BCKV/CRU/2627/PI(13023)/Ten 6

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.