MMEJ-based Precision Gene Editing for applications in Gene Therapy and Functional Genomics
ABSTRACT Experiments in gene editing commonly elicit error-prone non-homologous end joining for DNA double-strand break (DSB) repair. Microhomology-mediated end joining (MMEJ) can generate more predictable outcomes for functional genomic and somatic therapeutic applications. MENTHU is a computational tool that predicts nuclease-targetable sites likely to result in MMEJ-repaired, homogeneous genotypes (PreMAs) in zebrafish. We deployed MENTHU on 5,885 distinct Cas9-mediated DSBs in mouse embryonic stem cells, and compared the predictions to those by inDelphi, another DSB repair predictive algorithm. MENTHU correctly identified 46% of all PreMAs available, doubling the sensitivity of inDelphi. We also introduce MENTHU4, an MENTHU update trained on this large dataset. We trained two MENTHU-based algorithms on this larger dataset and validated them against each other, MENTHU, and inDelphi. Finally, we estimated the frequency and distribution of SpCas9-targetable PreMAs in vertebrate coding regions to evaluate MMEJ-based targeting for gene discovery. 44 out of 54 genes (81%) contained at least one early out-of-frame PreMA and 48 out of 54 (89%) did so when also considering Cas12a. We suggest that MMEJ can be deployed at scale for reverse genetics screenings and with sufficient intra-gene density rates to be viable for nearly all loss-of-function based gene editing therapeutic applications..
Medienart: |
Preprint |
---|
Erscheinungsjahr: |
2022 |
---|---|
Erschienen: |
2022 |
Enthalten in: |
bioRxiv.org - (2022) vom: 28. Okt. Zur Gesamtaufnahme - year:2022 |
---|
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Martínez-Gálvez, Gabriel [VerfasserIn] |
---|
Links: |
---|
Themen: |
---|
doi: |
10.1101/2020.04.25.060541 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
XBI017747430 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | XBI017747430 | ||
003 | DE-627 | ||
005 | 20230429101741.0 | ||
007 | cr uuu---uuuuu | ||
008 | 200427s2022 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1101/2020.04.25.060541 |2 doi | |
035 | |a (DE-627)XBI017747430 | ||
035 | |a (biorXiv)10.1101/2020.04.25.060541 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Martínez-Gálvez, Gabriel |e verfasserin |4 aut | |
245 | 1 | 0 | |a MMEJ-based Precision Gene Editing for applications in Gene Therapy and Functional Genomics |
264 | 1 | |c 2022 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a ABSTRACT Experiments in gene editing commonly elicit error-prone non-homologous end joining for DNA double-strand break (DSB) repair. Microhomology-mediated end joining (MMEJ) can generate more predictable outcomes for functional genomic and somatic therapeutic applications. MENTHU is a computational tool that predicts nuclease-targetable sites likely to result in MMEJ-repaired, homogeneous genotypes (PreMAs) in zebrafish. We deployed MENTHU on 5,885 distinct Cas9-mediated DSBs in mouse embryonic stem cells, and compared the predictions to those by inDelphi, another DSB repair predictive algorithm. MENTHU correctly identified 46% of all PreMAs available, doubling the sensitivity of inDelphi. We also introduce MENTHU4, an MENTHU update trained on this large dataset. We trained two MENTHU-based algorithms on this larger dataset and validated them against each other, MENTHU, and inDelphi. Finally, we estimated the frequency and distribution of SpCas9-targetable PreMAs in vertebrate coding regions to evaluate MMEJ-based targeting for gene discovery. 44 out of 54 genes (81%) contained at least one early out-of-frame PreMA and 48 out of 54 (89%) did so when also considering Cas12a. We suggest that MMEJ can be deployed at scale for reverse genetics screenings and with sufficient intra-gene density rates to be viable for nearly all loss-of-function based gene editing therapeutic applications. | ||
650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
650 | 4 | |a 570 |7 (dpeaa)DE-84 | |
700 | 1 | |a Manduca, Armando |e verfasserin |4 aut | |
700 | 1 | |a Ekker, Stephen C. |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t bioRxiv.org |g (2022) vom: 28. Okt. |
773 | 1 | 8 | |g year:2022 |g day:28 |g month:10 |
856 | 4 | 0 | |u https://doi.org/10.1093/nar/gkaa1156 |z lizenzpflichtig |3 Volltext |
856 | 4 | 0 | |u http://dx.doi.org/10.1101/2020.04.25.060541 |z kostenfrei |3 Volltext |
912 | |a GBV_XBI | ||
912 | |a SSG-OLC-PHA | ||
951 | |a AR | ||
952 | |j 2022 |b 28 |c 10 |