SNP Identification Research Articles

SNP and InDel Identification and Annotation from RNA-Sequencing Data

SNP and InDel Identification and Annotation from RNA-Sequencing Data

Twelve newly assembled jasmine chloroplast genomes: unveiling genomic diversity, phylogenetic relationships and evolutionary patterns among Oleaceae and Jasminum species

BackgroundJasmine (Jasminum), renowned for its ornamental value and captivating fragrance, has given rise to numerous species and accessions. However, limited knowledge exists regarding the evolutionary relationships among various Jasminum species.ResultsIn the present study, we sequenced seven distinct Jasminum species, resulting in the assembly of twelve high-quality complete chloroplast (cp) genomes. Our findings revealed that the size of the 12 cp genomes ranged from 159 to 165 kb and encoded 134–135 genes, including 86–88 protein-coding genes, 38–40 tRNA genes, and 8 rRNA genes. J. nudiflorum exhibited a larger genome size compared to other species, mainly attributed to the elevated number of forward repeats (FRs). Despite the typically conservative nature of chloroplasts, variations in the presence or absence of accD have been observed within J. sambac. The calculation of nucleotide diversity (Pi) values for 19 cp genomes indicated that potential mutation hotspots were more likely to be located in LSC regions than in other regions, particularly in genes ycf2, rbcL, atpE, ndhK, and ndhC (Pi > 0.2). Ka/Ks values revealed strong selection pressure on the genes rps2, atpA, rpoA, rpoC1, and rpl33 when comparing J. sambac with the three most closely related species (J. auriculatum, J. multiflorum, and J. dichotomum). Additionally, SNP identification, along with the results of Structure, PCA, and phylogenetic tree analyses, divided the Jasminum cp genomes into six groups. Notably, J. polyanthum showed gene flow signals from both the G5 group (J. nudiflorum) and the G3 group (J. tortuosum and J. fluminense). Phylogenetic tree analysis reflected that most species from the same genus clustered together with robust support in Oleaceae, strongly supporting the monophyletic nature of cp genomes within the genus Jasminum.ConclusionOverall, this study provides comprehensive insights into the genomic composition, variation, and phylogenetic relationships among various Jasminum species. These findings enhance our understanding of the genetic diversity and evolutionary history of Jasminum.

DNA Barcoding of Pomegranate (Punica granatum L.) Cultivars in Duhok Province- Kurdistan Region/ Iraq Using 18S–28S rRNA and ITS Region

Pomegranate is a tree species with a significant plant diversity, therefore molecular methods are necessary to define and verify approaches to recognize rapidly and correctly. This research looks at a genetic strategy for identifying pomegranate varieties in Duhok KRG. The approach is based on application of ITS region, PCR-RFLP, sequencing and SNP identification. For this study, 14 pomegranate accessions were taken from various regions, namely the Center of Duhok, Amedi, Akre, Zaxo, the South of Duhok, and Sulav. The PCR product of the 18S–28S rDNA intergenic spacer was 854bp, and the sequence analysis revealed a 99.94 percent similarity with other accession numbers in NCBI, demonstrating the use of the 18S–28S rDNA intergenic spacer for identifying and barcoding pomegranate cultivars. The PCR product of the ITS region was 700bp. This result was then employed for PCR-RFLP using two restriction enzymes namely RsaI GT/AC and HaeIII GG/CC which helped grouping as well as genetic similarities. This study Further involved sequencing examined genes were compared using the NCBI BLASTn tool and clustalo (Version 1.2.4) to determine gene location and SNP. According to this study, the result of PCR-RFLP revealed poor association between pomegranate physical morphology and genetic features, while SNP identification was identified between studied cultivars. Moreover, this result showed possible DNA barcoding of pomegranate cultivars under the study.

Genome-wide association studies: an intuitive solution for SNP identification and gene mapping in trees.

Analysis of natural diversity in wild/cultivated plants can be used to understand the genetic basis for plant breeding programs. Recent advancements in DNA sequencing have expanded the possibilities for genetically altering essential features. There have been several recently disclosed statistical genetic methods for discovering the genes impacting target qualities. One of these useful methods is the genome-wide association study (GWAS), which effectively identifies candidate genes for a variety of plant properties by examining the relationship between a molecular marker (such as SNP) and a target trait. Conventional QTL mapping with highly structured populations has major limitations. The limited number of recombination events results in poor resolution for quantitative traits. Only two alleles at any given locus can be studied simultaneously. Conventional mapping approach fails to work in perennial plants and vegetatively propagated crops. These limitations are sidestepped by association mapping or GWAS. The flexibility of GWAS comes from the fact that the individuals being examined need not be linked to one another, allowing for the use of all meiotic and recombination events to increase resolution. Phenotyping, genotyping, population structure analysis, kinship analysis, and marker-trait association analysis are the fundamental phases of GWAS. With the rapid development of sequencing technologies and computational methods, GWAS is becoming a potent tool for identifying the natural variations that underlie complex characteristics in crops. The use of high-throughput sequencing technologies along with genotyping approaches like genotyping-by-sequencing (GBS) and restriction site associated DNA (RAD) sequencing may be highly useful in fast-forward mapping approach like GWAS. Breeders may use GWAS to quickly unravel the genomes through QTL and association mapping by taking advantage of natural variances. The drawbacks of conventional linkage mapping can be successfully overcome with the use of high-resolution mapping and the inclusion of multiple alleles in GWAS.

Construction of the first high-density SNP genetic map and identification of QTLs for the natural rubber content in Taraxacum kok-saghyz Rodin

BackgroundTaraxacum kok-saghyz Rodin (TKS) is a promising commercial alternative natural rubber (NR) yielding plant. Cultivating TKS with a high NR content is an important breeding target, and developing molecular markers related to NR content can effectively accelerate the breeding process of TKS.ResultsTo construct a high-density SNP genetic map and uncover genomic regions related to the NR content in TKS, an F1 mapping population of TKS was constructed by crossing two parents (l66 and X51) with significant differences in NR contents. The NR content of the F1 plants ranged from 0.30 to 15.14% and was distributed normally with a coefficient of variation of 47.61%, indicating quantitative trait inheritance. Then, employing whole-genome resequencing (WGR), a TKS genetic linkage map of 12,680 bin markers comprising 322,439 SNPs was generated. Based on the genetic map and NR content of the F1 population, six quantitative trait loci (QTLs) for NR content with LOD > 4.0 were identified on LG01/Chr01 and LG06/Chr06. Of them, the 2.17 Mb genomic region between qHRC-C6-1 and qHRC-C6-2 on ChrA06, with 65.62% PVE in total, was the major QTL region. In addition, the six QTLs have significant additive genetic effects on NR content and could be used to develop markers for marker-assisted selection (MAS) in TKS with a high NR content.ConclusionThis work constructed the first high-density TKS genetic map and identified the QTLs and genomic regions controlling the NR content, which provides useful information for fine mapping, map-based cloning, and MAS in TKS.

Genetics of keratoconus; how realistic is gene therapy?

AbstractKeratoconus (KC) is a complex, non‐inflammatory eye condition that impairs the focusing ability of the eye by progressively thinning and distorting the cornea. Its causes remain elusive, as it is a genetically heterogeneous, multifactorial degenerative disorder. KC follows an autosomal (either recessive or dominant) pattern of inheritance and is associated with genes which interact with environmental, genetic and/or other factors.At present, the only fairly reliable treatment that slows down the progression of KC is cornea collagen cross‐linking. In extreme cases a corneal transplant may be required. This fact alone makes gene therapy for KC, a promising therapeutic approach. Such hopes are bolstered by the biophysical properties of the corneal tissues which include the corneal immune privilege, the transparency of the corneal tissue together with its and ex vivo stability, and the uncomplicated operative approach to the eye anterior chamber. In addition, recent advances in vectors, along with the ability to modulate the corneal milieu in order to ensure a relatively long survival of the target gene and allow its successful translation, further bolster the hopes for successfully treating KC via gene therapy.Over the last two decades, however, genome‐wide association studies and studies on SNP and genetic loci identification have identified more than 50 genomic loci that are implicated in both the dysregulation of the corneal collagen matrix formation and maintenance or the cell differentiation pathways that sustain corneal integrity. Among the most prominent genes involved in KC are the VSX1 gene, which is involved, among others, in posterior polymorphous corneal dystrophy; the SOD1 gene which determines the effects of reactive oxygen species; the ZNF469 gene which is also involved in the Brittle Cornea Syndrome; the TGF8 pathway which is involved in the regulation of the extracellular matrix composition; the TGFI gene which plays a role in cell‐collagen interactions. The roles of the MicroRNAs (especially that of the miRNA 184) and of mitochondrial DNA must, also, be stressed. Recently, we bibliographically identified and documented 18 different KC symptoms and clinical signs and cross referenced them to 24 different genes/genetic loci. It turns out that each of these symptoms is associated with from between 3 and 14 identified KC genes. We similarly identified 49 diseases and/or syndromes that involve at least some of the KC‐implicated genes and cross‐referenced them to these 24 genes. Again, it turns out that each one of the 49 diseases/syndromes is associated with from between 1 and 23 KC‐implicated genes.The complex interrelations among the different biophysical and biochemical processes involved in KC, the multitude of related genomic loci, and the large number of comorbidities, collectively, they cast gene therapy in an unfavourable light as a realistic treatment option for KC., On the other hand, the possible identification of a pivotal role for only a handful of genes, may open the path for gene therapy in KC.

Extent to which array genotyping and imputation with large reference panels approximate deep whole-genome sequencing

Understanding the genetic basis of human diseases and traits is dependent on the identification and accurate genotyping of genetic variants. Deep whole-genome sequencing (WGS), the gold standard technology for SNP and indel identification and genotyping, remains very expensive for most large studies. Here, we quantify the extent to which array genotyping followed by genotype imputation can approximate WGS in studies of individuals of African, Hispanic/Latino, and European ancestry in the US and of Finnish ancestry in Finland (a population isolate). For each study, we performed genotype imputation by using the genetic variants present on the Illumina Core, OmniExpress, MEGA, and Omni 2.5M arrays with the 1000G, HRC, and TOPMed imputation reference panels. Using the Omni 2.5M array and the TOPMed panel, ≥90% of bi-allelic single-nucleotide variants (SNVs) are well imputed (r2>0.8) down to minor-allele frequencies (MAFs) of 0.14% in African, 0.11% in Hispanic/Latino, 0.35% in European, and 0.85% in Finnish ancestries. There was little difference in TOPMed-based imputation quality among the arrays with >700k variants. Individual-level imputation quality varied widely between and within the three US studies. Imputation quality also varied across genomic regions, producing regions where even common (MAF>5%) variants were consistently not well imputed across ancestries. The extent to which array genotyping and imputation can approximate WGS therefore depends on reference panel, genotype array, sample ancestry, and genomic location. Imputation quality by variant or genomic region can be queried with our new tool, RsqBrowser, now deployed on the Michigan Imputation Server.

Isolation and sequencing of a single copy of an introgressed chromosome from a complex genome for gene and SNP identification.

This manuscript describes the identification, isolation and sequencing of a single chromosome containing high value resistance genes from a complex polyploid where sequencing the whole genome is too costly. The large complex genomes of many crops constrain the use of new technologies for genome-assisted selection and genetic improvement. One method to simplify a genome is to break it into individual chromosomes by flow cytometry; however, in many crop species most chromosomes cannot be isolated individually. Flow sorting of a single copy of a chromosome has been developed in wheat, and here we demonstrate its use to identify markers of interest in an Erianthus/Sacchurum hybrid. Erianthus/Saccharum hybrids are of interest because Erianthus is known to be highly resistant to soil borne diseases which cause extensive sugarcane yield losses in Australia. Sugarcane (Saccharum) cultivars are autopolyploids with a highly complex genome and over 100 chromosomes. Flow cytometry for sugarcane, as in most crops, does not resolve individual chromosomes to a karyotype peak for sorting. To isolate a single chromosome, we used genomic in situ hybridization (GISH) to identify the flow karyotype region containing the Erianthus chromosomes, flow sorted single chromosomes from this region, PCR screened for the Erianthus chromosomes and sequenced them. One Erianthus chromosome amplified and sequenced well, and from this data we could identify 57 resistant type genes and SNPs in nearly half of these genes. We developed KASP SNP assays and demonstrated that the identified SNP markers segregated as expected in a small introgression population. The pipeline we developed here to flow sort and sequence single chromosomes could be used in any crop with a large complex genome to rapidly discover and develop markers to important loci.

Improvement of millets in the post-genomic era.

Millets are food and nutrient security crops in the semi-arid tropics of developing countries. Crop improvement using modern tools is one of the priority areas of research in millets. The whole-genome sequence (WGS) of millets provides new insight into understanding and studying the genes, genome organization and genomic-assisted improvement of millets. The WGS of millets helps to carry out genome-wide comparison and co-linearity studies among millets and other cereal crops. This approach might lead to the identification of genes underlying biotic and abiotic stress tolerance in millets. The available genome sequence of millets can be used for SNP identification, allele discovery, association and linkage mapping, identification of valuable candidate genes, and marker-assisted breeding (MAB) programs. Next generation sequencing (NGS) technology provides opportunities for genome-assisted breeding (GAB) through genomic selection (GS) and genome-wide association studies (GAWS) for crop improvement. Clustered, regularly interspaced, short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) genome editing (GE) system provides new opportunities for millet improvement. In this review, we discuss the details on the WGS available for millets and highlight the importance of utilizing such resources in the post-genomic era for millet improvement. We also draw inroads on the utilization of various approaches such as GS, GWAS, functional genomics, gene validation and GE for millet improvement. This review might be helpful for understanding the developments in the post-genomic era of millet improvement.

Development and validation of a 1\u2009K sika deer (Cervus nippon) SNP Chip

BackgroundChina is the birthplace of the deer family and the country with the most abundant deer resources. However, at present, China’s deer industry faces the problem that pure sika deer and hybrid deer cannot be easily distinguished. Therefore, the development of a SNP identification chip is urgently required.ResultsIn this study, 250 sika deer, 206 red deer, 23 first-generation hybrid deer (F1), 20 s-generation hybrid deer (F2), and 20 third-generation hybrid deer (F3) were resequenced. Using the chromosome-level sika deer genome as the reference sequence, mutation detection was performed on all individuals, and a total of 130,306,923 SNP loci were generated. After quality control filtering was performed, the remaining 31,140,900 loci were confirmed. From molecular-level and morphological analyses, the sika deer reference population and the red deer reference population were established. The Fst values of all SNPs in the two reference populations were calculated. According to customized algorithms and strict screening principles, 1000 red deer-specific SNP sites were finally selected for chip design, and 63 hybrid individuals were determined to contain red deer-specific SNP loci. The results showed that the gene content of red deer gradually decreased in subsequent hybrid generations, and this decrease roughly conformed to the law of statistical genetics. Reaction probes were designed according to the screening sites. All candidate sites met the requirements of the Illumina chip scoring system. The average score was 0.99, and the MAF was in the range of 0.3277 to 0.3621. Furthermore, 266 deer (125 sika deer, 39 red deer, 56 F1, 29 F2,17 F3) were randomly selected for 1 K SNP chip verification. The results showed that among the 1000 SNP sites, 995 probes were synthesized, 4 of which could not be typed, while 973 loci were polymorphic. PCA, random forest and ADMIXTURE results showed that the 1 K sika deer SNP chip was able to clearly distinguish sika deer, red deer, and hybrid deer and that this 1 K SNP chip technology may provide technical support for the protection and utilization of pure sika deer species resources.ConclusionWe successfully developed a low-density identification chip that can quickly and accurately distinguish sika deer from their hybrid offspring, thereby providing technical support for the protection and utilization of pure sika deer germplasm resources.

SNP Identification in Sperm Associated Antigen 11B Gene and Its Association with Sperm Quality Traits in Murrah Bulls

Background: The beta-defensin family antigens present on sperm surface suggestively play pivotal role in sperm fertility by aiding in various steps of sperm maturation, motility, capacitation, immune recognition and sperm-oocyte interaction in female tract. It is imperative to explore genetic polymorphisms to build a better understanding of individual variation in male fertility. The experiment was designed to identify DNA polymorphism in Sperm Associated Antigen 11B (SPAG11B) gene and to analyze association between genetic variants with sperm quality traits in buffalo bulls (Murrah) in ICAR-National Dairy Research Institute, Karnal. Methods: Genomic DNA was extracted from hundred and thirty Murrah bulls. A 395 base pair region covering partial Intron 2, Exon 3 and Partial Intron 3 of bovine SPAG11 gene was amplified and genotyped using PCR-RFLP method. The PCR amplified product was purified, sequenced and further ClustalW analysis was done to align edited sequence with reported Bos taurus sequence (AC_000158.1). Gene and genotype frequencies, effective number of alleles, level of heterozygosity and polymorphic information content of various genotypes were estimated by standard procedure. Seminal parameters (Post thaw sperm motility, sperm viability, acrosomal integrity, HOST and abnormality) were estimated and statistical analysis was carried out. Result: A novel SNP (G greater than A substitution) at 2266 base of the SPAG11B gene was identified by sequencing. The fragment of SPAG11 gene containing 395 base pairs was amplified using PCR and digested with restriction enzyme i.e. MunI which showed three distinct genotypes viz., AA (266 bp and 107 bp fragment), AG (307 bp, 266 bp and 107 bp) and GG (373 bp fragment). Least squares means of seminal parameters for the SNP was estimated and compared after correction for non-genetic factors. Between genotypes, significant differences were found only for acrosomal integrity and was highest in AG (74.22±0.72) followed by AA (72.6±0.89) and GG (71.12±0.97), respectively. The identified novel SNP of SPAG11 gene showed significant association with acrosome integrity with genotype AG being superior to other genotypes. However, an association cannot be established with other seminal parameters with this SNP, further studies are required in order to validate the impact of g.2266G greater than A on sperm quality traits in a large population.

Transcriptome analysis reveals genes potentially related to high fiber strength in a Gossypium hirsutum line IL9 with Gossypium mustelinum introgression.

Cotton (Gossypium L.) is the most important fiber crop worldwide. Here, transcriptome analysis was conducted on developing fibers of a G.mustelinum introgression line, IL9, and its recurrent parent, PD94042, at 17 and 21 days post-anthesis (dpa). Differentially expressed genes (DEGs) of PD94042 and IL9 were identified. Gene Ontology (GO) enrichment analysis showed that the annotated DEGs were rich in two main biological processes and two main molecular functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis likewise showed that the annotated DEGs were mainly enriched in metabolic pathways and biosynthesis of secondary metabolites. In total, 52 DEGs were selected as candidate genes based on comparison of the DEGs and GO function annotation information. Quantitative real-time PCR (RT-qPCR) analysis results for 12 randomly selected DEGs were consistent with transcriptome analysis. SNP identification based on G.mustelinum chromatin segment introgression showed that 394 SNPs were identified in 268 DEGs, and two genes with known functions were identified within fiber strength quantitative trait loci (QTL) regions or near the confidence intervals. We identified 52 key genes potentially related to high fiber strength in a G.mustelinum introgression line and provided significant insights into the study of cotton fiber quality improvement.

Influence of Genotype on High Glucosinolate Synthesis Lines of Brassica rapa.

This study was conducted to investigate doubled haploid (DH) lines produced between high GSL (HGSL) Brassica rapa ssp. trilocularis (yellow sarson) and low GSL (LGSL) B. rapa ssp. chinensis (pak choi) parents. In total, 161 DH lines were generated. GSL content of HGSL DH lines ranged from 44.12 to 57.04 μmol·g−1·dry weight (dw), which is within the level of high GSL B. rapa ssp. trilocularis (47.46 to 59.56 μmol g−1 dw). We resequenced five of the HGSL DH lines and three of the LGSL DH lines. Recombination blocks were formed between the parental and DH lines with 108,328 single-nucleotide polymorphisms in all chromosomes. In the measured GSL, gluconapin occurred as the major substrate in HGSL DH lines. Among the HGSL DH lines, BrYSP_DH005 had glucoraphanin levels approximately 12-fold higher than those of the HGSL mother plant. The hydrolysis capacity of GSL was analyzed in HGSL DH lines with a Korean pak choi cultivar as a control. Bioactive compounds, such as 3-butenyl isothiocyanate, 4-pentenyl isothiocyanate, 2-phenethyl isothiocyanate, and sulforaphane, were present in the HGSL DH lines at 3-fold to 6.3-fold higher levels compared to the commercial cultivar. The selected HGSL DH lines, resequencing data, and SNP identification were utilized for genome-assisted selection to develop elite GSL-enriched cultivars and the industrial production of potential anti-cancerous metabolites such as gluconapin and glucoraphanin.

Polymorphism of DMA (DM a Chain) gene in IPB-D2 chicken

The DM gene group is a non-classical MHC Class II gene group that plays a role in the process of presenting antigens by producing DM protein. The DMA gene, which is a group of DM genes, has an a chain that helps present exogenous antigens to CD4 + via MHC class II molecules. IPB-D2 chickens are the result of selection from IPB-D1 chickens which have disease-resistant trait. The aim of this study was to determine genetic polymorphism of DMA genes in IPB-D2 chickens. In this study, blood samples were collected from 21 weeks old chickens that are raised in the field laboratory of the Faculty of Animal Science IPB University. The PCR was used to amplify 601 bp fragments for DMA gen locus. SNP identification used direct sequencing method and analyzed using MegaX and Bioedit. The results found 4 SNPs, namely base position c.2328 G>A on exon 3, c.2c612 G>A, c.2686 G>A, and c.2710 G>A on exon 4. All SNPs are polymorphic and in Hardy-Weinberg equilibrium. The highest allele frequency for each SNP is allele A (0.5745; 0.5851; 0.9362), except at SNP c.2612 G>A (0.4575).

Correction of database SNP accession numbers misassigned to SNPs of the 8K IRSC apple SNP array

Accurate SNP locus identifiers are essential for the correct matching and aggregation of multiple historical datasets. The National Center for Biotechnology Information (NCBI) issued unique “submitted SNP identification” numbers (ssIDs) for every published SNP submitted to its database. Discrepant ssID information was discovered for 78 SNPs for the 8K IRSC apple SNP array while attempting to collate multiple historical datasets, and a review of the archived SNP database from the NCBI led to their correction and a collation of SNP markers with no duplicate ssIDs. As the incorrect ssIDs were subsequently republished and uploaded to the Genome Database for Rosaceae, the aim of this short communication is to report the correct NCBI ssIDs for these 78 SNPs to correctly aggregate historical SNP data, prevent perpetuation of the misassigned ssIDs in further publications, and provide a citation for correcting the misassigned ssIDs in the Genome Database for Rosaceae (because the NCBI no longer supports storage of non-human SNP data).

Detecting SARS-CoV-2 variants with SNP genotyping.

Tracking genetic variations from positive SARS-CoV-2 samples yields crucial information about the number of variants circulating in an outbreak and the possible lines of transmission but sequencing every positive SARS-CoV-2 sample would be prohibitively costly for population-scale test and trace operations. Genotyping is a rapid, high-throughput and low-cost alternative for screening positive SARS-CoV-2 samples in many settings. We have designed a SNP identification pipeline to identify genetic variation using sequenced SARS-CoV-2 samples. Our pipeline identifies a minimal marker panel that can define distinct genotypes. To evaluate the system, we developed a genotyping panel to detect variants-identified from SARS-CoV-2 sequences surveyed between March and May 2020 and tested this on 50 stored qRT-PCR positive SARS-CoV-2 clinical samples that had been collected across the South West of the UK in April 2020. The 50 samples split into 15 distinct genotypes and there was a 61.9% probability that any two randomly chosen samples from our set of 50 would have a distinct genotype. In a high throughput laboratory, qRT-PCR positive samples pooled into 384-well plates could be screened with a marker panel at a cost of < £1.50 per sample. Our results demonstrate the usefulness of a SNP genotyping panel to provide a rapid, cost-effective, and reliable way to monitor SARS-CoV-2 variants circulating in an outbreak. Our analysis pipeline is publicly available and will allow for marker panels to be updated periodically as viral genotypes arise or disappear from circulation.

Comparative Analysis of SNP Discovery and Genotyping in Fagus sylvatica L. and Quercus robur L. Using RADseq, GBS, and ddRAD Methods

Next-generation sequencing of reduced representation genomic libraries (RRL) is capable of providing large numbers of genetic markers for population genetic studies at relatively low costs. However, one major concern of these types of markers is the precision of genotyping, which is related to the common problem of missing data, which appears to be particularly important in association and genomic selection studies. We evaluated three RRL approaches (GBS, RADseq, ddRAD) and different SNP identification methods (de novo or based on a reference genome) to find the best solutions for future population genomics studies in two economically and ecologically important broadleaved tree species, namely F. sylvatica and Q. robur. We found that the use of ddRAD method coupled with SNP calling based on reference genomes provided the largest numbers of markers (28 k and 36 k for beech and oak, respectively), given standard filtering criteria. Using technical replicates of samples, we demonstrated that more than 80% of SNP loci should be considered as reliable markers in GBS and ddRAD, but not in RADseq data. According to the reference genomes’ annotations, more than 30% of the identified ddRAD loci appeared to be related to genes. Our findings provide a solid support for using ddRAD-based SNPs for future population genomics studies in beech and oak.

Молекулярно-генетическая идентификация популяций Pinus sylvestris L. и Larix sibirica Ledeb. в Пермском крае с использованием SNP-маркеров

For the selection of identification SNP markers and identification at the population level, 5 populations of Scots pine (Pinus sylvestris L., Pinaceae) and 5 populations of the western race of Siberian larch (Larix sibirica Ledeb., Pinaceae) in the Perm Krai were studied. To determine nucleotide sequences and select identification SNP markers in 10 populations of two woody plant species of the Perm Krai, 14 pairs of nuclear and 3 pairs of chloroplast loci of P. sylvestris, as well as ten pairs of primers to 10 loci of potentially adaptively significant genes of L. sibirica were tested. Sequencing of 3 nuclear loci and 3 loci of chloroplast DNA of P. sylvestris, as well as 6 loci of nuclear adaptively significant genes of L. sibirica were sequenced. In the sequenced sequences of two plant species, 59 SNP markers were detected. Of these, 11 identification SNP markers were established, with a sufficiently high frequency of occurrence (≥0.5), suitable for identifying populations of two coniferous plant species.

Genetic mapping of male sterility and pollen fertility QTLs in triticale with sterilizing Triticum timopheevii cytoplasm

Cytoplasmic male sterility (CMS) phenomenon is widely exploited in commercial hybrid seed production in economically important crop species, including rye, wheat, maize, rice, sorghum, cotton, sugar beets, and many vegetables. Although some commercial successes, little is known about QTLs responsible for the trait in case of triticale with sterilizing Triticum timopheevii (Tt) cytoplasm. Recombinant inbred line (RIL) F6 mapping population encompassing 182 individuals derived from the cross of individual plants representing the HT352 line and cv Borwo was employed for genetic map construction using SNP markers and identification of QTLs conferring pollen sterility in triticale with CMS Tt. The phenotypes of the F1 lines resulting from crossing of the HT352 (Tt) with HT352 (maintainer) × Borwo were determined by assessing the number of the F2 seeds per spike. A genetic map with 21 linkage groups encompasses 29,737 markers and spanned over the distance of 2549 cM. Composite (CIM) and multiple (MIM) interval mappings delivered comparable results. Single QTLs mapped to the 1A, 1B, 2A, 2R, 3B, 3R, 4B, and 5B chromosomes, whereas the 5R and 6B chromosomes shared 3 and 2 QTLs, respectively. The QTLs with the highest LOD score mapped to the 5R, 3R, 1B, and 4B chromosomes; however, the QRft-5R.3 has the highest explained variance of the trait.

GCViT: a method for interactive, genome-wide visualization of resequencing and SNP array data

BackgroundLarge genotyping datasets have become commonplace due to efficient, cheap methods for SNP identification. Typical genotyping datasets may have thousands to millions of data points per accession, across tens to thousands of accessions. There is a need for tools to help rapidly explore such datasets, to assess characteristics such as overall differences between accessions and regional anomalies across the genome.ResultsWe present GCViT (Genotype Comparison Visualization Tool), for visualizing and exploring large genotyping datasets. GCViT can be used to identify introgressions, conserved or divergent genomic regions, pedigrees, and other features for more detailed exploration. The program can be used online or as a local instance for whole genome visualization of resequencing or SNP array data. The program performs comparisons of variants among user-selected accessions to identify allele differences and similarities between accessions and a user-selected reference, providing visualizations through histogram, heatmap, or haplotype views. The resulting analyses and images can be exported in various formats.ConclusionsGCViT provides methods for interactively visualizing SNP data on a whole genome scale, and can produce publication-ready figures. It can be used in online or local installations. GCViT enables users to confirm or identify genomics regions of interest associated with particular traits.GCViT is freely available at https://github.com/LegumeFederation/gcvit. The 1.0 version described here is available at https://doi.org/10.5281/zenodo.4008713.