Transfer of the Dominant Virus Resistance Gene AV-1 pro From Asparagus prostratus to Chromosome 2 of Garden Asparagus A. officinalis L

An introgression breeding programme was carried out to transfer the virus resistance gene AV-1 ^pro from the wild species Asparagus prostratus to the garden asparagus Asparagus officinalis. Serious crossing barriers caused by genetic distance and different ploidy levels of the crossing parents have been overcome using embryo rescue for the F₁, BC₁, and BC₂ generations. The male and female fertility was widely restored in BC₂ and was shown to be comparable to the cultivated asparagus. Five AV-1 resistant diploid (2n = 2x = 20) BC₂ plants were selected and reciprocally backcrossed with asparagus cultivars. Segregation analyses of fourteen seedborne BC₃ progenies suggested a monogenic dominant inheritance of the AV-1 resistance. Genotyping by sequencing analysis gave a strong hint for location of the resistance gene on asparagus Chromosome 2. Using an Axiom single nucleotide polymorphism (SNP) genotyping array for the analysis of three BC₃ families with 10 AV-1 resistant and 10 AV-1 susceptible plants each, as well as 25 asparagus cultivars, the AV-1 ^pro locus on Chromosome 2 was further narrowed down. The SNP with the highest LOD score was converted to a kompetitive allele specific PCR (KASP) marker, shown to be useful for the further backcross programme and serving as the starting point for the development of a diagnostic marker.

Candidate Genes for the High-Altitude Adaptations of Two Mountain Pine Taxa

Mountain plants, challenged by vegetation time contractions and dynamic changes in environmental conditions, developed adaptations that help them to balance their growth, reproduction, survival, and regeneration. However, knowledge regarding the genetic basis of species adaptation to higher altitudes remain scarce for most plant species. Here, we attempted to identify such corresponding genomic regions of high evolutionary importance in two closely related European pines, Pinus mugo and P. uncinata, contrasting them with a reference lowland relative—P. sylvestris. We genotyped 438 samples at thousands of single nucleotide polymorphism (SNP) markers, tested their genetic differentiation and population structure followed by outlier detection and gene ontology annotations. Markers clearly differentiated the species and uncovered patterns of population structure in two of them. In P. uncinata three Pyrenean sites were grouped together, while two outlying populations constituted a separate cluster. In P. sylvestris, Spanish population appeared distinct from the remaining four European sites. Between mountain pines and the reference species, 35 candidate genes for altitude-dependent selection were identified, including such encoding proteins responsible for photosynthesis, photorespiration and cell redox homeostasis, regulation of transcription, and mRNA processing. In comparison between two mountain pines, 75 outlier SNPs were found in proteins involved mainly in the gene expression and metabolism.

Genetic Analysis Using a Multi-Parent Wheat Population Identifies Novel Sources of Septoria Tritici Blotch Resistance

Zymoseptoria tritici is the causative fungal pathogen of septoria tritici blotch (STB) disease of wheat (Triticum aestivum L.) that continuously threatens wheat crops in Ireland and throughout Europe. Under favorable conditions, STB can cause up to 50% yield losses if left untreated. STB is commonly controlled with fungicides; however, a combination of Z. tritici populations developing fungicide resistance and increased restrictions on fungicide use in the EU has led to farmers relying on fewer active substances. Consequently, this serves to drive the emergence of Z. tritici resistance against the remaining chemistries. In response, the use of resistant wheat varieties provides a more sustainable disease management strategy. However, the number of varieties offering an adequate level of resistance against STB is limited. Therefore, new sources of resistance or improved stacking of existing resistance loci are needed to develop varieties with superior agronomic performance. Here, we identified quantitative trait loci (QTL) for STB resistance in the eight-founder "NIAB Elite MAGIC" winter wheat population. The population was screened for STB response in the field under natural infection for three seasons from 2016 to 2018. Twenty-five QTL associated with STB resistance were identified in total. QTL either co-located with previously reported QTL or represent new loci underpinning STB resistance. The genomic regions identified and the linked genetic markers serve as useful resources for STB resistance breeding, supporting rapid selection of favorable alleles for the breeding of new wheat cultivars with improved STB resistance.

Inter- and intra-breed genome-wide copy number diversity in a large cohort of European equine breeds

BACKGROUND

Copy Number Variation (CNV) is a common form of genetic variation underlying animal evolution and phenotypic diversity across a wide range of species. In the mammalian genome, high frequency of CNV differentiation between breeds may be candidates for population-specific selection. However, CNV differentiation, selection and its population genetics have been poorly explored in horses.

RESULTS

We investigated the patterns, population variation and gene annotation of CNV using the Axiom® Equine Genotyping Array (670,796 SNPs) from a large cohort of individuals (N = 1755) belonging to eight European horse breeds, varying from draught horses to several warmblood populations. After quality control, 152,640 SNP CNVs (individual markers), 18,800 segment CNVs (consecutive SNP CNVs of same gain/loss state or both) and 939 CNV regions (CNVRs; overlapping segment CNVs by at least 1 bp) compared to the average signal of the reference (Belgian draught horse) were identified. Our analyses showed that Equus caballus chromosome 12 (ECA12) was the most enriched in segment CNV gains and losses (~ 3% average proportion of the genome covered), but the highest number of segment CNVs were detected on ECA1 and ECA20 (regardless of size). The Friesian horses showed private SNP CNV gains (> 20% of the samples) on ECA1 and Exmoor ponies displayed private SNP CNV losses on ECA25 (> 20% of the samples). The Warmblood cluster showed private SNP CNV gains located in ECA9 and Draught cluster showed private SNP CNV losses located in ECA7. The length of the CNVRs ranged from 1 kb to 21.3 Mb. A total of 10,612 genes were annotated within the CNVRs. The PANTHER annotation of these genes showed significantly under- and overrepresented gene ontology biological terms related to cellular processes and immunity (Bonferroni P-value < 0.05). We identified 80 CNVRs overlapping with known QTL for fertility, coat colour, conformation and temperament. We also report 67 novel CNVRs.

CONCLUSIONS

This work revealed that CNV patterns, in the genome of some European horse breeds, occurred in specific genomic regions. The results provide support to the hypothesis that high frequency private CNVs residing in genes may potentially be responsible for the diverse phenotypes seen between horse breeds.

Copy Number Variants and Exome Sequencing Analysis in Six Pairs of Chinese Monozygotic Twins Discordant for Congenital Heart Disease

Congenital heart disease (CHD) is one of the most common birth defects. More than 200 susceptibility loci have been identified for CHDs, yet a large part of the genetic risk factors remain unexplained. Monozygotic (MZ) twins are thought to be completely genetically identical; however, discordant phenotypes have been found in MZ twins. Recent studies have demonstrated genetic differences between MZ twins. We aimed to test whether copy number variants (CNVs) and/or genetic mutation differences play a role in the etiology of CHDs by using single nucleotide polymorphism (SNP) genotyping arrays and whole exome sequencing of twin pairs discordant for CHDs. Our goal was to identify mutations present only in the affected twins, which could identify novel candidates for CHD susceptibility loci. We present a comprehensive analysis for the CNVs and genetic mutation results of the selected individuals but detected no consistent differences within the twin pairs. Our study confirms that chromosomal structure or genetic mutation differences do not seem to play a role in the MZ twins discordant for CHD.

Identifying Functional Genes Influencing Gossypium hirsutum Fiber Quality

Fiber quality is an important economic index and a major breeding goal in cotton, but direct phenotypic selection is often hindered due to environmental influences and linkage with yield traits. A genome-wide association study (GWAS) is a powerful tool to identify genes associated with phenotypic traits. In this study, we identified fiber quality genes in upland cotton (Gossypium hirsutum L.) using GWAS based on a high-density CottonSNP80K array and multiple environment tests. A total of 30 and 23 significant single nucleotide polymorphisms (SNPs) associated with five fiber quality traits were identified across the 408 cotton accessions in six environments and the best linear unbiased predictions, respectively. Among these SNPs, seven loci were the same, and 128 candidate genes were predicted in a 1-Mb region (±500 kb of the peak SNP). Furthermore, two major genome regions (GR1 and GR2) associated with multiple fiber qualities in multiple environments on chromosomes A07 and A13 were identified, and within them, 22 candidate genes were annotated. Of these, 11 genes were expressed [log₂(1 + FPKM)>1] in the fiber development stages (5, 10, 20, and 25 dpa) using RNA-Seq. This study provides fundamental insight relevant to identification of genes associated with fiber quality and will accelerate future efforts toward improving fiber quality of upland cotton.

Analyzing copy number variation using SNP array data: protocols for calling CNV and association tests

High-density SNP genotyping technology provides a low-cost, effective tool for conducting Genome Wide Association (GWA) studies. The wide adoption of GWA studies has indeed led to discoveries of disease- or trait-associated SNPs, some of which were subsequently shown to be causal. However, the nearly universal shortcoming of many GWA studies--missing heritability--has prompted great interest in searching for other types of genetic variation, such as copy number variation (CNV). Certain CNVs have been reported to alter disease susceptibility. Algorithms and tools have been developed to identify CNVs using SNP array hybridization intensity data. Such an approach provides an additional source of data with almost no extra cost. In this unit, we demonstrate the steps for calling CNVs from Illumina SNP array data using PennCNV and performing association analysis using R and PLINK.