Key Components

1. Sample Collection: Meta-transcriptomics begins with the collection of environmental samples. These samples are often complex, containing a wide range of microorganisms.

2. RNA Extraction: RNA is extracted from the sample, which includes mRNA, rRNA, tRNA, and other non-coding RNAs. This step is crucial as it determines the quality and representativeness of the data.

3. Sequencing: High-throughput RNA sequencing (RNA-seq) technologies are used to obtain sequences of the RNA transcripts. This step provides a vast amount of data on the RNA molecules present in the sample.

4. Data Analysis: Computational tools and bioinformatics methods are employed to process and analyze the sequencing data. This involves mapping RNA sequences to reference genomes or transcriptomes, identifying expressed genes, and quantifying their abundance.

5. Functional Annotation: The functional roles of identified transcripts are inferred based on known gene functions, allowing researchers to understand the metabolic and ecological functions of the microbial community.

Applications

1. Environmental Monitoring: Meta-transcriptomics can be used to monitor the health and functional status of ecosystems. For example, it can help assess the impact of pollution on microbial communities by revealing changes in gene expression related to stress response and degradation processes.

2. Microbiome Research: In human health, meta-transcriptomics offers insights into the gut microbiome’s functional state. It helps in understanding how microbial communities interact with their host, how they respond to dietary changes, and their role in health and disease.

3. Biotechnology: The technique can aid in the discovery of novel enzymes and bioactive compounds by profiling microbial communities in extreme environments or industrial processes.

4. Disease Pathogenesis: By analyzing RNA profiles from disease-associated environments, researchers can uncover pathogen-host interactions and identify potential targets for therapeutic interventions.

Challenges

1. Complexity of Data: The sheer volume and complexity of data generated by meta-transcriptomics can be overwhelming. Effective data management and advanced computational tools are required to extract meaningful insights.

2. Sampling Bias: Environmental samples can be heterogeneous, and RNA extraction methods may introduce biases, potentially affecting the accuracy of the results.

3. Reference Databases: Incomplete or biased reference databases can hinder the accurate functional annotation of transcripts, especially when studying novel or poorly characterized organisms.

Future Directions

Meta-transcriptomics is a rapidly evolving field, with ongoing advancements in sequencing technologies and bioinformatics. Future research may focus on improving data integration, developing more comprehensive reference databases, and enhancing our understanding of microbial community dynamics in various environments. As these challenges are addressed, meta-transcriptomics will continue to provide valuable insights into the functional roles of microorganisms and their interactions within ecosystems.

Conclusion

Meta-transcriptomics represents a powerful tool for exploring the functional aspects of microbial communities in their natural environments. By capturing a snapshot of gene expression and metabolic activities, this approach offers a deeper understanding of ecological interactions, health implications, and biotechnological potentials. As technology and methodologies advance, meta-transcriptomics is poised to make significant contributions to our knowledge of the microbial world.

Awards of $5 million to four grantees have been made in fiscal year 2013 under the Genomic Sequencing and Newborn Screening Disorders research program. The program will be funded at $25 million over five years, as funds are made available.

"Hundreds of US babies will be pioneers in genomic medicine through a US$25-million programme to sequence their genomes soon after they are born."

Source:

http://blogs.nature.com/news/2013/09/scientists-to-sequence-hundreds-of-newborns-genomes.html

http://www.genome.gov/27554919

https://gold.jgi.doe.gov/

Address of the bookmark: https://gold.jgi.doe.gov/

Local installation:

You can install Ribbon locally from Github by following the instructions here: https://github.com/MariaNattestad/Ribbon

Address of the bookmark: http://genomeribbon.com/

Address of the bookmark: https://sourceforge.net/projects/ksnp/files/

https://github.com/zhangzhwlab/delta

Address of the bookmark: https://github.com/zhangzhwlab/delta

1. Supply your genes/genomic segments/phylogenetic tree of interest in the input-box by
   • selecting the type of identifier and pasting identifiers (one per line)
   • or by using the gene ID search tool
   • or with the BLAST search tool
2. Click "Visualize context".

Consult the documentation to learn more about MGcV.

Address of the bookmark: http://mgcv.cmbi.ru.nl/

if you map reads to GRCh38 or hg38, use the following:

ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/001/405/GCA_000001405.15_GRCh38/seqs_for_alignment_pipelines.ucsc_ids/GCA_000001405.15_GRCh38_no_alt_analysis_set.fna.gz

There are several other versions of GRCh37/GRCh38. What’s wrong with them? Here are a collection of potential issues:

More at http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use

Address of the bookmark: http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use

I'm running "OPERA-LG_v2.0.5/bin/preprocess_reads.pl" and have the following error:

fail to open file './temporarySam'

[bwa_aln_core] write to the disk... 0.09 sec
[bwa_aln_core] 70778880 sequences have been processed.
[bwa_aln_core] calculate SA coordinate... 161.35 sec
[bwa_aln_core] write to the disk... 0.06 sec
[bwa_aln_core] 70989574 sequences have been processed.
[main] Version: 0.7.15-r1140
[main] CMD: bwa aln -t 30 all_p_ctg.fa -
[main] Real time: 2402.523 sec; CPU: 53429.488 sec
[E::hts_open_format] Failed to open file temporarySam
samtools sort: can't open "temporarySam": No such file or directory
[bwa_aln_core] convert to sequence coordinate... 1.00 sec
[bwa_aln_core] refine gapped alignments... 6.07 sec
[bwa_aln_core] print alignments... PREPROCESS:
Fastq format is recognized
[Thu Jun 14 18:16:47 2018] Building bwa index...
bwa index -p all_p_ctg.fa /home/urbe/Tools/OPERA-LG_v2.0.6/all_p_ctg.fa
[Thu Jun 14 18:18:35 2018] Finding the SA coordinates of the reads using BWA aln...
[Thu Jun 14 18:58:37 2018] Generate alignments of reads using bwa sampe...
bwa samse -n 1 all_p_ctg.fa read.sai - | grep '\(^@\|XT:A:U\)' | /usr/local/bin/samtools view -S -h -b -F 0x4 - | /usr/local/bin/samtools sort -@ 20 -no - temporarySam > FALCON-Unzip-Scaff.bam
Mapping long-reads using blasr...
/home/urbe/Tools/SSpace/SSPACE-LongRead_v1-1/blasr -nproc 40 -m 1 -minMatch 5 -bestn 10 -noSplitSubreads -advanceExactMatches 1 -nCandidates 1 -maxAnchorsPerPosition 1 -sdpTupleSize 7 /media/urbe/MyDDrive/ONTdata/allONT/allONT.fasta /home/urbe/Tools/OPERA-LG_v2.0.6/all_p_ctg.fa | cut -d ' ' -f1-5,7-12 | sed 's/ /\t/g' > FALCON-Unzip-Scaff.map
sh: 1: /home/urbe/Tools/SSpace/SSPACE-LongRead_v1-1/blasr: Permission denied
Sorting mapping results...
sort -k1,1 -k9,9g FALCON-Unzip-Scaff.map > FALCON-Unzip-Scaff.map.sort
Analyzing sorted results...
Extracting linking information...
i3 2000 5000
i2 1000 2000
i4 5000 15000
i0 -200 300
i5 15000 40000
i1 300 1000
Repeat detection...
/home/urbe/Tools/OPERA-LG_v2.0.6/bin//filter_conflicting_edge.pl pairedEdges_i0 contig_length.dat 100 2
Illegal division by zero at /home/urbe/Tools/OPERA-LG_v2.0.6/bin//filter_conflicting_edge.pl line 93.
readline() on closed filehandle FILE at bin/OPERA-long-read.pl line 250.
rm anchor_contig_info.dat contig_length.dat filtered_edges.dat filtered_edges_cov.dat *.sai
rm: cannot remove 'anchor_contig_info.dat': No such file or directory
mv FALCON-Unzip-Scaff.bam FALCON-Unzip-Scaff-with-repeat.bam
/home/urbe/Tools/OPERA-LG_v2.0.6/bin//filter_repeat.pl FALCON-Unzip-Scaff-with-repeat.bam repeat.dat | /usr/local/bin/samtools view - -h -S -b > FALCON-Unzip-Scaff.bam
rm FALCON-Unzip-Scaff-with-repeat.bam
/home/urbe/Tools/OPERA-LG_v2.0.6/bin/OPERA-LG config > log
Analyzing 1 library: FALCON-Unzip-Scaff.bam
min library mean : 0
minimum contig length is 500
Current library: 1 out of 7
Analyzing file: pairedEdges_no_repeat_i0
Analyzing file: pairedEdges_no_repeat_i1
Analyzing file: pairedEdges_no_repeat_i2
Analyzing file: pairedEdges_no_repeat_i3
Analyzing file: pairedEdges_no_repeat_i4
Analyzing file: pairedEdges_no_repeat_i5
ln -s results/scaffoldSeq.fasta scaffoldSeq.fasta

To resolve this, try downloading blasr version 1.3 above and re-run :)