NCBI Zea mays Annotation Release 100

The RefSeq genome records for Zea mays were annotated by the NCBI Eukaryotic Genome Annotation Pipeline, an automated pipeline that annotates genes, transcripts and proteins on draft and finished genome assemblies. This report presents statistics on the annotation products, the input data used in the pipeline and intermediate alignment results.

The annotation products are available in the sequence databases and on the FTP site.

This report provides:

For more information on the annotation process, please visit the NCBI Eukaryotic Genome Annotation Pipeline page.


Annotation Release information

This annotation should be referred to as NCBI Zea mays Annotation Release 100

Annotation release ID: 100
Date of Entrez queries for transcripts and proteins: Jul 7 2014
Date of submission of annotation to the public databases: Aug 2 2014
Software version: 6.0

Assemblies

The following assemblies were included in this annotation run:
Assembly nameAssembly accessionSubmitterAssembly dateReference/AlternateAssembly content
B73 RefGen_v3GCF_000005005.1Maize Genome Sequencing Project10-24-2013Reference12 assembled chromosomes; unplaced scaffolds

Gene and feature statistics

Counts and length of annotated features are provided below for each assembly.

Feature counts

FeatureB73 RefGen_v3
Genes and pseudogenes help51,116
  protein-coding39,627
  non-coding7,820
  pseudogenes3,669
  genes with variants11,406
mRNAs58,017
  fully-supported50,943
  with > 5% ab initio help5,770
  partial2,120
  with filled gap(s) help316
  known RefSeq (NM_) help19,723
  model RefSeq (XM_)38,294
Other RNAs help15,189
  fully-supported14,013
  with > 5% ab initio help0
  partial18
  with filled gap(s) help17
  known RefSeq (NR_) help155
  model RefSeq (XR_) help13,859
CDSs58,003
  fully-supported50,943
  with > 5% ab initio help5,994
  partial1,284
  with major correction(s) help1,923
  known RefSeq (NP_) help19,709
  model RefSeq (XP_) help38,294

Detailed reports

Masking of genomic sequence

Transcript and protein alignments are performed on the repeat-masked genome. Below are the percentages of genomic sequence masked by WindowMasker and RepeatMasker for each assembly. RepeatMasker results are only used for organisms for which a comprehensive repeat library is available.

For this annotation run, transcripts and proteins were aligned to the genome masked with WindowMasker only.
Assembly nameAssembly accession% Masked with RepeatMasker% Masked with WindowMasker
B73 RefGen_v3GCF_000005005.177.56%67.25%

Transcript and protein alignments

The annotation pipeline relies heavily on alignments of experimental evidence for gene prediction. Below are the sets of transcripts and proteins that were retrieved from Entrez, aligned to the genome by Splign or ProSplign and passed to Gnomon, NCBI's gene prediction software.

Depending on the other evidence available, long 454 reads (with average length above 250 nt) may be aligned as traditional evidence and reported in the Transcript alignments section or aligned with short reads and reported in the Short read transcript alignments section.

Transcript alignments

RefSeq transcript alignment quality report

The known RefSeq transcripts (NM_ and NR_ accessions) are a set of hiqh-quality transcripts maintained by the RefSeq group at NCBI. Alignment statistics for this group of transcripts, such as percent and number of sequences not aligning at all, percent best alignments split between multiple scaffolds, and percent alignments not covering the full CDS are indicative of the genome quality and are provided below.

B73 RefGen_v3
Primary Assembly
Number of sequences retrieved from Entrez22,377
Number (%) of sequences not aligning285 (1.27%)
Number (%) of sequences with multiple best alignments (split genes)206 (0.93%)
Number (%) of sequences with CDS coverage < 95% help931 (4.24%)

Short read transcript alignments

The following short reads (RNA-Seq) from the Sequence Read Archive were also used for gene prediction:

  Hide alignments statistics

Protein alignments

References

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