Construction of a high-resolution genetic map and identification of quantitative trait loci for salt tolerance in jute (Corchous spp.).

BACKGROUND: Jute (Corchorus spp.) is the most important natural fiber crop after cotton in terms of cultivation area and production. Salt stress greatly restricts plant development and growth. A high-density genetic linkage map is the basis of quantitative trait locus (QTLs) mapping. Several high-density genetic maps and QTLs mapping related to salt tolerance have been developed through next-generation sequencing in many crop species. However, such studies are rare for jute. Only several low-density genetic maps have been constructed and no salt tolerance-related QTL has been mapped in jute to date. RESULTS: We developed a high-density genetic map with 4839 single nucleotide polymorphism markers spanning 1375.41 cM and an average distance of 0.28 cM between adjacent markers on seven linkage groups (LGs) using an F2 jute population, LGs ranged from LG2 with 299 markers spanning 113.66 cM to LG7 with 1542 markers spanning 350.18 cM. In addition, 99.57% of gaps between adjacent markers were less than 5 cM. Three obvious and 13 minor QTLs involved in salt tolerance were identified on four LGs explaining 0.58-19.61% of the phenotypic variance. The interval length of QTL mapping varied from 1.3 to 20.2 cM. The major QTL, qJST-1, was detected under two salt stress conditions that explained 11.81 and 19.61% of the phenotypic variation, respectively, and peaked at 19.3 cM on LG4. CONCLUSIONS: We developed the first high-density and the most complete genetic map of jute to date using a genotyping-by-sequencing approach. The first QTL mapping related to salt tolerance was also carried out in jute. These results should provide useful resources for marker-assisted selection and transgenic breeding for salt tolerance at the germination stage in jute.

Genetic analysis of 12 X-STR loci in the Serbian population from Vojvodina Province.

The analysis of 12 X-STR loci included in the Investigator® Argus X-12 kit was performed on a sample of 325 unrelated persons from Vojvodina Province, Republic of Serbia. No significant differences were observed in the allele frequencies in males and females. Heterozygosity values among the studied loci ranged from 67.62 to 94.28%. All loci in female individuals were consistent with the Hardy-Weinberg equilibrium test. The combined power of discrimination values in male and female individuals was 0.9999999994 and 0.999999999999999, respectively. The combined mean exclusion chance was 0.999998 in deficiency cases, 0.9999999977 in normal trio cases, and 0.9999994 in duo cases. Loci DXS10135 and DXS10101 were found to be most polymorphic. The haplotype diversity was found to be greater than 0.993 for all linkage groups. The exact test for pairwise linkage disequilibrium for the 12 loci in the male samples showed significant linkage disequilibrium for the DXS10103-DXS10101 and DXS10134-DXS10146 pairs of loci. The results from the current study confirmed that the panel of 12 X-STR loci is highly polymorphic and informative and can be implemented as a powerful tool in deficient paternity testing and kinship analysis, as well as a useful complement tool of autosomal short tandem repeats (STRs) in forensic investigation. Population differentiation analyses indicated significant differences in genetic structure between the Serbian population and the geographically and ethno-linguistically distant populations, while genetic homogeneity was present in populations with similar geographic origin.

Genetic diversity study on 12 X-STR loci of investigator® Argus X STR kit in Bangladeshi population.

The X-chromosome short tandem repeat (STR) loci are of particular interest for solving complex kinship and paternity cases. Here, we report the genetic data from 209 unrelated Bangladeshi individuals (102 males and 107 females) that were genotyped using the 12 X-chromosomal STR markers included in the Investigator® Argus X-12 kit (Qiagen). The 12 X-STR markers are located in four linkage groups (linkage group I: DXS10135, DXS10148, and DXS8378; linkage group II: DXS7132, DXS10079, and DXS10074; linkage group III: DXS10103, HPRTB, and DXS10101; and linkage group IV: DXS10146, DXS10134, and DXS7423). Allelic frequencies of the 12 X-STR loci and haplotype frequencies of the four linkage groups were investigated. No significant difference was observed in the allele frequencies of males and females. Distributions of heterozygosity were observed from 64.5 to 92.5% among the studied 12 X STR loci. DXS10135 and DXS10101 loci were found to be most polymorphic. For all the four linkage groups, the haplotype diversity was found to be greater than 0.986. A total of 95, 73, 66, and 74 haplotypes were observed in linkage groups I, II, III, and IV, respectively. Hardy-Weinberg equilibrium tests showed no significant deviation from expected values for all 12 loci (p > 0.05). The exact test for pairwise linkage disequilibrium for the 12 loci in the male samples did not show any significant linkage disequilibrium except the DXS10103 and DXS10101 loci after the p values were corrected by Bonferroni's correction for multiple testing (p > 0.05/66). A combined power of discrimination in male and female individuals were 0.999999998159791 and 0.999999999999993, respectively. The combined mean exclusion chance were 0.999997635 in deficiency cases, 0.999999996 in normal trio cases, and 0.999999178 in duo cases. The currently investigated Bangladeshi population showed significant differences when compared with previously reported X-STR data from other 12 populations. The results of the data analysis indicated that all the loci in the Investigator® Argus X 12 kit were fairly informative and might be useful in forensic application and kinship analysis in Bangladeshi population.

An SSR-based genetic map of pepper (Capsicum annuum L.) serves as an anchor for the alignment of major pepper maps.

Of the Capsicum peppers (Capsicum spp.), cultivated C. annuum is the most commercially important, but has lacked an intraspecific linkage map based on sequence-specific PCR markers in accord with haploid chromosome numbers. We constructed a linkage map of pepper using a doubled haploid (DH) population derived from a cross between two C. annuum genotypes, a bell-type cultivar 'California Wonder' and a Malaysian small-fruited cultivar 'LS2341 (JP187992)', which is used as a source of resistance to bacterial wilt (Ralstonia solanacearum). A set of 253 markers (151 SSRs, 90 AFLPs, 10 CAPSs and 2 sequence-tagged sites) was on the map which we constructed, spanning 1,336 cM. This is the first SSR-based map to consist of 12 linkage groups, corresponding to the haploid chromosome number in an intraspecific cross of C. annuum. As this map has a lot of PCR-based anchor markers, it is easy to compare it to other pepper genetic maps. Therefore, this map and the newly developed markers will be useful for cultivated C. annuum breeding.

Molecular Breeding to Overcome Biotic Stresses in Soybean: Update.

Soybean (Glycine max (L.) Merr.) is an important leguminous crop and biotic stresses are a global concern for soybean growers. In recent decades, significant development has been carried outtowards identification of the diseases caused by pathogens, sources of resistance and determination of loci conferring resistance to different diseases on linkage maps of soybean. Host-plant resistance is generally accepted as the bestsolution because of its role in the management of environmental and economic conditions of farmers owing to low input in terms of chemicals. The main objectives of soybean crop improvement are based on the identification of sources of resistance or tolerance against various biotic as well as abiotic stresses and utilization of these sources for further hybridization and transgenic processes for development of new cultivars for stress management. The focus of the present review is to summarize genetic aspects of various diseases caused by pathogens in soybean and molecular breeding research work conducted to date.

GCsnap: Interactive Snapshots for the Comparison of Protein-Coding Genomic Contexts.

The biological function and evolutionary history of protein-coding genes are not only written in their nucleotide sequences. The comparison of genomic contexts throughout different lineages may highlight genomic mechanisms in the generation of new protein families, while the conservation of gene clusters may unravel, for instance, metabolic pathways. Various tools and databases exist that allow for the analysis and comparison of genomic contexts, but each has its own limitations. Online databases allow for quick comparisons, but only for those genomes for which data were pre-calculated. More advanced tools may allow for the comparison of any genome, but are often limited to a given phylogenetic kingdom or provide only a snapshot of the genomic contexts without further information about the genes involved. Here, we introduce GCsnap, a flexible Python-based tool that allows for the interactive comparison of the genomic contexts of protein-coding genes from any genome at any taxonomic level, integrating them with functional and structural information. By connecting the output to different protein databases, users can navigate through the different genomic contexts from a simple interactive platform, facilitating the further analysis of the contexts found. GCsnap is not limited to a single input format, can perform batch jobs and accepts protein classification maps. Results are stored in detailed, human and machine-readable files, and customizable, publication-ready figures. GCsnap is freely available from https://github.com/JoanaMPereira/GCsnap and can be set up easily on any computer.

A Microbiomic Analysis in African Americans with Colonic Lesions Reveals Streptococcus sp.VT162 as a Marker of Neoplastic Transformation.

Increasing evidence suggests a role of the gut microbiota in colorectal carcinogenesis (CRC). To detect bacterial markers of colorectal cancer in African Americans a metabolomic analysis was performed on fecal water extracts. DNA from stool samples of adenoma and healthy subjects and from colon cancer and matched normal tissues was analyzed to determine the microbiota composition (using 16S rDNA) and genomic content (metagenomics). Metagenomic functions with discriminative power between healthy and neoplastic specimens were established. Quantitative Polymerase Chain Reaction (q-PCR) using primers and probes specific to Streptococcus sp. VT_162 were used to validate this bacterium association with neoplastic transformation in stool samples from two independent cohorts of African Americans and Chinese patients with colorectal lesions. The metabolomic analysis of adenomas revealed low amino acids content. The microbiota in both cancer vs. normal tissues and adenoma vs. normal stool samples were different at the 16S rRNA gene level. Cross-mapping of metagenomic data led to 9 markers with significant discriminative power between normal and diseased specimens. These markers identified with Streptococcus sp. VT_162. Q-PCR data showed a statistically significant presence of this bacterium in advanced adenoma and cancer samples in an independent cohort of CRC patients. We defined metagenomic functions from Streptococcus sp. VT_162 with discriminative power among cancers vs. matched normal and adenomas vs. healthy subjects' stools. Streptococcus sp. VT_162 specific 16S rDNA was validated in an independent cohort. These findings might facilitate non-invasive screening for colorectal cancer.

Identification of patterns related to linkage groups or disequilibrium by factor analysis / Identificação de padrões relacionados a grupos de ligação ou de desequilíbrio por análise de fatores

ABSTRACT: Empirical patterns of linkage disequilibrium (LD) can be used to increase the statistical power of genetic mapping. This study was carried out with the objective of verifying the efficacy of factor analysis (AF) applied to data sets of molecular markers of the SNP type, in order to identify linkage groups and haplotypes blocks. The SNPs data set used was derived from a simulation process of an F2 population, containing 2000 marks with information of 500 individuals. The estimation of the factorial loadings of FA was made in two ways, considering the matrix of distances between the markers (A) and considering the correlation matrix (R). The number of factors (k) to be used was established based on the graph scree-plot and based on the proportion of the total variance explained. Results indicated that matrices A and R lead to similar results. Based on the scree-plot we considered k equal to 10 and the factors interpreted as being representative of the bonding groups. The second criterion led to a number of factors equal to 50, and the factors interpreted as being representative of the haplotypes blocks. This showed the potential of the technique, making it possible to obtain results applicable to any type of population, helping or corroborating the interpretation of genomic studies. The study demonstrated that AF was able to identify patterns of association between markers, identifying subgroups of markers that reflect factor binding groups and also linkage disequilibrium groups.

RESUMO: Padrões empíricos de desequilíbrio de ligação (LD) podem ser utilizados para aumentar o poder estatístico do mapeamento genético. Este trabalho foi realizado com o objetivo de verificar a eficácia da análise de fatores (AF) aplicada a conjuntos de dados de marcadores moleculares do tipo SNP, visando identificar grupos de ligação e blocos de haplótipos. O conjunto de dados SNPs utilizado foi oriundo de um processo de simulação de uma população F2, contendo 2000 marcas com informações de 500 indivíduos. A estimação das cargas fatoriais (loadings) da AF foi feita de duas formas, considerando a matriz de distâncias entre os marcadores (A) e considerando a matriz de correlação (R). O número de fatores (k) a ser utilizado foi estabelecido com base no gráfico scree-plot e com base na proporção da variância total explicada. Os resultados indicam que as matrizes A e R conduzem a resultados similares. Com base no scree-plot considerou-se k igual a 10 e os fatores interpretados como sendo representativos dos grupos de ligação. O segundo critério conduziu a um número de fatores igual a 50, e os fatores interpretados como sendo representativos dos blocos de haplótipos. Isto mostra o potencial da técnica que permite obter resultados aplicáveis ​​a qualquer tipo de população, corroborando a interpretação de estudos genômicos. O trabalho demonstrou que a AF foi capaz de identificar padrões de associação entre marcadores, identificando subgrupos de marcadores que refletem grupos de ligação fatorial e também grupos de desequilíbrio de ligação.

A first-generation microsatellite linkage map of the ruff.

A linkage map of the ruff (Philomachus pugnax) genome was constructed based on segregation analysis of 58 microsatellite loci from 381 captive-bred individuals spanning fourteen breeding years and comprising 64 families. Twenty-eight of the markers were resolved into seven linkage groups and five single marker loci, homologous to known chicken (Gallus gallus) and zebra finch (Taeniopygia guttata) chromosomes. Linkage groups range from 10.1 to 488.7 cM in length and covered a total map distance of 641.6 cM, corresponding to an estimated 30-35% coverage of the ruff genome, with a mean spacing of 22.9 cM between loci. Through comparative mapping, we are able to assign linkage groups Ppu1, Ppu2, Ppu6, Ppu7, Ppu10, Ppu13, and PpuZ to chromosomes and identify several intrachromosomal rearrangements between the homologs of chicken, zebra finch, and ruff microsatellite loci. This is the first linkage map created in the ruff and is a major step toward providing genomic resources for this enigmatic species. It will provide an essential framework for mapping of phenotypically and behaviorally important loci in the ruff.

Otimização do mapeamento genético vegetal de populações duplo-haplóide via simulação computacional / Optimization of vegetal genetic mapping of double-haploid populations via computational simulation

O mapeamento genético é um passo necessário para entender a organização genômica e a relação entre genes e o fenótipo. Um dos principais problemas está em encontrar a ordem, o espaçamento correto dos marcadores em um mapa genético, assim como o número de indivíduos a compor uma população. Deste modo, o objetivo deste estudo foi avaliar o nível de saturação do genoma e o tamanho ideal de populações simulada duplo-haplóide para a construção de mapas de ligação mais confiáveis por meio de simulação computacional. Foram simulados genomas parentais e populações duplo-haplóide considerando marcadores moleculares do tipo dominante, espaçados de forma equidistante a 5, 10 e 20 cM. Os tamanhos das populações geradas foram de 100, 200, 300, 500, 800 e 1000 indivíduos, com dez grupos de ligação cada e 100 repetições por amostra. Procedeu-se a análise de todas as populações geradas obtendo um genoma analisado o qual foi comparado com o genoma simulado inicialmente. Observou-se que o tamanho ideal de populações duplo-haplóide para mapeamento genético foi de no mínimo 200, 500 e 1000 indivíduos para genomas saturados, medianamente saturados e com baixa saturação. Populações de mesmo tamanho tendem a produzir mapas com maior acurácia em níveis de saturação do genoma mais elevados.

Genetic mapping is a necessary step to understand the genomic organization and the relationship between genes and phenotypes. A major problem is to find the order, the correct spacing of the markers in a genetic map, and the number of individuals to compose a population. Thus, the objective of this study was to evaluate the saturation level of the genome and the optimal size of simulated double-haploid populations for the construction reliable linkage maps by means of computer simulation. Parental genomes and double-haploid populations were simulated considering dominant molecular markers, spaced equidistantly at 5, 10 and 20 cM. The sizes of the generated populations were 100, 200, 300, 500, 800 and 1000 individuals, with ten linking groups and 100 replicates per sample. It was proceeded the analysis of all generated population obtaining a genome which was compared with the first simulated genome. It was observed that the optimal size of double-haploid populations for genetic mapping has been at least 200, 500 and 1000 individuals for saturated genomes, medium unsaturated and low saturation. Populations of the same size tend to produce maps with greater accuracy in higher levels of genome saturation.