scholarly journals Chinese Fir Breeding in the High-Throughput Sequencing Era: Insights from SNPs

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 681 ◽  
Author(s):  
Huiquan Zheng ◽  
Dehuo Hu ◽  
Ruping Wei ◽  
Shu Yan ◽  
Runhui Wang
Keyword(s):  
Population Structure ◽  
Genetic Structure ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Breeding Population ◽  
Population Diversity ◽  
Chinese Fir ◽  
High Density ◽  
Population Structure Analysis ◽  
Snp Panel

Knowledge on population diversity and structure is of fundamental importance for conifer breeding programs. In this study, we concentrated on the development and application of high-density single nucleotide polymorphism (SNP) markers through a high-throughput sequencing technique termed as specific-locus amplified fragment sequencing (SLAF-seq) for the economically important conifer tree species, Chinese fir (Cunninghamia lanceolata). Based on the SLAF-seq, we successfully established a high-density SNP panel consisting of 108,753 genomic SNPs from Chinese fir. This SNP panel facilitated us in gaining insight into the genetic base of the Chinese fir advance breeding population with 221 genotypes for its genetic variation, relationship and diversity, and population structure status. Overall, the present population appears to have considerable genetic variability. Most (94.15%) of the variability was attributed to the genetic differentiation of genotypes, very limited (5.85%) variation occurred on the population (sub-origin set) level. Correspondingly, low FST (0.0285–0.0990) values were seen for the sub-origin sets. When viewing the genetic structure of the population regardless of its sub-origin set feature, the present SNP data opened a new population picture where the advanced Chinese fir breeding population could be divided into four genetic sets, as evidenced by phylogenetic tree and population structure analysis results, albeit some difference in membership of the corresponding set (cluster vs. group). It also suggested that all the genetic sets were admixed clades revealing a complex relationship of the genotypes of this population. With a step wise pruning procedure, we captured a core collection (core 0.650) harboring 143 genotypes that maintains all the allele, diversity, and specific genetic structure of the whole population. This generalist core is valuable for the Chinese fir advanced breeding program and further genetic/genomic studies.

scholarly journals High-throughput genotype based population structure analysis of selected buffalo breeds

2018 ◽  
Author(s):  
Prakash B. Thakor ◽  
Ankit T. Hinsu ◽  
Dhruv R. Bhatiya ◽  
Tejas M. Shah ◽  
Nilesh Nayee ◽  
...  
Keyword(s):  
Population Structure ◽  
Genetic Structure ◽  
Structure Analysis ◽  
Milk Production ◽  
High Throughput ◽  
Snp Markers ◽  
High Density ◽  
Sequence Information ◽  
Snp Chip ◽  
Geographical Regions

AbstractThe water buffalo (Bubalus bubalis) has shown enormous milk production potential in many Asian countries. India is considered as the home tract of some of the best buffalo breeds. However, genetic structure of the Indian river buffalo is poorly understood. Hence, for selection and breeding strategies, there is a need to characterize the populations and understand the genetic structure of various buffalo breeds. In this study, we have analysed genetic variability and population structure of seven buffalo breeds from their respective geographical regions using Axiom® Buffalo Genotyping Array having 124,030 Single Nucleotide Polymorphisms (SNPs). Blood samples were obtained from 302 buffaloes comprising Murrah, Nili-Ravi, Mehsana, Jaffarabadi, Banni, Pandharpuri and Surti breeds. Diversity, as measured by expected heterozygosity (He) ranged from 0.364 in the Surti to 0.384 in the Murrah breed. All the breeds showed negligible inbreeding coefficient. Pair-wise FST values revealed the lowest genetic distance between Mehsana and Nili-Ravi (0.0022) while highest between Surti and Pandharpuri (0.030). Principal component analysis and structure analysis unveiled the differentiation of Surti, Pandharpuri and Jaffarabadi in first two PCs, while remaining breeds were grouped together as a separate single cluster. Murrah and Mehsana showed early linkage disequilibrium decay while Surti breed showed late decay, similarly LD based Ne was drastically declined for Murrah and Mehsana since last 100 generations. In LD blocks to QTLs concordance analysis, 14.19 per cent of concordance was observed with 873 (out of 1144) LD blocks overlapped with 8912 (out of 67804) QTLs. Overall, total 4090 markers were identified from all LD blocks for six types of traits. Results of this study indicated that these SNP markers could differentiate phenotypically distinct breeds like Surti,Pandharpuri and Jaffarabadi but not others. So, there is a need to develop SNP chip based on SNP markers identified by sequence information of local breeds.Author SummaryIndian buffaloes, through 13 recognised breeds, contribute about 49% in total milk production and play a vital role in enhancing the economic condition of Indian farmers. High density genotyping these breeds will allow us to study differences at the molecular level. Evolutionary relationship and phenotypes relations with genotype could be tested with high density genotyping. Breed structure analysis helps to take effective breeding policy decision. In the present study, we have used the high-throughput microarray based genotyping technology for SNP markers. These markers were used for breed differentiation using various genetic parameters. Population structure reflected the proportion of breed admixture among studied breeds. We have also tried to dig the markers associated with traits based LD calculation. However, these SNPs couldn’t explain obvious variation up to the expected level, hence, there is need to develop an indigenous SNP chip based on Indian buffalo populations.

scholarly journals Construction and Analysis of High-Density Linkage Map Using High-Throughput Sequencing Data

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e98855 ◽  
Author(s):  
Dongyuan Liu ◽  
Chouxian Ma ◽  
Weiguo Hong ◽  
Long Huang ◽  
Min Liu ◽  
...  
Keyword(s):  
Linkage Map ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
High Density ◽  
Sequencing Data ◽  
High Throughput Sequencing Data ◽  
High Density Linkage Map

scholarly journals High-throughput genotype-based population structure analysis of selected buffalo breeds

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Prakash B Thakor ◽  
Ankit T Hinsu ◽  
Dhruv R Bhatia ◽  
Tejas M Shah ◽  
Nilesh Nayee ◽  
...  
Keyword(s):  
Population Structure ◽  
Genetic Structure ◽  
Structure Analysis ◽  
Principal Component ◽  
Snp Markers ◽  
Sequence Information ◽  
Population Structure Analysis ◽  
Geographical Regions ◽  
Indian River ◽  
Single Cluster

Abstract India is considered as the home tract of some of the best buffalo breeds. However, the genetic structure of the Indian river buffalo is poorly understood. Hence, there is a need to characterize the populations and understand the genetic structure of various buffalo breeds for selection and to design breeding strategies. In this study, we have analyzed genetic variability and population structure of seven buffalo breeds from their respective geographical regions using Axiom Buffalo Genotyping Array. Diversity, as measured by expected heterozygosity, ranged from 0.364 in Surti to 0.384 in Murrah breed, and pair-wise FST values revealed the lowest genetic distance between Murrah and Nili-Ravi (0.0022), while the highest between Surti and Pandharpuri (0.030). Principal component analysis and structure analysis unveiled the differentiation of Surti, Pandharpuri, and Jaffarabadi in first two principal components and at K = 4, respectively, while remaining breeds were grouped together as a separate single cluster and admixed. Murrah and Mehsana showed early linkage disequilibrium (LD) decay, while Surti breed showed late decay. In LD blocks to quantitative trait locis (QTLs) concordance analysis, 4.65% of concordance was observed with 873 LD blocks overlapped with 2,330 QTLs. Overall, total 4,090 markers were identified from all LD blocks for six types of traits. Results of this study indicated that these single-nucleotide polymorphism (SNP) markers could differentiate phenotypically distinct breeds like Surti, Pandharpuri, and Jaffarabadi but not others. So, there is a need to develop SNP chip based on SNP markers identified by sequence information of local breeds.

scholarly journals High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants

2021 ◽  
Author(s):  
Rafaela S. Fontenele ◽  
Simona Kraberger ◽  
James Hadfield ◽  
Erin M. Driver ◽  
Devin Bowes ◽  
...  
Keyword(s):  
Population Structure ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Genomic Diversity ◽  
Contact Tracing ◽  
Public Health Response ◽  
Genetic Population ◽  
Genomic Epidemiology ◽  
Derived Data

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 5680 were “novel” SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.

scholarly journals Genetic structure of the American ginseng (Panax quinquefolius L.) in Eastern Canada using reduced-representation high-throughput sequencing

Botany ◽  
2017 ◽  
Vol 95 (4) ◽  
pp. 429-434 ◽  
Author(s):  
Simon Joly ◽  
Annie Archambault ◽  
Stéphanie Pellerin ◽  
Andrée Nault
Keyword(s):  
Genetic Variation ◽  
Genetic Structure ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Natural Populations ◽  
American Ginseng ◽  
Panax Quinquefolius ◽  
Eastern Canada ◽  
Reduced Representation ◽  
Wide Range

The American ginseng (Panax quinquefolius L.) has been used for a wide range of medicinal purposes for more than 300 years, and is at risk in most of its range because of harvesting in natural populations, herbivory, and habitat loss. Its genetic structure is largely unknown in the previously glaciated areas of Eastern Canada, although such information could provide useful information for restoration strategies. We generated and analysed data from a reduced-representation high-throughput sequencing approach with a BAMOVA population model to partition the genetic variation within and among six natural populations of American ginseng in Eastern Canada. We found that an important and significant fraction of the genetic variation was structured among populations ([Formula: see text] = 42%; FST = 34%) at the geographical scale of the study (<250 km). No clear evidence of isolation-by-distance was observed. This important genetic structure observed among American ginseng populations from a region that was covered by ice during the last glaciations is similar to what had been found in previous studies on southern populations or throughout the species range.

scholarly journals A new mouse SNP genotyping assay for speed congenics: combining flexibility, affordability, and power

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kimberly R. Andrews ◽  
Samuel S. Hunter ◽  
Brandi K. Torrevillas ◽  
Nora Céspedes ◽  
Sarah M. Garrison ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Cost Effective ◽  
High Density ◽  
Snp Genotyping ◽  
Mouse Strains ◽  
Bioinformatic Pipeline ◽  
Genotyping Assay ◽  
Sequencing Technologies ◽  
Diagnostic Snps

Abstract Background Speed congenics is an important tool for creating congenic mice to investigate gene functions, but current SNP genotyping methods for speed congenics are expensive. These methods usually rely on chip or array technologies, and a different assay must be developed for each backcross strain combination. “Next generation” high throughput DNA sequencing technologies have the potential to decrease cost and increase flexibility and power of speed congenics, but thus far have not been utilized for this purpose. Results We took advantage of the power of high throughput sequencing technologies to develop a cost-effective, high-density SNP genotyping assay that can be used across many combinations of backcross strains. The assay surveys 1640 genome-wide SNPs known to be polymorphic across > 100 mouse strains, with an expected average of 549 ± 136 SD diagnostic SNPs between each pair of strains. We demonstrated that the assay has a high density of diagnostic SNPs for backcrossing the BALB/c strain into the C57BL/6J strain (807–819 SNPs), and a sufficient density of diagnostic SNPs for backcrossing the closely related substrains C57BL/6N and C57BL/6J (123–139 SNPs). Furthermore, the assay can easily be modified to include additional diagnostic SNPs for backcrossing other closely related substrains. We also developed a bioinformatic pipeline for SNP genotyping and calculating the percentage of alleles that match the backcross recipient strain for each sample; this information can be used to guide the selection of individuals for the next backcross, and to assess whether individuals have become congenic. We demonstrated the effectiveness of the assay and bioinformatic pipeline with a backcross experiment of BALB/c-IL4/IL13 into C57BL/6J; after six generations of backcrosses, offspring were up to 99.8% congenic. Conclusions The SNP genotyping assay and bioinformatic pipeline developed here present a valuable tool for increasing the power and decreasing the cost of many studies that depend on speed congenics. The assay is highly flexible and can be used for combinations of strains that are commonly used for speed congenics. The assay could also be used for other techniques including QTL mapping, standard F2 crosses, ancestry analysis, and forensics.

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