46 (5) ◽  
pp. 738-744 ◽  
Author(s):  
M E Humphry ◽  
T Magner ◽  
C L McIntyre ◽  
E A.B Aitken ◽  
C J Liu

A major locus conferring resistance to the causal organism of powdery mildew, Erysiphe polygoni DC, in mungbean (Vigna radiata L. Wilczek) was identified using QTL analysis with a population of 147 recombinant inbred individuals. The population was derived from a cross between 'Berken', a highly susceptible variety, and ATF 3640, a highly resistant line. To test for response to powdery mildew, F7 and F8 lines were inoculated by dispersing decaying mungbean leaves with residual conidia of E. polygoni amongst the young plants to create an artificial epidemic and assayed in a glasshouse facility. To generate a linkage map, 322 RFLP clones were tested against the two parents and 51 of these were selected to screen the mapping population. The 51 probes generated 52 mapped loci, which were used to construct a linkage map spanning 350 cM of the mungbean genome over 10 linkage groups. Using these markers, a single locus was identified that explained up to a maximum of 86% of the total variation in the resistance response to the pathogen.Key words: mungbean, powdery mildew, Erysiphe polygoni, QTL, molecular markers.


2012 ◽  
Vol 61 (1-6) ◽  
pp. 1-9 ◽  
Author(s):  
Kaixuan Zhang ◽  
Dan Wang ◽  
Chuanping Yang ◽  
Guanjun Liu ◽  
Guifeng Liu ◽  
...  

AbstractA linkage map for Betula platyphylla Suk was constructed based on RAPD, ISSR, AFLP and SSR markers by a pseudo-testcross mapping strategy. A F1segregating population including 80 progenies was obtained from the cross between two superior trees selected from Qinghai and Wangqing provenance, respectively. The paternal map was constructed with 282 markers consisting of 14 major and 15 minor (5 triplets and 10 doublets) linkage groups and spanning 1131 cM at an average distance of 4.0 cM between adjacent markers. The maternal map has 277 markers consisting of 15 major and 8 minor (5 triplets and 3 doublets) groups covering 1288 cM at an average distance of 4.6 cM between adjacent markers. In the same pedigree we investigated association of genetic markers with seedling stem height and circumference. The composite interval mapping was used to detect the number of quantitative trait loci and their position on the genetic linkage maps. Three QTLs (one on the male map and two on the female map) were found explaining 13.4%, 17.5% and 18.8% of the trait variation, respectively.


2018 ◽  
Author(s):  
Pier Francesco Palamara ◽  
Jonathan Terhorst ◽  
Yun S. Song ◽  
Alkes L. Price

AbstractInterest in reconstructing demographic histories has motivated the development of methods to estimate locus-specific pairwise coalescence times from whole-genome sequence data. We developed a new method, ASMC, that can estimate coalescence times using only SNP array data, and is 2-4 orders of magnitude faster than previous methods when sequencing data are available. We were thus able to apply ASMC to 113,851 phased British samples from the UK Biobank, aiming to detect recent positive selection by identifying loci with unusually high density of very recent coalescence times. We detected 12 genome-wide significant signals, including 6 loci with previous evidence of positive selection and 6 novel loci, consistent with coalescent simulations showing that our approach is well-powered to detect recent positive selection. We also applied ASMC to sequencing data from 498 Dutch individuals (Genome of the Netherlands data set) to detect background selection at deeper time scales. We observed highly significant correlations between average coalescence time inferred by ASMC and other measures of background selection. We investigated whether this signal translated into an enrichment in disease and complex trait heritability by analyzing summary association statistics from 20 independent diseases and complex traits (average N=86k) using stratified LD score regression. Our background selection annotation based on average coalescence time was strongly enriched for heritability (p = 7×10−153) in a joint analysis conditioned on a broad set of functional annotations (including other background selection annotations), meta-analyzed across traits; SNPs in the top 20% of our annotation were 3.8x enriched for heritability compared to the bottom 20%. These results underscore the widespread effects of background selection on disease and complex trait heritability.


2017 ◽  
Author(s):  
Zilu Zhou ◽  
Weixin Wang ◽  
Li-San Wang ◽  
Nancy Ruonan Zhang

AbstractMotivationCopy number variations (CNVs) are gains and losses of DNA segments and have been associated with disease. Many large-scale genetic association studies are performing CNV analysis using whole exome sequencing (WES) and whole genome sequencing (WGS). In many of these studies, previous SNP-array data are available. An integrated cross-platform analysis is expected to improve resolution and accuracy, yet there is no tool for effectively combining data from sequencing and array platforms. The detection of CNVs using sequencing data alone can also be further improved by the utilization of allele-specific reads.ResultsWe propose a statistical framework, integrated Copy Number Variation detection algorithm (iCNV), which can be applied to multiple study designs: WES only, WGS only, SNP array only, or any combination of SNP and sequencing data. iCNV applies platform specific normalization, utilizes allele specific reads from sequencing and integrates matched NGS and SNP-array data by a Hidden Markov Model (HMM). We compare integrated two-platform CNV detection using iCNV to naive intersection or union of platforms and show that iCNV increases sensitivity and robustness. We also assess the accuracy of iCNV on WGS data only, and show that the utilization of allele-specific reads improve CNV detection accuracy compared to existing methods.Availabilityhttps://github.com/zhouzilu/[email protected], [email protected] informationSupplementary data are available at Bioinformatics online.


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