1 DNA Extraction and Sequencing
Genomic DNA from young leaves was extracted using a cetyltrimethylam-monium bromide (CTAB)-based protocol (Uzunova et al., 1995). The concentration and quality of the total genomic DNA were determined using a NanoDrop2000 Spectrophotometer (Thermo Fisher Scientific). DNA libraries(350bp) for Illumina/BGI sequencing were constructed for each accession according to the manufacturer's specifications. After DNA library construction, sequencing was performed on an Illumina HiSeq XTen/NovaSeq/BGI platform by a commercial service (Biomarker Technologies, Beijing, China), with 150-bp read lengths.
2 Data analysis
The raw reads were further processed with a bioinformatic pipelinetool, BMKCloud(www.biocloud.net) online platform.
2.1 Quality control
Raw data (raw reads) of fastq format were firstly processed through fastp software. In this step, clean data(clean reads) were obtained by removing adapter from reads, reads containing ploy-N, reads with a length of less than 100 bp and low quality reads from raw data. At the same time, Q20, Q30, GC-content and sequence duplication level of the clean data were calculated. All the downstream analyses were based on clean data with high quality.
2.2 Reads mapping to the reference genome
The adaptor sequences and low-quality sequence reads were removed from the data sets. Raw sequences were transformed into clean reads after data processing. These clean reads were then mapped to the reference genome sequence. bwa-mem2 soft were used to map with reference genome.
2.3 SNP/INDEL Calling
The mapping results were sorted, and duplicate reads were rmdup using samtools(v1.9). SNPs and InDels within the xx accessions were called using the HaplotypeCaller module in GATK(v3.8) and were filtered with the following parameters: QD < 2.0 || MQ < 40.0 || FS > 60.0 || QUAL <30.0 || MQrankSum < -12.5 || ReadPosRankSum < -8.0 -clusterSize 2 -clusterWindowSize 5.The SNPs identified by GATK were further filtered: only SNPs with a minor allele frequency greater than xx% and less than xx% missing data were considered as high-quality SNPs. Finally, High-quality SNPs were obtained.
2.4 SNP/INDEL Annotation
SNP annotation was performed on the basis of the reference genome using snpEff software(3.6c (build 2014-05-20)) (Cingolani et al., 2012), and SNPs were categorized into intergenic regions, upstream or downstream regions, and exons or introns. SNPs in coding exons were further classified as synonymous SNPs or nonsynonymous SNPs.InDels in exons were grouped according to whether they led to a frameshift.
2.5 SV Calling
Based on the mapping results, Manta software was used to detect structural variation using default parameters, and large fragments of insertion, deletion, inversion, ectopic and other structural variations were obtained.
2.6 CNV Calling
Based on the mapping results, using freec software and using default parameters to detect copy number variation, gain and loss copy types were obtained.
2.7 Gene functional annotation
Gene function was annotated based on the following databases: Nr (NCBI non-redundant protein sequences);Pfam (Protein family); KOG/COG (Clusters of Orthologous Groups of proteins); Swiss-Prot (A manually annotated and reviewed protein sequence database); KO (KEGG Ortholog database); GO (Gene Ontology).
Remarks
Please kindly be aware that only the analyses listed in the contract will be performed. Some of above files may not exist in the final results.