BRR : 12246849
Tender Brief : Tender for Supply Of Next-Generation Sequencing (Ngs) Services For Whole Genome Sequencing (Wgs) Of Plant S Les, Including Dna Extraction, 80 Gb (Q30) Data Per S Le, Bulked Segregant Analysis (Bsa-Seq), Pairwise Variant Discovery, Comparative Analysis, Polymorphism Detection, Gene Annotation, Candidate Region /Gene Identification And Linked-Marker Discovery With S Le Transport (Dry Ice) , Next-Generation Sequencing (Ngs) Services For Whole Genome Sequencing (Wgs) Of Plant Samples, Including Dna Extraction, 80 Gb (Q30) Data Per Sample, Bulked Segregant Analysis (Bsa-Seq), Pairwise Variant Disc... Read More
Tender Value
₹
Ref. Document
Submission Date
01-10-2026
Participated Bidder List
5 No of Bidder(s)
| Sr No. | Bidder Name | Bid Analytics | Technical Bid | Financial Bid | AOC | Bid Value | Rank |
|---|---|---|---|---|---|---|---|
| 1 | cnet-technologies | Bid Analytics | |||||
| 2 | cnet-technologies | Bid Analytics | |||||
| 3 | cnet-technologies | Bid Analytics | |||||
| 4 | cnet-technologies | Bid Analytics | |||||
| 5 | cnet-technologies | Bid Analytics |
Work Detail
tender for supply of next-generation sequencing (ngs) services for whole genome sequencing (wgs) of plant s les, including dna extraction, 80 gb (q30) data per s le, bulked segregant analysis (bsa-seq), pairwise variant discovery, comparative analysis, polymorphism detection, gene annotation, candidate region /gene identification and linked-marker discovery with s le transport (dry ice) , next-generation sequencing (ngs) services for whole genome sequencing (wgs) of plant samples, including dna extraction, 80 gb (q30) data per sample, bulked segregant analysis (bsa-seq), pairwise variant discovery, comparative analysis, polymorphism detection, gene annotation, candidate region /gene identification and linked-marker discovery with sample transport (dry ice). detailed specification service required: reference-based whole genome sequencing (wgs) including dna extraction, high-quality sequencing, variant discovery, gene annotation, and comparative genomic analysis. sample type:young leaf samples (fresh plant tissue). sample transport: transport from field to servicing laboratory in dry ice, until extraction of high-quality dna suitable for wgs. cost must be included. sequencing platform: illumina novaseq 6000 or latest equivalent high-throughput platform. date: minimum ≥80 gb high-quality trimmed data (q30) per sample. service and analysis requirement: 1. dna extraction, qc and bulk preparation : • high-quality genomic dna extraction from each of the 60 individual leaf samples and 2-4 parents.separate qc record for each of the 60 dna samples. ormalisation of dna concentration followed by equal-quantity/equimolar pooling of 15 dnas each of four bulks. documentation of the exact contribution of each individual plant to bulks; 2. wgs data generation and quality control : •trimmed and quality-filtered paired-end whole-genome sequencing of 2-4 bulks.minimum ≥80 gb of high-quality, q30-trimmed data per bulk, unless the service provider proposes a scientifically justified equivalent coverage.adapter removal and quality filtering/trimming.• fastqc/multiqc or equivalent quality-control assessment. raw-read and clean-read statistics, q20/q30, gc content, read count and duplication statistics.; 3. reference-based genome analysis : • alignment of clean reads to the latest appropriate reference genome. reference genome accession/version must be reported. reference-based mapping/alignment statistics.total reads mapped and percentage mapped. mapping quality statistics.mean/median sequencing depth.; • genome-wide coverage and percentage of genome covered at relevant depth thresholds. coverage/depth plots for both bulk-1 and bulk-2. reference-based assembly and mapping statistics: total reads mapped, depth and genome coverage, percentage of genome covered, mapping quality metrics.; 4. variant discovery / polymorphism detection : • high-confidence snp and indel calling, say, between bulk-1 and bulk-2. • genomic coordinates of all detected variants. reference and alternative alleles for both the parental genotypes and discarding of common alternate alleles between the two parental genotypes. • read depth, genotype/allele information and quality score for each variant.a variant was retained only when the sequencing depth of both parents was at least 20 reads. • at least 90% of parent-1 reads were required to support the reference allele and similarly, at least 90% of parent-2 reads were required to support the alternative allele. •a stringent 90% allele-support threshold must be applied at each informative marker.the 90% threshold must be applied only to the parental samples, not to the bulks.; 5. bulked segregant analysis (bsa-seq) consider both snp and indel markers : when the parent-1-derived allele was the reference allele; • snp-index (bulk1) = parent-1 derived allele reads in bulk-1 / total bulk-1 reads; snp-index(bulk-2) = parent-1-derived allele reads in bulk 2/ total bulk-2 reads.; when the parent-2-derived allele was the alternative allele; snp-index (bulk-1) = parent-1 derived allele reads in bulk-1 / total bulk-1 read; snp-index(bulk-2) = parent-1-derived allele reads in bulk 2/ total bulk-2 reads.; thus, the calculated index always represented the proportion of reads carrying the allele inherited from parent-1, rather than simply representing the frequency of the vcf ref or alt allele.; • δsnp-index (snp-index bulk 1 − snp-index bulk-2) calculation across the genome.a positive δsnp-index therefore indicated that the parent-1-derived allele was more frequent in the bulk-1 than in the bulk-2. conversely, a negative δsnp-index indicated that the parent-1-derived allele was more frequent in the bulk-2. identification of statistically/significantly differentiated genomic regions/peaks. sliding window: a window size of 0.1 mb (1,000,00 bp) and a step size of 10 kb (100,00 bp) must be used. ; window level-qtl-seq stat: for each sliding window, mean bulk-1parent-1-derived allele index = sum of bulk-1 parent-1-derived allele indices / number of informative variants; mean bulk-2parent-1-derived allele index = sum of bulk-2 parent-1-derived allele indices / number of informative variants. mean δsnp-index = sum of individual δsnp-index values / number of informative variants. the resulting window-level dataset therefore summarized the genomic distribution of allele-frequency differences while reducing the influence of individual marker-level fluctuations.; 6. variant annotation and functional impact• annotation of snps and indels against the reference gene annotation.• classification into intergenic, upstream/downstream, intronic, exonic and other relevant categories.• synonymous, missense, nonsense/stop-gain, splice-site and other predicted effects where applicable.• functional impact prediction/prioritization of variants.• identification of variants located within or near candidate genes.; 7. additional deliverables • summary reports with all statistical outputs• raw data and analysis supporting files should be provided. ; • fasta, gff3, vcf, jpegand bam files for all the samples as applicable; • detailed compiled report with interpretations as per the instructions of the pi.
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