Materials and Reagents

50 ml Falcon tube
Young leaf tissue
Tris (Amresco, catalog number: 77-86-1 )
EDTA (Sigma-Aldrich, catalog number: E5134 )
NaCl (Sigma-Aldrich, catalog number: S3014 )
3% CTAB (Hexadecylrimethylammonium bromide) (Sigma-Aldrich, catalog number: H5882 )
2% polyvinylpyrolidone (PVP) (MW 40,000) (Amresco, catalog number: 9003-39-8 )
1% β-mercaptoethanol (Sigma-Aldrich, catalog number: M3148 )
5 M ammonium acetate (Sigma-Aldrich, catalog number: A1542 )
Chloroform:isoamyl alcohol mix [24:1 (v:v)]
Isopropanol (stored at -20 °C)
Ethanol
RNase A (> 70 Kunit/mg protein, > 20 mg protein/ml) (Sigma-Aldrich, catalog number: R4642 )
Extraction buffer (see Recipes)
TE buffer (see Recipes)

Equipment

65 °C water bath
37 °C water bath/block
IKA-A11 analytical grinding mill (IKA^®-Werke GmbH & Co. KG)
Cooled centrifuge (Sorvall RC5plus) with Fixed Angle Rotor (Fiberlite^TM F13-14 x 50cy) (Thermo Fisher Scientific, catalog number: 096-1450 ).
Agarose gel apparatus
Nanodrop spectrophotometer
Recommended hardware specifications (for bioinformatics pipeline)

CPU
Architecture: x86_64
CPU op-mode(s): 64-bit, 8 cores, Thread(s) per core: 2
Vendor ID: GenuineIntel
CPU MHz: 1596.000
Memory
MemTotal: 48 GB
SwapTotal: 4GB

Software

“Sff_extract” (https://bioinf.comav.upv.es/sff_extract/) – Converting and preprocessing, e.g., adapter removal and base-call clipping 454-GS FLX raw files to text formats (fasta and quality).
Note: Sff_extract is now part of the tool set seq_crumbs (https://bioinf.comav.upv.es/seq_crumbs/)
MIRA (https://sourceforge.net/projects/mira-assembler/) – A multi-pass DNA sequence data assembler/mapper for whole genome and/or transcriptome projects. MIRA is a multi-platforms assembler capable assembling reads from a combination of platforms or from each platform separately.
CAP3 (http://seq.cs.iastate.edu/cap3.html) – CAP3 is for small-scale assembly of sequences with or without quality values.
Trimmomatic (http://www.usadellab.org/cms/?page=trimmomatic) – Trimmomatic is a fast, multi-threaded command line tool that can be used to trim and crop Illumina (FASTQ) data as well as to remove adapters.
FASTX (http://hannonlab.cshl.edu/fastx_toolkit/) – Preprocessing, e.g., adapter removal and base-call clipping, short reads (fastq files).
Note: FASTX-Toolkit is a collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing.
Bowtie2 (http://bowtie-bio.sourceforge.net/bowtie2/index.shtml) – Alignment of short reads to a reference genome/transcriptome.
Samtools (http://www.htslib.org/) – SAM (Sequence Alignment/Map) format is a generic format for storing large nucleotide sequence alignments. SAMTools provide various utilities for manipulating alignments in the SAM format, including sorting, merging, indexing and generating alignments in a per-position format.
Getorf (http://emboss.sourceforge.net/download/) – EMBOSS tool for identification of open reading frame ORF in mRNA sequence.
MIcroSAtellite (MISA) identification tool (http://pgrc.ipk-gatersleben.de/misa) – This tool allows the identification and localization of perfect microsatellites as well as compound microsatellites which are interrupted by a certain number of bases.
SciRoKo (http://kofler.or.at/bioinformatics/SciRoKo/index.html) – A tool for fast whole-genome microsatellite search. For example, the whole rice genome may be searched in 55 sec.
VarScan (http://varscan.sourceforge.net/) – VarScan is a platform-independent mutation caller for targeted, exome, and whole-genome resequencing data generated on Illumina, SOLiD, Life/PGM, Roche/454, and similar instruments.

Data analysis

Data
1. 454-GS FLX Titanium mRNA contigs were deposited in transcriptome shotgun assembly (TSA) repository of NCBI: accession No. GBJO00000000 (Sherman et al., 2015).
2. Illumina short reads were deposited in short reads archive (SRA) of NCBI: experiment accession No. SRX651793 GBJO00000000 (Sherman et al., 2015).
De novo transcriptome assembly
1. Raw sequence reads of the 454-GS FLX Titanium platform were pre-processed by “Sff_extract” (https://bioinf.comav.upv.es/sff_extract/) and arguments for removing the adaptors and clipping the poly-A were applied.
2. De novo assembly with MIRA 3.2 (Chevreux et al., 2004)
3. Reduction of contig variability (merging transcript variants) by running Cap3 and creating super-contigs
  Note: Cap3 is downloaded separately from MIRA (see Software list section).
  
  Note: mango.fasta and mango.qual are output files of MIRA, created in the mango_d_results directory.
4. Filtering out contigs with length less than 200 bp
  Refer to the fasta file from here on as reference.transcriptome.contigs.fasta
Functional annotation
1. Identifying the coding region to annotate marker position, i.e., inside or outside coding sequence. Finding open reading frames (ORFs) by the “getorf” program of the EMBOSS package (Rice et al., 2000). The longest ORF with start and stop codons was chosen for each contig (-find 1) with a minimum cutoff of 50 amino acids (-minisize 150).
  Note: The argument (-minimize) is given in base pairs (50 bp x 3 = 150 bp).
2. Reference transcriptome contigs annotation to connect variability with functionality using Blast 2GO (Gotz et al., 2008).
  Blast2GO GUI options:
  1. Start → load sequences (e.g., fasta)
  2. Blast → Run Blast Description Annotator
  3. Mapping → Run mapping
  4. Annot → Run annotation
  5. InterPro → Run interproscan
SNP and SSR discovery
Adapter removal and low-quality base pairs clipping are performed by Trimmomatic (Bolger et al., 2014) and FASTX (http://hannonlab.cshl.edu/fastx_toolkit/).
Note: Optional but highly recommended if the alignment is performed on RNA-Seq.
1. Use R1 and R2 of trimmed pair files, i.e., sample_name_pair_L001_R1.fastq, sample_name_pair_L001_R2.fastq for downstream analysis.
2. Alignment of resequencing of Illumina HiSeq-2000 reads to the transcriptome reference with bowtie2 (http://bowtie-bio.sourceforge.net/bowtie2/index.shtml).
3. Running samtools (http://www.htslib.org/) and VarScan (Koboldt et al., 2009) for SNP discovery
  Note: The criteria for selecting an SNP subset are dependent on the project. However, a few criteria are advisable to ensure confident SNP loci in any project:
  1. No other SNPs in the flanking regions (100 bp each side) to enable of primer design for further analyses (Absolute differences of the SNP value between the previous and next values in ‘Position’ column should > 100).
  2. Only one SNP per reference-transcriptome contig (unique value at ‘Chrom’ column).
  3. Bi-allelic confidence (‘SamplesHet’ value > 0).
4. SSR discovery within the contigs the reference transcriptome.
  MIcroSAtellite (MISA) identification tool (http://pgrc.ipk-gatersleben.de/misa) and SciRoKo (Kofler et al., 2007) are run with default parameters.
5. Find the intersection between two tables by importing them into MS-Access or SQLite and run a SQL inner join command on contig-name, motif, and start-position.
6. Genotyping with Fluidigm
7. Filtering qualified SNPs for diversity analysis
  Fluidigm genotype calls are divided into four categories by visual inspection:
  1. Filtering out SNPs with a Category ≥ 2 (Table 1).
  2. Filtering out SNPs with more than 10% no calls.
  3. Filtering out samples with more than 33% no calls.
  4. Filtering out markers with PIC < 0.1.
  5. Filtering out markers with more than 90% of the samples have the same call, i.e., segregating exactly the same.
  6. Filtering out markers with less than 2 samples in each genotype.
  7. Leaving only one marker from each pair of linked markers (R^2 > 0.7).
  8. Leaving only one sample from group of sample having identical genotype. (Identity ≥ 0.95)
  *Notes:
  1. These steps can be performed with any programming language, e.g., R, python, perl, C, etc. or SQL.
  2. PIC is calculated as PIC = 1- ∑ pi^2; i = a, A
  3. R^2 is calculated as r^2 = D^2/(p1*p2*q1*q2); D = (p11*p22)-(p12p21 p11,p22,p12,p21 are the proportions of all possible combinations of two bi-allelic loci.
  Table 1. Quality scores of each locus genotyping calls given by visual inspection.

Recipes

Extraction buffer
100 Tris, pH 8
20 M EDTA
1.5 M NaCl
3% hexadecylrimethylammonium bromide (CTAB)
2% polyvinylpyrolidone (PVP)
1% β-mercaptoethanol
All solution except β-mercaptoethanol are dissolved by stirring over several hours, and autoclaved. β-mercaptoethanol is added just prior to tissue extraction.
TE buffer
10 mM Tris, pH 8.0
1 mM EDTA

Acknowledgments

The protocol has been developed in a study which was supported by the Chief Scientist of Ministry of Agriculture and Rural Development [Grant No.: 203-0859-12].

References

Bolger, A. M., Lohse, M. and Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30(15): 2114-2120.
Bowtie - An ultrafast memory-efficient short read aligner. JOHNS HOPKINS University.
Chevreux, B., Pfisterer, T., Drescher, B., Driesel, A. J., Muller, W. E., Wetter, T. and Suhai, S. (2004). Using the miraEST assembler for reliable and automated mRNA transcript assembly and SNP detection in sequenced ESTs. Genome Res 14(6): 1147-1159.
Fluidigm SNP Genotyping Guide. Fluidigm.
FASTX-Toolkit. Hannonlab.
Gotz, S., Garcia-Gomez, J. M., Terol, J., Williams, T. D., Nagaraj, S. H., Nueda, M. J., Robles, M., Talon, M., Dopazo, J. and Conesa, A. (2008). High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res 36(10): 3420-3435.
Koboldt, D. C., Chen, K., Wylie, T., Larson, D. E., McLellan, M. D., Mardis, E. R., Weinstock, G. M., Wilson, R. K. and Ding, L. (2009). VarScan: variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics 25(17): 2283-2285.
Kofler, R., Schlotterer, C. and Lelley, T. (2007). SciRoKo: a new tool for whole genome microsatellite search and investigation. Bioinformatics 23(13): 1683-1685.
MIcroSAtellite identification tool.
Reading/writing/editing/indexing/viewing SAM/BAM/CRAM format. Samtools.
Rice, P., Longden, I. and Bleasby, A. (2000). EMBOSS: the European Molecular Biology Open Software Suite. Trends Genet 16(6): 276-277.
Sff_extract. Bioinformatics at COMAV.
Sherman, A., Rubinstein, M., Eshed, R., Benita, M., Ish-Shalom, M., Sharabi-Schwager, M., Rozen, A., Saada, D., Cohen, Y. and Ophir, R. (2015). Mango (Mangifera indica L.) germplasm diversity based on single nucleotide polymorphisms derived from the transcriptome. BMC Plant Biol 15: 277.