Candidates are required to appear for an interview, with all the necessary certificates in original along with a set of attested copies in the office of the Principal, AU College of Science & Technology, Andhra University, Visakhapatnam. Applications may be sent by Email to andhrauniv.btisnet@nic.in / katruumadevi@gmail.com.

This blog provides a comprehensive step-by-step guide to detect piRNAs using bioinformatics tools and workflows.

Step 1: Prepare Your Data

1. Obtain RNA Sequencing Data
   Acquire raw small RNA-seq data in FASTQ format. Datasets can be sourced from repositories like NCBI SRA, EMBL-EBI, or specific small RNA sequencing projects.

2. Quality Control (QC)
   Use FastQC to assess the quality of raw reads:

   fastqc reads.fastq

   Evaluate the per-base quality, adapter content, and overrepresented sequences.

3. Trimming and Adapter Removal
   Use tools like Cutadapt or Trim Galore! to remove adapters and low-quality bases:

   cutadapt -a TGGAATTCTCGGGTGCCAAGG -o trimmed_reads.fastq reads.fastq

   Ensure the remaining reads are of high quality for downstream analysis.

Step 2: Map Reads to the Genome

Mapping reads to the reference genome is crucial for identifying piRNA loci.

1. Reference Genome Preparation
   Download the genome assembly of your organism from databases like Ensembl, UCSC Genome Browser, or NCBI.

2. Align Reads
   Use Bowtie or STAR for small RNA alignment:

   bowtie -v 1 -k 1 --best genome_index trimmed_reads.fastq -S aligned_reads.sam
   • -v 1: Allows one mismatch.
   • -k 1: Reports the best alignment.

3. Convert SAM to BAM
   Convert and sort alignments using SAMtools:

   samtools view -Sb aligned_reads.sam | samtools sort -o sorted_reads.bam

Step 3: Identify Small RNAs

piRNAs are characterized by their size (24–32 nt) and strand bias.

1. Extract Reads by Size
   Use tools like BEDtools or custom scripts to filter reads between 24 and 32 nt:

   bedtools bamtofastq -i sorted_reads.bam -fq all_reads.fastq seqkit seq -m 24 -M 32 all_reads.fastq > piRNA_size_reads.fastq

2. Check for Sequence Bias
   piRNAs often have a strong bias for a uridine at the 5’ end (1U bias). Use tools like WebLogo to visualize sequence motifs.

Step 4: Detect Ping-Pong Signature

The ping-pong amplification loop is a hallmark of piRNA biogenesis, characterized by a 10 nt overlap between piRNAs on opposite strands.

1. Generate Overlap Statistics
   Use the piPipes tool or custom scripts to calculate overlap:

   python ping_pong_overlap.py sorted_reads.bam

2. Visualize Overlap Distribution
   Plot the distribution of overlaps to confirm the presence of the 10 nt ping-pong signature.

Step 5: Annotate piRNA Clusters

piRNAs are often generated from genomic clusters.

1. Cluster Identification
   Use tools like proTRAC or PIRANHA to identify piRNA-producing clusters:

   proTRAC.pl -s sorted_reads.bam -g genome.fa -o clusters

2. Annotate Genomic Regions
   Annotate the identified clusters using gene annotation files (GTF/GFF). Tools like BEDtools intersect can help associate piRNA clusters with genes or transposable elements:

   bedtools intersect -a clusters.bed -b genome_annotation.gtf > annotated_clusters.bed

Step 6: Functional Analysis

Functional analysis of piRNAs can uncover their targets and regulatory roles.

1. Predict piRNA Targets
   Use tools like IntaRNA or RNAhybrid to predict interactions between piRNAs and potential target mRNAs:

   RNAhybrid -t target_transcripts.fa -q piRNAs.fa > piRNA_targets.txt

2. Enrichment Analysis
   Perform GO or KEGG enrichment analysis of target genes using tools like g:Profiler or DAVID.

Step 7: Validation and Visualization

1. Validate piRNA Candidates
   Cross-check the identified piRNAs against known piRNA databases, such as piRBase or piRNAdb.

2. Visualize Results

   • Use IGV (Integrative Genomics Viewer) to visualize piRNA alignment and clusters on the genome.
   • Generate heatmaps or circos plots to present piRNA distributions.

Step 8: Share and Publish Findings

1. Archive Data
   Submit sequencing data to public repositories like SRA or GEO with metadata specifying piRNA-related experiments.

2. Publish Results
   Share findings in journals or conferences, emphasizing novel piRNA candidates, target genes, or regulatory mechanisms.

Conclusion

Detecting piRNAs involves a combination of computational and analytical methods to identify these unique small RNAs and their roles in gene regulation and transposable element suppression. By following this step-by-step guide, you can confidently navigate the complexities of piRNA detection and contribute to the growing understanding of their biological significance.

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bcftools: a set of companion tools, currently bundled with SAMtools, for identifying and filtering genomics variants.

bowtie: widely used, open source alignment software for aligning raw sequence reads to a reference genome.

BAM Format: binary, compressed format for storing SAM data.

BCF Format: Binary call format. Binary, compressed format for storing VCF data.

CIGAR String: Compact Idiosyncratic Gapped Alignment Report. A compact string that (partially) summarizes the alignment of a raw sequence read to the reference genome. Three core abbreviations are used: M for alignment match; I for insertion; and D for Deletion. For example, a CIGAR string of 5M2I63M indicates that the first 5 base pairs of the read align to the reference, followed by 2 base pairs, which are unique to the read, and not in the reference genome, followed by an additional 63 base pairs of alignment.

FASTA Format: text format for storing raw sequence data. For example, the FASTA file at: http://www.ncbi.nlm.nih.gov/nuccore/NC_008253 contains entire genome for Escherichia coli 536.

FASTQ Format: text format for storing raw sequence data along with quality scores for each base; usually generated by sequencing machines.

genotype likelihood: the probability that a specific genotype is present in the sample of interest. Genotype likelihoods are usually expressed as a Phred-scaled probability, where P = 10 ^ (-Q/10). For example, if the genotype TT (both alleles are T) at position 1,299,132 in human chromosome 12 (reference G) is 37, this translates to a probability of 10^-37/10 = 0.0001995, meaning that there is very low probability that the reads in your sample support a TT genotype. On the other hand, a genotype of AA at the same position with a score of 0 translates into a probability of 10^-0 = 1, indicating extremely high probability that your sample contains a homozygous mutation of G to A.

mate-pair: in paired-end sequencing, both ends of a single DNA or RNA fragment are sequenced, but the intermediate region is not. The two ends which are sequenced form a pair, and are frequently referred to as mate-pairs.

QNAME: unique identifier of a raw sequence read (also known as the Query Name). Used in FASTQ and SAM files.

paired-end sequencing: sequencing process where both ends of a single DNA or RNA fragment are sequenced, but the intermediate region is not. Particularly useful for identifying structural rearrangements, including gene fusions.

Phred-scaled probability: a scaled value (Q) used to compactly summarize a probability, where P = 10^-Q/10. For example, a Phred Q score of 10 translates to probability (P) = 10^-10/10 = 0.1. Phred-scaled probabilities are common in next-generation sequencing, and are used to represent multiple types of quality metrics, including quality of base calls, quality of mappings, and probabilities associated with specific genotypes. The name Phred refers to the original Phred base-calling software, which first used and developed the scale.

Phred quality score: a score assigned to each base within a sequence, quantifying the probability that the base was called incorrectly. Scores use a Phred-scaled probability metric. For example, a Phred Q score of 10 translates to P=10^-10/10 = 0.1, indicating that the base has a 0.1 probability of being incorrect. Higher Phred score correspond to higher accuracy. In the FASTQ format, Phred scores are represented as single ASCII letters. For details on translating between Phred scores and ASCII values, refer to Table 1 of this useful blog post from Damian Gregory Allis.

read-length: the number of base pairs that are sequenced in an individual sequence read.

read-depth: the number of sequence reads that pile up at the same genomic location. For example, 30X read-depth coverage indicates that the genomic location is covered by 30 independent sequencing reads. Increased read-depth translates into higher confidence for calling genomic variants.

RNAME: reference genome identifier (also known as the Reference Name). Within a SAM formatted file, the RNAME identifies the reference genome where the raw read aligns.

SAM Flag: a single integer value (e.g. 16), which encodes multiple elements of meta-data regarding a read and its alignment. Elements include: whether the read is one part of a paired-end read, whether the read aligns to the genome, and whether the read aligns to the forward or reverse strand of the genome. A useful online utility decodes a single SAM flag value into plain English.

SAM Format: Text file format for storing sequence alignments against a reference genome. See also BAM Format.

SAMtools: widely used, open source command line tool for manipulating SAM/BAM files. Includes options for converting, sorting, indexing and viewing SAM/BAM files. The SAMtools distribution also includes bcftools, a set of command line tools for identifying and filtering genomics variants. Created by Heng Li, currently of the Broad Institute.

single-read sequencing: sequencing process where only one end of a DNA or RNA fragment is sequenced. Contrast with paired-end sequencing.

VCF Format: Variant call format. Text file format for storing genomic variants, including single nucleotide polymorphisms, insertions, deletions and structural rearrangements. See also BCF format.

NextGenerationSequencing
A high-throughput sequencing method which parallelizes the sequencing process, producing thousands or millions of sequences at once.

DeepSequencing
Techniques of nucleotide sequence analysis that increase the range, complexity, sensitivity, and accuracy of results by greatly increasing the scale of operations and thus the number of nucleotides, and the number of copies of each nucleotide sequenced.

Paired-EndSequencing
Sequence both ends of the same fragment and keep track of the paired data.

Adapter
Short oligonucleotides which are attached to the DNA to be sequenced. An adapter can provide a priming site for both amplification and sequencing of the adjoining, unknown nucleic acid.

Library
A collection of DNA fragments with adapters ligated to each end.

BridgeAmplification
Generation of in situ copies of a specific DNA molecule on an oligo-decorated solid support.

EmulsionPCR
A method for bead-based amplification of a library. A single adapter-bound fragment is attached to the surface of a bead, and an oil emulsion containing necessary amplification reagents is formed around the bead/fragment component. Parallel amplification of millions of beads with millions of single strand fragments produces a sequencer-ready library.

Alignment
Mapping of sequence reads to a known reference sequence

Referencesequence/genome 
A fully assembled version of a genome that can be used for mapping short DNA sequence reads for comparisons of genomes from various individuals

CoverageDepth
The number of nucleotides from reads that are mapped to a given position of reference genome.

Specificity 
The percentage of sequences that map to the intended targets out of total bases per run.

Uniformity 
The variability in sequence coverage across target regions.

Homopolymer
Uninterrupted stretch of a single nucleotide type (e.g., TTT or GGGGGG)

InDel
InDel stands for Insertion or deletion. A form of structural variation in which a DNA segment is either deleted or inserted.

SNP 

SNP stands for Single Nucleotide Polymorphism. A single base difference found when comparing the same DNA sequence from two different individuals.

ICGEB NEW DELHI, INDIA

Biotechnology research positions

Projects include:

a) protein structure determination
b) malaria parasite biology
c) genomics and metagenomics
d) molecular and cellular biology
e) bioinformatics and computational biology

Minimum eligibility for students who have already obtained a MSc:

1) INSPIRE award for PhD
2) SPM award for PhD
3) CSIR/DBT/DST JRF for PhD

Applicants should submit their curriculum vitae by email to: sb.icgeb@gmail.com by 30 August 2016

The BINC is a nationwide examination aimed at certifying professionals in bioinformatics and tests their theoretical and practical knowledge across three phases of examination. He is entitled to receive a DBT research fellowship leading to a Ph.D. from any premier research institute in India.

https://github.com/MesquiteProject/MesquiteCore

Address of the bookmark: http://mesquiteproject.org/

DBT Invites online applications from the bioinformatics students and requisitions from biotech/bioinformatics companies.

Biotech Industry :

Biotech/Bioinformatics companies interested to provide hands on industrial training to the students of Bioinformatics under BIITP may apply online. The companies would have no obligation towards any payments to trainees. The companies would be paid bench fee to cover expenses towards training. Trainees would be provided to companies subject to availability.

Attn: Bioinformatics Students

Bioinformatics students interested in training in biotech / bioinformatics companies may apply online. Stipend of Rs. 10,000/- per month will be paid to candidates placed for training. The candidates will be selected for training through an interview.

Eligiblity :

a) B.E /B.Tech./M.Sc./M.Tech./Advanced Post Graduate Diploma in Bioinformatics from an Indian recognized university with minimum 55% marks or equivalent grade at highest degree/diploma completed in the year 2015 or 2016 are only eligible to apply.

b) The Advanced Post Graduate diploma should be of at least one year duration after graduation.

c)  Students whose result of last semester/final year is not declared can also apply mentioning their marks upto the semester/year upto which result declared. The final result with original mark sheet(s) of all the semesters/years will have to be produced at the time of interview.

Application Procedure :

The online application form is available below :

Application Form For Students (New User)

Requisition form for companies (New User)

Already registered User Click Here

The following documents are to be sent to Mr. Manoj Gupta, Manager, Biotech Consortium India Limited, 5th floor, Anuvrat Bhawan, 210, Deen Dayal UpadhyayaMarg, New Delhi-110002.

More at http://www.bcil.nic.in/biitp2016-17/index.asp

• DNA-mapping*
• ChIP-seq*
• RNA-seq*
• ATAC-seq*
• scRNA-seq
• Hi-C
• Whole Genome Bisulfite Seq/WGBS

(*Also available in "allele-specific" mode)

snakePipes can be installed via conda :

'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'.

Source code (https://github.com/maxplanck-ie/snakepipes) and documentation (https://snakepipes.readthedocs.io/en/latest/) are available online.

Address of the bookmark: https://github.com/maxplanck-ie/snakepipes

CDAC Pune Vacancy Details:
Total No. of Posts: 23

Name of the Post: Technical

Name of the Discipline:
A. Computer Science/ Information Technology and Allied disciplines.

B.Electronics Communications/ Electrical/ Telecommunication/Instrumentation & Control/ Medical Electronics/ Power Electronics/ VLSI & Embedded System and Allied disciplines.

C.Biotechnology/ Bioinformatics/ Health informatics/ Geoinformatics/ Meteorology/ Environmental Science/ Ocean Sciences/Oceanography/Environmental Engineering

1. Visually Impaired: 09 Posts

2. Hearing Impaired: 08 Posts

3. Orthopedically Impaired: 06 Posts

Educational Qualification : Candidates should possess Graduation in relvany discpline with relevant experience.

Selection Process: Candidates will be selected based on applicants performance in interview.

How to Apply: Eligible candidates can apply online through the website www.cdac.in from 27-07-2016 at 10.00 AM to 31-08-2016 at 18.00 PM.

More at http://www.cdac.in/index.aspx?id=current_jobs