NCBI Physella acuta Annotation Release GCF_028476545.1-RS_2023_08

The genome sequence records for Physella acuta RefSeq assembly GCF_028476545.1 (ASM2847654v2) were annotated by the NCBI Eukaryotic Genome Annotation Pipeline, an automated pipeline that annotates genes, transcripts and proteins on draft and finished genome assemblies.

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

This report provides:

• Annotation Release information: The name of the release, important dates, the software version
• Assemblies: A brief description of the annotated assembly(ies)
• Gene and feature statistics: The counts and characteristics of the annotated features
• BUSCO results: Annotation completeness assessed with BUSCO
• Alignment of the annotated proteins to a set of high-quality proteins: The number of annotated proteins with hits to a set of high-quality proteins
• Masking of genomic sequence: How much of the genome was masked
• Transcript and protein alignments: The number and type of evidence retrieved from public databases and used for gene prediction

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 "GCF_028476545.1-RS_2023_08".

Date of Entrez queries for transcripts and proteins: Aug 25 2023
Date of submission of annotation to the public databases: Aug 31 2023
Software version: 10.1

Assemblies

The following assemblies were included in this annotation run:

Assembly name	Assembly accession	Submitter	Assembly date	Reference/Alternate	Assembly content
ASM2847654v2	GCF_028476545.1	CEFE CNRS	02-06-2023	Reference	1 assembled chromosomes; unplaced scaffolds

Gene and feature statistics

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

Feature counts

Feature	ASM2847654v2
Genes and pseudogenes	31,810
protein-coding	24,894
non-coding	6,197
Transcribed pseudogenes	5
Non-transcribed pseudogenes	712
genes with variants	7,178
Immunoglobulin/T-cell receptor gene segments	0
other	2
mRNAs	41,285
fully-supported	34,225
with > 5% ab initio	5,047
partial	1,197
with filled gap(s)	659
known RefSeq (NM_)	0
model RefSeq (XM_)	41,285
non-coding RNAs	7,373
fully-supported	3,301
with > 5% ab initio	0
partial	11
with filled gap(s)	6
known RefSeq (NR_)	0
model RefSeq (XR_)	5,675
pseudo transcripts	5
fully-supported	4
with > 5% ab initio	0
partial	0
with filled gap(s)	0
known RefSeq (NR_)	0
model RefSeq (XR_)	5
CDSs	41,298
fully-supported	34,225
with > 5% ab initio	5,284
partial	1,050
with major correction(s)	201
known RefSeq (NP_)	0
model RefSeq (XP_)	41,298

Detailed reports

The counts below do not include pseudogenes.

BUSCO analysis of gene annotation

BUSCO v4.1.4 was run in "protein" mode on the annotated gene set picking one longest protein per gene, and run using the mollusca_odb10 lineage dataset. Results are reported for the gene set from the primary assembly unit, and presented in BUSCO notation.

Alignment of the annotated proteins to a set of high-quality proteins

The final set of annotated proteins was searched with BLASTP against the UniProtKB/Swiss-Prot curated proteins, using the annotated proteins as the query and the high-quality proteins as the target. Out of 24881 coding genes, 15920 genes had a protein with an alignment covering 50% or more of the query and 3227 had an alignment covering 95% or more of the query.

Definition of query and target coverage. The query coverage is the percentage of the annotated protein length that is included in the alignment. The target coverage is the percentage of the target length that is included in the alignment.

Below is a cumulative graph displaying the number of genes with alignments above a given query or target coverage threshold. For comparison, corresponding statistics for other organisms annotated by the NCBI eukaryotic annotation pipeline were added to the graph.

Query: annotated proteins
Target: UniProtKB/Swiss-Prot curated proteins

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 (if calculated), for each assembly. RepeatMasker results are only calculated for organisms with complete Dfam HMM model collections.

For this annotation run, transcripts and proteins were aligned to the genome masked with WindowMasker only.

Assembly name	Assembly accession	% Masked with WindowMasker
ASM2847654v2	GCF_028476545.1	42.22%

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 Nucleotide, Entrez Protein, and SRA, and aligned to the genome.

Transcript alignments

The alignments of the following transcripts with Splign were used for gene prediction:

RNA-Seq alignments

The alignments of the following RNA-Seq reads with STAR were also used for gene prediction:

  Hide alignments statistics, by sample (SAME, SAMN, SAMD, DRS)  Show alignments statistics, by run (ERR, SRR, DRR)

Protein alignments

The alignments of the following proteins with ProSplign were used for gene prediction:

References

• RefSeq: Pruitt KD, Brown GR, Hiatt SM, Thibaud-Nissen F, Astashyn A, Ermolaeva O, Farrell CM, Hart J, Landrum MJ, McGarvey KM, Murphy MR, O'Leary NA, Pujar S, Rajput B, Rangwala SH, Riddick LD, Shkeda A, Sun H, Tamez P, Tully RE, Wallin C, Webb D, Weber J, Wu W, Dicuccio M, Kitts P, Maglott DR, Murphy TD, Ostell JM. Nucleic Acids Research 2014, 42(Database issue):D756-63
• BUSCO: Manni M, Berkeley MR, Seppey M, Simão FA, Zdobnov EM. Molecular biology and evolution 2021.38(10):4647-4654
• RepeatMasker: Smit AFA, Hubley R, Green P. RepeatMasker Open-3.0. 1996–2004. http://www.repeatmasker.org
• WindowMasker: Morgulis A, Gertz EM, Schäffer AA, Agarwala R. Bioinformatics 2006, 2:134-41
• Splign: Kapustin Y, Souvorov A, Tatusova T, Lipman D. Biology Direct 2008, 3:20
• STAR: Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. Bioinformatics 2013 Jan 1;29(1):15-21.
• Minimap2: Li H. Bioinformatics 2018 Sep 15;34(18):3094-3100