Single Nucleotide Polymorphisms Mining Research Articles

Identification of single nucleotide polymorphisms (SNPs) in selected rice phosphate transporter (OsPHT) genes

Phosphorus (P) is one of the fundamental elements for plant growth and development. Due to the scarcity of viable P in the soil for plants, P deficiency was often the culprit that restrained plant’s wellbeing. Plasma membrane phosphate transporters (PHT) are a group of proteins responsible for phosphate (Pi) uptake from soil and further allocation to plant organs and tissues. The PHT can be further categorized into constitutively expressed low-affinity Pi transporter or high-affinity Pi transporter that are induced upon Pi starvation. Significant variability in P use efficiency has been observed among different rice varieties. Genotypic differences such as single nucleotide polymorphisms (SNPs) could be responsible for the variation observed aside from the well-studied phenotypic responses. Nevertheless, the occurrence of the SNPs in OsPHT genes remain unexplored. Therefore, the objective of this study was to analyse and profile the SNPs in five selected high affinity OsPHT genes which are responsible for P uptake under P deficiency. The SNPs mining was conducted using Rice SNP-Seek Database against 3024 rice varieties with Oryza sativa japonica cultivar Nipponbare as the reference sequence. Results showed that a total of zero, seven, three, one and ten non-synonymous SNPs was identified in OsPHT1;2, OsPHT1;3, OsPHT1;6, OsPHT1;9 and OsPHT1;10, respectively. A base substitution of C to A at position 16028497 of chromosome 10 of OsPHT1;3 was found to change tyrosine to a stop codon. This could result in a truncated protein which has only 213 amino acids as compared 526 amino acids in the complete protein. The large number of non-synonymous SNPs in OsPHT1;10 could explain the redundant function of this gene in the translocation and uptake of P in rice. In short, the identified SNPs especially the non-synonymous SNPs could potentially disrupt the biosynthesis of phosphate in rice which requires further investigation.

Genetic diversity of selected Moringa oleifera lam. Provenances from the coastal region of Kenya

Moringa oleifera Lam (syn. M. Pterygosperma Gaertn) is one of the most economically important crops widely cultivated globally. Traditionally, it has been used as a remedy for conditions such as diabetes, inflammation, cancer, bacterial, viral, and fungal infections, joint pain and heart disease. Moringa oleifera has also been utilized for human consumption, as forage and for water purification. Considering it is a cross pollinated plant, M. oleifera has huge variability. Due to the fast-growing nature and adaptability to variable climatic conditions, M. oleifera has been popularly cultivated in Coastal and Eastern Kenya. Studying the genetic diversity of the drumstick tree is essential in selecting valuable genotypes and for improvement of its cultivars for improved breeding programs. The use of marker-assisted selection of cultivar for the desired traits will benefit faster breeding programs. Single nucleotide polymorphisms (SNPs), being the most recent molecular markers, were used in this study. Seventeen M. oleifera provenances from Coastal Kenya were analyzed by genotyping by sequencing (GBS). Briefly, M. oleifera leaves were homogenized, crushed and DNA extracted, genome complexity reduction and library preparation was carried out followed by barcoding, electrophoresis, pooling, preparation of sequencing libraries and sequencing. Next generation sequencing (NGS) technologies, Illumina Hiseq 2500, was used for sequencing and SNP mining. Binning was carried out to remove noise. In silico assembly of sequence contigs was undertaken. Data analysis was undertaken using DArT R and KDCompute Platforms. Genetic characterization was achieved by carrying out cluster analysis, principle coordinate analysis (PCoA), 3D plot and phylogenetic tree. One hundred and sixty four (164) genotypes were identified. It was evident from the analysis undertaken that the genotypes consistently clustered into four clades/groups. However, the clusters obtained by each analysis tool comprised different genotypes due to the assumptions employed by each tool. The similarity coefficient from Hierarchical clustering ranged from 63% to 100% indicating that the genotypes had low variability. An interactive and highly robust 3D plot was produced using DArT R (Adegenet package). Interestingly, Pwani University genotypes clustered separately. It is noteworthy that these genotypes consistently clustered uniquely and independently irrespective of the tool used. This is possibly due to the seeds being of unique origin. Nevertheless, the high similarity between the genotypes could be attributed to the M. oleifera plants in the various provenances having the same ancestry. Given the high frequency of SNPs and their involvement as a source of allele variations, this research could contribute to the discovery of associations between gene allelic forms and phenotypes, enabling the alleles to be linked to desirable traits (fast growth and high seed production).

MinSNPs: an R package for the derivation of resolution-optimised SNP sets from microbial genomic data.

Here, we present the R package, minSNPs. This is a re-development of a previously described Java application named Minimum SNPs. MinSNPs assembles resolution-optimised sets of single nucleotide polymorphisms (SNPs) from sequence alignments such as genome-wide orthologous SNP matrices. MinSNPs can derive sets of SNPs optimised for discriminating any user-defined combination of sequences from all others. Alternatively, SNP sets may be optimised to determine all sequences from all other sequences, i.e., to maximise diversity. MinSNPs encompasses functions that facilitate rapid and flexible SNP mining, and clear and comprehensive presentation of the results. The minSNPs' running time scales in a linear fashion with input data volume and the numbers of SNPs and SNPs sets specified in the output. MinSNPs was tested using a previously reported orthologous SNP matrix of Staphylococcus aureus and an orthologous SNP matrix of 3,279 genomes with 164,335 SNPs assembled from four S. aureus short read genomic data sets. MinSNPs was shown to be effective for deriving discriminatory SNP sets for potential surveillance targets and in identifying SNP sets optimised to discriminate isolates from different clonal complexes. MinSNPs was also tested with a large Plasmodium vivax orthologous SNP matrix. A set of five SNPs was derived that reliably indicated the country of origin within three south-east Asian countries. In summary, we report the capacity to assemble comprehensive SNP matrices that effectively capture microbial genomic diversity, and to rapidly and flexibly mine these entities for optimised marker sets.

Evaluation of Different SNP Analysis Software and Optimal Mining Process in Tree Species.

Single nucleotide polymorphism (SNP) is one of the most widely used molecular markers to help researchers understand the relationship between phenotypes and genotypes. SNP calling mainly consists of two steps, including read alignment and locus identification based on statistical models, and various software have been developed and applied in this issue. Meanwhile, in our study, very low agreement (<25%) was found among the prediction results generated by different software, which was much less consistent than expected. In order to obtain the optimal protocol of SNP mining in tree species, the algorithm principles of different alignment and SNP mining software were discussed in detail. And the prediction results were further validated based on in silico and experimental methods. In addition, hundreds of validated SNPs were provided along with some practical suggestions on program selection and accuracy improvement were provided, and we wish that these results could lay the foundation for the subsequent analysis of SNP mining.

Genome wide mining of SNPs and INDELs through ddRAD sequencing in Sahiwal cattle

The study was conducted in Sahiwal cattle for genome wide identification and annotation of single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs) in Sahiwal cattle. The double digest restriction-site associated DNA (ddRAD) sequencing, a reduced representation method was used for the identification of variants at nucleotide level. A total of 1,615,211 variants were identified at RD10 and Q30 consisting of 1,480,930 SNPs and 134,281 INDELs with respect to the Bos taurus reference genome. The SNPs were annotated for their location, impact and functional class. The SNPs identified in Sahiwal cattle were found to be associated with a total of 26,229 genes. A total of 1819 SNPs were annotated for 209 candidate genes associated with different production and reproduction traits. The variants identified in the present study may be useful to strengthen the existing bovine SNP chips for reducing the biasness over the taurine cattle breeds. The diversity analysis provides the insight of the genetic architecture of the Sahiwal population Studied. The large genetic variations identified at the nucleotide level provide ample scope for implementing an effective and efficient breed improvement programme for increasing the productivity of Sahiwal cattle.

Molecular sexual determinants in Pistacia genus by KASP assay.

Pistacia is a genus of dioecious plant species whose trees can take 4-5years to reach the economically valuable fruit-bearing stage. The fruits have great importance as raw material in the food, healthcare, and baking industries. For that reason, the identification of individual plants in the early juvenile period for the pollination and positioning of trees is crucial for growers. The objective of this study is to develop markers for each Pistacia species that can help in screening the sex of plant seedlings before they reach the reproductive stage, without waiting for morphological characteristics to appear. Within this context, by using the power of the kompetitive allele-specific PCR (KASP) assay technology as a marker screening system, we successfully discriminated seven out of eight Pistacia species: P. atlantica, P. integerrima, P. khinjuk, P. mutica, P. terebinthus, P. vera, and P. lentiscus. We used a high-throughput DNA sequence read archive (SRA) to assemble a reference genome that was employed in our studies as a de novo bioinformatics method. Four genomic regions from SRA and three single-nucleotide polymorphism (SNP) positions from Kafkas et al. BMC Genomics 16:98, 2015) were selected and sequenced with collected plant material from predominantly the Antepfıstıgı Research Institute Collection Garden, and eight species were aligned intraspecifically for SNP mining. In total, 12 SNP markers were converted to KASP markers, and 5 of them (SNP-PIS-133396, SNP-PIS-167992, P-ATL-91951-565, P-INT-91951-256, P-KHI-91951-115) showed clear allelic discrimination between male and female plants. SNP-PIS-167992 and P-ATL-91951-565 were identified as the best marker assays because they showed allelic frequency differences for all individuals and for both homozygous and heterozygous characters. These markers could be the most comprehensive ones for the whole genus because they showed discriminative power for several species. This study is the first one to use the KASP assay for sex discrimination in Pistacia species, and it can be regarded as a precursor study for sex discrimination by KASP for plants in general.

Insights Into the Genetic Diversity of Nordic Red Clover (Trifolium pratense) Revealed by SeqSNP-Based Genic Markers.

Red clover (Trifolium pratense) is one of the most important fodder crops worldwide. The knowledge of genetic diversity among red clover populations, however, is under development. This study provides insights into its genetic diversity, using single nucleotide polymorphism (SNP) markers to define population structure in wild and cultivated red clover. Twenty-nine accessions representing the genetic resources available at NordGen (the Nordic gene bank) and Lantmännen (a Swedish agricultural company with a red clover breeding program) were used for this study. Genotyping was performed via SeqSNP, a targeted genotype by sequencing method that offers the capability to target specific SNP loci and enables de novo discovery of new SNPs. The SNPs were identified through a SNP mining approach based on coding sequences of red clover genes known for their involvement in development and stress responses. After filtering the genotypic data using various criteria, 623 bi-allelic SNPs, including 327 originally targeted and 296 de novo discovered SNPs were used for population genetics analyses. Seventy-one of the SNP loci were under selection considering both Hardy-Weinberg equilibrium and pairwise FST distributions. The average observed heterozygosity (HO), within population diversity (HS) and overall diversity (HT) were 0.22, 0.21 and 0.22, respectively. The tetraploids had higher average HO (0.35) than diploids (0.21). The analysis of molecular variance (AMOVA) showed low but significant variation among accessions (5.4%; P < 0.001), and among diploids and tetraploids (1.08%; P = 0.02). This study revealed a low mean inbreeding coefficient (FIS = −0.04) exhibiting the strict outcrossing nature of red clover. As per cluster, principal coordinate and discriminant analyses, most wild populations were grouped together and were clearly differentiated from the cultivated types. The cultivated types of red clover had a similar level of genetic diversity, suggesting that modern red clover breeding programs did not negatively affect genetic diversity or population structure. Hence, the breeding material used by Lantmännen represents the major genetic resources in Scandinavia. This knowledge of how different types of red clover accessions relate to each other and the level of outcrossing and heterozygosity will be useful for future red clover breeding.

Involvement of purple acid phosphatase gene into nitrogen uptake of oil palm (Elaeis guineensis)

Abstract. Maryanto SD, Tanjung ZA, Roberdi, Sudania WM, Pujianto, Hairinsyah, Utomo C, Liwang T. 2021. Involvement of purple acid phosphatase gene into nitrogen uptake of oil palm (Elaeis guineensis). Biodiversitas 22: 1385-1390. Nitrogen is the most important nutrient element in terms of plant growth. Plant purple acid phosphatases (PAPs) are known to participate in the phosphate (Pi) acquisition and utilization. Moreover, PAP gene plays an important role in nitrogen fixation. A single nucleotide polymorphism (SNP) was previously detected in the exon 7 of EgPAP3, based on SNP mining analysis of oil palm (Elaeis guineensis Jacq.). genome database. This study was aimed to obtain a Cleaved Amplified Polymorphic Sequences (CAPS) marker based on SNP within EgPAP associated with efficient nitrogen uptake oil palm progenies. Primer pairs were designed and used for PCR amplification of 3 oil palm progenies that showed low N-content, 3 progenies with moderate N-content, and 3 progenies with high N-content. The amplicon was purified prior to single-pass DNA sequencing analysis. Based on Pearson’s chi-square and odds ratio statistical analysis, the SNP has strong positive correlation with the phenotype. The SNP is located at chromosome 13 with a distance of 17.7771 cM from start codon. The sequencing analysis revealed that three progenies with high N-content samples had GG allele motif, while moderate N-content progenies had GA allele and low N-content progenies had AA allele motifs respectively. In addition, a restriction site of NIaIV was found to be adjacent to the SNP location, thus the PCR products of all samples were digested with NIaIV restriction enzyme. NIaIV was able to distinguish between high, medium and low efficient DNA samples. Whole high N-content progenies with GG allele motifs were undigested indicating a single band size of 670 bp identical to the untreated PCR product (control). Moderate N-content progenies produced a 670 bp, 550 bp, and 120 bp bands because of digested by NIaIV. Low N-content progenies also resulted in double bands of 550 bp and 120 bp due to digested by NIaIV. Furthermore, NIaIV restriction enzyme was applied to digest other 54 oil palms DNA samples with unknown genotypes. Whole GG samples were consistently shown to have single band, GA and AA samples were also consistent in producing two bands with different lengths. Based on this result, CAPS marker based on SNP in EgPAP3 was successfully developed to screen between high and low efficient N-uptake of oil palm progenies.

Distribution of Indian population-specific transporter SNPs among Asians and their physiological consequences

Membrane transporters are the very crucial protein which transport endo and exogenous compound across the organelle and cellular membrane. These transportation make feasible various biological processes ranging from cell signaling to drug transportation. The two major human protein families of membrane transporter are ABC and SLC which transport molecules using active energy and cellular gradient respectively. Alteration of these protein structures can modulate the molecule transportation rate thus affect their routine physiological functions. Single nucleotide polymorphism (SNP) is one of the widely distributed and well-studied genomic-variant which reported to affect these membrane transporters at the genomic level and alter host physiology and in fact some time cause pathophysiology as well. Presence of these associated-SNPs are very crucial, thus their consideration in various clinical purposes make a significant contribution. Various genomic projects and SNP mining made it clear that most of these SNPs are not global in their occurrence, their alleles are population-specific, and thus their population-specific mining and association studies are very essential before their use. The current study aims for analysis of distribution pattern of Indian population-specific transporter SNPs among the Asian population and their association with the biological processes. The resulted distribution patterns will be useful for the selection of marker SNPs for various pathophysiology's and clinical studies.

Identification and distribution of a single nucleotide polymorphism responsible for the catechin content in tea plants

Catechins are the predominant products in tea plants and have essential functions for both plants and humans. Several genes encoding the enzymes regulating catechin biosynthesis have been identified, and the identification of single nucleotide polymorphisms (SNPs) resulting in nonsynonymous mutations within these genes can be used to establish a functional link to catechin content. Therefore, the transcriptomes of two parents and four filial offspring were sequenced using next-generation sequencing technology and aligned to the reference genome to enable SNP mining. Subsequently, 176 tea plant accessions were genotyped based on candidate SNPs using kompetitive allele-specific polymerase chain reaction (KASP). The catechin contents of these samples were characterized by high-performance liquid chromatography (HPLC), and analysis of variance (ANOVA) was subsequently performed to determine the relationship between genotypes and catechin content. As a result of these efforts, a SNP within the chalcone synthase (CHS) gene was shown to be functionally associated with catechin content. Furthermore, the geographical and interspecific distribution of this SNP was investigated. Collectively, these results will contribute to the early evaluation of tea plants and serve as a rapid tool for accelerating targeted efforts in tea breeding.

A Fast and Scalable Workflow for SNPs Detection in Genome Sequences Using Hadoop Map-Reduce.

Next generation sequencing (NGS) technologies produce a huge amount of biological data, which poses various issues such as requirements of high processing time and large memory. This research focuses on the detection of single nucleotide polymorphism (SNP) in genome sequences. Currently, SNPs detection algorithms face several issues, e.g., computational overhead cost, accuracy, and memory requirements. In this research, we propose a fast and scalable workflow that integrates Bowtie aligner with Hadoop based Heap SNP caller to improve the SNPs detection in genome sequences. The proposed workflow is validated through benchmark datasets obtained from publicly available web-portals, e.g., NCBI and DDBJ DRA. Extensive experiments have been performed and the results obtained are compared with Bowtie and BWA aligner in the alignment phase, while compared with GATK, FaSD, SparkGA, Halvade, and Heap in SNP calling phase. Experimental results analysis shows that the proposed workflow outperforms existing frameworks e.g., GATK, FaSD, Heap integrated with BWA and Bowtie aligners, SparkGA, and Halvade. The proposed framework achieved 22.46% more efficient F-score and 99.80% consistent accuracy on average. More, comparatively 0.21% mean higher accuracy is achieved. Moreover, SNP mining has also been performed to identify specific regions in genome sequences. All the frameworks are implemented with the default configuration of memory management. The observations show that all workflows have approximately same memory requirement. In the future, it is intended to graphically show the mined SNPs for user-friendly interaction, analyze and optimize the memory requirements as well.

Development and characterization of 24 SNP markers in Kuruma shrimp (Marsupenaeus japonicus) by illumina sequencing

We performed Illumina-based RNA-Seq for Kuruma shrimp Marsupenaeus japonicus and discovered single-nucleotide polymorphisms (SNPs) markers using de novo assembly transcriptome without reference genome. Totally 43,001 putative SNPs were obtained using Genome Analysis Toolkit (GATK) software from 15684 contigs, furthermore, 9149 contigs were annotated based on Basic Local Alignment Search Tool (BLAST) against GenBank’s non-redundant protein database (NR). Among these, 24 SNPs were validated by PCR amplification of multiple specific alleles (PAMSA) procedure using 30 individuals from Xiamen population. All loci had two alleles and the minor allele frequency ranged from 0.1041 to 0.4583. Expected (H E) and observed (H O) heterozygosities ranged from 0.1866 to 0.5071 and 0.1250 to 0.9167, respectively. This was the first SNP mining study in M. japonicus using high throughout transcriptome technology and provided useful information for future conservation and management of this overexploited marine crustacean species.

In Silico Data Mining of Single Nucleotide Polymorphisms in EZH2 and Their Role in Cancer

Background: Enhancer of zeste homolog 2 (EZH2) is a catalytic subunit of Polycomb Repressor Complex 2. PRC2 catalyzes methylation of H3K27me and it silences specific gene transcriptions. EZH2 is known to play a vital role in cancer initiation, development, progression, metastasis, and drug resistance. The expression of EZH2 is regulated by a variety of oncogenic transcription factors, tumor suppressor micro-RNAs, and cancer-associated non-coding RNAs. Post-translational modifications also control EZH2 activity. The altered expression of EZH2 has major implication in altering cellular plasticity and, hence, understanding various deleterious mutations can help comprehend its role in cancer metastasis. Objectives: The aim of this study is to summarize the data from COSMIC into useful information from the perspective of severity of the mutations in EZH2 and their contributory role as a potential biomarker in diagnosis and therapeutics associated cancers. Methods: Data mining was carried out for various SNPs in EZH2 SET domain from COSMIC, and the severity of each mutation on the functionality of the enzyme was analyzed, using multiple online in-silico tools. The frequently deleterious SNPs were further subjected to advanced tools to understand the changes which render the enzyme functionally erratic during cancer. Results: The results obtained enhanced the understanding of EZH2 mutation and predicted the plausible biomarkers that could be targeted for the purpose of diagnosis and therapeutics. About 14 prospective biomarkers for various cancers were identified and, further, their role in altering the EZH2 function was discussed. Conclusions: The various predictive and prognostic impacts of these SNPs in the selected residues are discussed which can be efficiently targeted for an improved cancer diagnosis and designing appropriate treatment strategies.

Development of a Genetic Map for Onion (Allium cepa L.) Using Reference-Free Genotyping-by-Sequencing and SNP Assays.

Single nucleotide polymorphisms (SNPs) play important roles as molecular markers in plant genomics and breeding studies. Although onion (Allium cepa L.) is an important crop globally, relatively few molecular marker resources have been reported due to its large genome and high heterozygosity. Genotyping-by-sequencing (GBS) offers a greater degree of complexity reduction followed by concurrent SNP discovery and genotyping for species with complex genomes. In this study, GBS was employed for SNP mining in onion, which currently lacks a reference genome. A segregating F2 population, derived from a cross between ‘NW-001’ and ‘NW-002,’ as well as multiple parental lines were used for GBS analysis. A total of 56.15 Gbp of raw sequence data were generated and 1,851,428 SNPs were identified from the de novo assembled contigs. Stringent filtering resulted in 10,091 high-fidelity SNP markers. Robust SNPs that satisfied the segregation ratio criteria and with even distribution in the mapping population were used to construct an onion genetic map. The final map contained eight linkage groups and spanned a genetic length of 1,383 centiMorgans (cM), with an average marker interval of 8.08 cM. These robust SNPs were further analyzed using the high-throughput Fluidigm platform for marker validation. This is the first study in onion to develop genome-wide SNPs using GBS. The resulting SNP markers and developed linkage map will be valuable tools for genetic mapping of important agronomic traits and marker-assisted selection in onion breeding programs.

SNP mining in transcripts and concomitant estimation of genetic variation in Macrobrachium rosenbergii stocks

Macrobrachium rosenbergii is an aquaculture species of global importance whose production has sharply declined since 2005. Single nucleotide polymorphisms (SNPs) in transcribed sequences are likely to have high association with economic traits and are important for marker assisted selection. SNPs were mined in 34 reported transcripts from 4 wild M. rosenbergii stocks of India using the amplicon approach and high-throughput sequencing platforms. Out of 320 SNPs detected, 134 were common to all stocks while 3 were diagnostic. Pair-wise Nei’s genetic distances (0.304–0.469) showed phylogeny consistent with geographical distribution. AMOVA analysis revealed estimated variance of 21.5 among populations. The transition to transversion ratio was 2.20. Changes in amino acid classes and peptide stability were recorded for 80 non-synonymous SNPs while change in codon preference was noted for 138 synonymous ones. Four pathogen defence genes were highly polymorphic, of which lectin 3 had the highest SNP rate (6 SNPs/100 bp). This approach for mining SNPs and using them for population differentiation in a single step is reported for the first time.

Mining of single nucleotide polymorphisms in the 3' untranslated region of liver cancer-implicated miR-122 target genes.

Currently there has been a lot of focus on the microRNA (miR)-122 to understand the genetics of hepatocellular carcinoma (HCC), pathology of hepatitis B virus (HBV) and hepatitis C virus (HCV) infections, hepatic insulin resistance, and lipid metabolism (1-4). Interestingly, miR-122 expression levels were significantly reduced than the normal levels in HBV-associated liver cancer, but not in HCV related liver cancer (5). Also, there is an overwhelming amount of data suggesting the role of single nucleotide polymorphisms (SNPs) in hepatic genes and its association with the altered risk/development of hepatic cancer and its progression. Polymorphisms in the miRNA-binding sites of the target genes are more frequent than SNPs in miRNA genes and therefore, it is considered that polymorphisms in the cytokines and other genes have correlations with chronic HBV or HCV infections. These SNPs in the miRNA binding sites of the target genes can potentially enhance or weaken the interaction between the miRNAs and the target transcripts. Therefore, it is important to study the SNPs in miR-122 binding sites of the target genes to understand the genetic basis of HCC.

Single nucleotide polymorphism mining and nucleotide sequence analysis of Mx1 gene in exonic regions of Japanese quail.

Aim:An attempt has been made to study the Myxovirus resistant (Mx1) gene polymorphism in Japanese quail.Materials and Methods:In the present, investigation four fragments viz. Fragment I of 185 bp (Exon 3 region), Fragment II of 148 bp (Exon 5 region), Fragment III of 161 bp (Exon 7 region), and Fragment IV of 176 bp (Exon 13 region) of Mx1 gene were amplified and screened for polymorphism by polymerase chain reaction-single-strand conformation polymorphism technique in 170 Japanese quail birds.Results:Out of the four fragments, one fragment (Fragment II) was found to be polymorphic. Remaining three fragments (Fragment I, III, and IV) were found to be monomorphic which was confirmed by custom sequencing. Overall nucleotide sequence analysis of Mx1 gene of Japanese quail showed 100% homology with common quail and more than 80% homology with reported sequence of chicken breeds.Conclusion:The Mx1 gene is mostly conserved in Japanese quail. There is an urgent need of comprehensive analysis of other regions of Mx1 gene along with its possible association with the traits of economic importance in Japanese quail.

Introgression browser: high-throughput whole-genome SNP visualization.

Breeding by introgressive hybridization is a pivotal strategy to broaden the genetic basis of crops. Usually, the desired traits are monitored in consecutive crossing generations by marker-assisted selection, but their analyses fail in chromosome regions where crossover recombinants are rare or not viable. Here, we present the Introgression Browser (iBrowser), a bioinformatics tool aimed at visualizing introgressions at nucleotide or SNP (Single Nucleotide Polymorphisms) accuracy. The software selects homozygous SNPs from Variant Call Format (VCF) information and filters out heterozygous SNPs, multi-nucleotide polymorphisms (MNPs) and insertion-deletions (InDels). For data analysis iBrowser makes use of sliding windows, but if needed it can generate any desired fragmentation pattern through General Feature Format (GFF) information. In an example of tomato (Solanum lycopersicum) accessions we visualize SNP patterns and elucidate both position and boundaries of the introgressions. We also show that our tool is capable of identifying alien DNA in a panel of the closely related S. pimpinellifolium by examining phylogenetic relationships of the introgressed segments in tomato. In a third example, we demonstrate the power of the iBrowser in a panel of 597 Arabidopsis accessions, detecting the boundaries of a SNP-free region around a polymorphic 1.17 Mbp inverted segment on the short arm of chromosome 4. The architecture and functionality of iBrowser makes the software appropriate for a broad set of analyses including SNP mining, genome structure analysis, and pedigree analysis. Its functionality, together with the capability to process large data sets and efficient visualization of sequence variation, makes iBrowser a valuable breeding tool.

Mining of gene-based SNPs from publicly available ESTs and their conversion to cost-effective genotyping assay in sorghum [Sorghum bicolor (L.) Moench

Single Nucleotide Polymorphisms (SNPs) are the commonest type of nucleotide variation distributed throughout the genome and have enormous potential to saturate genetic maps. However, their identification is constrained by the huge investment required for their detection. In this study, we used publicly available EST (Expressed Sequence Tag) sequences to identify SNPs in Sorghum bicolor. A total of 12,421 putative SNPs were identified from 2,921 contiguous transcripts leading to an average SNP interval of one putative SNP for every 275.26 bp. The proportion of transition type mutations (0.598) was larger than transversion types conforming to biological expectations. In order to demonstrate the utility of the SNPs for development of markers with relatively cheap assays, we experimentally validated SNPs using Single Strand Conformation Polymorphism (SSCP) technique in sorghum accessions, which are used as parents for development mapping populations. Genotyping these parents of mapping populations with SSCP markers showed up to 33% polymorphism in the markers suggesting that the SNPs can be used as potential resource for S. bicolor crop improvement programs.

Deep sequencing of the transcriptome and mining of single nucleotide polymorphisms (SNPs) provide genomic resources for applied studies in Chinook salmon (Oncorhynchus tshawytscha)

We deep-sequenced the transcriptome of Chinook salmon (Oncorhynchus tshawytscha) that yielded 2.5 million high-quality reads (combined for four fish) with an average length of 378 bp. De novo assembly resulted in 44,264 contigs with an average length of 567 bp and an average depth of 29 reads. Nearly half (42 %) of the contigs were annotated through alignment against protein, gene ontology (GO) and taxonomic databases using BLASTX. Overrepresented GO categories included metabolism (32 %), biosynthesis (11 %), transport (7 %), transcription (5 %) and other important pathways (response to stress, lipid metabolism and reproduction: 3 %). We identified 3,793 putative single nucleotide polymorphisms (SNPs) in silico, of which 718 were annotated. We characterized a sample of 54 annotated SNPs within contigs with transition-to-transversion ratios <1. Of these, 26 were nonsynonymous SNPs. Transcriptome sequencing remains a source of novel polymorphisms that holds promise for applied studies in Chinook salmon, an important salmonid species native to the North Pacific.